University of Southern California Dissertations and Theses

Digital transformation in the resources industry: an exploration of promising management practices

(USC Thesis Other)

Digital transformation in the resources industry: an exploration of promising management practices

PDF

Download

Open document

Flip pages

Download a page range

Download transcript

Copy asset link

Request this asset

Transcript (if available)

Content Digital Transformation in the Resources Industry: An Exploration of Promising Management Practices by Manish Panjwani Rossier School of Education University of Southern California A dissertation submitted to the faculty in partial fulfillment of the requirements for the degree of Doctor of Education May 2023 © Copyright by Manish Panjwani 2023 All Rights Reserved The Committee for Manish Panjwani certifies the approval of this Dissertation Dr. Ana Barcus Dr. Jennifer Phillips Dr. Helena Seli, Committee Chair Rossier School of Education University of Southern California 2023 iv Abstract The purpose of this study was to explore critical external and internal factors and practices promising to accelerate digital adoption in the resource industries. The resources industry, consisting of chemicals, natural resources, energy, and utility companies, has been slower to embrace digital transformation than other industries such as financial services, consumer products, and communications media and technology (CMT), due to the unique challenges of being asset-intensive with large capital outlay, and where technology has not kept pace with the way refineries, plants, and power-grids work. However, in 2023, the industry faces external and internal changes, such as technological advancements, customer expectations, and post-pandemic labor shortages, which make digital transformation essential for business survival, preventing job losses, and to aid in the energy transition. Based on the literature review, and the conceptual framework informed by the Burke-Litwin model of leadership, organization, and performance change, this study was implemented using qualitative methodology via individual semi- structured interviews with C-suite or senior executives within the resources industry who are responsible for leading digital transformation in their organization. Based on data analysis of the interview transcripts of 13 C-suite executives, this study identified 17 emerging themes, and six areas of promising practices for driving digital transformation in the resources industry. The six areas include talent, digital strategy, technology, culture, external factors, and emerging new areas such as the energy transition. Whilst four of these areas, talent, strategy, technology and culture, are also present in other industries undergoing transformation, a few specific practices emerged specific to the resource industry that include ecosystem partnership and focus on energy transition amongst others. This study discusses these key findings and presents recommendations for practice that promise to increase the adoption of digital transformation in the resources industry. Furthermore, the study highlights four new areas of research that emerged as surprise findings or gaps, including building a business case for digital transformation programs, navigating an orderly energy transition, the role of government, and the impact of advances in operational technology on digital transformation in the resources industry. Keywords: digital transformation, compressed transformation, resources industry, energy transition, artificial intelligence, cloud, data analytics, operations technology, information technology, the internet of things, talent, culture. vi Dedication To my wife Manju, I could not have achieved this without your encouragement, love and support. To my children Aarushi and Aarav. Thank you for your patience and understanding. To my father, Late Prof. Santosh Panjwani, for instilling the values of education in me and being the inspiration behind this undertaking. vii Acknowledgments I would like to thank my committee chair Dr. Helena Seli for being a prolific coach and guide during the entire dissertation process. Every conversation pointed me in the right direction, and her ability to effectively and efficiently turn around feedback on every draft continues to confound me. I would like to also acknowledge other committee members Dr. Jennifer Phillips, and Dr. Ana Barcus for your thoughtful feedback and guidance during the process. A very special thanks to all my interview participants (you know who you are) who shall go un- named for confidentiality reasons. I would like to acknowledge my friend and colleague Jack Azagury for re-grounding me back to my original dissertation topic during that fateful lunch discussion in December 2021 by asking me a simple question: Why have you changed your dissertation topic? I would like to thank Jairam Abichandani, Puneet Ahuja, Christophe Beck, Omar Boulos, Scott Hahn, Dr. Chaitali Nangrani, Cecilia Nguyen, Dr. Michael Nguyen, Dr. Arvind Reddy, Marty Rodgers, Manish Sharma, and Mike Sivo for always being my well-wishers, and inquiring about my progress. Thanks for your understanding when I missed social and family events, taking care of my health, and encouraging me to continue on this journey. A special acknowledgment to my dear friend Dr. Sanjay Singh for the bi-weekly Saturday phone catchup that would always include some words of encouragement. Thank you for rooting for me throughout this journey. A very special thank you to Cecilia Nguyen and Puneet Ahuja both for their support during this journey and for serving as my testers for the interview protocol used in my dissertation interview. viii I would like to acknowledge my colleagues – Robert Blessing, Omar Boulos, Vivek Chidambaram, Keely Langkowski, Brett Mossman, Ramoj Paruchuri, Mark Pintar, Mike Preston, Kathy Sanders, Jessica Van Singel, and Ojas Wadivkar for helping me network and arrange my interview participants. Heartfelt respect for my mother Indira Panjwani, and my brother Arun Panjwani, for their unconditional love, and well wishes that supported me through this endeavor. Thank you to my dear sister, Dr. Jyoti Panjwani, for being the first doctor in our family, and serving as a guiding source of inspiration. Last, and most importantly, to my wife Manju who nudged me to get started, my daughter Aarushi, and my son Aarav – thank you for your steadfast support and encouragement. Your many sacrifices over the last three years such as letting me have all the weekends, foregoing vacations, missing fun social events, and above all your constant encouragement have not gone unnoticed and this life-long dream is as much your accomplishment. For those who I may have missed acknowledging, my apologies in advance, and my utmost gratitude. Thank you, Manish Panjwani (mpanjwan@usc.edu | panjwaniman@gmail.com | 770-329-5482) ix Table of Contents Abstract ........................................................................................................................................... iv Dedication ....................................................................................................................................... vi Acknowledgements ....................................................................... Error! Bookmark not defined. List of Tables .................................................................................................................................. xi List of Figures ............................................................................................................................... xii Chapter One: Introduction to the Problem of Practice .................................................................... 1 Background of the Problem ................................................................................................. 2 Field Context and Mission ................................................................................................... 4 Purpose of the Study and Research Questions .................................................................... 6 Importance of the Study ...................................................................................................... 6 Overview of Theoretical Framework and Methodology ..................................................... 7 Definitions ........................................................................................................................... 8 Organization of the Dissertation .......................................................................................... 9 Chapter Two: Review of the Literature ......................................................................................... 11 What is Digital Transformation? ....................................................................................... 11 Critical External and Internal Factors and Practices in Financial Services, Products, and Communications, Media, and Technology Industries ................................ 12 Burke-Litwin Model of Leadership, Change, and Performance ....................................... 30 Conceptual Framework ..................................................................................................... 48 Conclusion: Resources Industry on the Cusp of Digital Transformation .......................... 51 Chapter Three: Methodology ........................................................................................................ 53 Research Questions ........................................................................................................... 53 Overview of Methodology ................................................................................................ 54 The Researcher .................................................................................................................. 55 Data Source: Interviews .................................................................................................... 56 x Data Analysis ..................................................................................................................... 60 Validity and Reliability ..................................................................................................... 60 Ethics ................................................................................................................................. 61 Chapter Four: Findings .................................................................................................................. 63 Participants ........................................................................................................................ 64 Research Question 1: How do C-Suite Executives in Resources Industries Define and Perceive Digital Transformation? ............................................................................... 66 Research Question 2: How do Executives Navigate External Environment Impacts in Driving Successful Digital Transformation in Resources Industries? ............. 78 Research Question 3: How do the Internal Contextual Factors Impact the Executives’ Ability to Drive Successful Digital Transformation in Resources Industries? .......................................................................................................................... 91 Research Question 4. What are the Individual, Team and Organizational Values, Talent and Process Efficiencies that C-Suite Executives in Resources Industries Perceive are Needed to Drive Successful Digital Transformation? ................................ 102 Summary of Results and Findings ................................................................................... 109 Chapter Five: Discussion and Recommendations ....................................................................... 112 Discussion of Findings .................................................................................................... 112 Recommendations for Practice ........................................................................................ 118 Limitations and Delimitations ......................................................................................... 129 Recommendations for Future Research ........................................................................... 130 Implications for Equity .................................................................................................... 133 Conclusion ....................................................................................................................... 133 References ................................................................................................................................... 135 Appendix A: Detailed Conceptual Model ................................................................................... 149 Appendix B: Interview Protocol .................................................................................................. 150 xi List of Tables Table 1: Interview Participant Demographics From 13 Companies …………………………....65 Table 2: Participants’ Comments Related to Definition of Digital Transformation……………..68 Table 3: Recommendations Across Key Barriers to Digital Transformation in the Resources Industry ………………………………………………………………..126 Table B1: Interview Protocol Questions and Probes by Research Questions …………………152 xii List of Figures Figure 1: The Burke-Litwin Model of Organizational Performance and Change……………….32 Figure 2: A Model of Organizational Performance and Change: The Transformational Factors 34 Figure 3: A Model of Organizational Performance and Change: The Transactional Factors …..38 Figure 4: Revised Burke-Litwin Model …………………………………………………………45 Figure 5: Conceptual Model to Drive Digital Transformation Programs ……………………….50 Figure 6: Participants’ Prioritization of the Top Three Factors that likely Drive the Most Impact on Digital Transformation in the Resources Industry ……………………...….92 Figure 7: Summary of A Priori Codes Mentioned by Interview Participants………………….110 Appendix A: Detailed Conceptual Framework…………………………………………………150 1 Chapter One: Introduction to the Problem of Practice Lack of digital transformation heightens the risk of business failure resulting in loss of jobs. In a recent study by Schadler (2018), 38% of organizations indicated that technological changes (e.g., digital transformation) will have the greatest effect on their business decisions over the next year, scoring higher than competition, economics, and politics in terms of impact. Accenture’s research on accelerated digital transformation across 20 industries shows that leading companies in enterprise technology were growing two times faster than most companies, and by doubling down on their technology investments recently, they are now growing five times faster (Daugherty et al. 2021). Digital transformation is defined as the use of new digital technologies such as mobile, artificial intelligence, cloud, blockchain, and the Internet of things (IoT) technologies to enable major business improvements to augment customer experience, streamline operations, or create new business models (Warner & Wäger, 2019). For the resources industry - which covers asset-intensive manufacturing industries such as chemicals, oil and gas, power utilities, and metals and mining companies - this implies a fundamental alteration in the ways of doing business by “redefining business and industry processes and relationships” (Dehning et al., 2003, p. 639). There is evidence that digitally transformed companies are more successful. Over time, digitized solutions can transform a company’s business model by shifting the basis of its revenue stream from transactional sales to sophisticated, value-laden offerings that produce recurring revenue (Ross et al., 2017). By not transforming, companies risk extinction as new disruptive players displace inefficient organizations. The problem of lack of digital transformation in the resources industry is important to address as business leaders increasingly struggle to find talent 2 with digital competencies, build the right innovation culture, and leadership needed for their organizations to remain competitive (Petter et al., 2018). There is a confluence of external and internal factors, such as changing customer expectations, post-pandemic labor shortages, exponential technology changes, and energy transition, that are threatening business disruption in the resources industry. In addition, a large portion of the workforce in the resources industry is from marginalized groups and typically with low levels of education, making this group ill-prepared for the transition to new ways of working in the digital world (Aster Fab, 2014). A shortage of qualified workforce risks the success of digital transformation, further exacerbating existing pressures in the industry. This in turn could lead to business failure which equates to a human loss of jobs and income. There is little research on resources industries specific to the lack of digital transformation. The purpose of this study is to explore critical external and internal factors and practices promising to accelerate digital adoption in resources industries. Background of the Problem The reviewed literature highlights five key success factors that are needed to drive digital transformation that are broadly categorized under information technology (IT), new ways of working, leadership, education, and talent acquisition. The reviewed literature also addresses why it is difficult for organizations in manufacturing industries to accomplish those success factors. Vogelsang et al. (2019) in their study based on 46 expert interviews at 31 manufacturing industries found most interviewees mentioned missing skills which focused on IT knowledge and communication technologies as the key barrier to digital transformation. The key IT skills needed for driving digital transformation are varied and many. Organizations require employees with a broader skill set, including technical, communication, and business awareness 3 (Kappleman et al., 2017). In addition, Colbert et al. (2016) found that managers need a digital workforce, inside and outside of the IT department, that can apply and use technology to innovate and transform the organization. These digitally fluent employees are expected to use technology strategically to problem solve, generate ideas, and work collaboratively with others in virtual environments (Wang et al., 2019). Kappleman et al. (2017) highlighted that finding such employees is challenging, and the competition for talent is increasing. In essence, digital transformation requires a fundamental shift in the way organizations operate and approach work. Barton et al. (2018) contend that agile methodologies have become a popular way for organizations to navigate this transformation, as they emphasize flexibility, cross-functional teams, and iterative development. Furthermore, Deiser and Newton (2013) observed that managers are becoming producers who create and distribute content through social media platforms, with consumers engaging and creating resonance through feedback. This shift highlights the need for CEOs and HR leaders to focus on creating a shared culture, designing engaging work environments, and constructing new models of leadership and career development that embrace digital technologies (Deloitte, 2016). Overall, digital transformation is not just about adopting new technologies but also requires organizations to re-invent themselves structurally to adopt new business models, acquire skills around agile and adopt new ways of working, and adjust culturally to a new workforce to thrive in the digital age (Mihalcea, 2017). Senior leadership teams without digitalization experience are a significant barrier to business model transformation (El Sawy et al., 2016). Bouchikhi and Kimberly (2003) noted that senior leaders often struggle to radically transform the organization's business model when senior leadership teams without digital experience fail to escape the “identity trap” that intimately ties the organization's core competencies to its values, history, collective memory, 4 politics, habits, and emotions. Senior leaders must not only articulate a vision people can rally around but also create the conditions that enable digital maturity, attracting the best talent and bringing out the best in that talent (Kane et al., 2019). Competition for digitally savvy talent has never been higher, but companies’ methods for acquiring and keeping the skilled employees they need are outmoded (Kane, 2019). Digital maturity of human resources management implies a shift from the traditional paradigm of the workplace towards engagement, learning, and development of employees, and the search for talent (Mihalcea, 2017). Building these skills and capabilities around IT, agile ways of working, and leadership, require focus to drive digital transformation, and yet, has received limited scholarly attention and is now an essential context for the study of strategic change (Warner & Wäger, 2019). These factors highlight potential reasons for lack of digital transformation in resource industry where workforce is largely unskilled, especially in IT, new ways of working are difficult to adopt and implement, and large portion of senior leadership has been wedded to traditional operating models and values. In the current environment where the ‘war on talent’ further reduces availability of suitable talent, the path to successful digital transformation in resources industry becomes ever more difficult. Yet, some organizations in this industry appear to be transforming to digital despite these challenges, and this research explores practices that might be contributing to their success. Field Context and Mission The exploratory research focused on the resources industry sector which is comprised of asset-intensive manufacturing companies that serve as the source of materials or feedstock to all other industries. They can be broadly classified into four different sub-groups of industries. 5 1. Chemicals – specialty chemicals, commodity chemicals, gases, and agriculture products that include pesticides. Examples include Dow, DuPont, Monsanto, Huntsman Chemicals, and Ecolab. 2. Energy (Oil and Gas) companies – focused on oil exploration and digging (upstream), retail sales (downstream), transportation and delivery (midstream). Examples include ExxonMobil, Baker Hughes, Chevron, Shell, Conoco-Phillips, Phillips 66, and Murphy Oil. 3. Utilities - Power generation and transmission companies such as Entergy, Oklahoma Gas and Energy (OG&E), Duke Energy, and Enbridge. 4. Metals and Mining companies such as Rio Tinto, Anglo American, Tata Steel, and BHP Billiton. The study focused on exploring the experience of C-Suite Executives in leadership transformation roles who have seen success in driving Digital Transformation. Typical roles of Chief Digital Officer (CDO), Chief Information Officer (CIO), Chief Technology Officer (CTO), Chief Transformation Officer (CTO), Chief Supply Chain Officer (CSCO), Chief Administrative Officer (CAO), Chief Executive Officer (CEO) usually fit this profile for driving large scale digital transformation in most organizations. The study focused on organizations within the four sub-group of industries that comprise the resources industry that are currently driving or have driven digital transformation, are global in their operations, and have a C-suite leader tasked with leading the transformation. 6 Purpose of the Study and Research Questions This study explored critical external and internal factors and practices promising to accelerate digital adoption in resource industries. The research questions that guided the study are the following: 1. How do C-Suite executives in resources industries define digital transformation? 2. How do executives navigate external environment impacts in driving successful digital transformation in resources industries? 3. How do internal contextual factors impact the ability of C-Suite executives to drive successful digital transformation in resources industries? 4. What are the individual, team and organizational values, talent and process efficiencies that C-Suite executives in resources industries perceive are needed to drive successful digital transformation? Importance of the Study It is important to address the problem of lack of digital transformation in the resources industry for several reasons. Exponential technology change is driving digital transformation and companies that do not change risk reduced growth or even failure. Neary et al. (2018), in a study on computer-based job displacement, surveyed 3200 individuals and found that 74% plan to invest in AI technologies, 52% said that the pressure to reduce cost will require them to use AI, and 25% out of 3200 individuals indicated a belief that AI-powered solutions will automate manual and repetitive tasks. Spending on technologies to support digital transformation was forecasted to be $1.3 trillion in 2018, with a compound annual growth rate of nearly 18% through 2021 (IDC, 2017). In their famous study, “The Future of Employment,” Frey and Osborne (2017) noted that 47% of total U.S. employment may be subject to automation. In an 7 asset-intensive industry such as the resources industry, a large portion of the workforce is from marginalized groups and typically with low levels of education. This makes the workforce ill- prepared for learning new digital technologies and new ways of working, and therefore, making it hard to these asset-intensive industries to transform digitally. As such, a shortage of qualified workforce would risk the success of digital transformation, further exacerbating existing pressures in the resources industry. Further, with digital transformation, the jobs of production workers are being disrupted with the rise in use of industrial robots and other automated machinery (Acemoglu & Restrepo, 2018; Graetz & Michaels, 2018). Given the composition of the workforce in resources industries, most of the negative impact of negative growth and business closure will be felt by those most marginalized such as plant workers, field technicians, and rig workers. Lastly, an additional benefit of the adoption of modern technology may accelerate the transition to cleaner energy in the resources industry. There is limited research combining the various studies that lead to solutions to barriers in driving successful digital transformation in resources industries. As Vogelsang et al. (2019) concluded that while their study based on 46 expert interviews at 31 manufacturing industries found five barriers to digital transformation: missing skills, technical debt, individual fear, organizational and cultural factors, and environmental reasons, more fields of action could be further researched. An exploration of better critical external and internal factors and practices capable of transforming businesses in the resources industry ultimately benefits marginalized groups, the companies that comprise the resources industry, and the environment. Overview of Theoretical Framework and Methodology The theoretical framework that guided this study is the Burke-Litwin Model of leadership, change, and performance as it examines an organization at multiple levels including 8 external environment, leadership, management processes, systems and policies, and group and individual motivation as influenced by the work climate (Burke, 2018). Burke (2018) further classified these factors into transformational and transactional. This study and research with C- suite executives led to key insights on various aspects that map to the Burke-Litwin set of factors to help determine what might be the right transformational leadership, organizational culture and climate, and motivation factors that will help drive successful digital transformations in resources industries. The study was implemented using qualitative methodology via individual interviews with C-suite or senior executives in organizations within the resources industry who are responsible for leading change or digital transformation in their organization. Definitions ● Artificial Intelligence (AI) is defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation” (Kaplan & Haenlein, 2019b, p. 17). ● Compressed Transformation refers to a strategy that looks across the entire enterprise’s operations, choosing a parallel transformation program to reimagine and transform end- to-end business processes by harnessing technology, and executing with incredible speed to drive down costs, improve the experience for customers, partners, and employees and deliver value over time. (https://www.accenture.com/compressed transformation defined) ● Digital Transformation is defined as the integration of digital technology into all areas of a business resulting in fundamental changes to how businesses operate and how they deliver value to customers, shape the employee experience, and operate in an innovation culture. (https://enterprisersproject.com/what-is-digital-transformation#q1) 9 ● Energy Transition refers to the global energy sector’s shift from fossil-based systems of energy production and consumption — including oil, natural gas, and coal — to renewable energy sources like wind and solar, as well as lithium-ion batteries (S&P Global, 2020 https://www.spglobal.com/en/research-insights/articles/what-is-energy- transition). ● Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals, or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human- to-computer interaction (https://www.iotforall.com/what-is-internet-of-things). ● Resources industry refers to those groups of industries that serve as the source of raw materials or feedstock for all other product-based industries and are typically classified under the following four sub-groups of industries: chemicals, energy (oil and gas), utilities (power generation and transmission), and metals and mining. These are usually asset-intensive industries with large capital assets such as chemical plants, refineries, mines, power plants, and transmission and distribution networks. Organization of the Dissertation Five chapters are used to organize this study. This chapter provided the reader with the general background related to the lack of digital transformation in resources industries and the key concepts and terminology commonly found in a discussion about digital transformation. Further, it provided a background of the problem of practice, challenges of the resources industry, as well as the review of the Burke-Litwin theoretical framework that was used to guide this explorative qualitative study. Chapter Two provides a review of the current literature surrounding the scope of the study. Topics of leadership, organization culture and change, 10 motivation, and others will be discussed that are required to drive successful digital transformation in resources industries. Chapter Three details the choice of participants, data collection, and analysis. In Chapter Four, the findings are described and analyzed. Chapter Five provides recommendations for practice to support the implementation of digital transformation in resources industries. 11 Chapter Two: Review of the Literature The resources industry, which is highly asset intensive, has lagged in the adoption of digital transformation due to various challenges related to the capital-intensive nature of the industry, technology integration between OT and IT, and skills shortage. This chapter begins by exploring critical external and internal factors and practices in other industries that have seen success in their digital transformation. It explores similarities and differences in the resources industry specific to contextual and individual factors as discovered in the literature review. The chapter then presents the theoretical framework and its relevance to the study, followed by the conceptual framework informed by the Burke-Litwin model of change. The conclusion summarizes the key takeaways from the literature review and how it informs the study. What is Digital Transformation? Digital transformation is defined as the use of new digital technologies such as mobile, artificial intelligence, cloud, blockchain, and the Internet of things (IoT) technologies to enable major business improvements to augment customer experience, streamline operations, or create new business models (Warner & Wäger, 2019). Also, the definition of digital transformation is different for different industries and so it has to be specified in the context of the industry, technology applicable to those industries, and evolving innovation in automation of business processes in those industries. The Enterprisers project (2016) provides an overall understanding of digital transformation in general terms as the “integration of digital technology into all areas of a business resulting in fundamental changes to how businesses operate and how they deliver value to customers” (The Enterprisers Project, 2016, https://enterprisersproject.com/what-is- digital-transformation#q1). Beyond technology, the enterprise project definition also highlights digital transformation as a cultural change that requires organizations to continually challenge 12 the status quo, experiment often, and accept and learn from failures. With respect to business process, the Enterpriser’s project highlighted the need for organizations to have the ability to completely redesign long-standing business processes that companies have operated on for years, and that some were even were built upon, to shift to completely new business processes and practices, some of which may not have been completely defined. This study explored critical external and internal factors and practices promising to accelerate digital adoption in resources industries. Given resources industries are highly asset- intensive, digital technologies will have a significant impact on the operations of the core business in the refineries, plants, and mines which present different challenges due to automation of operations, skills, and labor impact. Due to the capital-intensive nature of investments required to embed technology into assets, challenges with the integration of OT and IT, driving change in complex business processes, and lack of skills in the labor pool, adoption and adaption have been limited in this industry (Cortada, 2004). Critical External and Internal Factors and Practices in Financial Services, Products, and Communications, Media, and Technology Industries This section reviews critical external and internal factors and practices in other industries which have seen some success in digital transformation. The literature review points to those industries leading the uptake and benefits of digital technologies to be in those industries such as financial services, products industries, or technology industries that focused more on customers, and services, and did not have a large manufacturing or operations component (Dehning et al., 2003). A successful example of digital transformation that crosses across the industrial consumer goods industry is that of ThyssenKrupp, a German company that manufactures, sells, services, and maintains elevators. With competition strong on service maintenance, and the quality of 13 services expected by consumers, ThyssenKrupp decided to create a digital maintenance system called MAX that collected end-to-end data on elevator performance, and one that could analyze upcoming issues and thereby, service the elevators for predictive problems even before the customers could experience the outage. This not only increased customer satisfaction and created a quality brand image, it also generated new sources of maintenance service contract revenues. In other words, “ThyssenKrupp digitally transformed their business model by developing an innovative maintenance management system. ThyssenKrupp’s MAX system delivered a data- driven maintenance system which created new benefits for their customers and in turn generated a new revenue stream” (Schallmo & Williams, 2018, p. 24). Digital Transformation in Financial Services Industry The financial services industry typically comprises institutions offering banking, insurance, and investment services (Van den Berghe & Verwiere, 2001). However, research conducted by Van den Berghe and Verwiere (2001) showed that these segments of the financial services industry are converging which is serving as an external factor driving transformation in the industry. Financial convergence, as defined by Van Den Berghe and Verwiere (2001), includes all types of interfaces between suppliers and demand for all types of financial products and services in the financial services industry. Part of this interface is driving an institutional change where “financial conglomerates” (Van den Berghe & Verwiere, 2001, p. 173) are starting to crop up, where these are companies that provide banking, insurance, and investment services. In a survey of 612 firms across 10 countries in the financial services industry, Zhu et al. (2014) found that the biggest driver of digitalization or e-business was technology readiness, followed by financial resources, global scope, and regulatory environment. Company size matters and, 14 large companies were slow in their adoption, while external competition intensity did drive up the adoption of change (Zhu et al., 2014). In examining the strategic role of IT investments in various industries, Dehning et al. (2003) found that the growth impact, based on stock prices, was significantly larger in financial services firms versus manufacturing firms due to the information intensity of the financial industry. Also, Dos Santos et al. (1993) found that early adopters of technology or companies that made innovative IT investments saw positive stock price growth. Im et al. (2001) examined the growth of companies’ stock prices and concluded that the industry variable (financial services companies versus non-financial companies) served as a proxy for industry-level information intensity. The financial services industry is more about products and services that are not physical in nature and are therefore more suitable for the adoption of digital transformation as driven by external factors of convergence, regulations, and led by the adoption of new technologies. In exploring open systems, Zachariadis and Ozcan (2017) articulated that the application of open application programming interfaces (API) gives rise to new organizational structures and digital platform business models and its applicability has been a good fit for the financial services industry in this digital age, which has resulted in good uptake. Blakstad and Allen (2018), in their book Fintech Revolution, discussed the evolving landscape in the finance industry with a greater focus on customers and the use of technology that has created alternate financial models allowing those institutions that do leapfrog traditional financial services organizations. This has brought down barriers around financial services companies and driven business transformation, integrations across financial products, and consumption of those products in these new fintech 15 services where more people can access financial services without really needing a bank or financial institution (Blakstad & Allen, 2018). Digital Transformation in Consumer Packaged Goods Industry The consumer packaged goods industry (CPG) is a category of companies that manufacture and sell their products to direct consumers, such as food production, packaged goods, clothing, beverages, automobiles, and electronics (Hayes & Scott, 2021). Due to extensive competition on price, quality, and substitute products, the CGP industry relies on advertising, marketing, and brand differentiation to sustain the business and drive growth, and the most powerful force across all aspects of the consumer goods industry is technological advancement (Hayes & Scott, 2021). In a post-Covid McKinsey study on the retail industry, it was found that Digital (data, mobile, and the Internet of Things [IoT]) ubiquity has been the most important trend that is revolutionizing how consumers and brands learn about and engage with each other (Kopka et al., 2020). Also, Kopka et al. (2020) found that due to stay-at-home mandates during COVID-19, digital engagement and uptake have increased across all platforms. Technology advancement has revolutionized supply chains in the consumer goods industry by driving operational efficiencies, creating new sales and marketing channels, and driving personalized and direct digital advertising capabilities. Not only do consumers research, purchase, and engage with brands digitally, and companies in this sector, consumers participate in continuous consumer feedback and on-demand access to consumer data in real-time (Hayes & Scott, 2021). Reinartz et al. (2019) illustrate this with a simple example of how Amazon is not only the largest online retailer and retail platform but is also competing with Google to become the most extensive product search engine (McGee, 2017). Consumers use these platforms to browse categories, compare prices, and find products to purchase, and in return provide Amazon 16 and Google with significant power to influence purchaser decision-making of consumers (Reinartz et al, 2019). As such, connectedness with consumers, and interoperability of consumer products have become key selling points for companies in this sector (Hayes & Scott, 2021). In summary, based on the literature review, four trends are driving the successful uptake of digital transformation in the consumer goods industry. First is consumer centricity and how they interact with the consumer goods companies by demanding not only the lowest price, and best quality but more personalization and providing continuous feedback through various communication channels including social media platforms which may impact brands. Second, the supply chain for the CPG industry needs to not only be efficient and effective but also needs to be integrated across the value chain so that the product life cycle which is the conversion from raw materials to the end consumer product is shortened (Knezevia, 2020). Third, producers not only need to improve product quality, but they also need to personalize them to meet consumer demands. Lastly, the retail industry has become transformed from traditional brick and mortar to online retailers or e-tailers such as Amazon, and eBay which have implemented digital platforms and technology that create multi-channel or omnichannel approaches and access to consumers who can directly order products over the internet (Cortada, 2003). Digital Transformation in Communications, Media, and Technology Industry Communications, Media, and Technology (CMT) include a broad range of companies that are further divided into subsectors such as communications that include publishing, social platforms such as Facebook (now Meta), media and entertainment companies such as Netflix, and technology companies that include hardware such as Dell, IBM, semiconductors such as Intel, software such as Microsoft, and telecommunications such as AT&T (Chen et al., 2022). This group of industries is focused on new technologies (Chen et al., 2022), and as such, are not 17 only the driving force behind the digital transformation (Kopka et al., 2020) but also the beneficiaries of it. For example, the transformation of the semiconductor and hardware industry started in the 1990s with the use of computer modeling in the design and manufacture of smaller and more efficient chips with higher processing power (Cortada et al., 2003). The IT services industry buoyed by technological advancements in semiconductors, hardware, and software “redefined many activities, products, and practices of existing industries through the implementation of computer-based uses of IT” (Cortada et al., 2003, p. 225). Stating that the number of companies that reinvented themselves due to technology industry digital advances is boundless, Cortada et al. (2003) cite many examples such as the toy industry including products with embedded computer chips within their products such as talking dolls; the fast food industry now had computer-controlled cooking of fries and hamburgers; and, the automobile industry makes cars a mobile data center with software monitoring, driving, and serving up information in digital dashboards. Companies reinvented themselves from the old to this new digital economy in the new economy by not only improving current products and services but also adding new information-based services like GE which integrated many of its manufacturing divisions using data across them to create value with new information-based services for its customers (Cortada et al., 2003). The World Economic Forum’s Digital transformation of industries 2016 project report highlighted the four digital trends reshaping the media and entertainment industry are demographics, consumer expectations, ecosystem transformation, and technology. The digitization of the media industry has been shaped by consumer expectations and behavior from the younger generation who demand instant access to all types of content, anytime and anywhere. They are not only consumers of media and entertainment content, very adept at 18 identifying fake news or spin, but are also content creators and curators of content on various media platforms such as magazines, mostly internet-based applications, and communicate through these digital channels. The communication channels have been transformed using high bandwidth and telecommunications technology advancements. The ecosystem of the media landscape has been transformed and challenged by startups, and new legal frameworks, all driven by technology trends of mobile and internet penetration through open source and free software funded by advertisements, made pervasive via connected devices and cloud computing (World Economic Forum, 2016). This digitization of media and integration with mobile technology and multiple screens through connected devices has created a new form of connected viewing experiences that has transformed the relationship between the audiences and media in the digital space (Holt & Sanson, 2013). The disruption of traditional models of television (TV), cable, DVDs, and VHS, to new models, is complete. Due to enhanced communications technology, multiplatform, socially networked, and cloud-based platforms have emerged and the distribution and consumption of films, video games, news, sports, and television are now accomplished over digital distribution via streaming, subscription video on demand (SVOD) such as Netflix, over the top (OTT) services such as Amazon Prime Video, Free or Advertisement video on demand (FVOD or A VOD), Pay-per-view (PPV) on TV networks, and Electronic sell through or download-to-own (EST or DTO) services such as Apple’s iCloud (Holt & Sanson, 2013). The communications, media, and technology industry continues to create new technology via R&D and drive further adoption of digital trends not only in its industries but across other industries driven by a new generation of consumers with new consumer behaviors and expectations. 19 Digital Transformation in Resources Industry: Energy, Chemicals, Natural Resources (Metals and Mining), and Utilities The Resources industry comprises a group of industries (Chemicals, Energy, Natural Resources - Metals & Mining, and Utilities) that fall under the manufacturing industries given the asset-intensive heavy manufacturing nature of these industries. Manufacturing is the process of turning raw materials or parts into finished goods using machinery, human labor, tools, and chemical processing (Kenton et al., 2021). As such, resource industries are central to the modern world economy. Savastano et al. (2019) highlighted five key factors that impact digital transformation in manufacturing industries: technologies such as 3D printing, or digital fabrication; digital technology tools for advanced manufacturing systems such as smart factories, open-source collaboration platforms, and industrial internet of things (IIOT); IT that digitally enhances the ecosystem such as IT systems, smart sensors, web technologies, cloud computing, and big data analytics; innovation processes that drive digital maturing of processes such as supply chain integration; and, Digital design tools such as web-based rapid prototyping tools, and CAD/CAM tools. Also, there are sustainability implications of digital transformation in resources industries and, combined with the “economic, ecological and social aspects that are often referred to as the triple bottom line (TBL) of sustainability” (Savastano et al., 2019, p. 16). The chemicals industry is a very diverse industry engaged in the manufacturing of thousands of substances that fall under the categories of basic or commodity chemicals such as calcium and sulfur; specialty chemicals such as paints, adhesives, sealants, and coatings that are derived from basic chemicals; industrial or pharma derivatives like pesticides, fertilizers; and, consumer care products like soaps and detergents (Sigman et al., 2001). Chemists, chemical engineers, lab technicians, and plant workers are required to produce over 70,000 products 20 consumed by automakers, agriculture, energy, cosmetics, chemicals, and food and beverage industries (Boyle, 2022). The unique aspect of process manufacturing in the chemicals industry is the concept of closed-loop processes where raw materials flow continuously or semi- continuously into the chemical plant from entry to exit (Cortada, 2003). As such, visibility to workers is lacking and the processing of products is mostly controlled by sensors, instrumentation managed through a control room where all the process instrumentation is located and maintained, and computer chips including related hardware and software were embedded from early on in the 1960s and 1970s into these closed-loop systems that were all tied into the control room (Cortada, 2003). While this was not easy, most chemical plants had started to have to link shop floor instruments together by way of digital technology of the 1960s and created these highly computerized control rooms. The plant design and engineering tools have not changed until today, and more systematic use of modern technology and engineering tools in chemical plants and operations is in the very early stages. DuPont, a leading chemicals company, led a transformation effort in the 2000s to create a more integrated operation using simulation software from Aspen Technology, enterprise resource planning tools from SAP AG, and a modernized supply chain (Cortada, 2003). Most of the efforts were still delivering back office digitization, and internet-enabled sales, service, and trading platforms such as e-Chemicals, ChemConnect, and others started to make their entry to contribute to e-transactions for the Chemicals industry by the end of 2000 and R&D was another area that leveraged modeling tools, and benefited from digital technologies to speed up the complex processes and calculations (Cortada, 2003). The natural resources industries include metals and mining, pulp and paper that use extraction of metals, minerals, and forest reserves to create products such as industrial metal 21 products, jewelry, gemstones, steel, and aluminum used in building infrastructure, and automobiles (Mansa, 2022). The huge labor intensity of the steel industry offered computers and microprocessors to be embedded in new equipment in plants for the benefits of digitalization to be felt, however, the uptake of digital technology stood in sharp contrast to that of the other manufacturing industries in the Automobile industry (Cortada, 2003). Also, Cortada (2003) further highlighted that the initial uptake was in back office applications such as accounting, payroll, sales tracking, and inventory control, and the slow uptake to move beyond the informational stage to web-based buying which required gathering of real-time data on production schedules, inventory, and prices for all products was difficult at the touch of a button because of end to end integration of old technology like EDI (Enterprise Data Interface). In mining, taking advantage of remote and autonomous operations, robotics, digitally enhanced equipment, sensor data, predictive analytics, and machine learning, in other words, digital transformation, can provide a single infrastructure that brings a new level of agility and automation for the mining industry that streamline operations (Leonida, 2021). Rio Tinto, an industry leader in the mining industry which owns the largest automated haulage systems, has led the charge on digital transformation by using advanced data analytics and communications infrastructure to create a Mining Automation System (MAS) and used digital mines (a simulation replica of their mines) for agile and efficient decision making (Jones, 2018). The energy industry includes companies that produce and supply energy – fossil fuels, renewals, and power – to other industries and end consumers. Cortada (2003) explained the four parts of how the energy industry is structured: The first [is] production, which involved the location and extraction of natural gas and crude oil from the earth. The second [consists] of refineries, which [manufacture] such finished 22 products as gasoline, jet fuel, kerosene, and other liquid, petroleum-based products. This second cluster was often called the Petrochemical Industry. A third piece of the industry [consists] of firms or divisions of companies that [market] and [sell] products, both wholesale and retail. Gas stations fit into this segment of the industry. The fourth component [is] transportation, which in the United States usually [consists] of all the pipelines that [move] oil from wellheads to refineries (as well as ships for foreign oil) and by truck and pipe to retail outlets. Over the past century, the largest firms in the industry have generally attempted to play an active role in each of the four segments. (p. 167) An integrated energy company like ExxonMobil is engaged in all activities across the value chain of a Resources industry by drilling and producing oil, refining and delivering the refined product through pipelines, mining coal, and nuclear, and producing specialty chemicals through the refining of oil and gas (Chen et al., 2021). From a digital transformation and the use of new technology, each segment presents different opportunities. For example, in production to determine where to drill and extract oils requires data analytics of the geological composition of the location. After drilling, reporting on offshore drilling, optimization of drill bit life, and reduction in testing efforts, all require the use of technology and similar to other resources industries, the creation of a central remote control room to monitor these activities (Cortada, 2003). Refining is the closest it gets in this sector to manufacturing where the same concepts of closed-loop processes require control instruments, monitoring, and management to optimize production (Cortada 2003). In the wholesale and retail segment, software from the retail industry was easily adopted to digitize the payments and billing processes. Lastly, in the fourth segment of transportation, as Cortada (2003) highlighted, the supply chain was rewired to reduce cost and drive efficiencies in delivering the product through pipelines, trucking, and tied to business 23 administration, accounting, finance, and audit systems. The use of technology in modeling and automation was adopted to move away from manual tasks to open and close valves and switches, check tank levels, and read meters in the pipeline segment (Cortada, 2003). Energy has become an example of an industry that, by the 2000s, effectively leveraged technology, but only in collaboration with industry-wide coordination of such activities such as prospecting (oil and gas exploration), and transportation via rewiring of the supply chain, and procurement activities globally driven primarily by two technologies–the internet, and telecommunications (Cortada, 2003). The Utility sector includes companies that provide electricity, gas, and water to end consumers or industries and also operate as transmitters or distributors of power (Murphy et al., 2022). While the utilities are privately held companies, they are considered part of the public service infrastructure and, therefore are, highly regulated by the government. For the Utility industry, there are several digital transformation-driven products such as Smart homes, energy transition, and smart meters all of which drive efficiencies, better customer care, and sustainability (Glickman & Leroi, 2015). Digital transformation offers a massive opportunity for utilities, but success will require a significant investment in new talent and capabilities and careful prioritization. As the evidence suggests, most of the resources industries have applied digital technologies primarily in the areas of product development (Extraction and geological analytics in energy, R&D in chemicals, mining, and metals, amongst others), manufacturing automation and supply chain, and some simulations in mining, metals, and chemicals (Cortada, 2003). Cortada (2003) summarized the resources industry quite well when he stated that “all companies adopted digital technology for and as an extension of ongoing practices. There is little or no 24 evidence that the intent was to change radically any existing process or business model” (p. 191). It is also important to highlight that there is a structural separation between operations technology and information technology in resource manufacturing. This is due to the gap in technical interoperability between plant-level controllers and enterprise resource planning systems. This is primarily at the human-machine interface (HMI) level, and at the application- machine level (AML) interfaces where the new industrial development of commercial dialog systems is via robust interfaces strictly defined for specific applications, lacking the adoption of new interfaces that work at various application domains (Griol et al. 2012). The digital transformation of manufacturing, also called Industry 4.0 (IX.4), has found some interest within the academic and practitioner community, and the advantages of digital transformation are remarkable in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies have made advances or developed strategies and capabilities necessary to achieve superior performance to obtain a competitive advantage (Savastano et al., 2019). Individual and Contextual Factors that Drive Digital Transformation The resources industry has undergone a significant downturn during the pandemic due to a lack of travel, and consumption of various products that this industry provides products and services. The impact on oil and gas has been significant as has been seen in the depressed performances of most of those companies. While digital technologies are considered a major asset for leveraging organizational transformation, given their disruptive nature and cross- organizational impacts, to achieve successful digital transformation, changes must occur at various levels within the organization, including the redesign of the core business processes, availability of resources, reskilling of the workforce with digital capabilities, the right leadership, 25 and implementation of a collaborative digital culture (Nadkarni & Prügl, 2021). The literature review of other individual and contextual factors that drive digital transformation may be summarized under the following six categories – technology, skills, ways of working, leadership, talent, and education. Technology IT-enabled structural change is occurring at breakneck speed in a great number of industries due to exponential growth in technology applications, maturing understanding of the role of IT by organizations, and other tangible factors such as the knowledge worker, business process redesign, and organizational restructuring, and inter-organizational relationships (Dehning et al., 2003). In a study of 112 IT investments, made by companies, Chatterjee et al. (2002) argued that the technology infrastructure investments that created robust technology platforms resulted in an abnormally positive impact on companies' transformation as they could be leveraged by a variety of existing and future IT applications. These new technologies are transforming and fundamentally redefining the business and industry processes at both the company and industry levels (Armstrong & Sambamurthy, 1999; Chatterjee et al., 2001). Further, companies that use IT to transform introduce radical business model change that disrupts industry practices and traditional business models giving the transformed company a leading position in the market with high, sustainable returns (Dehning et al., 2003). Furthermore, Rayna and Striukova (2016) described disruptive technologies as the “bearer of radical changes in business models and ecosystems” (p. 214). Digital technologies, in particular, have led to major shifts in the industries that have adopted them, and the fourth wave of technological advancement, also called Industry 4.0 is getting significant attention, the core of which is a smart factory that combines optimized industrial manufacturing process with cutting edge technology 26 such as internet-based platforms, cloud, data, cyber, and allow for collaboration between man and machine (Savastano et al. 2019). Savastano et al., (2019) also contended that the wave of disruptive technological innovation is driving a cultural shift, that is forcing companies to think about redesigning their business processes and models in a way that they are not only collaborating internally but integrating across the value chain with the ecosystem of partners. Skills According to the Organization for Economic Cooperation and Development (OECD) Survey of Adult Skills on the digital literacy skills of workers ages 16-64 across all industries, nearly one-third (31%) of workers lack digital skills (OECD Survey of Adult Skills, 2012-14). In a recent study by Schadler (2018), 38% of organizations indicated that technological changes, e.g., digital transformation, will have the greatest effect on their business decisions over the next year, scoring higher than competition, economics, and politics in terms of impact. Business leaders increasingly struggle to find talent with digital competencies, the creation of the right culture in companies, and the leadership needed for organizations to remain competitive (Petter et al., 2018). Some organizations have found that online multiplayer gaming, and engaging in hackathons promote skill-building and the learning of creative, technology, and collaborative problem-solving skills that are relevant to the digital workplace (Hernandez, 2017; Pagliery, 2014; Rubenfine, 2014). As this evidence suggests, pure IT skills are not the only skills that are required to drive successful digital transformation. While there is a view that technology displaces workers, Wheelan (2019) in making the case for productivity in human capital suggested that while technology does displace workers in the short run, it does not result in mass unemployment in the long run. It creates new jobs elsewhere and results in more prosperity as 27 educated workers will fare better in a process described as creative destruction by economists (Wheelan, 2019, p. 139). Leadership Technology and skills lead to productivity and improved quality of work, but without strong and effective leadership that drives effective business strategies that exploit digital technologies, no transformation can be successful (Cortada et al., 2003). Noel M. Tichy, whose studies on leadership were done in the context of many business changes and applied technologies, observed that leaders decide on what needs to be done, and also pick the right teams to make things happen (Tichy, 2002). Laudien and Daxböck (2016) noted that managers tend to make use of prior experience, favoring strategic choices they are familiar with over unfamiliar options that could achieve transformational change (Gavetti & Levinthal, 2000). As organizations drive transformational change, they require strong leaders at the helm. Rogers (2016) argued that “digital transformation is fundamentally not about technology, but about strategy” (p. 308), meaning that senior leadership teams must find ways to capitalize on new and unexpected business model innovations that optimize customer needs and experiences. Government leadership is also needed to drive change via policy and incentives, especially in the case where environmental benefits are seen in the case of the energy transition for the resources industry. There is also a role of government and policymakers in driving any form of change in the corporations of nations. In the words of Roger Ferguson, Jr., former vice chairman of the board of governors of the Federal Reserve, Policymakers who fail to appreciate the relationship between the relentless churning of the competitive environment and wealth creation will end up focusing their efforts on methods and skills that are in decline. In so doing, they establish policies that are aimed 28 at protecting weak, outdated technologies, and in the end, they slow the economy’s march forward. (Wheelan, 2019, p. 191) Ways of Working To drive digital transformation, companies also need to re-invent themselves structurally to adopt new business models, which require skills around agile (Mihalcea, 2017), and new ways of working. Barton et al. (2018) contended that agile development methodologies such as Scrum and Lean software development are popular ways organizations are navigating digital transformation. Agile software development methods are typically characterized by cross- functional teams, flexibility, and autonomy within teams, an iterative approach to understanding user needs and quickly delivering products, and encouraging constant feedback. In this digital re- invention process, managers become producers who create content and distribute this content as stories through social media platforms. The consumers engage with responses that create resonance and engagement (Deiser & Newton, 2013). CEOs and HR leaders need to shift their focus to understanding and creating a shared culture, designing a work environment that engages people, and constructing a new model of leadership and career development (Deloitte, 2016). Education All of the above categories, IT, skills, leadership, and agile ways of working, require a different focus from academia to help with building capabilities for a digital transformation which has received limited scholarly attention in the context of driving strategic change (Warner & Wäger, 2019). Scholarly attention would also then drive educational intervention in this area. Though a recognized digital divide exists across generations, specifically around how digital natives and non-natives learn and work, education offers one of the key mechanisms in addressing the digital skills gap. However, the presence of technological resources in schools and 29 the high performance of the so-called Technology Generation or Generation Z are not enough to develop students' digital competence (Francisco-José et al., 2016). Teachers' Information and Communication Technology (ICT) competencies remain a crucial element for educational development. These can be understood as the suite of necessary skills and knowledge that teachers must possess to make more integrated use of these technological tools as educational resources in their daily practice (Suárez-Rodríguez et al., 2012). Continuing education curricula should be focused on helping reduce the divide between digital natives and non-natives (Prensky, 2001). In a study of workforce readiness in IT fluency with data collected from a large sample of freshmen in 2001, and a random stratified sample of seniors in 2005, Kaminski et al. (2009), found that basic IT knowledge and technology skills such as word processing, presentation tools, and web browsers were significantly higher while more advanced digital skills such as database management, web animation, programming, digital video, and audio rated significantly lower. Talent Kane et al. (2017) reported that one of the most critical challenges in driving successful digital transformation, and one that most companies struggle with, is finding the right talent and then retaining those people by designing career paths that meet their needs. Seventy percent of the more than 3,700 executives, managers, and analysts surveyed agreed that their organizations needed a new or different talent base to compete effectively in a digital world (Kane et al., 2017). Organizations can deploy two strategies to build digital technology skills - attracting digital talent and developing digital talent. Training methods such as gamification lead to skills needed around problem-solving, collaboration, and experimenting with new ideas (Hernandez, 2017). Training on new ways of working such as agile methodologies is also needed. One of the other aspects that in-demand talent looks for is the brand of the employer (Sommer et al., 2017). A 30 study by Mihalcea (2017) revealed that in an open talent economy, the employer brand is very important in the recruiting and retention of high-potential employees and must be focused on learning and leadership development, mobility, rewards, and competency systems. In summary, employer branding makes an organization attractive to its current and future employees (Maxwell & Knox, 2009). Kane (2019) went as far as proposing that companies need to focus on people who are the real key to digital transformation and business issues to adapt and compete in the digital age. In conclusion, the six categories of internal contextual factors – technology, skills, ways of working, leadership, talent, and education – may be called the basic building blocks required to drive digital transformation in the resources industry. Of these culture, operations technology integration challenges, ways of working, and talent shortage are most applicable to the resources industry. Leadership, and information technology skills are applicable across other industries as well. Burke-Litwin Model of Leadership, Change, and Performance To build a model that describes the causes of organizational performance and change, one must first understand how organizations function and then understand how organizations might be changed (Burke & Litwin, 1992). W. Warner Burke and George H. Litwin suggested causal linkages that affect performance and how change occurs as a result. Change is depicted in terms of process and content, with both transformational and transactional factors. Transformational change is driven by external factors that impact an organization’s mission and strategy, leadership, and culture. These transformational factors then impact transactional factors such as structure, management practices, systems, and climate. Together, the transformational and transactional factors impact motivation that affects performance (Burke & Litwin, 1992). 31 The Model Figure 1 depicts the model where the role of transformational and transactional factors are closely tied to the concepts of culture and climate. Burke and Litwin (1992) clearly distinguished between the set of organizational variables that influence and are influenced by climate – typically the transactional level of human behavior and interactions; and, those that are influenced by culture – the transformational factors that fundamentally change the culture of the organization. There are 12 boxes with bidirectional arrows that show the influences of factors or variables on each other. The model is built upon systems theory (Katz & Kahn, 1978) where the external environment box represents the input and the individual and organizational performance box represents the output. The model accounts for key variables at the total system level, with variables such as mission, strategy, and culture, at a group or local work unit level (climate), and at an individual level with variables such as motivation, individual needs, and values and task- individual skills match (Burke & Litwin, 1992). 32 Figure 1 The Burke-Litwin Model of Organizational Performance and Change Note. This figure shows the 12 boxes with each of the factors of the original Burke-Litwin model. From “A Causal Model of Organizational Performance and Change” by Burke, W.W., & Litwin, G.H., 1992, Journal of Management, 18(3), p. 528. (Retrieved from: https://i1.wp.com/odhenetwork.co.uk/wp-content/uploads/2012/08/org- dev.png?resize=500%2C705) 33 The model is causal which is denoted by the variables with bi-directional arrows which implies that a change in one variable causes a change in the chain of the connected variables even though they may not be directly connected. Also, the model is two-dimensional and closed loop demonstrating that organizational change that requires a company to change business strategy is originated from external environment impacts, more than any other factor. As such, in the case of large-scale total organizational change, mission, strategy, leadership, and culture carry more weight than structure, management practices, and systems. This implies that just leaders communicating the new strategy are not enough to drive effective change; culture change has to be planned and aligned with strategy and leadership behavior (Burke & Litwin, 1992). These variables, when changed, impact the total system and therefore carry more weight. When the structure is changed it may or may not impact the total system depending on where the structural change is implemented. In summary, the 12 primary variables of the model need to be considered, including their interactions, to predict the total behavior output of the organization. Transformational Factors Transformational is defined as those “areas in which alteration is likely caused by interaction with environment forces (both within and without) and will require entirely new behavior sets from organizational leaders” (Burke & Litwin, 1992, p. 529). Figure 2 shows the transformational factors of change – external environment, leadership, mission and strategy, and organization culture - that constitute the upper half of the Burke-Litwin model and that ultimately impact the outcome which is the individual and organizational performance. Organizational change is multilayered, with the external environment interacting with the transformational aspect of change, affecting change's transactional aspect (Burke, 2018). 34 Figure 2 A Model of Organizational Performance and Change: The Transformational Factors Note. This figure shows the transformational factors of the Burke-Litwin model. From “A Causal Model of Organizational Performance and Change” by Burke, W.W., & Litwin, G.H., 1992, Journal of Management, 18(3), p. 530. 35 External Environment The external environment refers to any outside condition or situation such as financial conditions, pandemics, market disruption by new business models, and political and government events, that influences the performance of an organization. As Burke (2018) highlighted that “Organizational change stems from environmental impacts than from any other factor – it is an evolution versus a revolution” (p. 228). Costanza et al. (2015) suggested that an adaptive organizational culture increases the chances of survival in companies because it encourages proactive attention to environmental threats and creates structures to address them. Leadership Leadership consists of that team of senior executives, often called the C-suite, that provides overall direction and serves as behavioral role models for the rest of the organization including the perceptions that the employees form of the leadership values and practices (Burke & Litwin, 1992). Burke and Litwin (1992) in their model of causal change differentiated between leadership and management where leadership lays out the mission and strategy and creates the organizational culture, versus managers who execute the strategy and create the work climate driven by performance incentives. Organizational transformation requires a change leader who personally identifies with the change that is needed, is completely aligned with the organization's transformation mission, has a leader-follower relationship with employees, and drives improvement to what already exists by creating a climate of change (Burke, 2015). Further, as Kezar (2011) expanded, change leaders must lead change through four lenses of human resources, structural, political, and symbolic leveraging change models and multidimensional frameworks around social cognition, teleological, dialectical, and cultural change models. 36 Mission and Strategy Mission and strategy are what the top management believes it has declared as the mission of the organization typically in a mission statement, and the strategy is about how they expect to achieve the mission, and what the employees believe is the purpose of the organization (Burke & Litwin, 1992). The foundation for any company’s transformation is values, vision, strategy, and execution where values define how a company operates on an innate level – shaping daily behavior and influencing decisions, vision enables a company to determine where it is headed, and strategy sets overarching goals so that the values and vision can produce results, and execution of the strategy delivers the outcomes (Austin & Presley, 2016). Organizational Culture Burke and Litwin (1992) defined culture as a “collection of overt and covert rules, values, and principles that are enduring and guide organizational behavior” (p. 532). This forms the basis for the meaning system of how to do things for the organization members. Culture, which is difficult to articulate, "is reflected in the symbolic action approach, in which managers create change by modifying organizational members' shared meaning" (Kezar, 2011, p. 51). As mentioned earlier, adaptive organizational culture proactively addresses external threats and these include social control whereby you can change member behavior through reward and incentive systems. This is how “culture can explicitly be used to influence its members' perceptions, values, and behaviors” (Costanza et al., 2015, p. 363). Transactional Factors Transactional is defined as those primary ways of altercations that are “via short-term reciprocity among people ad groups at the work unit level” (Burke & Litwin, 1992, p. 530). At the work unit level, these interactions form the climate of the organization. Figure 3 shows the 37 transactional factors of change – management practices, systems, individual needs and values, motivation, work unit climate, structure, task requirements, and individual skills and abilities – that form the lower half of the Burke-Litwin model of change (Burke, 2018). The transformational aspect of change requires leaders who define strategy and culture, whereas transactional change requires managers who manage and execute the strategy (Burke & Litwin, 1992). 38 Figure 3 A Model of Organizational Performance and Change: The Transactional Factors Note. This figure shows the transactional factors of the Burke-Litwin model. From “A Causal Model of Organizational Performance and Change” by Burke, W. W., & Litwin, G. H., 1992, Journal of Management, 18(3), p. 531. 39 Management Practices Management practices are the way managers utilize human and material resources available to them to execute the organization’s strategy (Burke & Litwin, 1992). Burke and Litwin (1992) refer to a cluster of specific behaviors that managers demonstrate to encourage or inspire subordinates. To be successful, leaders must be able to organize groups of people and manage them to achieve the strategy. How managers respond to change, and how they specifically behave is key to followership and therefore paramount to driving change in the organization, and a successful manager creates a climate that is clear, transparent, fosters team spirit, and provides opportunities for accomplishment (Burke, 2018). A common tenet for all leaders to go by is that “if no one is following you, by definition, you are not leading” (Austin & Presley, p. 1). Work Climate Work climate is what members of a local unit feel, experience, and expect collectively that affects their relationships with each other, their supervisors, and other work units within the organization (Burke & Litwin, 1992). Based on 80,000 interviews of managers in over 400 companies, Marcus Buckingham and Curt Coffman (1999) highlighted the direct link between employee opinion, engagement, and business unit performance. Managers create this work climate and people follow leaders who offer trust, compassion, stability, and hope (Rath & Conchie, 2008). Structure Burke and Litwin (1992) defined structure as “the arrangement of functions and people into specific areas and levels of responsibility, decision-making authority, communication, and relationships to assure effective implementation of the organization’s mission and strategy (p. 40 532). A structure that creates a culture of communication is critical to organizational success. Cultures of communication reflect trust, widespread participation in decision-making, openness, candor, and one that embraces diversity (Dozier et al., 2002). Systems Systems, as a category, cover the standardized policies, processes, and mechanisms that facilitate work and are primarily manifested in an organization’s reward systems, management information systems, and various control systems such as performance appraisal, goal, and budget development, and human resource allocation systems (Burke & Litwin, 1992). Though culture and systems affect one another, Burke and Litwin (1992) believed that culture has a stronger influence on systems and vice versa. Kerr and Slocum (1987) provided data that suggested a strong linkage between corporate culture and the organization’s reward system and how the reward system is a key component of and how it can also be used to change the culture. This thought can be extended to say that the reward system also influences the values and beliefs or culture of an organization (Burke & Litwin, 1992). Schnieder et al. (1996) went as far as saying that only by altering the everyday policies, practices, procedures, and routines, thereby impacting the beliefs and values that guide employee actions, can change occur and be sustained. Motivation Motivation is a behavioral tendency that is aroused to move toward a goal, take the needed action, and persist until satisfactorily attained (Burke & Litwin, 1992). Motivation is the net resultant energy attained by the sense of achievement, power, affection, discovery, and other human motives typically aroused by aligning rewards and recognitions with where the organization wants to go. Buckingham and Coffman (1999) highlighted four key things that motivate employees: tangible rewards, intangible recognition, quality communications with 41 leaders, and frequent communication and feedback from supervisors. Rewards and recognition mean different things to different people and, leaders need to find out what individuals value and then personalize the recognition to motivate them. (Buckingham & Coffman, 1999). Task Requirements and Individual Skills and Abilities Task requirements and individual skills and abilities, also called job-person match, are the required behavior for task effectiveness driven by specific skills and knowledge that are required for people to accomplish the work for which they are assigned and are responsible (Burke & Litwin, 1992). Individual skills must match the task requirements and a learning organization where the rate of learning is greater than the rate of change may be the only sustainable competitive advantage remaining for businesses (Senge, 1990). According to Hansen and Nguyen (2020), there is a significant correlation between a learning organization and organizations that practice responsible innovation that drives change. Garvin et al. (2008) highlighted three building blocks to learning and skills development – a supportive learning environment, concrete learning processes, and leadership that reinforces learning. Dr. Warner Burke (2018) has espoused the concept of learning agility which is a combination of motivation and skill. Individual Needs and Values Individual needs and values are those “specific psychological factors that provide the desire and worth for individual actions or thoughts” (Burke & Litwin, 1992, p. 533). Many behavioral scientists believe that job enrichment leads to enhanced motivation, yet this is not universally applicable as it is seen that while some may be motivated by their jobs being enriched, others may be motivated by enrichment in off-the-job activities (Burke & Litwin, 1992). Also, as diversity increases in the American workforce, it has become more important to 42 understand differences among people regarding their needs and values related to work and what gives them job satisfaction (Burke & Litwin, 1992). The study of humans requires the examination of multi-person systems not limited to a single setting and must take into account aspects of the environment that go beyond the immediate for that individual (Bronfenbrenner, 1977). Irrespective, as Austin (2016) explained, commitment to people is key: You create and provide an environment in which employees can succeed, where their ideas will be heard and employed, and where they have state-of-the-art tools to accomplish their mission. It means they feel confident that their efforts will be recognized and rewarded based on merit, and that their employer will stand with them when the going gets tough. (p. 6) Individual and Organizational Performance Individual and organizational performance is the output or result as well as the indicator of effort and achievement of the Burke-Litwin model of organizational performance and change. This may be in the form of increased productivity, customer satisfaction, profit, and quality which are the intended outcomes of the change transformation (Burke & Litwin, 1992). Leaders, supervisors, and organizational culture are the crucial foundation stones for strategic employee communications, motivation, and performance. Yet, many organizations do not focus on these and as a result have low levels of employee trust, engagement, retention, and other performance indicators which then in aggregate impact overall organizational performance (Alvesson, 2002). The Revised Burke-Litwin Model In light of significant external factors such as the financial system collapse and significant new developments in business management, Spangenberg and Theron (2013) critiqued the Burke-Litwin model of leadership, change, and performance and proposed a revised 43 Burke-Litwin model (shown in Figure 4), with five key changes to the original model. First, the model has been logically restructured to be more comprehensive with all-around interaction with external factors, a clearer definition of outcomes, and with leadership at the center focused on openness, adaptability, and being futuristic. The model is open and acknowledges that leaders and organization members have the openness to interpret and report to the external environment as they identify or see financial threats or global upheavals in a timely manner (Kipp, 2005). Also, the revised model is adaptable to accommodate future macroeconomic uncertainties or geopolitical upheavals by incorporating the fluidity of external factors across all variables and incorporating futuristic leadership which has an adaptive-innovative approach to visioning and creation and implementation of the strategy (Spangenberg & Theron, 2013). The comprehensiveness of the model is evident in that it can be used as an independent organizational development instrument across both private and public sectors to measure the outcomes of the organization, team, and individual performance which are more clearly defined so that the leaders can understand their own purpose, functioning and effectiveness as leaders in driving the change (Spangenberg & Theron, 2013). The revised model puts leadership at the helm of what Spangenberg and Theron (2013) call the “strategic triangle” (p. 32) which includes strategy, organizational culture, and human capital at the base of that triangle. This leads to the second major change in the adapted Burke-Litwin model where human capital is included due to its increasing importance across various aspects of driving organizational effectiveness and performance. Instead of serving a pure human resources function, the role of human capital has expanded to influence human talent, competence, and motivation of talent that delivers superior performance, including in developing an ethical vision and strategy (Spangenberg & Theron, 2013). In considering human capital as a source of competitive advantage for organizations, 44 Campbell, Coff, and Kryscynski (2012) suggested that compensation design, employee selection, and job design should be included in human capital strategies. 45 Figure 4 Revised Burke-Litwin Model Note. This figure shows the revised Burke-Litwin model. From “A critical review of the Burke- Litwin model of leadership, change, and performance” by Spangenberg, H., & Theron, C., 2013, Management Dynamics, 22(2), p. 33. Definingtheorganisationalcontext Schneider (1998) contends that, despite unpredictable external or internal interferences, leaders can create conditions that are conducive to individual and team effectiveness. Schneider describes such a condition as providing a context for performance – the circumstances that influence the ability of employees to contribute meaningfully to the achievement of organisational goals. In other words, leadership in organisations does not take placeinavacuum,buttakesplaceinorganisationalcontexts (PorterandMcLaughlin,2006). Fiedler(1996:249)summarisestheaboveviewsasfollows: Externalcontextualfactors The impact of contextual factors from the external environment has been addressed by various researchers. Yukl (2008) and Howell and Avolio (1993) emphasise the impact of high uncertainty and turbulence on leaders and leadershipstyles,whileGordon(1991)contendsthatstable versus dynamic markets moderate the effect of cultural traits on performance. Other enduring factors that may affect business effectiveness and performance are the state of the economy, market forces, politics, and labour unions (Mair,2003;BurkeandLitwin,1992). Possibly the most damaging external contextual influence on the world economy during the past decade was the subprime mortgage scandal, leading to the major global financial crisis referred to earlier. Three studies that have beenconductedsincethenprovideasoundunderstandingof the impact of this major crisis – initially on financial corporationsintheUSA,andlaterspillingovertofinancial institutions in Europe. Demyanyk and Von Hemert (2011) analysed the quality of subprime mortgage loans, and discovered that the upswing and downswing of the subprimemortgagemarketfollowedatypicalsituationofa lendingboomthatledtoabustscenario,whereunjustifiable growth led to the market downfall. Second, Kregel (2008) contendsthatthecrisiswastheresultofinsufficientmargins of safety criteria on how creditworthiness was assessed. Thecoreoftheproblemwastheunder-evaluationandfaulty pricing of risk by leaders responsible for managing the approval of mortgage loans. Third, according to Nemchek (2010),thepoorjudgementanddecision-makingbyleaders and followers described above, combined with poor oversightandirregularities,causedthesubprimemortgage debacle. Mostseriousresearchersintheareaagreethatleadershipsuccessis the result of the characteristics and behaviour of the leader, the natureoftheleadershipsituationaswellastheinteractionbetween theleaderandtheleadershipsituation. Organisational,teamandindividualperformance andeffectiveness Managing structureand coreprocesses Process efficiency Managing organisational climate Individualvalues andmotivation Managing human talent Individual talent Strategy Organisational culture Humancapital Leadership Externalcontextual factors Externalcontextual factors Externalcontextual factors FIGURE2 REVISEDBURKE-LITWINMODEL External contextualfactors Internalcontextualfactors 33 ManagementDynamics . Volume22No2,2013 46 The third major change is related to the role of business process reengineering (BPR) at the management level which is based on the recognition that agility and flexibility of the business to pivot versus just cost and quality is driven by business process management to compete in business (Herzog et al., 2007). In a study that tested three change initiatives, Lok et al. (2005) found that BPR had the greatest impact on performance over continuous improvement and benchmarking, and executive commitment, strategic alignment, and employee empowerment as core requirements for the success of change initiatives. In another survey-based study on BPR involving 73 medium and large-sized manufacturing companies, Herzog et al. (2007) also identified education, training, teamwork, employee cooperation, IT support, process orientation, BPR value proposition, and tools and techniques as key success factors for successful change transformation. This aligns with the fourth change which is related to the external and internal contextual factors that pervade the entire adapted or revised Burke-Litwin Model. The external contextual factors surrounding the entire adapted model allow for interaction with leadership about all other factors with the eternal environment, and overall, the external contextual and internal contextual factors influence the organization at all levels including the outcomes at the individual, team, and organizational performance level (Spangenberg & Theron, 2013). The last major change in the revised Burke-Litwin model is a better description of outcomes of leadership still called performance and effectiveness at the organizational, team, and individual levels. For organizational performance and effectiveness, measures such as profitable growth to demonstrate financial performance; favorable earnings, financial resources, and asset value to demonstrate organizational effectiveness; market share, competitiveness, customer satisfaction, and productivity to demonstrate market standing; and capital investments, index of projected future performance, expansion plans to demonstrate future growth are recommended 47 (Spangenberg & Theron, 2013). For team and individual performance and effectiveness, measures such as adaptive leadership, interpersonal relationships, ability, skills, competencies, resources availability (equipment, information, and qualified staff), individual well-being, and job satisfaction of individuals at work and task levels are measured (Spangenberg & Theron, 2013). The model may also be viewed with a lens of four levels where Level 1 is the strategic level with leadership at the helm of the triangle of strategy engaged in the creation of strategy, organization culture, and human capital; Level 2 is the management level that includes management of the structure, core processes, organizational climate, and human talent; Level 3 is about driving process efficiencies, individual values, and motivation, and releasing individual talent; and Level 4 is about the outcomes or team, individual and organizational performance. All of the above are in tight inter-relationship and in the context of external and internal factors. In conclusion, the revised model does not modify or add any factors from the original model, however, it does enunciate the role and influence of leadership with more accountability, the importance of business process efficiency or BPR which is critical to driving digital transformation, the role of human capital in creating organizational change strategy, and managing talent capacity, capability, and motivation. Given all of these are critical success factors in driving digital transformation, have formed the basis of my RQs for exploring the role of successful critical external and internal factors and practices in leadership, culture, systems (HR, IT, talent), and policies in driving successful digital transformations in resources industries. Relevance of Burke-Litwin Model in driving Digital Transformation In their book Managing the Change Process, authors Carr et al. (1996), discussed how in a study how 700 executives scored a C (70-79%) on questions related to evaluating, managing, 48 and planning organizational change, and a D (60-69%) on managing the people aspects, understanding the nature of change and their individual response to change as leaders. As stated earlier, Clark and Estes found that 70% of change initiatives fail (2008). This forms a key basis for this exploratory study specific to the resources industry which has lagged in driving digital transformation compared to other industries. As the literature review highlighted categories around leadership, skills, technology, ways of working, talent, and education, and on reflection, they all fit the Burke-Litwin model for leadership, organizational and performance change specific to external factors, leadership, organizational culture, and systems and policies that encompass technology change and new ways of working. The first step towards improving organizational effectiveness is to determine how it is currently functioning and to do this, an organizational diagnosis is necessary and the Burke-Litwin model provides a template with a common understanding of the right variables and their interrelationships for the respondents (Shinn, 2001). The use of qualitative research in which respondents can provide rich data lends itself to his study and organizational models such as Burke-Litwin help measure organizational behavior and Performance (Olivier 2017). Conceptual Framework The purpose of the study was to explore critical external and internal factors and practices promising to accelerate digital adoption in resource industries that are being driven by a confluence of external and internal changes both external and internal as those of customer expectations, technological advances, and post-pandemic labor shortages. As described above, for my theoretical framework, the study implemented the Burke-Litwin Model of leadership, change, and performance as it examines the organizations at multiple levels including external environment, leadership, management processes, systems, and policies, group and individual 49 motivation as influenced by the work climate (Burke, 2018). Burke (2018) further classified these factors into transformational and transactional. Given that 60% to 70% of change initiatives fail due to abandonment (Clark & Estes, 2008), the purpose of the study was to explore and identify key insights on various aspects that map to Burke-Litwin set of factors to help determine what might be the right transformational leadership, organizational culture and climate, and motivation factors that will help drive successful digital transformations in Resources industries. The key concepts, based on Burke-Litwin’s model of change, that will help drive successful transformations are the recognition of the external environment changes in how work is done in a more agile way, the enormous rate of technology change that is driving digitization across the industries, and organizational culture and climate that motivates the workforce and helps organizations create the capacity and capability to drive that change. Figure 5 below reflects my conceptual framework based on the Burke-Litwin model of leadership, change, and performance. Each of the variables is aligned with my research questions and tightly tied to exploring the problem of practice. 50 Figure 5 Conceptual Model to Drive Digital Transformation Programs Legend: Interventions Causes Outcomes Impact or leads to Bi-directional impact External Changes in Customer, Industry, Technologies and Labor Capacity Growth (2X-3X) of Industry Peers CHANGE (Digital Transformation) PROGRAM Leadership Culture Systems & Policies Impact Monitoring & Feedback Monitoring & Feedback Inputs & Impact 51 The inputs to the model are the changes that the customers are demanding, the industry is undergoing, and the technology and labor capacity and capabilities that exist. Central to the conceptual model is the change transformation program or the digital transformation for the industry with the expected outcome matching what has been observed with 2X or 3X growth in the business. The three key factors of the Burke-Litwin model that were explored are leadership, organizational culture, and systems and policies. Each of these is the key tenet that fits the problem of practice and ties closely to my RQs, starting with leadership which drives the strategy and mission and is more influential as described in the revised Burke-Litwin model above. In addition, culture is central to all things like driving motivation, skills, job satisfaction, and the climate. Lastly, all of these changes are driven by new ways of working, and technology changes that will impact HR policies, IT systems, and training content and methods. All the arrows in the model are bi-directional to show the impact and influence flow both ways. This is not to say that the factors that do not show a direct arrow are not influencing each other - in fact, each of the three variables take inputs, influence each other in terms of impact and driving change, and in tandem drive the outcomes of this model. A more detailed version of the conceptual model to drive digital transformation is presented in Appendix A. Conclusion: Resources Industry on the Cusp of Digital Transformation As the literature review has shown, digital transformation has been a new wave, driving disruptive change in various industries. The resources industry has lagged behind other industries such as financial services, products, and CMT, in the area of digital transformation due to the unique characteristics of being asset intensive with large capital outlays where technology has not kept pace with the way refineries, plants, and mines work. Also, the skills required for operations technology in these industries are different from those of information technology 52 skills in other industries, and there is a lack of innovation in the integration between OT and IT. The advent of Industry 4.0 is bringing a new wave of changes that promise to drive digital transformation within resources and manufacturing industries. As Savastano et al. (2019) concluded, while the major patterns of behavior in the adoption of technologies are emerging, and getting identified in the industry, due to the historical use of technology, it appears to be in “the midst of what appears to be early stages in its deployment and such related applications as pervasive computing, ubiquitous wireless communications, and construction of new organizational forms” (Cortada, 2003, p. 127). Using the conceptual model informed by the Burke-Litwin model for organizational change and performance this study utilized qualitative interview tools and explored the areas of leadership, organization culture, systems, and policies to suggest promising practices in driving and managing digital transformation in resources industries. 53 Chapter Three: Methodology Based on the literature review, and the conceptual framework informed by the Burke- Litwin model of leadership, organization, and performance change, this study explored critical external and internal factors and practices promising to accelerate digital adoption in resource industries. As mentioned in Chapter 1, digital transformation in the resources industry is being driven by a confluence of external and internal changes such as customer expectations, technological advances, and post-pandemic labor shortages. Resources companies need to drive digital transformation because it is important for business survival, helps prevent the loss of jobs that mostly impact the marginalized, and helps with the energy transition. This chapter provides an overview of the methodology I have chosen and explains why the methods are appropriate for this study, including data collection tools and protocols, participants, credibility and trustworthiness of data collected, researcher positionality, the use of ethics in the process, and limitations and delimitations. Research Questions This study explored critical external and internal factors and practices promising to accelerate digital adoption in resource industries. The four research questions (RQs) that guided the study are as follows: RQ1. How do C-Suite executives in resources industries define Digital Transformation? RQ2. How do executives navigate external environment impacts in driving successful digital transformation in resources industries? RQ3. How do the internal contextual factors impact the executives’ ability to drive successful digital transformation in resources industries? 54 RQ4. What are the individual, team and organizational values, and talent and process efficiencies that C-Suite executives in resources industries perceive are needed to drive successful digital transformation? Overview of Methodology I implemented qualitative methodology, using a semi-structured interview protocol, to conduct this study. My conceptual framework drew on the Burke-Litwin Model of leadership, change and performance. The conceptual model examined the organizations at multiple levels including the external environment, leadership, management processes, systems and policies, and group and individual motivation as influenced by the work climate (Burke, 2018). Burke (2018) further classified these factors into transformational and transactional. Transformational factors include the external environment, mission and strategy of an organization, leadership, and organizational culture. Transactional factors are the management practices, systems, policies, structures, and work unit climate of organizations. Two data collection methods were evaluated for this qualitative study - surveys and interviews. Creating a survey would require close attention to question ordering, question formatting, testing, and conducting a mini-survey (Robinson & Leonard, 2019). I would have to rely on each question being interpreted by participants in the right context and accept that the questions would solicit the data I needed to collect for my research study (Rosenberg, 2017). While the survey would target a purposive sample, I would not be able to control who may or may not respond to the survey. This is a limitation of my exploratory study where I needed to solicit input from experts in the field. It would be challenging for me to test the questions for empathy and clear understanding for my participants ensuring relevance to my research questions (Robinson & Leonard, 2019). While the questions in the survey would include an 55 appropriate blend of open, closed, mixed, and mostly nominal and ordinal, there would be limited scope for clarifications and follow-ups in a survey. Also, I would miss out on probes or reading body language to add more context, something that the interview protocol offers. In the end, soliciting rich, meaningful response to the research study is the purpose of the data collection tool and the interview method fit this exploration study best (Merriam & Tisdell, 2016). Given 60% to 70% of change initiatives fail due to abandonment (Clark & Estes, 2008), my interviews explored key concepts, based on Burke-Litwin’s model of change, that will help drive successful transformations. These are the recognition of the external environment changes in how work is done in a more agile way, the enormous rate of technology change that is driving digitization across the industries, and an organizational culture and climate that motivates the workforce and helps organizations create the capacity and capability to drive that change. All of the research questions were addressed via a qualitative semi-structured one-on-one interview with C-suite or senior executives in the company responsible for driving change or digital transformation in the organization. As each participant may define digital transformation differently, as part of research question 1, I provided a definition for digital transformation to ground the discussions. All of the interview questions were designed for participants to provide insights based on their organizations and their lived experiences. The Researcher Paradigms of inquiry are best seen as philosophical worldviews that are a “basic set of beliefs that guide action” (Guba, 1990, p. 17) of which I related closely to the pragmatic worldview. The pragmatic worldview arises out of “actions, situations, and consequences” (Creswell & Creswell, 2018, p. 10). Saunders et al. (2019) asserted that for a pragmatist, research starts with a problem, and the research contributes to practical solutions to inform or improve 56 future practice. All concepts used are only relevant when they support action (Kelemen & Rumens, 2008). I saw three issues in my positionality and bias in the data collection process for my problem of practice. As a consultant and an expert in the field of digital transformation, I could constantly be bringing my pragmatic viewpoints into the discussion. To mitigate this, I constantly reflected on my thought process and checked whether my data collection captures the interviewees’ worldview or reflects my own biases. In other words, I often went back to the problem of practice I was exploring and kept it untainted from the bias of my own views (Merriam & Tisdell, 2016). Second, I am a digital transformation advisor, and, in some cases, my relationship with the participant as their consulting advisor might allow for bias in guiding the interview and would have to be controlled. I had to constantly check myself and stay objective in my role as a researcher. Also, I interviewed peers or leaders deeper into industry trends than myself, and as such, I did not see participants feeling pressured or intimidated by me in any way that made their responses less objective. Finally, when it came to coding data, I would tend to be biased towards my a priori codes that tie the insights to my conceptual model as informed by the Burke-Litwin theoretical model of organizational change. To mitigate this tendency, I constantly checked myself from that tendency, and used triangulation as another mitigating strategy to ensure that I transcribed and translated into insights exactly what the interviewees intended. In other words, I had to often step away “to see the forest from the trees” (Merriam & Tisdell, 2016, p. 207). Data Source: Interviews Data sources are interviews with participants who are experts in the field of digital transformation and are currently leading or have successfully led digital transformation in the 57 resources industry. For a saturation and balanced data collection, I targeted 10-12 senior executives. Given the qualitative exploratory nature of the study, semi-structured interview allowed participants to share their rich, lived experiences, guided by a list of more or less structured questions that required specific data from respondents, focusing on key aspects of the conceptual framework, and yet, offering flexibility with no predetermined wording on responses (Merriam & Tisdell, 2016). The data collection took place during the November 2022 through February 2023 time frame and was based on the schedule availability of the senior executives involved. Ideally, the length of interviews was for an hour with time for follow-up, as needed. Interviewing in qualitative research is more open-ended and less structured (Merriam & Tisdell, 2016). Given my study was exploratory in nature and focused on a common definition of digital transformation, it was best accomplished by a semi-structured approach. As Merriam and Tisdell (2016) highlighted that in this approach, the largest part of the interviews was guided by a list of more or less structured questions that required specific data from all respondents, and yet, offered flexibility as it has no predetermined wording on responses. The interviewee provided data through narrative analysis, and conversation analysis with no single perception of what management practices best drive successful digital transformations (Roulston, 2010). Participants The target population for my interview was senior executives (typically, CEOs, CTOs, CDOs, CIOs, Managing Directors, Vice Presidents, or similar) who have been tasked with driving or have had success in driving digital transformation in their companies. The most common and appropriate sampling strategy for qualitative exploratory studies is non- probabilistic or what Chien (1981) called purposive and Patton (2015) called purposeful. Purposeful sampling is based on the assumption that the researcher picks the sample from whom 58 the most can be learned about the area of study (Merriam & Tisdell, 2016). Given that my study was an exploration of promising management practices, this sampling approach fit best. LeCompte and Schensul (2010) established a criterion-based selection of such experts based on attributes that a researcher must align on based on the purpose of the study. Based on my study and research questions, my criteria for the sample included: 1. Senior Executives who have or are driving digital transformation. 2. Belong to the resources industries sector – energy, chemical, utilities, and other asset- intensive industries. 3. Companies are large (over 500 million USD in annual net revenue) and operate globally. To recruit a purposeful sample of senior executives, I worked through my company (a large consulting organization called Accenture), and my professional network to recruit a sample that met all participation criteria. Instrumentation The interview protocol, presented in Appendix B, consists of 14 questions, and a total of 31 probes. All of the questions are open-ended and followed an inquiry path that aligned with my theoretical and conceptual model as informed by the Burke-Litwin model of change. The interview items address the research questions more or less sequentially. The first few questions address RQ1, provide for basic grounding on a definition of digital transformation, and guide discussions toward concepts of leadership behaviors, organization policy, culture, talent, and motivation. The next set of questions focused on exploring external and internal factors, motivational, leadership, and organizational culture and thus, addressed RQs 2, 3, and 4. This section also allows interviewees to discuss barriers and challenges to successful digital transformation in their organizations. The remainder of the questions allowed for discussions 59 around actions they believe will overcome those barriers, prioritization of those actions to help drive successful digital transformation in their organizations, and addressed RQs 3, and 4. The last question was a catch-all question to allow for anything that the interviewee may want to add in addition to the guided questions and also to provide feedback on the process for future interview protocols (Merriam & Tisdell, 2016). Data Collection Procedures To recruit a purposeful sample of senior executives, I worked through my company (a large consulting organization called Accenture), and my professional network to recruit a sample that met all participation criteria. Creswell and Creswell (2018) noted that a basic characteristic of qualitative research includes data collected in the natural setting. The researcher is the key instrument who uses multiple sources of data working inductively to create patterns and themes by organizing data from rich information collected (Creswell & Creswell 2018). I, as the researcher, was the primary instrument of data collection as I interviewed a sample of 10-12 senior executives recruited based on the criteria identified above. The purpose of the interviews was to enter into the interviewees’ perspectives, and the quality of information obtained during the interview was largely dependent on me, the interviewer (Patton, 2002). Ideally, the interviews would have been in the offices (the natural setting) of the senior executives. However, due to the pandemic and global travel limitations, virtual interviews presented an attractive and sometimes a better option (Roulston, 2010). Virtual interviews also offered more scheduling flexibility for participants as they made the interview process location independent, and allowed them to participate more easily. As such, interviews were conducted remotely using the ZOOM communications platform with automatic text recording turned on, and the camera on. Also, I used pen and notepads to transcribe interview notes based on a pre-planned instrument, 60 highlighting my a priori codes. Data collection occurred between November 2022 to February 2022. Each interview lasted from 50-115 minutes in duration. All recordings and handwritten notes were transcribed within 24 to 48 hours after the interview. I performed a test of the recording tool before and after the interview itself. Lastly, I asked for permission to have a follow-up session with each interviewee, as needed, for any more questions or clarifications. Data Analysis Data analysis was conducted based on my conceptual framework. I used a priori coding which is a deductive process that connects emergent or open coding with the conceptual framework or literature (Corbin & Strauss, 2015). Specifically, I tracked and highlighted my defined a priori codes during the interview process in field notes, and highlighted those during my review of each interview transcript as well by drawing squares around them. Also, I updated my codebook organized by each interviewee, a priori codes, and open codes. These were tracked directly to the key themes of leadership, culture, change, motivation, and talent that align with my conceptual model. The themes helped identify patterns and accentuate the importance of each of those factors for driving digital transformation. I used MS Excel, as a tool, to tabulate the numbers of times each theme was used and the context in which it was used to help me prioritize the level of importance of those a priori themes in my conceptual model. It also allowed me to track and find new themes that I may not have considered. Validity and Reliability Ensuring validity and reliability in qualitative research involves investigating in an ethical manner which establishes the trustworthiness of the study (Merriam & Tisdell, 2016). To maximize the credibility and trustworthiness of my study, both qualitative validity and reliability steps and checks were incorporated throughout my data collection protocol. Qualitative validity 61 is based on determining if the findings are accurate from the standpoint of the researcher, the interviewee, or the readers of the study (Creswell & Miller, 2000). I used respondent validation by replaying to them my interpretation of what I heard during the interview, and my reflections to ensure that they were valid. Qualitative reliability is achieved by the researcher documenting as many procedural steps as necessary, and creating a database that stores detailed case study protocols (Yin, 2009). I have documented my protocols and procedures and stored them in a database. In addition, as suggested by Gibbs (2007), I checked the transcripts to make sure they were error-free, and that my code definitions stayed uniform, and I had my codes cross-checked by my chair for reliability (Creswell & Creswell, 2018). Lastly, I did check for my biases and to ensure trustworthy data collection, I reflected on the interview protocol, transcribed notes, and reviewed any documents or artifacts, referred to by the interviewee (Patton, 2002). Ethics Merriam and Tisdell (2016) pointed out that the researcher in a qualitative study is responsible for ensuring that a study is carried out in an ethical manner. With that in mind, I carefully considered consent, confidentiality, and power dynamics that may be in play throughout this study. Participants were provided with an information sheet that provided context and background information about the study and that also made participants aware that their participation is voluntary, and that they may cease participation in the study at any time. I disclosed to the Institutional Review Board (IRB) and to the dissertation committee of my role as a consultant (in the past only) in some of the organizations or companies being used for data collection or those that are clients of my company in the cases where that is true. Glesne (2011) noted that this process creates a sense of empowerment for the study participants. I also coded the data so as to not reveal participants’ names. This is to maintain confidentiality for each of the 62 participants. Given the possible sensitivity of some comments provided during interviews, participants’ comments will remain anonymous. To avoid any power dynamics or claims of coercion, I only selected study participants in such a way that anyone in the organization with reporting relationships was not cross-interviewed. No compensation was offered for participation to make this purely voluntary. Lastly, I applied for and received IRB approval prior to recruiting my participants and data collection. 63 Chapter Four: Findings The purpose of this study is to explore critical external and internal factors and practices that can accelerate digital adoption in resources industries. This qualitative research is exploratory in nature and is focused on the resources industry sector, which comprises asset- intensive manufacturing companies classified into three sub-industry segments that include Chemicals and Natural Resources (metals and mining), Energy, and Utilities. To gather open- ended and less structured data, one-on-one interviews were conducted, which is a qualitative research method (Merriam & Tisdell, 2016). Given the exploratory nature of my study, a semi- structured interview approach was employed, where participants were guided by a list of more or less structured questions, as shown in the Interview protocol in Appendix B. All research questions were addressed via qualitative, semi-structured, one-on-one interviews with experts in the field of digital transformation. All these experts are senior executives (such as CIOs, CTOs, and CDOs) responsible for driving change or digital transformation in their respective companies. Each participant was allowed to provide data through narrative and I, as the researcher, performed conversation analysis with no predetermined notion to arrive at an objective view of what management practices best drive successful digital transformations in the resources industry (Roulston, 2010). This chapter provides an overview of the participants and presents findings based on the data analysis of the interviews conducted. The chapter is organized by the research questions (RQs) that this research set out to explore and, the findings are presented in terms of the key themes that emerged for each of the research questions. As mentioned earlier, data analysis was conducted based on my conceptual framework, using a priori coding, which is a deductive process that connects emergent or open coding with the conceptual framework or literature 64 (Corbin & Strauss, 2015). During and after the interview process, I tracked and coded my defined a priori codes in my field notes and interview transcripts directly to the key themes of leadership, culture, change, motivation, and talent that align with my conceptual model. Most of the themes that emerged were aligned with the conceptual model and accentuated the importance of each of those factors for driving digital transformation. Themes were evaluated based on the number of participants who mentioned it, and more importantly also how emphatic and strongly they voiced it during their interview. In some cases, even if four to five participants mentioned a theme, I evaluated if each team stood on its own based on the weight of attention from the participants given to those themes. Participants A purposeful sample of 21 senior executives was identified based on industry spread, knowledge from my work colleagues, and my professional relationships, and those who fit the following criteria: 1. Senior Executives who have or are driving digital transformation. 2. Belong to the resources industries sector – energy, chemical, utilities, and other asset- intensive industries. 3. Companies are large (over 500 million USD in annual net revenue) and operate globally. To recruit a purposeful sample of senior executives, I worked through my company (a large consulting organization), and my professional network to recruit a sample that meets all participation criteria. Given the goal was to interview 10-12 participants to reach saturation, of the 21 companies identified, 16 were contacted as part of Round 1 based on a good spread across energy, chemicals, and utilities company coverage, and five were placed in Round 2 only to be contacted if the required number of participants were not available. A total of 13 participants 65 were interviewed between November 28, 2022, and January 30 th , 2023, representing 13 companies. Of the remaining eight companies, two companies did not respond, two did not have a central transformation role or role not identified, one required regulatory and board approval that was difficult to pursue, and one did not have availability until April 2023. Two of the Round 2 companies were not contacted as the planned number of interviews to reach saturation was exceeded. Table 1 shows the basic demographics of the participants from the 13 companies and for anonymity, and to protect the confidentiality of participants, additional demographic details have not been reported. Table 1 Interview Participant Demographics From 13 Companies Pseudonym Title of digital transformation leader Industry Gender Participant 1 Chief Information Officer Chemicals Female Participant 2 Vice President of Transformation Energy Female Participant 3 Chief Digital Officer Super Major Male Participant 4 Vice President - Technology, Data, & Security Utilities Male Participant 5 Vice President of Business Transformation Super Major Male Participant 6 Chief Technology Officer Chemicals Male Participant 7 Chief Information Officer Energy Male Participant 8 Chief Information Officer Energy Male Participant 9 Chief Information Officer Energy Male Participant 10 Chief Transformation Officer Energy Male Participant 11 Chief Information Officer Utilities Male Participant 12 Vice President of Digital Transformation Utilities Male Participant 13 Chief Information Officer Chemicals Male 66 As the researcher, I served as the primary instrument of data collection and analysis. All interviews were conducted remotely using the ZOOM platform, were video and audio recorded, transcribed using the close captioning and automated transcription feature of ZOOM, and I also used pen and printed instrument sheets to transcribe interview notes based on a pre-planned instrument, highlighting my a priori codes. Each interview ranged from 50 to 90 minutes in duration. The rest of this chapter presents the 17 themes organized by each research questions. Research Question 1: How do C-Suite Executives in Resources Industries Define and Perceive Digital Transformation? The purpose of this research question was to align with participants on base concepts such as the definition of digital transformation, how they define it, and how they think their peer groups define it. Questions and probes were designed to gauge whether and why they think the resource industry has lagged in the adoption of digital transformation. Also, questions were asked about which industries they most look up to when it comes to lessons learned or whom they aspire to be. Additionally, they were asked what they stand to gain most by undertaking digital transformations in their companies. The following five themes emerged from the interview findings. Theme 1: Common Definition of Digital Transformation Emerging in Resources Industry Interview data demonstrate that the participants hold a common definition of digital transformation as it being about business transformation and not just technology transformation. All participants communicated with clarity that digital transformation is about using new advanced technologies to drive business value in terms of revenue growth and operational efficiencies and enhancing customer and employee experiences. For 11 out of 13 participants, it is “really an end-to-end view of how, using …all aspects of digital could improve …whether it's 67 the interaction that you have with your customers and your suppliers’ potential customers potential suppliers, but also internally, with your employees” (Participant 1). As Participant 2 highlighted “digital transformation is about technologies and tools that unlock business value,” confirming that it about looking at end-to-end business process transformation, and not just technology transformation. Participant 9’s comments further elaborated the point that “Digital transformation is far broader” than just “transforming IT,” and stated that companies either “Go Digital, or Die!” and that “Digital is an enabler of differentiated capability using new technology” that enables “ways of reinventing the business, workforce of the future, and being competitive in this ruthless market.” Digital Transformation, according to Participant 3, is also “about shaping mindset, the culture of an organization, and leadership behaviors.” For their company, Participant 3 summarized three themes for digital transformation that can accelerate business processes at scale: 1) “to enhance asset value for today and for the future with the energy transition.”, 2) “to optimize the value chain by increasing the margins of every product” made, and 3) to “optimize the employee and customer experience.” However, two participants still described digital transformation as more of a technology- focused initiative, where Participant 4 stated that for him, digital transformation is “primarily around cloud computing–taking our technology from on-premise environment to cloud.” Similarly, Participant 6’s digital transformation “experience has been largely trying to bring real- time data, and aggregate intelligence… to drive a better way of running your operations.” Based on all participants, digital transformation is about delivering value to the organization through technologies such as cloud, data, analytics, machine learning, and artificial intelligence. Table 2 shows how each of the participants defined digital transformation. 68 Table 2 Participants’ Comments Related to Definition of Digital Transformation Participant Definition of digital transformation Participant 1 “What comes to mind is really an end-to-end view of how, using …all aspects of digital could improve …whether it's the interaction that you have with your customers and your suppliers’ potential customers potential suppliers, but also internally, with your employees.” Participant 2 “Digital transformation means a lot of things to different people based on their background, where they come from, and the context they may have of what the company is trying to achieve. As a businessperson, digital transformation is about technology tools (whether to buy or build) that unlock business value.” Participant 3 “Digital transformation is a new set of technology that enables differentiated capabilities to create value by increasing revenue growth, reduce CO2 emissions, and making the work environment safer. Technology is not new to us …we have been around for 140 years and know technology…Digital is an enabler of differentiated capability using new technology. For us there are three themes of Digital Transformation that has the capability to accelerate processes at scale to: 1. Enhance Asset Value for today and for the future with Energy transition, 2. Optimize the Value Chain by increasing the margins of every product we make, and 3. Optimize the Employee and Customer experience.” Participant 4 “When I hear Digital Transformation, the first thing that comes to mind for me is primarily around Cloud – taking our technology from on- premise environment to cloud.” Participant 5 Digital Transformation is “the nexus of the business” (processes), “systems, and data” which delivers on …simultaneously delivering an increase in customer experiences, employee experience, cost reduction, effectiveness and improvements” Participant 6 “There are different dimensions of digital transformation... but, our experience has been, it's largely trying to bring real time data, and in aggregate intelligence in and around trying to drive a better way of running your operations and so it's not simply digitizing manual procedures.” It is also the ability to “to collect insights and trying to improve what you do by building a learning engine behind it.” 69 Participant Definition of digital transformation Participant 7 “It is an IT term that should be simplified for business”…and that it should be made clear to business executives that it is about “business transformation.” Participant 8 “In reality it is changing the way you do business by taking advantage of new technology and securely scaling the business. And it has to cover a broad set of domains – customer, supply chain, manufacturing asset management, maintenance etc. with scale across the enterprise.” Participant 9 “Digital transformation is far broader” than “transforming IT. Ram Charan describes it well” when he says, “go digital or die!.” It “is ways of reinventing the business, workforce of the future, and being competitive in this ruthless market. Digital Transformation is also about shaping mindset, culture of an organization, leadership behaviors. Without these three things we saw failures early on in our journey. Compressed transformation is what we call half-life of ROI. Traditionally we used to look at 10 years for ROI, now we want ROI in 3 years.” Participant 10 “Changing the way, a task is performed using digital technologies. Most think of digital transformation as changing technology. It is about redefining the business through change in culture, people, interactions, ways of working and technology.” Participant 11 “Digital transformation is about intentionally changing the business model on how a company makes money, makes and sells its services and products. And digital is the enabler of that change.” Participant 12 Digital Transformation is “using new technology to lead a business transformation. It is what new digital technologies can offer to enable business transformation….it is about Business Transformation to drive business outcomes.” Participant 13 Digital transformation… “the two lenses that we look through is really transforming the way we operate our businesses today through the different forms and technologies in the umbrella of digital as well as where we can consider new offerings from a market standpoint altogether.” 70 A common definition of digital transformation emerged based on participants’ comments and, as 11 of 13 participants highlighted, in the resources industry digital transformation is about changing business processes, ways of working, leveraging technology as an enabler to deliver on business value, and improving the customer and employee experience. This aligns with the definition that was laid out in Chapter 1 as part of this research where I defined Digital Transformation as the integration of digital technology into all areas of a business resulting in fundamental changes to how businesses operate and how they deliver value to customers, shape the employee experience, and operate in an innovation culture (https://enterprisersproject.com/what-is-digital-transformation#q1). Each participant found the definition, that I shared with them after their responses, either “better” or “more eloquent” and Participant 8 called it “Perfect!”. Theme 2: Perception of Peers in Resources Industry as being at Different Points of Maturity and Taking Different Approaches to Digital Transformation When I asked participants for their perceptions about how their peers view digital transformation, 12 of 13 participants felt that their industry peers are arriving at a common understanding of “what” digital transformation is and are aligned with it being defined as “changing the way you do business by taking advantage of new technology and securely scaling the business” (Participant 8). However, 8 of 13 participants shared their perception that the “how” one goes about implementing it is different for each company depending on where they have come from (history, culture), where they are in their journey (level of maturity in digital transformation), and where they are going (the future business strategy). As stated by Participant 3, “peers are generally aligned on the definition of digital transformation... the approaches to 71 digital transformation differ – the digital transformation approach has to be integrated with the culture and business strategy of the company.” Each organization in the resources industry is approaching digital transformation in a different way. Participant 1 pointed out that “many companies only tend to pick particular areas that they focus on, for instance, customer” and “analytics and data purely and not necessarily all of the other digital opportunities.” Participant 2 said, “different people think differently depending on where or what sphere they come from.” Echoing similar sentiments, Participant 5 said “everyone is coming from a different point but where you are going is relevant because heading in the right direction is important.” Further, Participant 5 elaborated, “Resources is a divergent industry, and we all have divergent strategies, and digital transformation needs to be strategy led, and so, it will all be different” for different peer organizations. Similar sentiments were also shared by Participant 13 whose comments summarize this theme best: Everyone gets that you cannot be a leader without understanding that digital means business transformation with tech. So, the WHAT is consistent across the peers. HOW you come at it – how you prioritize different parts of the business and the technology you use to digitalize it – HOW you go about doing it - pilot, proof of concepts, Proof of Value, and then show value and Scale – everyone comes at it differently given where they are based on their big pressure points. Theme 3: Perception That Resources Industry Lags in Digital Adoption Due to its Capital and Asset Intensive Nature, and Technology Debt Participants’ interview comments indicated that four characteristics related to the nature of the resources industry as reasons the resources industry lags in its adoption of digital transformation. First, 10 of the 13 participants highlighted the asset-intensive (and therefore 72 capital-intensive) nature of the resources industry as a barrier to the adoption of digital transformation as big plants and factories, big assets, require large capital investments and those take priority over digital transformation initiatives. As stated by Participant 1, “The chemicals industry is behind because we focus on manufacturing… we don’t talk sales, we don’t talk customers…and this impacts the ability to see the impacts of digital transformation beyond manufacturing plants, assets, reliability, etc.” The second characteristic that emerged is best reflected in the comments from Participant 3 who said that for the resources industry, going digital “does not modify” the core “product – Oil and Gas, Chemicals” and “the business process model to make the product is not changed by digital.” What six of 13 participants believe, was best articulated in the comments from Participant 5 who said given that the “nature of the resources industry and the product it makes – that include long cycle times” and a lack of impact on the core product from digital, makes resources companies less amenable to invest in digital transformation versus say a "business producing digital widgets” (such as financial services industry with cryptocurrencies) “where the” core “product changes have more of this digital transformation in their DNA.” Third, seven of 13 participants highlighted that Technology (debt), which is further exacerbated by general merger and acquisition (M&A) activity that is common in the resources industry and a part of most companies’ business strategy competes with investment dollars, is a barrier to digital adoption. Participant 6 pointed out that, due to the incompatibility of systems, it takes significant investments in terms of time, money, and effort to merge different systems post an M&A. He referred to this investment as “grudge spend” to integrate data, systems, applications, and processes. On the other hand, Participant 2 believes that the resources industry has failed to understand how new technologies and data can be used to drive business value 73 which has led to a lag in the adoption of digital transformation in the industry. Participant 3 lamented that “we are technology natives, not digital natives” and for us “investment in technology innovation means our research and development, not in digital technologies.” Comments from Participants 4, 6, and 9 all indicated that being “saddled with technology debt” in Enterprise Resource Planning (ERP) systems, “changes took a long time in our industry” (Participant 4). And the fact that the resources industry is “dealing with transforming 20 plus years of legacy ERP in 4 years requires “massive re-tooling of the platform which is hard for everyone” (Participant 6). Specific to the utility industry, in addition to technology debt, and competing capital investment priorities, Participant 4 called out the regulatory credits that incentivize investing in “grid uptime” and “good operations” which make digital investments a second choice. However, he believes this is changing as digital “devices on the grid are getting traction” to meet “customer expectations, and as a result, digital is getting traction.” However, he still finds that “capacity and credits for a solar plant” versus a “coal plant” driven “by the regulatory nature of the industry” give a reason for pause and make them think about investments towards digital transformation. This theme is best summarized by Participant 13 who said that “it is easier to digitize an industry such as financial services because their product can be digitized” referring to crypto, and services offered. Resources industries are “capital intensive” with “big factories, loads of products, 50-year-old technology is still relevant,” and the “fundamental nature of the product is not changed by digital.” Also, “mergers, acquisitions,” and divestitures “are part of our industry” and business strategy. “Digital transformation is also part of the business strategy along with M&A and they compete for investment dollars and distracts from digital transformation” (Participant 13). 74 Theme 4: Resources Industry as Drawing Inspiration from Manufacturing, Construction, Retail, Banking, Airlines, and Food and Beverage Companies When I asked the participants which industries they look to for inspiration or lessons learned, most participants highlighted the retail, financial services (investment and retail banking), technology, and food and beverage companies. Some also highlighted other manufacturing heavy industries such as agrochemicals, construction, and airline industries. Participant 1 said that both the retail and banking industries provide good learning as the “focus on the customer” is a “huge opportunity area.” Participant 2’s comments resonated as she said her organization looks at the retail industry for the “focus on customer as priority #1 to increase the top line” and how they use data to “predict customer behavior.” Participant 2 also highlighted that they look at “financial services, investment management firms such as Vanguard who handle large volumes of data seamlessly end-to-end, and use data to drive value.” Participants 6, 7, and 8 said their organizations look at the food and beverage industry, construction, and any industry “that have assets – require asset management, turn-around, and maintenance activities.” Their marketing divisions also looks at retail and airlines “for loyalty programs like Starbucks” and Amazon “for payments (Alexa Pay) to change the end customer experience!” Providing specific reasons for what resources industries find inspiring digital transformation, Participant 10 explained how agricultural or agrochemical industries are digitally transforming where “a farmer operates a field using digital technology through micro- fertilization, how the farmer interacts with buyers, using analytics to gauge demand and pricing, managing to microclimates to minute levels of pest control.” According to Participant 11, silicon valley technology companies such as Netflix, Facebook, Google, Alphabet, Apple, and Tesla impart tons of lessons since the dot com bust. For example, Tesla is a car company, but 75 technology is so embedded in it, Netflix not only disrupted cable but then, they also took on content creation and entered Disney’s space. Participant 7 agreed that technology companies are looked up to for “the innovation culture required to embrace digital technologies that exist in technology companies.” According to Participant 4, “to be the best utility in the world we have to give our customers an Amazon-like experience” because customers want to be kept informed of the status when the power is out. Participant 8 comments summarized the industries that inspire the resources industry well when he said that with the growth of “edge devices” that are being used in plants and equipment, resources industries have to look to “similar industries in manufacturing with assets” such as, Food and beverage and construction industries, that use digital tools to proactively monitor and do predictive analysis using AI to increase throughput, improve core business processes and thereby also increase revenues. Frankly, any industry that has manufacturing assets where you can use technology, data, and AI to monitor performance and sense aberrations and then take proactive actions to address or prevent problems before they happen. And this also helps customers who are consuming those assets or leveraging those services and could also become a source of revenue. Theme 5: Perception of Biggest Gains from Digital Transformation to go to Resources Industry in the Next Decade All leaders (participants) interviewed were unequivocal about the benefits of digital transformation, and see enormous benefits within the resources industry, and as such, are driving the digital transformation agenda across their organizations. In the words of Participant 3, “While we (in the resources industry) have been laggards in digital,…resources industries have the most to gain from digital transformation” and “our time is now for”…”the industrial sector to 76 unlock the next wave of value.” Following are the four areas of benefits that digital transformation leaders within the resources industry anticipate. Emerge as a Stronger and Better Company All participants expressed confidence that as a result of implementing digital transformation, they would emerge as a stronger company meeting growth aspirations, operational excellence, and customer-centricity. As described by Participant 1, “significant benefits can be derived if we are successful,” because ”in a digitally transformed organization, we will emerge as a better and more competitive company, will have stickiness with customers, efficient supply chains, and make informed decision across the organization.” Similar feelings were expressed by Participant 5 who said, “with digital transformation, we will have achieved”… “considerably better customer experience, increased employee experience with meaningful work, and our products and processes will be cheaper and better.” Participant 4 also mentioned that the “customer experience and employee experience” would be “enhanced with a self-healing grid” in the utility industry. Transparent and Visible Supply Chain Transportation and logistics that facilitate the movement of products, both raw materials and finished goods, is a huge component of the value chain in the resources industry. Several participants referred to digital improving efficiency of the supply chain for the resources industry. However, Participant 2’s comments best help to visualize the value from transparency and visibility of supply chains in the resources industry when she said, “you think about a traffic map, and if you posted cameras and watched people in the traffic move, I think our industry is going to look much more like that. We will track the transportation of our product.” 77 Facilitate Orderly Energy Transition Digital promises to facilitate an orderly energy transition for a greener world and still provide energy security. Participant 2 declared that because of digital “concepts and principles,” that stay the same but more “focused on the future” and their focus on the energy transition and ESG, they learned that their “operating framework was flexible” and allowed them to sign “an LOI (letter of intent) for a new line of business” around “carbon capture.” Participant 8 agreed that the evolution of new technology in the energy transition is just starting to be explored. Participant 3 further noted a trend that he is seeing more is that technology companies, that are digital natives and have revolutionized the entire value construct, are starting to see the value of partnering with traditional energy companies “that will be the governing factor for the rate of change in the energy transition.” Energy companies will surpass the digital natives in future value capture in the industrial sector by use of technology.” The “traditional energy companies are well capitalized, have the scale and capabilities” to make “a difference in this space, and the closer that we can work together,” nothing could be “more important to society” and “I’ve seen tangible evidence that”… “the collaboration with technology companies bringing the innovation” and the “resources industry brings the scale to create a Net Zero energy system. So, as Participant 10 asserted that with a more “diverse energy mix, lower cost energy system that produces less CO2, energy transition is not just a side benefit of digital transformation, it is the driver of digital transformation in the resources industry. Safe and Better Working Conditions Based on participants’ comments, it is widely believed that digitization of resources industries will create a safer and better work environment for blue-collar workers. According to Participant 3, most of the digital successes in the resources industry have been in the operations 78 environment in “detecting methane leaks with sensor, inspecting tanks with telemetry,” that make the jobs of blue-collar workers easier and safer. Participant 9 added that a “better environment” (ESG) “with less CO2,” having a “zero cost clean energy,” means “our food is cheaper, travel is cheaper, and increase in leisure time for humanity” … “increased automation – will mean fewer people in risky jobs” in the resources industry. All 13 participants seemed bullish on the benefits of digital transformation of the resources industry. Each participant felt that while the resources industry has been late to the party, their time is now. The theme is best summarized in comments from Participant 12 who said that if “we execute on digital transformation we become a customer-centric company with good customer experience” and “drive our assets and operations with predictive maintenance and reliability across the entire value chain” and “achieve energy transition targets.” Research Question 2: How do Executives Navigate External Environment Impacts in Driving Successful Digital Transformation in Resources Industries? The purpose of research question 2 was to explore the external environment factors that drove participants to undertake digital transformation in their organizations, and how they navigate or are navigating those external factors as they are pursuing digital transformation in their organizations. Key questions and probes were asked to gauge the impact of macro trends, world events such as the war in Ukraine, and the pandemic in their decision and ability to navigate their digital transformation journeys. to undertake why they think the resource industry has lagged in the adoption of digital transformation. Specific questions targeted the impact of changing customer behaviors and expectations, technology advances, and governmental regulations as potential factors in their decision to undertake digital transformation of their companies, and the challenges to manage through them. The following five themes emerged 79 from the interview findings: a) Facing the largest energy transition in history, the resources industry needs to transform for its survival, b) Customers are demanding eco-friendly produced products, c) New technology advances are enabling digital transformation for the resources industry, d) Companies are realizing that they need to be digital to face multiple black swan events, and e) Government has a role to play through policy in facilitating digital transformation. Each will be discussed in detail below. Theme 6: Energy Transition Serving as an Impetus for Resources Industry to Transform for Survival Energy transition seems to be a key driver of digital transformation in the resources industry not the outcome of it. Ten participants highlighted that Energy transition is part of the overall strategy, customers are asking and willing to pay for “green energy,” and that collaboration between technology companies that bring innovation, a government that drives regulations and ESG standards, and resources companies that bring capital and scale should collaborate to create the net zero energy system of the future. (Participant 6). Participant 2 highlighted that data as a core pillar of digital transformation drives value in measuring, anticipating, and reporting ESG regulatory requirements. Participant 4 said that his utility company is driving “digital transformation because of new industry power sources such as solar, backup generation at home, and ESG focus are requiring us to change.” Participant 10’s comments summarized the overall impact of the energy transition as the impetus for companies to transform for their survival stating that our world needs a stable energy system and traditionally that system has been stable and homogeneous, and one that was hydrocarbons dominated. Participant 10 mentioned that currently, “the energy system is unstable as many sources of energy now have come into play and are competing, such as hydrocarbons, 80 wind, solar, batteries, biofuels.” He added, it is a “heterogeneous energy system rather than the homogeneous one” that the industry started with, which means there will have five different sources, and they are all going to compete. Each will be dispatched and, consumed in a certain way, which means that companies will need “different processes that are nimble and flexible – trading, customer billing, customer service, sales, etc.,” depending on how a consumer is going to use all or some of them and manage them differently. As a company one needs to do something different, be smaller, and be nimble to “be able to turn up and down much faster” based on consumption. Also, Participant 10 said, companies will have to build the “ability to have a much stronger trading business across” those four or five sources. “All of that means that” resources industries “will have to transform.” Theme 7: Changing Customer Expectations as Forcing Resources Industry Leaders to Transform with Speed Interview data demonstrated the participants’ perception that their customers are demanding products that are produced efficiently, in an environmentally friendly manner, are price competitive, and want data transparency and analytics to help their choices on what products they consume, and when. For example, in the utility industry, as shared by Participant 4, “customer expectations are changing and they are asking for more data, information, to control their power choices and consumption.” It started with Smart Meters in 2012, and now consumers have Smart thermostats at home, battery backup, and solar roofs. “Consumers are willing to use different sources of power to be green, seek more information on outages, billings, and status of services when outages occur. This has required a transformation of systems and processes.” Customers are demanding the products they want along with data that demonstrates positive outcomes for sustainability. This was highlighted in the interview comments by 81 Participant 12 who said, “customers are very logical about products they want… and signal…that while we run a highly complex process and applying technology was driving efficiencies, we needed more data insights using AI and supplement employees with better decisions for customers.” In other words, customers are demanding better outcomes and services. Participant 6 had similar comments for the chemicals industry, where “using digital twins to provide a net zero water management solution is not sufficient anymore, and customers want best in class products and services deliver on outcomes” and do it “sustainably” which is “the primary driver of our transformation – how do we better serve customers.” In the energy industry, Participant 3 said that customer demanded that “we evolve to an integrated service provider” which resulted in them merging downstream, chemicals, and lubes into a single business which drove transformation. Participant 10 summarized this theme well when he said that “customer beliefs and motivation” have changed to “to demand something with a lower carbon footprint even if it is not economically the best choice” and “technology is allowing for data mining and data analytics, to aggregate data and expose the data to be consumed in a fashion” that is allowing consumers to make that choice and “to see the efficiencies they are driving.” Not only are consumers asking for energy to be produced efficiently and in an environmentally friendly manner, but they are also looking for price competitiveness. For Participant 13, as he explained in his interview, this led to their digital transformation program creating what they call Certified Digital Core Products that are scaled solutions to serve customer expectations and demand. Customers demand more of our products at competitive prices. So, to produce more we either add production capacity – which is expensive, or we optimize efficiencies in existing plants. So, our “Intelligent Process Optimization” Certified digital Core product 82 did that. Second, this reduces our cost of production which helps drive down prices to keep us competitive. Another certified digital core product we created was Supply- Demand forecasting which helped predict customer demand early which helped reduce inventory levels and reduce costs. Lastly, Digital Process Mining (DPM) Core Digital Product allows us to partner and serve customers better by doing credit checks and reducing credit holds in the Order Management process by streamlining credit checking and enhancing the customer experience. Theme 8: New Technology Advances as Facilitating Digital Transformation in Resources Industry Technology advances have been the primary enabler of digital transformation in the resources industry where automation, AI, Cloud, data analytics, machine learning, and sensor devices are driving down cost, improving customer service, and driving efficiencies in operations and according to Participant 4, “new Technology stacks, Tech standards, Agile ways of working change the way we do business.” Two of the 13 participants (2 and 5) attributed digital transformation initiatives as a result of their companies’ strategy and vision where Participant 2 highlighted that “advancing digital capabilities to accelerate business” was one of the top three pillars in their Chairman’s vision “to be the best energy company in the world.” In addition, Participant 3 felt that focus on data platforms is key as digital drives quality, “trusted and verified data access across the enterprise” which allows for “standardization across finance, asset management, sub-surface all at the enterprise level” and the potential of unlocking a lot of value. Participant 5’s comments resonated with those of Participant 4 as he said that “corporate advancement of technology” was one of the five key areas of their strategy. People want the “Amazon experience,” that digital technology allows for “that increases expertise, and increases 83 efficiency, and engages the end-user – as end-users value doing it on their own if you make it easy for them – this is the “amazon experience.” The example used was ordering something online versus talking to a customer service representative on a phone. Participant 9 explicitly stated that “there are four events that force us to think about Digital Transformation,” and of them, three are technology related. First is data, and according to Participant 9, any company produces more data than even the product they make. Advanced data analytics is key to exploiting the value of data in a digital world and the “company that will harness data will conquer the world.” Second, is the “fast technology cycles that we have seen, and one has to be agile to take advantage of the disruption it brings.” For example, Google invest over a billion dollars in building their AI engine and then comes along OpenAI, a $100M startup, that disrupted the AI field. Third is “data science, that takes a very neutral approach to help with a mindset change and ignores historical guesses,” and then shows what “the data interestingly suggests that in order to trade lithium” (as an example in commodity trading) “you need to track with a commodity that you never expected or tracked.” A similar example was noted for carbon emissions when Knox Energy was being investigated and was tracking only four variables, where “data science models looked at other thousands of variables and found six additional variables that could help reduce CO2 emissions in addition to the four being tracked. Participant 9 in highlighting “the power of data, analytics and digitalization” concluded that “the company that values the data equally as they value the products that they make will win.” Supporting commentary from Participant 13 described how they created “Core Digital Services” using their technologies and strategy of simplification, modernization, and digitization. Leveraging digital technologies such as AI, ML, and Data, they built over 100 pilots aligned with business priorities in operations. They called them “Proof of Values” to show value to the 84 business. Of these, those that showed the most value were converted to “Lighthouse projects” that “produced a Certified Core Digital Product that was scaled across the enterprise.” An example of a Certified Core Digital Product is their Intelligent Process Optimizer which has sensors and meters on assets that monitors variables using AI, and ML and optimizes the speed and quality of a product by improving the process, real-time problem fixes, and adjustment of capacity. Another Certified Core Digital Product is Digital Process Mining which improves the customer experience by streamlining the Order Management processes. Yet another example provided by Participant 13 is their Intelligent Predictive Maintenance service which senses and responds to issues before they occur and helps maximize the uptime and productive capacity of assets. According to Participant 13, all of their “Certified Core Digital Product Services” are data services derived from data gathered from sensors and other digital devices attached to assets. Theme 9: Frequent “Black Swan” Events as Forcing Resource Companies to Become Nimble, Resilient, and Digitally Enabled to Maintain a Secure Energy System Participants communicated a belief that in the era of war and pandemic-induced dampened business environment, supply chain challenges, cost pressures, mergers, and divestitures, acceleration of Digital transformation has been a key response in resources industries to maintain a secure energy system. All 13 participants mentioned that the Covid pandemic, the war in Ukraine, the energy industry downturn cycle, and merger or divestiture activity that has either accelerated or caused them to initiate digital transformation programs in their companies. Participant 9 covered it well by saying that “most companies are prepped to handle one black swan event. Now we see many black swan events – Covid-19, the war in Ukraine, Energy transition, climate change, focus on CO2 emissions.” In citing Southwest airlines, Participant 9 called it “a fundamental failure of business because their technology stack 85 just could not scale up as they lost focus on technology change during Covid.” For the utility industry, Participant 4 said that “Covid forced the work from home flexibility which now is becoming the norm,” and now we have to power people’s homes for work versus work locations” which “is a big change in consumption pattern and expectations.” Participant 6 commented that “Covid did not bring anything new to the table from a digital transformation perspective,” it accelerated digital transformation for them as “we had to serve customers who faced dislocation, re-engineered processes, and addressed some new demand for food services due to the disruptions in supply chain.” Participant 12 comments resonated with those of Participant 6 when he said, “the Pandemic forced us to operate remotely, accelerated new ways of working, being more flexible, dynamic and operate from anywhere.” Several participants provided comments about the impact of the war in Ukraine on the resources industry. Participant 4 noted that the war has significantly increased their fuel costs to produce electricity, leading to higher electricity bills for consumers. His company believes that digital transformation through driving efficiencies in operations could help reduce these costs. Participant 10 highlighted the impact of the war on energy security dynamics, stating that Europe would never trust an oil-rich Russia under Putin’s leadership. He further added that the recent breakdown in trade contracts, as a result of the energy dependence being leveraged as a weapon in this war, has led countries to reevaluate how to make their energy supply more secure. Digital transformation will have a big role in this reevaluation process. The comments overall suggest that global events are influencing who the future energy consumers and producers will be. According to Participant 3, the resources industry faced a “compelling platform for change” due to the “one-two punch” with the market changing due to the downturn cycle of business and the Covid pandemic which “was the catalyst” and as “oil prices went negative,” and 86 “this was an accelerant for digital transformation.” Participant 3, further said it “accelerated the hybrid model of how we work, forced collaboration in a digital environment, and made us more adaptable to market condition changes.” Interview data from most participants confirmed that the environment is changing more rapidly and with agile ways of working, advanced analytics, and a nimbler construct. Three participants attributed mergers, acquisitions, or divestiture as activities that jumpstarted their digital transformation. According to Participant 8, “our company sold a majority share to another company…and we used this event as an opportunity to transform business processes, technology, and legacy applications.” Covid did help accelerate the journey. Participant 13’s comments resonate as well as he cited, “merger with another Mega company” and “Covid helped elevate the appetite of broader organization to embrace digital transformation as Covid created a shortage of raw materials,” and “we wanted to become sharp with Digital” transformation which offered “new ways of working, and different ways of connecting.” According to participant 9, “the world is different now, and the bottom-line is you have to be digital to survive!” “You have to be” rebuilding “talent,” doing “big data,” and keeping up with “fast technology cycles to beat black swan events.” Theme 10: Government’s Leadership Role in the Pivot to Energy Transition Based on participants’ interview data, there is a perception of broad-based consensus amongst the resources industry that while the government has a role to define policy and regulations around ESG, emissions, and security of infrastructure which is key to ESG (Environment, Sustainability, and Governance), without interfering in areas best driven by free market forces. In other words, the government should engage in “the What” and should leave “the How” to the industry. Participant 1 was opposed to any government intervention at all, 87 saying “I hope not!,” as she believes that “Government regulations on sustainability, security, rarely have an end-to-end view of impact and costs. They look at specific areas in isolation and create problems elsewhere.” All other participants felt that Government has a role to play in the following areas: Preserve and Protect Nature One of the key areas is preserving the beauty and quality of natural resources. Preserving and protecting the natural beauty of places such as Colorado, West Texas, and reservations, where pipelines that transport oil and gas are laid are important to Participant 2’s organization. “If the government did not set the vision to keep it beautiful, we would see vertical wells, shallow wells scaled today” (Participant 2). Participant 12 expanded on this ESG theme stating “this is central to achieving the goals of energy transition – set policy and goals around recycling, track and trace, establish proof of credibility across the value chain with CO, emission…lead all of this with right policies and regulation. Cyber Security The resources industry operates power plants, power grids, nuclear plants and refineries. In the words of Participant 3, the “resources industry operates critical infrastructure” and “it is very important that it be policy enabled” to be protected from cyber threats. In other words, protecting against cyberattacks is paramount for national security, and therefore, the government needs to define standards and ensure that security standards are followed by the resources industry. Data Sovereignty In the technology realm, data storage and movement of data across international borders requires attention. In a world where “data is called the new oil,” Participant 3 felt that the government needs to design “policies on how you move data around the world.” This is 88 primarily grouped under data sovereignty policies which determine that while a country may own the data, it may still be subject to rules and regulations of countries where it may reside. Responsible AI With emerging advanced analytics and “Responsible AI,” Participant 3 sees the need for “a societal role on policy on Open AI.” Similar comments from other participants pointed to responsible AI as an important consideration in the development and deployment of open AI systems. As AI technology continues to advance, it is essential that Government develop policies and standards to govern its use in an ethical and responsible manner. A societal role in policy on OpenAI is an important step in this direction, and government must work together with the resources industry to ensure that AI is developed and deployed in a way that benefits society as a whole. Safety “Policy constructs on use of technology as safeguards in operations that calls for companies to protect the environment and save lives” requires Government leadership (Participant 3). Participant 4’s comments highlighted the need for Government’s role in creating “policies and guidelines around cloud, security, operational technology (OT) environments” such as power grids and plants to ensure that these critical infrastructure systems are secure, reliable, and resilient. However, he cautioned that government “regulations should not dictate how you run your business.” He illustrated this with the example of how government regulations discourage the construction of new coal plants even if a new coal plant is the most cost-effective and best option for providing energy to consumers. Participant 4, further added, that as some of “these regulations do not lead to sound business decisions,” and government should balance regulations with business agile and flexible decision-making for the industry. Additionally, Participant 4 also 89 highlighted that policies should provide clarity on recovery mechanisms for cloud infrastructure investments to encourage utilities to adopt and benefit from cloud transformation programs. Data Privacy In discussing future technologies, Participant 3 highlighted that “with the advent of the Metaverse… not only your personal data privacy is important, but so is your avatar’s that will expose your privacy.” Other participants’ comments were also insightful in this area as the concept of the Metaverse involves a creation of a virtual world that mimics the physical world where users interact with each other by creating a digital version of themselves called avatars. This creates an additional layer of complexity to privacy concerns because the avatars could reveal confidential information in the digital world. Also, hackers could hack into avatars to gain similar confidential and identity data. As such, there may be a need for new regulations and policy to address the unique data privacy challenges introduced by the Metaverse. Upskilling Population Education, research, innovation. Participants 10, 11, and 12 all commented on the fact that government should incentivize training, education, societal connectivity, and upskilling citizens to be digital (with an innovation and data mindset), and regulation should stay close to the technology advancement that incubates a change. Examples such as Sulphur-di-oxide, Nitrous Oxide emission regulations in California have laid positive precedence. Participant 11 felt that the government's role is to be participating, to be involved in the end, watching closely the activity that's going on, not to get in and start controlling and prescribing “how” things are achieved, but rather be co-creating “what” needs to be achieved, so what is 90 “the art of the possible,” and then providing the space and the time for the free market to come up with, and experiment and explore “the how” in the best possible way. Participant 11 further added that government should approach this as a partnership and collaboration where regulations prescribe the standards and rules up front and do a better job in co-creating and allowing for transparency, while at the same time enabling the industry to go fast. Participant 5 summarized the sentiments of most participants when he said that “We have a dual energy challenge – meet market demand for energy and reduce CO2 emissions” related to climate change. In describing the role of government in facilitating an orderly energy transition using digital technologies, Participant 5 said: How can we make the largest impact with the lowest cost to society? Digital transformation can help here, and Government has a role to play in this whole new market…the new Energy system – with new policies, and new regulations. A proper partnership is needed between people making the rules and people who are trying to solve the problem. The fundamentals of that partnership are Stability, Clarity, and Legislation that drives the right behaviors. Don’t pick winners and losers, let the market forces do that. Focus on outcome versus intermediate solutions. So, create legislations that incentivize people to do the right thing for outcomes - with clarity and stability. Having a very secure and long-term incentive legislation, and reliable market conditions – so that we can be clear on the right things to invest in…what we need is a fiscal fundamental market regime that does not pick winners or losers and let technology and innovation be the winner. 91 There are six key points in this quote from Participant 5: 1) Digital transformation can make a large impact in creating an energy system that meets the world’s energy needs with the lowest cost to society; 2) Government has a role to play in creating new policies and regulations for the new energy system; 3) A proper partnership is needed between those making the rules and those solving the problem; 4) The focus should be on outcomes rather than intermediate solutions; 5) Legislation should incentivize people to do the right thing with clarity and stability; and, 6) For all of this to work, the industry needs a fiscal fundamental market regime that does not pick winners or losers but instead lets technology and innovation be the winner. Research Question 3: How do the Internal Contextual Factors Impact the Executives’ Ability to Drive Successful Digital Transformation in Resources Industries? Research question 3 explored the internal contextual factors that impact participants’ ability to drive digital transformation in their organizations. Questions and probes were specific to internal factors such as leadership, organizational culture and climate, systems and policy, technology, and partnership ecosystem. Participants were asked to provide their rich descriptions based on their lived experiences on the importance, challenges, and ideas to work through each of those factors that either helped or hindered their efforts in driving digital transformation in their organizations. Figure 6 ranks the top three prioritized factors for all 13 participants and it shows that talent, strategy, technology, and funding rank in the top four most prioritized internal factors. Leadership was highlighted by each participant as a key factor and in some cases included in talent. Based on the interview data, four major themes emerged that are described below. 92 Figure 6 Participants’ Prioritization of the Top Three Factors That Likely Drive the Most Impact on Digital Transformation in the Resources Industry Note. Each of the 13 participants was asked if they had a magic wand and could have three of the barriers to digital transformation in their companies disappear. Their responses for each of the factors have been represented in the bar chart. 8 6 5 5 3 3 3 2 2 1 1 0 1 2 3 4 5 6 7 8 9 TALENT DIGITAL STRATEGY TECHNOLOGY FUNDING LEADERSHIP AGILE CULTURE BUS VALUE CHANGE INCENTIVES CUSTOMER EXPERIENCE ECOSYSTEM FREE MARKET Top Three Factors Required To Drive Digital Transformation 93 Theme 11: Alignment with Organization’s Business Strategy and Mission as Key to Driving Digital Transformation Based on all participant interviews, there is a strong belief across all participants that a digital strategy with clarity of value to the business, grounded in process efficiencies through automation, that garners leadership sponsorship, provides for education and empowerment of individuals and teams, creates a culture of innovation is key to driving successful digital transformation in resources industries. All participants who are driving digital transformation with any level of success highlighted that it was key to have the digital strategy aligned with the organization’s business strategy and vision. Participant 8 simply stated that “alignment of vision, a digital roadmap, with business is key.” Participant 11 described how the organization’s CEO, CFO, and CLO all sat with him “to understand and agree on a common nomenclature for digital transformation and how it aligns with the business strategy.” He further went on to explain the details of agreeing on “Digital Enablement, Digital Optimization, and Digital Transformation” as distinct and that each of them aligns with their business strategy. This has been the basis of their success for the last four to five years of their digital transformation journey. Participant 11, further communicated the perception that any change by definition is disruptive and hard, and so it faces resistance and rejection at first. Their company first pursued “enablement” by having education discussions and creating teams. Next, they went on to “optimize” the capital-intensive, asset-incentive components, and how work gets done. Automation, for Participant 11’s company, which demonstrated “productivity” and “efficiencies” was an important part of the business strategy. Once demonstrated, “it then helped mobilize and recruit a lot of naysayers to the business model change – “Digital transformation” – which was all about growth and then allocating capital from certain parts of the business to other new digital businesses that were 94 aligned to their business strategy. To illustrate the point, Participant 11 described how his company prioritized optimization of their oil transport using AI algorithms, to save capital that was then reinvested in new businesses such as unregulated retail energy, power walls, etc. These new businesses were part of their business strategy aligned with the energy transition in the resources industry and the shift toward renewable energy sources. The new businesses were also set up to operate differently just like digital natives’ businesses. Participant 12 also had a similar point of view around leadership and the board recognizing the importance of digital transformation. According to Participant 12, the critical feature of a successful digital transformation strategy is to have it “central and aligned with the organizational strategy.” Based on several participants’ comments, without this alignment, organizations risk fragmenting their efforts and failing to achieve their overall digital transformation. To successfully implement a digital transformation, organizations must focus on transforming their business processes, not just adapting them to new technologies, and must communicate the value of the transformation to employees, customers, and leaders. By showing how the digital transformation strategy is aligned with the organization's overall strategy, companies can ensure better adoption and get everyone on board with the transformation agenda, and having them work towards the same goals. Failure to do so can lead to a disjointed effort that fails to deliver the desired results. Participant 1’s comments helped articulate that companies struggle with their digital transformation journeys when this alignment with business strategy is absent when she said: There is no digital transformation strategy…that to me is the missing piece…because without that [digital] strategy it's like trying to build a house without architectural plans… 95 you might be able to start to build the plumbing, and the rooms. But, are they going to hang together? In summary, participant comments give a strong perception that alignment of digital transformation strategy with the overall business strategy of the organization is key for it to take off successfully. Theme 12: “A Culture of Disciplined, Focused, Leadership Direction is Vital to DT!” (Participant 8) Based on the comments of interview participants, it is evident that having strong leadership focused on driving digital transformation, with the top-down sponsorship and support of the CEO and the board, is viewed as a major requirement for successfully implementing digital transformation in the resources industry. The participants communicated experiences that most companies that have a leader who understands the business, can work across IT to drive change, and is charged with leading the transformation (CDO, CIO, CTO, etc.) have seen progress (Accenture Research on CTO). All 13 participants spoke about the importance of the role of a chief digital or transformation officer to lead the digital journey. The role is important and difficult explained Participant 10, because this leader not only needs to have a top-down vision but also the “courage to take digital transformation forward based on the belief that it will yield results.” Participant 10 further expanded that driving digital transformation takes courage because it has inherent risks for both the leader personally and the company, since “our financial markets are not designed to tolerate beyond two to three quarters of poor performance.” In the words of Participant 7, “it is most important to having a good charismatic leader who has that vision and can articulate that vision, and get the company to understand and follow. Participant 7 further said that he feels “very lucky to have a supportive leader who expanded my role as 96 Transformation lead, increased my budget, provides support and resources.” Participant 1 made a compelling case and the cost of not having the role when she said, “We need a CDO who has been there, done that. This is not effective in our case” and if “we had the right leadership and... “had the right structure,”… “I think that a lot of…barriers would be…removed. Our problem is lack of leadership.” The second important aspect of this role is that a single person cannot do it alone, it needs the support and sponsorship of the C-suite and the Board. As Participant 2 said, you “need hands-on leadership to drive digital transformation. Our CEO, CFO, and COO, are all sitting at the table together on this.” Further, she added, “our CEO is an incredible leader and has the right DNA for understanding how to drive value and brought a clean perspective externally” which leads to the third point. The third aspect that most participants highlighted is that the chief digital office or chief transformation officer role is not an IT leadership role, and in most cases, the digital transformation leader is usually from the business and even from outside the organization. Participant 4 said that his organization hired a marketing leader “from the retail industry to bring fresh thinking in the digital space,” while Participant 5 said that his organization “pulled a very senior leader out of business in the role of Chief Transformation Officer to drive it,” and Participant 13 said his company hired a leader from the CPG industry. Lastly, the impact of leadership is best described in the comments from Participant 6 who said that “Leadership identifies the big ideas, gets right people in right roles, drives it... and sets the clock speed,” which resonated with the comments of Participant 2 who said that their leader “not only made us recognize that what we had been doing may not be the best way, and here's how to change and do things differently, and fulfill the vision through this digital transformation.” Participant 9 summarized it well by talking about the kind of change impact the 97 “right leadership behaviors” can have in driving and managing change. According to him, leaders who possess self-awareness, are open to feedback and have the willingness to challenge institutional knowledge, are capable of promoting a mindset change to adopt new ways of working within the organization. This is essential for an organization to adapt and thrive in a rapidly changing environment where an effective leader is seen as engaging employees early in the change process, providing them with the resources and support needed to succeed. Overall, there is a perception amongst all participants that, leadership plays a critical role in driving successful digital transformation in organizations. Theme 13: Business Leadership and Organizational Culture’s Key Role in Digital Transformation as Articulating and Demonstrating Business Value Value drives adoption amongst business leaders, the C-Suite, and the broader organization because according to Participant 2 when you prove and show the value, “it drives up motivation and changes the culture to be more acceptable to digital transformation.” Unfortunately, in the absence of business leadership that can show the value for business value and change culture, then as Participant 1 lamented, it becomes “one of the things that's an inhibitor for us being able to be successful.” According to Participant 6, “while the culture of the organization may not be ready, you have to show them successes and, over time, that problem melts away” especially when they “see themselves as the beneficiaries” of digital transformation. Participant 6 suggested that limited funds should be prioritized towards the most valuable projects and recommended that leadership help identify the biggest opportunities while committing to providing financial support for multiple years. Participant 7 agreed that at the executive level, the focus is on driving value and efficiency and that there is a strong interest in capital structures and projects. They 98 emphasized the importance of measuring the value of digital activity in terms of increased yields, efficiency, and better energy management, using hard economic calculations that consider both tangible and intangible factors such as preventing asset failure or extending asset life. Participant 8 said he accomplishes this by focusing on “outcomes that the business could agree on” and taking an enterprise architecture approach to prioritize for the scale of value for maximum impact on the organization. He also indicated a shift in funding priorities from a three to five- year ROI to a one-year payout period demonstrating a commitment to prioritizing funding for digital initiatives that provide value quickly. Participant 9 comments also conveyed a similar shift in their organization where “value and depth of adoption” are dependent on value seen in margins, and the organization does not talk in terms of cost, but in “terms of EBITA” or “the value multiplier that scaling” leadership, culture, and mindset shift bring for the organization. Overall, these participants’ comments emphasize the importance of aligning digital transformation with the organization’s goals, demonstrating business value, and prioritizing funding and resources towards activities that provide value quickly and have a significant impact on the organization’s overall performance. It is evident from the comments of interview participants that digital transformation leaders drive a culture of value with slightly different approaches. While Participant 5 uses a “principled approach” by bringing teams of their own and partner resources and “let the teams do different things and generate value in some very hazardous, difficult places,” Participant 11 drove their organization’s digital journey by having stakeholders with the “biggest assets and largest workflows” generate ideas and then conceptualize using MVPs (Minimal Viable Products) that generate the most value. This way “ownership and skin in the game trickle down to the organization’s managers and supervisors.” Participant 3 agreed when he said that “you 99 have to be able to show the business value of digital transformation to get buy-in.” Also, he was pulled out of the business and was put in front of other business leaders who are more receptive to him showing how “digital transformation drives value.” In effect, he feels like a “Chief Change Officer,” who conducts a PODCAST series, runs a Facebook site, enrolls other leaders to talk about their digital successes, meets with executive teams to communicate regularly, partners with the CIO on strategy and technology alignment, and communicates the business case through value cases in digital transformation. “Business leaders want to see the value and for that, we created tangible business cases to show value,” Participant 3 added, and this “creates the pull” as they see “how other business leaders created operational efficiencies and accelerate value from data.” In summary, all of the other factors fall in place that is required for digital transformation if one articulates value, and as Participant 10 stated, ultimately digital transformation needs to “show me the money.” And, according to Participant 10, to show the money or value, all of the following are important – “Leadership” that creates the vision and gets the organization behind the vision, “People” talent that is needed to drive digital transformation by working on “the right business processes to create value,” and “Culture to change the way I was working before - all the way at activity and task level.” For Participant 13, all conflicts at the business level about where resources (people and dollars) will be allocated to drive innovation were resolved by “following the value” from MVPs, and “everyone got aligned on those that would drive most enterprise-wide value from the scale.” Theme 14: Digital Transformation Requires Rearchitecting the Partner Ecosystem Based on interview data, participants perceive that the role of ecosystem partners has changed due to new entrants in the digital space. In the words of participant 5, “Ecosystems is 100 the new buzzword for partnerships,” and companies now need new technology companies and advanced universities as new partners. He further added that “another way to not fail in digital transformation is to never think you have all the answers” for which one needs an ecosystem of partners and to create an organization that is “completely flexible” for which you “leverage ecosystems to flex up and down.” Participants who highlighted the importance of ecosystem partners, have rearchitected usage in the following three areas. First, to leverage ecosystems for IT and other deeper skills, including agile methodologies, as stated by Participant 3. Participant 7’s comments echoed similar sentiments when he said that “strong ecosystem partnerships will be needed with firms who have the domain skills, technology skills, through co-sourcing agreements, bringing experts in key areas, and flexibility to staff up or down.” The second key reason participants advocate rearchitecting ecosystem partnerships is for the co-creation of ideas and leveraging investments. Participant 8 solved the lack of investment dollars and keeping up with the pace of technology change, by partnering with ecosystem partners such as Microsoft, Google, and AWS and taking advantage of their innovation cycles and saving his own company’s funds for capital projects. Participant 8 specifically highlighted the area of cyber security where he felt that no company can spend enough dollars in that area and if they did, they would have “no other funding left for other initiatives other than cyber defense and to solve for this, we rely on the hyper-scalers and their investments in cyber.” Participant 9 described a similar strategy where his organization also leverages the innovation investment dollars of ecosystem partners and “save our dollars for capital projects.” Participant 10 suggested taking advantage of a unique trend in the resources industry where they are used to forming Joint Ventures (JVs) to leverage large investments in capital projects and to extend that thinking into digital transformation. He said: 101 the way to de-risk is through partnerships – JVs are very common in the resources industry as due to the high capital costs companies partner and create JVs – it’s in their DNA. They should do the same with technology companies and leverage technology investments in tech innovation, R&D, etc. You have to partner with the digital natives to co-create. And they are becoming more open to it now – we bring industry knowledge, and they bring technology and investment dollars. When it comes to rearchitecting the ecosystem partnerships for digital transformation, comments from Participant 8 and Participant 13 summarized it best as “some get it, some don’t – align them to your digital transformation” and leverage them for: 1. Talent – both innovation, and execution talent where you “leverage the scale, efficiencies, competence, and reliability of the traditional big players like Accenture” for the deployment of digital services, “and TCS for run and maintain services.” And, fill the gaps for “speed and innovation with smaller and newer firms whom we are becoming more comfortable with.” (Participant 13). 2. Innovation dollars to co-innovate with partners leveraging their innovation cycle. 3. Cyber security, where Participant 8 is leveraging the best-of-breed security advancements and adapting to his organization’s security framework. Overall, it appears that participants believe that ecosystem partners are crucial in achieving successful digital transformation, and organizations need to be flexible and open to partnering with others to stay competitive and keep up with the pace of innovation. 102 Research Question 4. What are the Individual, Team and Organizational Values, Talent and Process Efficiencies that C-Suite Executives in Resources Industries Perceive are Needed to Drive Successful Digital Transformation? The purpose of research question 4 was to delve deeper into exploring the individual, team and organizational aspects and how leaders motivate, challenge thinking, and alleviate the fear of change within their organization. Talent, resistance to change, fear of job displacement and the role that leaders play to motivate the various segments of the organization were the main themes that emerged in the interviews. The three key main themes are presented below that speak to the participant’s perception of barriers, and opportunities to address them and drive digital transformation. Theme 15: Different Breed of Talent as being Required to Drive Digital Transformation Based on participant comments, talent as a factor of digital transformation, is rated in the top three list of factors needed for digital transformation by eight participants as shown in Figure 6, and their insights may be classified under three sub-themes. First, a hybrid set of skills are required for digital transformation. Participant 5 highlighted that a broad set of capabilities are needed to think through or “imagine how to build the business case and execute…one has to understand how the markets work, customer needs, and technology.” Both Participants 3 and 11 likened the role of a digital transformation leader to that of a product owner that requires acceleration of digital fluency and a “hybrid skill set.” Participant 3 further said, “we hire a new generation of people who come with integrated skills – a thermodynamics engineer is also a coder – skills that exist in this new generation, for others we sent them to MIT or RICE to build hybrid skills” for our talent capacity needs. Participant 11 described digital talent needs as “a very different level of skills needed – not just technology, it is also orchestration and translation 103 skills” where “one has to be able to conceptualize and drive the change.” Participant 11 confessed that this is not easy to do and they try to “address this through job rotation, reskilling, training to build hybrid skills.” The second sub-theme related to the talent that emerged, based on participant interview comments, focuses on the hiring and retention of talent, with participants highlighting the challenges of finding well-rounded people with digital skills and the need to create a culture of learning and development to retain them. According to participant 7, their leadership understands the aging workforce problem and the challenges they need to address as a result because the young, new workforce needs new tools and digital is required to hire and retain this new workforce. Both IT and business groups within the organization struggle with this as both need “well-rounded people.” Participant 8 spoke about the challenges of finding talent and said, “you have to onboard, retain, and outsource” and “skills in cyber, cloud, DevOps, and over the last year, all of them went to AWS, Microsoft, and Google. Now with the tech meltdown in 2023, we are starting to see that ease.” To address this, Participant 8 further said that “we built a common platform and a shared services team that was infinitely scalable.” Participant 9 described the workforce entering the job market in the last decade as one gone from “embracing digital” to “grown digital” and that digital is the only world they know and “so for us to attract the talent we need to be digital.” Also, talent attrition is at an all-time high with digital skills being in high demand. To counter this, Participant 9 created a “Culture of Learning – an initiative that provides each employee half a day a week to learn something from a digital university that we have created in our organization.” Training tracks include data science, data engineering, cloud, security, cloud essentials, solution architecture, and every employee has the flexibility to learn 104 what they like. There is a three-year commitment on the part of Participant 9’s organization, and their “philosophy is to train more people than the people who leave.” The third sub-theme related to talent, as articulated by Participant 2, is peoples’ readiness to change “as there are different levels of experiences and it takes time to get alignment, and some cannot see the vision and you need people to see the vision to execute it.” To accelerate this “adoption curve,” Participant 2 recommended a “nimble governance and agile leadership,” without which one “impacts execution, which impacts people’s morale and motivation goes down” during a digital transformation. Participant 6 also spoke about the skills and adoption of the recipients of change and said that digital transformation requires “skills, capabilities, and people readiness on the customers’ side that we serve” as well. Participant 6 further added, “You have to put the right people in the right roles, remove barriers for them, set the clock speed, and create the inspiration for risk.” Even if all the talent problems are resolved, there is a challenge with balancing skills capacity and bandwidth. Both Participant 4 and Participant 7 highlighted that having the bandwidth to do all the digital transformation and adoption work, and also perform the day-to-day jobs is a challenge. Participant 13 highlighted another challenge related to blending the two types of skills required for digital transformation and said they grapple with “blending the best of both worlds.” He said, “One group is about spotting the opportunity and innovating. Second skill is a different skill that takes that and executes it at scale into 74 factories,” and you have to get the “super-agile blending of these” and get the transition from one to the other right. In summary, based on the interview data, participants perceive that a blend of business innovation and technology execution skills is needed to drive successful digital transformation, and going digital is crucial to attract and retain new-age talent. Also, once digital talent is 105 acquired, trained, and gained experience, their retention becomes most important as there is high demand for those skills. To manage the attrition of digital talent, one needs to train at a faster clip, motivate employees to retain them, and manage the two key types of skills appropriately to drive a successful digital transformation. Theme 16: Culture and Climate that Encourages New Ways of Working, Risk-taking, Imagination, and Innovation as being key to Digital Transformation Culture and climate were discussed by 11 of 13 participants as key factors in driving digital transformation in the resources industry. Four key sub-themes emerged in the various mentions by the participants that included new ways of working that required cross-team collaboration, enterprise-level thinking, and empowered teams, that drove the digital strategy with clarity (Participant 1). Participant 3 assayed a similar “enterprise first mindset and shifting from a business unit” mindset that should be “incentivized by HR” to align leadership and the organization “to reduce resistance” and move from “a competing business unit (BU) mindset to enterprise-wide collaboration” mindset. This forces all the “power of the organization to row in the same direction, towards the same goal” said Participant 7. Participant 8 was emphatic in his comments when he said that “digital transformation cannot work without collaboration” culture. The second key aspect of culture that facilitates digital transformation is for it to allow for risk- taking as explained by Participant 7: You need a culture that removes barriers, that trusts employees to act responsibly, and make good, sound decisions. It is a culture that is entrepreneurial, and allows risk-taking, especially when it comes to new technologies – invest in experimental technologies where value can be derived. This does not take place in the resources industries, it does in the technology industry, and we need to learn from that culture of technology innovation 106 and investment. We may invest in four to five things, and only one may pan out. To solve for this, we need to make this cultural shift to risk-takers, and reward risk-taking. A culture and climate that promotes imagination were also highlighted by Participant 5 as it is “difficult to see where digital transformation will take us until it happens.” Citing UBER as an example, he said that it “stares you in the face and no one saw it coming until UBER saw it.” You have to promote this imagination as part of the new ways of working. Participant 2’s comments highlighted the need for a culture of imagination, as she talked about how they had to “reimagine the business” and had to “draft people …who had to feel and say that they work for this company” and for that “to get our culture and values” right. And, as Participant 12 stated, “if you have the right culture to innovate, embrace change, etc., you can do digital transformation.” Based on the insights and examples from participants’ interviews, creating a culture and climate that promotes innovation requires cross-team collaboration, enterprise-level thinking, empowered teams, a culture of imagination, and clarity of digital strategy. In addition, as Participant 9 best explained how to overcome the cultural barriers that impede digital transformation requires “four things – seeking different perspectives, working for the greater good, creating an environment of trust, and operating for excellence.” Additionally, he said that to drive the right culture, “you have to make sure that the incentives are lined up to drive the right behavior” and shift from the “institutional way of thinking and think about agile, nimble ways of working.” Citing lithium as the new commodity needed in EVs, Participant 9 suggested adopting new, innovative, and imaginative approaches to challenges, such as trading in lithium for the EV industry versus the other commodities that do not fall in the same basket of commodities, such as crude, that the industry is well versed in. Based on these insights and examples from interview participants, there seems a clear perception that a culture and climate 107 that encourages new ways of working, collaborating, innovating, imagining, and risk-taking is a key requirement in driving digital transformation in the resources industry. Theme 17: Organizational Leadership’s Key Role in (Motivating People and) Overcoming Fear of Job Displacement Requires a Commitment to Employee Reskilling All 13 participants commented on the key role that organizational leadership must play in driving digital transformation by alleviating fears of change within the organization. Participant 9 stated that “everyone reacts to change differently, and at the end of the day it is about people, personalities, and personal aptitude to change.” In the words of Participant 2, one has to motivate at the individual level by “understanding what motivates them” and “why they do what they do,” and then allay their fears and “incentivize them in a way that makes them willing to change.” Participant 3 said that “resistance to business process change by people whose jobs are impacted or roles change,” is there in all companies that are not digital natives and leadership has a role to play. Participant 12 felt that the fear was “more about the job changing versus their job going away,” and so it is important that as part of change management leadership, people need to be explained and shown the difference in their skill and therefore job levels due to digital transformation. To this point, he said, “show the difference in users of technology, that IT people are now engaged in business and beyond IT, how you improve.” Some participants do not see the fear of job displacement as a problem. For example, Participant 9 saw their “workload quadruple” as a result of digital transformation and they “don’t have enough people with talent to do it,” and their goal is “to upskill people at a faster pace than attrition” as those skills are in demand. Participant 11 called this “fear is real” and something that is “hard to solve.” He had a very good explanation of how digital transformation leads to upskilling and improvement of jobs only if there is growth in the business. 108 You usually start with the demand pull on RPA to automate and eliminate the grunt work people do. They then move to higher skills work. Then we do ML and prescriptive analytics and actions recommended to further ease the work of people. This pace of reskilling and the pace of redeployment of people assumes that the new work is there, which implicitly assumes growth. Now if there is no growth in the business, job losses will be there at the expense of increases in productivity and efficiencies. So, this fear is there, and this is hard to address completely. Participant 13 downplayed the fear and the issue in the resources industry saying that while they are “very aware of this worry…it is not huge at our company…as there is a very large ambiguity tolerance given the nature of our history with mergers, acquisitions and divestitures” and our people “see opportunities in volatility versus other relatively static businesses.” He further felt that their “culture of science and technology allows employees to embrace learning readily, get better, and go after more value-add work moving up the value chain versus spend time with more operations.” Also, leadership is committed to upskilling their employees and seeing jobs getting richer. Overall, Participant 6 summarized it best in terms of the role of leadership irrespective of whether the issue is seen as real or not by companies because, in the end, it is a “dislocation of capability.” For example, if the digital transformation is in the area of customer service, the customer service organization will resist being dislocated and leadership has to provide them with the security of what’s next for them. Also, as Participant 6 highlighted, the “other fear is that of exposure as transformation puts the spotlight on the performance of groups that have historically not been held accountable” and, as a result, “adoption is impeded.” Based on the interview comments from all participants, there is a perception that the fear of job displacement – be it job loss, capability dislocation, or job change – is a real concern when it comes to digital 109 transformation. While some participants see this as a problem that can be addressed through upskilling and redeployment of employees, others feel that it is a hard issue to solve completely, especially if there is no growth in the business. However, all participants agreed that leadership plays a crucial role in addressing this fear by providing security and empathy to employees and committing to job reskilling to ensure that people are motivated in taking the digital transformation journey. Summary of Findings Data from 13 interviews with 13 participants from 13 companies were analyzed to answer four research questions about digital transformation in the resources industry. Seventeen themes emerged from the data analysis as presented in this chapter. Figure 7, a summary of all a priori codes mentioned by participants, shows that all except one of the factors aligned with the conceptual model that explored internal and external factors of change under the key areas of culture, systems and policy, leadership, and external factors that were part of the a priori codes. The one internal factor about the fear of job loss may be also aligned to culture that emerged as a side impact of digital transformation in the resources industry. 110 Figure 7 Summary of A Priori Codes Mentioned by Interview Participants Note: Coding as mentioned by each of the 13 participants was mapped to gauge what was seen as relevant by the participants based on interview data analysis. The figure shows the number of participants who discussed each of the a priori codes in their interviews. 6 12 13 13 13 13 8 13 12 10 5 0 2 4 6 8 10 12 14 EXTERNAL - ROLE OF GOVERNMENT EXTERNAL - MACRO TRENDS, PANDEMIC, WAR, CUSTOMERS INTERNAL - LEADERSHIP - ALIGN STRATEGY & MISSION INTERNAL - LEADERSHIP - SPONSORSHIP & LEAD BY EXAMPLE INTERNAL - SYSTEMS & POLICY - TECHNOLOGY & ECOSYSTEM PARTNERSHIPS INTERNAL - SYSTEMS & POLICY - HRM - HIRE, TRAIN, RETAIN TALENT INTERNAL - SYSTEMS & POLICY - ALIGN GOALS WITH REWARDS INTERNAL - SYSTEMS & POLICY - WAYS OF WORKING - AGILE, INNOVATIVE, PROCESS REIMAGINATION INTERNAL - CULTURE - CLIMATE OF GROWTH MINDSET - MOTIVATION DNA INTERNAL - CULTURE - ESG IMPACT OF ENERGY TRANSITION INTERNAL - FEAR OF JOB DISPLACEMENT A Priori Codes Mentioned By Interview Participants 111 As seen in Figure 7, all 13 participants mentioned leadership, talent, technology, ecosystem partnerships, alignment with business strategy, innovative and new ways of working, as factors perceived to be key in driving digital transformation in the resources industry. Following that 12 of 13 participants highlighted how the external “black swan events”, in addition to the normal business cycles in the resources industry, such as Covid-19, Russia’s war on Ukraine, and changing customer expectations have served as an accelerator of digital transformation in the resources industry. Also, it is clear from the interviews, and as Figure 7 highlights, that having a climate of collaboration, and a growth mindset are important for driving digital transformation in the resources industry. Further, the need for incentives and rewards that encourage this behavior to achieve the goals was mentioned by eight of 13 participants. Six of 13 participants spoke about the role of government leadership in policies that facilitate an orderly energy transition, digital transformation, and cyber threat protection. Lastly, five of 13 acknowledged the significant concern regarding job loss as a real obstacle to the adoption of digital transformation. They stressed the need for leadership to commit to upskilling as a way to alleviate that fear in those whose roles and jobs may be displaced as a result of digital transformation in their organizations. Chapter Five contains recommendations for how the resources industry should focus on the key factors to achieve the benefits that they all outlined from digital transformation. In the words of Participant 3, “Our time is now” and “we (in the resources industry) stand to benefit the most in the next 100 years from digital transformation” are clear indicators of things to come in the resources industry with the energy transition, changing customer demands, and the ever- changing global macro environment. 112 Chapter Five: Discussion and Recommendations Chapter Five discusses key findings and presents recommendations for increasing the adoption of digital transformation in the resources industry. An integrated view of the key findings and recommendations is also presented. The discussion of findings has been delimited to focus on key issues versus repeating alignment to the a priori codes that formed the basis of the research questions grounded in the Burke-Litwin model of change-based conceptual model. Key recommendations for practice based on key findings that are aligned with the conceptual model are presented, and subsequently, the focus shifts to areas that emerged as surprise findings or gaps that require future research. Finally, the chapter also includes limitations and delimitations of the study, implications for the field, and concluding remarks. Discussion of Findings Based on the findings from this qualitative study, the resources industry seems to be aligned that digital transformation means more than solely a technology transformation and requires a reimagination of the business processes to add business value, and improve the customer and employee experience. However, how an organization arrives at the decision to undertake digital transformation and how each organization executes its digital transformation is different for each organization and depends on an organization’s history, culture, and business rationale. Also aligned with the literature review, this study found that the resources industry looks for inspiration from retail, financial services (investment and retail banking), technology, airlines, and food and beverage companies. Also, the findings highlighted four reasons why resources industries have lagged in digital adoption compared to these industries. First, its product (oil, chemicals, electricity, power, etc.) is not impacted (modified or enhanced as they are for banks with cryptocurrencies, digital media content for media companies) nor are new 113 products created (information-based services for IT companies, digital media creation, and consumption for communications and media companies) by digital transformation. Second, the resources industry is predominantly a B2B (Business-to-business) operation with no direct interaction with end consumers, while other industries are B2C (Business-to-consumer), and therefore customer-centric, and customer demands drive change and adoption of these new digital ways to operate. Third, other industries do not require a brick-and-mortar establishment to operate as they can sell and reach their customer online (OTT for media companies, Amazon website for retail, software as a subscription for technology companies) as a result of digital transformation. In contrast, for the resources industry, gasoline or chemicals (the product is a physical product) cannot be altered by digital means, cannot be sold online or delivered to the consumer, and therefore needs a brick-and-mortal establishment (Cortada, 2003). Lastly, mergers and acquisitions (M&A) is a key aspect of the resources industry that also impacts focus being taken away from digital transformation. Based on the literature review, and as stated in chapter 1 of this study, there is limited research in this area for the resources industry. As Vogelsang et al. (2019) concluded that while their study, based on 46 expert interviews at 31 manufacturing industries, found five barriers to digital transformation namely missing skills, technical debt, individual fear, organizational and cultural factors, and environmental reasons, more areas could be further researched. Findings from this study, based on the study’s conceptual model informed by the Burke-Litwin model of change, were in alignment with themes of talent, strategy, technology, leadership, culture, and external factors that included changing customer expectations, environmental factors, and macro world events. In addition, this study also identified new themes that may require future research, namely, the role of government, energy transition, value-driven business case, and advancements in operations technology. 114 Talent Findings The study found that driving successful digital transformation requires a blend of business innovation and technology execution skills, and at the same time “going digital” in turn is essential for attracting and retaining the new generation of talent. Also, once digital talent is acquired, trained, and has gained experience, their retention becomes most important as there is high demand for those skills. According to the Organization for Economic Cooperation and Development (OECD), a third of workers in the age group of 16-64 across all industries, lack digital literacy skills (OECD Survey of Adult Skills, 2012-14). Kaminski et al. (2009) also found that advanced digital skills such as database management, programming, web animation, and digital video and audio skills were significantly hard to find. To manage the attrition of digital talent, one needs to train employees at a fast pace that exceeds the rate of attrition (Participant 9), and keep employees motivated, and manage the two key types (innovation and execution) of skills appropriately to drive a successful digital transformation (Participant 5, and Participant 6). Digital Strategy Findings Rogers (2016), as highlighted in the literature review, argued that “digital transformation is fundamentally not about technology, but about strategy” (p. 308). Based on interview comments, there is a strong belief across all participants that a digital strategy with clarity of value to the business, grounded in process efficiencies through automation, that garners leadership sponsorship, provides for education and empowerment of individuals and teams, creates a culture of innovation is key to driving successful digital transformation in resources industries. Value drives adoption amongst business leaders, the C-Suite, and the broader organization, and once people see the value, it also increases motivation and helps change the culture to be more accepting of digital transformation. 115 Technology Findings Technology advances have been the primary enabler of digital transformation in the resources industry where automation, AI, cloud, data analytics, machine learning, and sensor devices are driving down costs, improving customer service, and driving efficiencies in operations. These digital technologies, as highlighted in the literature review, have led to major shifts in the manufacturing industries and the fourth wave of technological advancement called Industry 4.0 (Savastano et al., 2019). It is clear from 40% of the participants that customers and employees want the “Amazon experience where things are so easy to do that you would rather do it yourself” as stated by participant 5. In addition, it appears that participants believe that ecosystem partners are crucial in achieving successful digital transformation, and organizations need to be flexible and open to partnering with others in order to stay competitive and keep up with the pace of innovation, leveraging technology companies’ innovation dollars, and for their innovation and execution digital talent. As presented in the extant literature review, some researchers such as Rayna and Striukova (2016) have described these disruptive technologies as the bearer of radical changes in business models for organizations. Leadership Findings Based on comments from interview participants, the study found that strong leadership is essential for driving successful digital transformation in the resources industry. This aligns with the literature review of Cortada et al. (2003) who highlighted that without strong and effective leadership, no transformation can be successful. In particular, the findings emphasize that having a leader with a top-down vision, the courage to take both personal and business risks, and the ability to articulate and clearly communicate the vision is crucial for driving digital transformation. Noel Tichy (2002) observed that leaders need to decide what needs to be done, 116 and also pick the right team to make things happen. Also, the leader must have empathy in addressing the fear of job displacement, brought about by digital transformation, by providing security and empathy to employees and committing to job reskilling to ensure that people are motivated in taking the digital transformation journey. Such a leader can command the respect of leadership, business and IT teams, can challenge institutional knowledge, and promote a mindset change in driving the adoption of new ways of working within the organization. Culture Findings Based on participant comments, the study findings highlight that in order to drive digital transformation in the resources industry, it is important to create a culture and climate that promotes innovation, cross-team collaboration, and risk-taking. This aligns with the literature review of Petter et al. (2018) that highlights the importance of creating the right culture and leadership in companies that attracts the talent with the right digital competencies. To drive digital transformation, companies need to re-invent themselves structurally, adopt new business models, which require skills around agile, and new ways of working (Mihalcea, 2017). Participants also mentioned the need for HR to incentivize enterprise-level thinking over business unit siloed thinking, and empower teams to execute the digital strategy aligned with overall organizational goals. They also stressed the importance of removing barriers, trusting employees to make sound decisions, and promoting an entrepreneurial culture that allows for risk-taking, particularly when experimenting with new technologies. Customer Expectations and other External Events Findings Participants communicated a belief that companies were set up to handle one “black swan” event in history, referring to those highly unpredictable, extremely rare, and catastrophic events such as Covid-19, the war in Ukraine, and energy transition due to climate change, that 117 have now become a norm. In the era of war and pandemic-induced dampened business environment, supply chain challenges, cost pressures, mergers, and divestitures, the acceleration of digital transformation has been a key response in resources industries to survive. Also, it seems that customer expectations are changing as they are increasingly conscious of the impact that their choices have on the environment and are demanding products that are produced sustainably. This aligns with the literature review where research by scholars such as Deiser and Newton (2013) discussed how consumers engage with organizations on digital social media platforms with responses that create resonance and engagement. Technology is enabling consumers to access data and information about usage, downtimes, outages, and environmental impacts, allowing them to make informed decisions about what they consume. At the same time, customers are prioritizing price competitiveness which means that companies must find ways to balance changing consumer demands with higher production efficiencies to remain successful. Additional Findings As mentioned in the introduction to this chapter, there were additional findings that may require further research. In addition to how a proper business case should be created to secure funding for digital transformation, the findings reveal that the energy transition is a key driver of digital transformation in the resources industry, not just an outcome of it. This also leads to a need for collaboration with the government where the government has a key role in policy to facilitate an orderly transition and secure the energy and power infrastructure of a nation. Wheelan (2019) stressed that policymakers must focus on a competitive environment that creates wealth and not focus their efforts on methods and skills that are in decline. New digitized and nimble processes around trading, customer billing, customer service, and sales to accommodate the different ways customers will consume and manage the various energy sources will be driven 118 by data as a core pillar of digital transformation. Here, developments in operational technology are starting to emerge which aligns with the literature review where Savastano et al. (2019) highlighted the emergence of Industry 4.0, and how they contribute to and change the digital transformation for the resources industry also may require future research. Recommendations for Practice The key recommendations for practice are provided below for the six key areas, namely talent, digital strategy, technology and ecosystems, leadership, culture, and external factors including customer expectations. These recommendations are grounded in promising practices from literature that are aligned to address the challenges identified by the study. Also, recommendations for four areas that require future research are also provided. Additionally, a summary of key areas of findings, and recommended actions for practice is summarized and provided in Table 3. Talent Recommendations Kate et al. (2017) reported that one of the most critical challenges in driving digital transformation that most companies struggle with is finding the right talent, and then retaining that talent by designing career paths that meet their needs. Based on participant comments, talent as a factor of digital transformation is rated as the top factor needed for digital transformation by eight of the participants as shown in Figure 6, and is hard to solve because digital transformation requires a hybrid and broad set of skills that include understanding of the industry, markets, business process, customer needs, technology, new agile ways of working, orchestration and translation skills. These are the three recommendations identified to address the findings: 1. Create a job rotation, reskilling, and training program to build hybrid skills. 119 2. Focus from HR on hiring, training, and retaining talent that is well-rounded, and has required digital skills. Also, there is a need to create a culture of learning and development to retain them. This aligns with the study by Mihalcea (2017) which revealed that learning and leadership development, mobility, rewards, and competency systems must be focus areas for recruiting and retention. 3. To counter attrition due to the high demand for digital skills, organizations should create a digital university to train their employees in digital tracks such as data science, data engineering, cloud, cybersecurity, cloud essentials, solution architecture, and agile methodologies. Digital Strategy Recommendations It is evident from comments from interview participants that leaders drive the business and value case in different ways. This aligns with the literature review of Cortada et al. (2003) who highlighted that without effective business strategies that exploit digital technologies, no transformation can be successful. Some follow a principled approach by bringing teams together with external partners to generate ideas, while others create MVPs (minimal viable products) to demonstrate value from scaling MVPs. Subsequently, most organizations prioritize based on value anticipated from scaling MVPs and create a business case for change. However, most of the participants still struggle to compete with other capital projects with higher ROIs for the limited funding available. While some recommendations for digital strategy aligning with value are presented below, future research is needed on building an unassailable business case for digital transformation in the resources industry that accounts for tangibles, intangibles, and cost of business survival. 120 1. Create and communicate a clear digital strategy specific to the organization and aligned with the vision and strategy of the business. 2. Develop a business case that articulates business value and includes both tangible and intangible benefits. 3. Secure commitment to long-term funding, and balance funding and capacity (human resources) to run and maintain plants, and power grids in addition to investment in digital transformation. Technology Recommendations Six of 13 participants rated technology and ecosystem as their top three factors crucial to driving digital transformation. All 13 participants felt that technology was the key enabler for digital transformation, and two even viewed digital transformation as a pure technology transformation. As presented in the literature review, companies that use IT to transform introduce radical business model change that disrupts established industry models and practices and gives the transformed company a leading position in the market (Dehning et al., 2003). When it comes to rearchitecting the ecosystem partnerships for digital transformation, comments from participants indicate that they are leveraged for innovation and execution talent, innovation dollars, and cybersecurity. Key recommendations for practice to get the biggest returns from technology are as follows: 1. Modernize and standardize digital platforms with an enterprise-wide mindset to derive benefits of scale. 2. Create a data strategy that leverages digital technologies such as cloud, AI, and big data analytics to extract value from volumes of data that the organization owns to 121 increase productivity, product margins, operational efficiency, and creation of new data products as additional revenue streams. 3. Leverage technology ecosystem partners for their innovation funds, and co-create ideas for industry-specific digital solutions, cybersecurity, and exchange learnings. 4. Factor in M&A activity, and the talent capacity and funding needed to integrate or divest systems, to minimize disruptions to digital transformation programs. Leadership Recommendations All participants emphasized that leadership plays a critical role in driving successful digital transformation in organizations. The CEO and the Board need to sponsor and support digital transformation initiatives, and the chief digital or transformation officer needs to have the vision, courage, and ability to articulate and communicate the vision to the organization. Rogers (2016) stressed that senior leadership teams must find ways to capitalize on new and unexpected business model innovations that optimize customer experiences, and business needs. The impact of leadership can be significant in promoting a mindset change to adopt new ways of working, which is essential for organizations to adapt and thrive in a rapidly changing environment. The following are four recommendations for practice to address findings in this area of leadership: 1. Create the role of Chief Digital Officer or Chief Transformation Officer, preferably from the business or external to the organization, who commands respect from business leaders within the organization and has the CEO and Board sponsorship. 2. CTO/CDO should garner and ensure senior leadership sponsorship and funding commitments before beginning digital transformation with clarity on value and “non- negotiables” such as cloud, data analytics, and AI, as core building blocks to digital transformation, followed by business process reimagination and automation. 122 3. CTO/ CDO should have the ability to get the right people in the right roles, rotate jobs for those who won’t make the journey, set the speed of change, remove barriers, and create inspiration for risk-taking (Tichy, 2002). 4. Funding prioritization for digital transformation initiatives against competing capital projects with higher and faster ROI, and for training and upskilling programs for those employees whose jobs are displaced by digital transformation. Culture Recommendations Schadler (2018) in his study indicated that digital transformation will have the biggest effect on their business decisions over the next years. Based on the findings, where participants suggested that to drive digital transformation in the resources industry, organizations need to focus on creating a culture that promotes imagination, and fosters innovation, collaboration, and risk-taking. This requires a shift towards an agile, nimble way of working that encourages experimentation, and rewards risk takers who experiment with re-imagining business processes. The following are four recommendations for practice that may help shape such a culture in an organization. 1. Create a change program that shows benefits and rewards for those who demonstrate a willingness to change, innovate, and collaborate, and one that removes the fear of job displacement. 2. Empower teams and individuals to execute the digital transformation plan. 3. Align HR to incent individuals and teams based on what motivates them to achieve end goals – pay, recognition, education, growth, and career progression. 4. Celebrate successes – even small ones - to counter negative voices and build confidence. 123 Customer Expectations and other External Events Recommendations Multiple “black swan” events are the new normal for the resources industry and companies need to factor them into their strategy, in addition to M&A, as part of business as usual activities. To continue to operate as a business, they have to serve customers’ changing demands, rebuild talent, offer analytics and outage status to consumers, and keep up with fast technology cycles to beat multiple macro events. The following three recommendations for practice are provided to address the findings in the area of changing customer demand, and external events. 1. Customer centricity mindset for a B2B business – create a Chief Customer Officer role that monitors changing customer demands and behaviors to leverage digital to quickly adapt products and services to meet changing customer needs, and respond to “black swan” events. 2. Data transparency and choice. Instill an open customer communications approach where customers get to see the cost of new technology and sustainability benefits and offer choices based on what they may be willing to pay. 3. Create a workaround or alternate solution leveraging digital that addresses black swan events like Covid-19, for business continuity of every critical business process in the value chains for business operations and survival. Recommendation for Additional Findings As part of this study, four additional findings were noteworthy to highlight based on participants’ interviews. The first, an unassailable business case for funding, was covered under the theme of digital strategy and business value. The second is the energy transition that the resources industry is embarking on based on the demand from consumers, and other market 124 forces to move from a fossilized homogenous energy system to a more heterogeneous and cleaner energy system. This leads to an important role that government has to play in terms of defining the “what” of policies and standards that companies will need to follow to create this future energy system that is safe, secure, clean, and cost-effective. Lastly, technology vendors are starting to create operations technology – or technology that runs plants, power grids, and refineries – and this will have an impact on the digital transformation of the resources industry in the coming years. Three recommendations to prepare for these findings are presented below. 1. Create a new partnership between the resources industry, the government, and technology companies grounded in a “common purpose” of how to seamlessly transition from today’s homogenous energy system to tomorrow’s heterogenous “Net Zero” energy system. 2. The return on investment in the energy transition is an unknown for most resources industry companies. Evaluate and get started with the role an organization can play in the energy transition. 3. Technology that is used at the operations level that is used in plant, refinery, and power grid systems is not yet reached sophistication, and advancements in operations technology (OT) are starting to emerge. As industry lines converge, the resources industry needs to look at large industries with similar characteristics with OT at the heart of the business. Examples include agrochemical companies, startups focused on solar, wind, and methane emissions management, and aerospace companies where disaggregated plants run by multiple and different providers are being used to then assemble the final product using operational technology. While this integration of operations technology has started to find interest, so far only a limited number of 125 companies have taken advantage to achieve superior performance (Savastano et al., 2019). More research is needed in this area of operational technology changes and impact on digital transformation for the resources industry. 126 Table 3 Recommendations Across Key Barriers to Digital Transformation in the Resources Industry Barriers Recommendations for practice Lack of digital talent • Drive digital education campaign with the “art of the possible” scenarios for resources industries to drive a mindset change in the organization • Create hybrid talent with business, industry, technology, and agile ways of working skills by constantly rotating talent in various jobs, re-skilling, and educating people in new technologies, collaboration skills, entrepreneurial skills, and agile ways of working. • Create an ongoing training program that systematically keeps digital skills current within the employee base • Compensate digital skills at market-relevant pay to retain and attract talent • Create a digital brand for the company that is responsibly managing the energy transition with a focus on sustainable solutions for a cleaner, safer planet • Leverage ecosystem partners to flex capability and capacity for digital skills Lack of digital strategy alignment with business strategy • Create and communicate a clear digital strategy specific to the organization that is aligned with the vision and strategy of the business • Develop a business case that articulates business value and includes both tangible and intangible benefits • Secure commitment to long-term funding, and balance funding and capacity (human resources) to run and maintain plants, and grids in addition to investment in digital transformation 127 Barriers Recommendations for practice Pace of technology change and changing ecosystem • Modernize and standardize digital platforms with an enterprise-wide mindset to derive benefits of scale • Create a data strategy that leverages digital technologies such as cloud, AI, and big data analytics to extract value from volumes of data that the organization owns to increase productivity, product margins, operational efficiency, and creation of new data products as additional revenue streams • Leverage technology ecosystem partners for their innovation funds, and co-create ideas for industry-specific digital solutions, cybersecurity, and exchange learnings • Factor in M&A for talent capacity and funding needed to integrate or divest systems to minimize disruptions to digital transformation programs Lack of leadership • Educate board, and C-suite leadership on DT and increase “digital fluency” • Garner and ensure senior leadership sponsorship before beginning digital transformation with clarity on value and “non-negotiables” such as cloud, data analytics, AI, and business process automation as core building blocks to digital transformation • Create the role of Chief Digital or Transformation Officer who comes from the business or is external to the organization, and one who commands respect from business leaders within the organization • CTO/ CDO needs to get the “right people in the right roles”, eliminate those who won’t make the journey, set the speed of change, remove barriers, and create inspiration for risk-taking • Funding prioritization for digital transformation initiatives against competing capital projects with higher and faster ROI • Address fear of job displacement by providing upskilling, job- rotation opportunities to impacted employees 128 Barriers Recommendations for practice Culture of innovation and new ways of working • Change program that shows benefits and rewards for those who demonstrate a willingness to change, innovate, collaborate, and one that removes the fear of job displacement • Empower teams and individuals to execute the digital transformation plan • Align HR to incent individuals and teams based on what motivates them to achieve end goals – pay, recognition, education, growth, and career progression. • Celebrate successes – even small ones to counter negative voices Changing customer demands and external events • Customer centricity – create a chief customer officer who monitors changing customer demands and behaviors to leverage digital to quickly adapt products and services to meet changing customer needs, and respond to “black swan” events. • An open customer communications approach where customers get to see the cost of new technology and sustainability benefits versus what they may be willing to pay • Create a workaround or alternate solution leveraging digital that addresses black swan events like Covid-19, for business continuity of every critical business process in the value chains for business operations and survival. Additional themes – OT, ET, Role of government • Create a new partnership between the resources industry, the government, and technology companies grounded in a “common purpose” of how to seamlessly transition from today’s homogenous energy system to tomorrow’s heterogenous “Net Zero” energy system • ET’s ROI is unknown. Evaluate and get started with the role an organization can play in ET • Large tech at the OT level is not sophisticated, but it is emerging. As industry lines converge, the resources industry needs to look at large industries with similar characteristics with OT at the heart of the business. Examples are agrochemical companies, startups focused on solar, wind, and methane emissions management, and aerospace companies where disaggregated plants run by multiple and different providers are being used to then assemble the final product using operational technology. More research is needed in this area of operational technology changes and impact on digital transformation for the resources industry 129 Limitations and Delimitations Limitations are various factors such as events, occurrences, incidents that are beyond the researchers control such as inadequate sample size, difficulty in recruitment, amongst others, that weaken the effectiveness of a research study (Simon & Goes, 2013; Creswell & Creswell, 2018). As I used qualitative methods, an inherent limitation is in the area of validity and reliability in that it is extremely difficult to replicate the exact same interview in the same exact natural settings (Wiersma, 2000). Second, given the semi-structure interview protocol I used for data collection, there is a limitation of how openly participants may have shared their lived experiences, and how truthful they are being. The interview time of 60 minutes may be another delimitation, as there may be more to discuss based on each participants lived experiences. To mitigate this challenge, I requested extra time from the participants if possible. Most participants were very generous with their time during the interview and offered additional time for any follow-up questions or clarifications after the interview. Delimitations effect the scope of the study driven by the researcher’s conscious decisions on what is included in, and excluded from the study (Simon & Goes, 2013). The key delimitation of the study is the criteria that I established to recruit my interviewees. Based on my selection criteria, and the purposive sample size I recruited, I believe that data gathered focused on the area of study. There is a possibility that other potential interviewees exist in the population whose insights may not align with the findings of my study. A second delimitation comes from my conceptual model which is delimited to the key factors that I selected based on a sub-set of the Burke-Litwin model of change. There may be other factors that my interview protocol may not have considered. The last open-ended question in the interview protocol provides room for delimiting those factors. And, as seen in my findings, the participants 130 identified other new factors that were not considered in my interview protocol and should form the basis for future research. Recommendations for Future Research The study recommends four key areas for future research namely, the role of government, energy transition, value-driven business case, and advancements in operations technology. As mentioned earlier, these are new and emerging areas whose impact on digital transformation in the resources industry is still being defined or understood. As such, more research is needed to understand their impact. Also, there might be more new gaps or themes that may emerge through future research in these areas. The four recommended areas for future research recommended by this study are explained below. Funding Business Case Forty percent of the participants highlighted that competing for limited funds for a digital transformation program was an “uphill battle.” While many CTOs are using MVPs to show value, and drive change in thinking, they agree that it is hard to compete against large capital projects that promise ROIs in multiples of 100s, and sometimes in 1000’s percentage points. In addition, capital projects form the backbone of business for companies in the resources industry. In the same vein, participants also highlighted that digital transformation is required for the survival of the business. How can someone put a cost to survival over anything else? Future research should be conducted on how to create an unassailable business case for digital transformation initiatives against competing capital projects with higher and faster ROI where all tangibles and intangibles need to be identified, including the cost of business survival. 131 Energy Transition The resources industry is at the cusp of the largest transition in recent history, called the energy transition, driven by the climate change debate. Social forces, market forces, and changing customer demands are forcing a move from the current homogenous energy system from fossil fuels to a more heterogeneous energy system comprised of non-fossil and green sources of energy such as solar, wind, and hydrogen. As mentioned in literature review in chapter 2, sustainability implications of digital transformation in resources industries and combined with the “economic, ecological and social aspects that are often referred to as the triple bottom line (TBL) of sustainability” (Savastano et al., 2019, p. 16). CERAWeek 2023, often called the DA VOS of global energy conferences, focused on the energy trilemma of balancing security, transition, and affordability (https://ceraweek.com/program/themes.html). It is unclear who is going to be the new winners and losers in this new energy system of the future. Future research should focus on how the resources industry feeds the world’s energy demand with a new heterogenous mix of energy sources that is safe, secure, clean, cost-effective, and meets the CO2 emission goals for managing climate change. In other words, the problem statement is: how does one create a new net-zero energy system that is cost effective that is orderly and does not disrupt the industry or impact its employees adversely? The Role of Government One of the surprising findings from this study was the participants’ support for the role of government in facilitating digital transformation. It was a participants’ view that the government has a role to define policy and regulations around ESG, emissions, and security of infrastructure which is key to ESG (Environment, Sustainability, and Governance), without interfering in areas best driven by the free market forces. In other words, the government should engage in “the 132 What” and should leave “the How” to the industry. More research is required to create a framework for engagement with the government as partners who can help with – nature preservation, cyber security, data sovereignty, responsible AI, workers’ safety, upskilling citizens, and data privacy. Advancements in Operational Technology As Cortada (2003) highlighted, all processes in manufacturing industries follow a closed loop, and technological advancements in manufacturing processes in chemical plants, energy refineries, and power grids are all focused on the management of the closed loop processes in a centralized control tower. In addition, Cortada (2003) also highlights R&D as another area for the resources industries where digital technologies may be used. These changes to manufacturing systems IT are expensive as they are tied to capital assets and difficult to reconfigure. The pace of change in front-office IT was easier and technology companies focused on products that served that market first. As highlighted in literature review in Chapter 2, Cortada (200) summarized the resources industry quite well when he stated that “all companies adopted digital technology for and as an extension of ongoing practices. There is little or no evidence that the intent was to change radically any existing process or business model” (p. 191). It is also important to highlight that there is a structural separation between operations technology and information technology in resource manufacturing. This is due to the gap in technical interoperability between plant-level controllers and enterprise resource planning systems. This is primarily at the human-machine interface (HMI) level, and at the application-machine level (AML) interfaces where the new industrial development of commercial dialog systems is via robust interfaces strictly defined for specific applications, lacking the adoption of new interfaces that work at various application domains (Griol et al. 2012). The digital transformation of 133 manufacturing, also called Industry 4.0 (IX.4), has found some interest within the academic and practitioner community, and the advantages of digital transformation are remarkable in terms of improved efficiency, sustainability, customization, and flexibility, only a limited number of companies have made advances or developed strategies and capabilities necessary to achieve superior performance to obtain a competitive advantage (Savastano et al., 2019). Also, as Participant 10 noted, collaboration between resources companies and technology companies are just starting in this area. Further research is needed on the technology advancements being invented, the impact of those new technologies in the digital transformation of the core processes, and how that drives future benefits for the resources industry. Implications for Equity The resources industry employs a large number of blue-collar workers in the rigs, mines, plants, and refineries. In addition, as mentioned in chapter 1, a large portion of the workforce is from marginalized groups and typically with low levels of education, making this group ill- prepared for the transition to new ways of working in the digital world (Aster Fab, 2014). Upskilling, job rotation, and upward mobility to better employment are key areas to focus on as part of digital transformation in the resources industry. Also, the digital transformation of the resources industry is creating a safer and better work environment for blue-collar workers. According to Participant 3, most of the digital successes in the resources industry have been in the operations environment in “detecting methane leaks with sensor, inspecting tanks with telemetry,” which make the jobs of blue-collar workers easier and safer. Conclusion The purpose of this study was to explore critical external and internal factors and practices promising to accelerate digital adoption in resource industries. Research suggested that 134 the resources industry has been lagging behind other industries such as financial services, products, and CMT, in the area of digital transformation due to the unique characteristics of being asset intensive with large capital outlays where technology has not kept pace with the way refineries, plants, and mines work. Also, the skills required for operations technology in these industries are different from those of information technology skills in other industries, and there is a lack of innovation in the integration between OT and IT. This study found 17 emerging themes, and six areas of promising practices for driving digital transformation in the resources industry. Some complimented factors highlighted in existing research such as talent, digital strategy, technology, culture, and external factors like changing customer behavior. New areas such as changing ecosystem partnerships, alignment of digital strategy with business strategy, an innovation culture, and new ways of working, were also identified as key to driving digital transformation in the resources industry. The study also found that the fear of job loss was real and that upskilling citizens, especially blue-collar workers, is the responsibility of leaders within the organization and the government to alleviate this fear. Four new areas were also identified by this research study as areas that need further exploration in future studies. These include the following: identifying categories of tangible and intangible benefits to build a business case that competes with capital projects to secure funding for digital transformation programs, the ability to navigate an orderly energy transition, the role of government in digital transformation in the resources industry, and impact of upcoming advances in operational technology and its impact on digital transformation in the resources industry. 135 References Acemoglu, D., & Restrepo, P. (2019). Automation and new tasks: How technology displaces and reinstates labor. The Journal of Economic Perspectives, 33(2), 3-30. http://doi.org/10.1257/jep.33.2.3 Alvesson, M. (2002). Understanding organizational culture. Sage. Armstrong, C. P., & Sambamurthy, V. (1999). Information technology assimilation in firms: The influence of senior leadership and IT infrastructures. Information Systems Research, 10(4), 304-327. Aster Fab. Industry Perspectives. (2021, October). Blue-collar employees: Digital training and onboarding on the rise. Retrieved from: https://aster-fab.com/blue-collar-employees- digital-training-and-onboarding-on-the-rise/ Austin, W., & Presley, S.P. (2016). Making space: Strategic leadership for a complex world. The Aerospace Press. Balanskat, A., & Blamire, R. (2007). ICT in schools: Trends, innovations and issues in 2006-07. European Schoolnet. http://goo.gl/FdDFYs Barton, D., Carey, D., & Charan, R. (2018). One bank's agile team experiment: How ING revamped its retail operation. Harvard Business Review, 96(2), 59-61. Blakstad, S., & Allen, R. (2018). FinTech Revolution. Palgrave Macmillan Cham. Bogdan, R. C., & Biklen, S. K. (2007). Qualitative research for education: An introduction to theories and methods (5th ed.). Allyn and Bacon. Bouchikhi, H., & Kimberly, J. R. (2003). Escaping the identity trap. MIT Sloan Management Review, 44(3), 20-26. 136 Boyle, M. (2022, July 31). Who are the consumers of the chemical sector? Retrieved from: https://www.investopedia.com/ask/answers/042015/what-types-industries-are-main- consumers-products-chemicals-sector.asp Bronfenbrenner, U. (1977). Toward an experimental ecology of human development. American Psychologist, 32(7), 513-531. Buckingham, M., & Coffman, C. (1999; 2014). First, break all the rules: What the world's greatest managers do differently. Simon and Schuster. Burke, W. (2018). Organizational change: Theory and practice (5th Edition). Sage Publications. Burke, W., & Litwin, G. (1992). A causal model of organizational performance and change. Journal of Management, 18(3), 523-545. Campbell, B. A., Coff, R., & Kryscynski, D. (2012). Rethinking sustained competitive advantage from human capital. Academy of Management Review, 37(3), 376-395. Carr, D. K., Kelvin, H. J., Kelvin, J., Hard, K. J., & Trahant, W. J. (1996). Managing the change process: A field book for change agents, consultants, team leaders, and reengineering managers. McGraw Hill Professional. Chatterjee, D., Pacini, C., & Sambamurthy, V . (2002). The shareholder wealth and trading volume effect of IT infrastructure investments. Journal of Management Information Systems 19(2), 7-43. Chatterjee, D., Richardson, V . J., & Zmud, R. W. (2001). Examining the shareholder wealth effects of announcements of newly created CIO positions. MIS Quarterly, 43-70. 137 Chein, I. (1981). Appendix: An introduction to sampling. In L.H. Kidder (Ed.), Selltiz, Wrightsman & Cook’s research methods in social relations (4 th Ed.). 418-441: Holt, Rinehart, and Winston. Chen, J., Gordon, S., & Valasquez, V. (2021, December 27). Energy sector. Retrieved from: https://www.investopedia.com/terms/e/energy_sector.asp#:~:text=The%20energy%20sec tor%20includes%20corporations,the%20rest%20of%20the%20economy Chen, J., Mansa, J., & Jackson, A. (2022, February 26). Technology, media, and telecom (TMT) sector. Retrieved from: https://www.investopedia.com/terms/t/technology-media-and- communications-tmc-sector.asp Clark, R. E., & Estes, F. (2008). Turning research into results: A guide to selecting the right performance solutions. Information Age Publishing, Inc. Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory (4 th ed.). Sage. Costanza, D. P., Blacksmith, N., Coats, M. R., Severt, J. B., & DeCostanza, A. H. (2016). The effect of adaptive organizational culture on long-term survival. Journal of Business and Psychology, 31(3), 361-381. Costanza, D. P., & Finkelstein, L. M. (2015). Generationally based differences in the workplace: Is there a there there?. Industrial and Organizational Psychology, 8(3), 308-323. Colbert, A., Yee, N., & George, G. (2016). The digital workforce and the workplace of the future. Academy of Management Journal, 59(3), 731-739. doi:10.5465/amj.2016.4003 138 Cortada, J. W. (2003). The digital hand: How computers changed the work of American manufacturing, transportation, and retail industries. Oxford University Press. Cortada, J. W. (2005). The digital hand: Volume II: How computers changed the work of American financial, telecommunications, media, and entertainment industries. Oxford University Press. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches. Sage. Creswell, J. W., & Miller, D. L. (2000). Determining validity in qualitative inquiry. Theory into Practice, 39(3), 124-130. Daugherty, P., Ghosh, B., Rippert, A., Venkatraman, R., & Wilson, J.H. (2021). Make the leap, take the lead. Retrieved from: https://www.accenture.com/_acnmedia/Thought-Leadership- Assets/PDF-5/Accenture-Future-Systems-2021-Report-2.pdf Dehning, B., Richardson, V. J., & Zmud, R.W. (2003). The value relevance of announcements of transformational information technology investments. MIS Quarterly, 27(4), 637-656. Deiser, R., & Newton, S. (2013). Six social-media skills every leader needs. McKinsey Quarterly, 1, 62-75. Deloitte. (2016). The new organization: Different by design. Global human capital trends 2016. Retrieved from https://www2.deloitte.com/global/en/pages/human- capital/articles/introduction-human-capital-trends.html. Dos Santos, Brian L., Ken Peffers, and David C. Mauer. (1993). The impact of information technology investment announcements on the market value of the firm. Information Systems Research 4(1), 1-23. 139 El Sawy, O. A., Kræmmergaard, P., Amsinck, H., & Vinther, A. L. (2016). How LEGO built the foundations and enterprise capabilities for digital leadership. MIS Quarterly Executive, 15(2), 141-166. Enterprisers Project. (2016). What is digital transformation? Retrieved from: https://enterprisersproject.com/what-is-digital-transformation#q1 Francisco-José Fernández-Cruz, Ma-José Fernández-Díaz. (2016). Generation Z’s teachers and their digital skills. Comunicar, 24(46), 97-105. doi:10.3916/C46-2016-10 Frank, M. R., Sun, L., Cebrian, M., Youn, H., & Rahwan, I. (2018). Small cities face greater impact from automation. Journal of the Royal Society Interface, 15(139), 20170946. http://doi.org/10.1098/rsif.2017.0946 Frey, C.B., & Osborne M.A. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114, 254-280. Garvin, D. A., Edmondson, A. C., & Gino, F. (2008). Is yours a learning organization? Harvard Business Review, 86(3), 109. Gavetti, G., & Levinthal, D. (2000). Looking forward and looking backward: Cognitive and experiential search. Administrative Science Quarterly, 45(1), 113-137. Gibbs, G. R. (2007). Thematic coding and categorizing. Analyzing Qualitative Data, 703, 38-56. Glesne, C. (2011). Becoming qualitative researchers: An introduction. Pearson. Glickman, J., & Leroi, A. (2015). Adapt and adopt: Digital transformation for utilities. Bain & Company, Inc. Graetz, Georg, & Michaels, Guy. (2018). Robots at work. Review of Economics and Statistics, 100(5), 753–68. 140 Griol, D., Molina, J. M., & Callejas, Z. (2012). Bringing together commercial and academic perspectives for the development of intelligent AMI interfaces. Journal of Ambient Intelligence and Smart Environments, 4(3), 183-207. Grunig, L. A., Grunig, J. E., & Dozier, D. M. (2002). Excellent public relations and effective organizations. Lawrence Erlbaum Associates. Guba, E. G. (1990). The paradigm dialog. Sage Publications, Inc. Hansen, J. Ø., Jensen, A., & Nguyen, N. (2020). The responsible learning organization: Can Senge (1990) teach organizations how to become responsible innovators?. The Learning Organization, 27(1), 65-73. Hayes, A., & Scott, G. (2021, May 18). Consumer Goods Sector. Retrieved from Investopedia website: https://www.investopedia.com/terms/c/consumer-goods-sector.asp Hernandez, P. (2017). Video games and other top hobbies of promising IT job seekers. Datamation, http://www.datamation.com/careers/video-games-and-other-tophobbies-of- promising-it-job-seekers.html Herzog, N. V., Polajnar, A., & Tonchia, S. (2007). Development and validation of business process reengineering (BPR) variables: A survey research in Slovenian companies. International Journal of Production Research, 45(24), 5811-5834. Hew, K.F., & Brush, T. (2007). Integrating technology into K-12 teaching and learning: Current knowledge gaps and recommendations for future research. Educational Technology Research Development, 55(3), 227-243. doi: http://dx.doi.org.libproxy1.usc.edu/10.1007/sl 14230069022-5 Holt, J., Steirer, G., & Petruska, K. (Eds.). (2016). Connected viewing. Sage. Huang, M.-H., & Rust, R. T. (2018). Artificial intelligence in service. Journal of Service 141 Research, 21(2), 155–172. Im, K. S., Dow, K. E., & Grover, V. (2001). A reexamination of IT investment and the market value of the firm—An event study methodology. Information Systems Research, 12(1), 103-117. Jones, O. (2018, June). Digital mines: The need for restructuring university courses. AusIMM Bulletin, 58-61. Kaminski, K., Switzer, J., & Gloeckner, G. (2009). Workforce readiness: A study of university students’ fluency with information technology. Computers & Education, 53(2), 228-233. Kane, G. C., Palmer, D., Phillips, A. N., & Kiron, D. (2017). Winning the digital war for talent. MIT Sloan Management Review, 58(2), 17-19. Kane, G. C., Phillips, A. N., Copulsky, J., & Andrus, G. (2019). How digital leadership is(n't) different. MIT Sloan Management Review, 60(3), 34-39. Kane, G. (2019). The technology fallacy: People are the real key to digital transformation. Research-Technology Management, 62(6), 44-49. Kaplan, A., & Haenlein, M. (2020). Rulers of the world, unite! the challenges and opportunities of artificial intelligence. Business Horizons, 63(1), 37-50. http://doi.org/10.1016/j.bushor.2019.09.003 Kappelman, L., Johnson, V., Maurer, C., McLean, E., Torres, R., David, A. & Nguyen, Q. (2018). The 2017 SIM IT issues and trends study. MIS Quarterly Executive, 17(1), 53-88. Katz, D., & Kahn, R. L. (1978). Organizations and the system concept. Classics of Organization Theory, 80, 480. 142 Kelemen, M. L., & Rumens, N. (2008). An introduction to critical management research. Sage. Kenton, W., Gordon, S., & Jackson, A. (2021, December 01). Manufacturing. Retrieved from: https://www.investopedia.com/terms/m/manufacturing.asp Kerr, J. L., & Slocum, J. W. (1987). Linking reward systems and corporate cultures. Academy of Management Executive, 1(2), 99-108. Kezar, A. (2011). Understanding and facilitating organizational change in the 21st century: Recent research and conceptualizations. Wiley. Kipp, M. F. (2005). Strategic leadership in permanent whitewater. Handbook of Business Strategy, 6(1), 163-170. Knežević, B. (2018). Challenges of digital transformation and information overload in retail industry. Theory and Applications in the Knowledge Economy, 536. Kopka, U., Little, E., Moulton, J., Schmutzler, R., & Simon, P. (2020). What got us here won’t get us there: A new model for the consumer goods industry. McKinsey. Laudien, S. M., & Daxböck, B. (2016). The influence of the industrial internet of things on business model design: A qualitative-empirical analysis. International Journal of Innovation Management, 20(08), 1-28. Doi: doi: 10.1142/S1363919616400144 LeCompte, M. D., & Schensul, J. J. (2010). Designing and conducting ethnographic research: An introduction (Vol. 1). Rowman Altamira. Leonida, C. (2021). Building solid foundations for digital mines. Engineering and Mining Journal, 222(11), 18-20. Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic inquiry. Sage. 143 Lok, P., Hung, R. Y., Walsh, P., Wang, P., & Crawford, J. (2005). An integrative framework for measuring the extent to which organizational variables influence the success of process improvement programmes. Journal of Management Studies, 42(7), 1357-1381. Mansa, J. (2022, August 01). What is the metals and mining sector?. Retrieved from: https://www.investopedia.com/ask/answers/040615/what-metals-and-mining- sector.asp#:~:text=Key%20Takeaways,%2C%20industrial%20applications%2C%20and %20investments. Maxwell, J. A. (2013). Qualitative research design. Sage. Maxwell, R., & Knox, S. (2009). Motivating employees to "live the brand": A comparative case study of employer brand attractiveness within the firm. Journal of Marketing Management, 25(9-10), 893-907. McGee, Chantel. (2017, April 4). Amazon is becoming a ‘more important search engine than Google,’ says NYU professor. Retrieved from: https://www.cnbc.com/2017/04/04/nyu- scott-galloway-amazon-becoming-bigger-search-engine-than-google.html Merriam, S. B., & Tisdell, E. J. (2016). Qualitative research: A guide to design and implementation (4th ed.). Jossey-Bass. Mihalcea, A. (2017). Employer branding and talent management in the digital age. Management Dynamics in the Knowledge Economy, 5(2), 289-306. doi:10.25019/mdke/5.2.07 Mueller, J., Wood, E., Willoughby, T., Ross, C., & Specht, J. (2008). Identifying discriminating variables between teachers who fully integrate computers and teachers with limited integration. Computers & Education, 5(4), 1523-1537. doi: http://dx.doi.org.libproxy1.usc.edu/10.1016/j.compedu.2008.02.003 144 Murphy, C., Ciera, M., and Ecker, J. (2022, August 25). Utilities and utilities sector: What you need to know. Retrieved from: https://www.investopedia.com/terms/u/utilities_sector.asp Nadkarni, S., & Prügl, R. (2021). Digital transformation: A review, synthesis and opportunities for future research. Management Review Quarterly, 71(2), 233-341. Neary, B., HORÁK, J., Kovacova, M., & Valaskova, K. (2018). The future of work: Disruptive business practices, technology-driven economic growth, and computer-induced job displacement. Journal of Self Governance and Management Economics, 6(4), 19-24. http://doi.org/10.22381/JSME6420183 Olivier, B. H. (2017). The use of mixed-methods research to diagnose the organizational performance of a local government. SA Journal of Industrial Psychology, 43(1), 1-14. Pagliery, J. (2014, June 19). “Why I put ‘World of Warcraft’ on my resume,” CNN.com, Available at http://money.cnn. com/2014/06/19/technology/world-of-warcraft-resume/. Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Sage. Patton, M.Q. (2015). Qualitative research and evaluation methods (4 th ed.). Sage. Petter, S., Barber, D., Barber, C.,S., & Berkley, R.,A. (2018). Using online gaming experience to expand the digital workforce talent pool. MIS Quarterly Executive, 17 (4), 315-332. doi:10.17705/2msqe.00004 Prensky, M. (2001). Nativos digitales, inmigrantes digitales. On the Horizon, 9(5), 45-51. (http://goo.gl/4oYb) (23-05-2014). Ramboll Management. (2006). E-Learning Nordic 2006: Impact of ICT on education. Ramboll Management. (http://goo.gl/8VircM) (23-05-2014). Rath, T., & Conchie, B. (2008). Strengths based leadership: Great leaders, teams, and why people follow. Simon and Schuster. 145 Rayna, T., & Striukova, L. (2016). From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological Forecasting and Social Change, 102, 214-224. Reinartz, W., Wiegand, N., & Imschloss, M. (2019). The impact of digital transformation on the retailing value chain. International Journal of Research in Marketing, 36(3), 350-366. Robinson, S. B., & Leonard, K. F. (2019). Designing quality survey questions. Sage publications. Rogers, D. L. (2016). The digital transformation playbook: Rethink your business for the digital age. Columbia University Press. Ross, J. W., Beath, C. M., & Sebastian, I. M. (2017). How to develop a great digital strategy. MIT Sloan Management Review, 58(2), 7-9. Roulston, K. (2010). Reflective interviewing: A guide to theory and practice. Sage. Rubenfire, A. (2014, August 12). Can ‘world of warcraft’ game skills help land a Job?. The Wall Street Journal. https://www.wsj.com/articles/can-warcraft-game-skills-help-land-a- job-1407885660 Saunders, M.N.K., Lewis, P., & Thornhill, A. (2019). Research methods for business students. 8th Edition. Pearson. Savastano, M., Amendola, C., Bellini, F., & D’Ascenzo, F. (2019). Contextual impacts on industrial processes brought by the digital transformation of manufacturing: A systematic review. Sustainability, 11(3), 891. Schadler, T. (2018). The sorry state of digital transformation in 2018. Forrester Research. Schallmo, A., & Daniel, R. (2018). Digital transformation now! Guiding the successful digitalization of your business model. Springer Science+ Business Media, LLC. 146 Schneider, B., Brief, A. P., & Guzzo, R. A. (1996). Creating a climate and culture for sustainable organizational change. Organizational Dynamics, 24(4), 7-19. Senge, P. M. (1990). The leader’s new work: Building learning organizations. Sloan Management Review, 32(1), 7-23. Shinn, G. S. (2001). Intentional change by design. Quality Progress, 34(5), 46. Sigman, R., Ladeuille, B., & Grandy, N. (2001). OECD environmental outlook for the chemicals industry. OECD. Doi: https://www.oecd.org/env/ehs/2375538.pdf Simon, M. K., & Goes, J. (2013). Dissertations and scholarly research: Recipes for success. Dissertation Success LLC. Sommer, L. P., Heidenreich, S., & Handrich, M. (2017). War for talents - How perceived organizational innovativeness affects employer attractiveness. R&D Management, 47(2), 299-310. doi:10.1111/radm.12230 Spangenberg, H., & Theron, C. (2013). A critical review of the Burke-Litwin model of leadership, change and performance. Management Dynamics: Journal of the Southern African Institute for Management Scientists, 22(2), 29-48. Suárez-Rodríguez, J.M., Almerich, G., Díaz-García, I. &- Fernández-Piqueras, R. (2012). Competencias del profesorado en las TIC: Influencia de factores personales y contextúales. Universitas Psychology, 11( 1), 293-309. (http://goo.glA/Cz6jD) (24-07- 2014). Tichy, N. M. (2002). The cycle of leadership: How great leaders teach their companies to win (Vol. 13). Harper Collins. 147 Van den Berghe, L., & Verweire, K. (2001). Convergence in the financial services industry. The Geneva Papers on Risk and Insurance. Issues and Practice, 26(2), 173–183. http://www.jstor.org/stable/41952561 Vogelsang, K., Liere-Netheler, K., Packmohr, S., & Hoppe, U. (2019). Barriers to digital transformation in manufacturing: Development of a research agenda. doi:10.24251/HICSS.2019.594 Wang, Y. & Haggerty, N. (2009) Knowledge transfer in virtual settings: The role of individual virtual competency. Information Systems Journal, 19(6), 571-593. Warner, K. S. R., & Wäger, M. (2019). Building dynamic capabilities for digital transformation: An ongoing process of strategic renewal. Long Range Planning, 52(3), 326-349. doi:10.1016/j.lrp.2018.12.001 Wheelan, C. (2019). Naked economics: Undressing the dismal science. WW Norton & Company. Wiersma, W. (2000). Research methods in education: An introduction. Allyn & Bacon. World Economic Forum. (2016). Four digital trends reshaping the media industry. Retrieved from: https://reports.weforum.org/digital-transformation/digital-trends-in-the-media- industry/ Yin, R. K. (2009). Case study research: Design and methods (Vol. 5). Sage. Zachariadis, M., & Ozcan, P. (2017). The API economy and digital transformation in financial services: The case of open banking. SWIFT Institute Working Paper No. 2016-001. http://dx.doi.org/10.2139/ssrn.2975199 148 Zhu, K., Kraemer, K. L., & Dedrick, J. (2004). Information technology payoff in e-business environments: An international perspective on value creation of e-business in the financial services industry. Journal of Management Information Systems, 21(1), 17-54. 149 Appendix A: Detailed Conceptual Model The following reflects a more detailed version of the conceptual model. Each the key factors of leadership, culture, and systems and policy are further expanded to reflect the type of areas the interview discussions may cover. Detailed Conceptual Model to Drive Digital Transformation Legend: Interventions Causes Outcomes Impact or leads to Bi-directional impact External Changes in Customer, Industry, Technologies and Labor Capacity Growth (2X-3X) of Industry Peers CHANGE (Digital Transformation) PROGRAM Leadership Behaviors • Realign strategy/mission • Program sponsorship & lead Transformation by example • Right people in right jobs (People on the bus – Collins) Culture • Climate of motivation with growth mindset at , individual & group levels • ESG impact through energy transition • Compliant-like motivation – part of org DNA Systems/Policy • Goal setting <->Rewards • HRM – create capacity for change - Hiring ,retention & training • IT/MIS- innovation mindset, ecosystems partnership, agile ways of working Impact Monitoring & Feedback Monitoring & Feedback Inputs & Impact 150 Appendix B: Interview Protocol Research Questions: RQ1. How do C-Suite executives in resources industries define Digital Transformation? RQ2. How do executives navigate external environment impacts in driving successful digital transformation in resources industries? RQ3. How do the internal contextual factors impact the executives’ ability to drive successful digital transformation in resources industries? RQ4. What are the individual, team and organizational values, talent and process efficiencies that C-Suite executives in resources industries perceive are needed to drive successful digital transformation? Respondent Type: C-Suite executives in the role or tasked with leading digital transformations in their organization. Typical roles that would fit this profile for respondents would be CTO, CIO, CDO. Also, demographic criteria would include executives who are in the resources industry, have a global presence, and are considered experienced in the field of digital transformation. Introduction to the Interview: Good Morning/Afternoon/Evening <Name of Participant>. Thank you for taking the time out of you busy schedule to meet with me today. By way of introduction, my name is Manny Panjwani and I am working on my doctoral thesis as part of my OCL program at the Rossier School of Education at USC. As you know based on our email exchange, the purpose of our discussion today is to talk to you about digital transformation for the purposes of my doctoral dissertation. The purpose of my study is to explore critical external and internal factors and practices promising to accelerate digital adoption in Resource industries that are being driven by a confluence of external and internal changes both external and internal like those of customer expectations, technological advances, and post pandemic labor shortages. I am going to record this interview so that I am aptly able to go back and capture the key insights that you provide to me today. Are you good with that? Great, why don’t we start with your introductions, and before that can I answer any questions that you may have about our meeting today? 151 In the introductions, I ask for career, personal interests, professional interests, and find common interests that I can then establish a rapport with the participant. Then after putting the participant at ease, I go into how the interview will flow, time of 1 hour, and then go into asking the questions in Table B1. Table B1 Interview Protocol Questions and Probes by Research Questions Interview Questions Potential Probes RQ Addressed Key Concept Addressed I1. When you hear the words “Digital transformation” (DT), what comes to mind? I1.P1. Digital transformation means a lot of things to a lot of people. How would you describe it? I1.P2. Ok…so Let’s align on this definition for the purposes of this discussion. RQ1 Change/Transformation I2. How do you think your peers in the industry would define Digital transformation? I2.P1. How or why do you think your thinking is different or similar? I2.P2. As industry lines are blurring, what specific industry or industries are you looking at for lessons learned in driving digital transformation? RQ1 Basics grounding of concepts – DT, Leadership behaviors, Systems/Policy, and Culture (people, innovation, motivation) 152 I3. Please elaborate on why you are considering Digital transformation in your organization? I3.P1. Why are customer expectations changing? Why…? Why …? I3.P2. Are technology changes a part of this? Yes/No : If yes, what are those changes specific to your organization? What do you plan to do about it? Why…Why…? I3.P3. When you talk about DT in your company, how do you feel about the responses from your leaders? I3.P4. From you peers? I3.P5. From your sub-ordinates ? RQ2, RQ3 External Factors ; Internal Factors; Motivation levels I4. How is your decision to consider digital transformation related to events/what may be going on in the world? I4.P1. Why are these external factors (e.g. War, Covid, Customer expectations or whichever participant mentions) leading to digital transformational change as the answer for you? I4.P2. Similar probes as in I3 if not covered there in the interview. RQ2 External Factors 153 I5. What do you perceive to be the key barriers to digital transformation in your organization/industry? I5.P1. Could you tell me more about this one or that one…(External and internal factors - Center to Leadership values, Team /Individual strengths/values, Org and Culture) I5.P2. Keep probing on each of the Burke-Litwin factors. RQ2, RQ3, RQ4 GAPs and challenges to address around Leadership, Culture, and People (Individual and Teams) – The AS IS. I6. Describe why you see these as key issues or barriers? I6.P1. Probes to get to bottom of issue to align or get to the Burke- Litwin set of factors to help determine what might be the right transformational leadership, organizational culture and climate, and motivation (skill, etc.) factors RQ4 Reasons or what may need to change. From AS IS in I4 . to TO-BE state in I5. I7. Are these issues specific to the Resources industries? I7.P1. For each issue: What do you think that and what are the best ways to navigate Issue 1 or respond to it? What are you doing about it I7.P2. Same Q for Issue 2 I7.P3. Same Q for Issue 3….. RQ4, RQ3 Getting to Purpose of Study specific to Population – Resources industry. I8. What makes these issues difficult to solve? I8.P1. Why , why, why questions? RQ4 & RQ3 Challenges to solve for the key factors - Leadership, 154 Systems/Policy and Culture I9. What is stopping you from or what are the barriers you are facing in solving these issues? I9.P1. Probe on each specifically: Organization culture and climate; Leadership; and Skills & Motivation RQ4 & RQ3 Getting specific to Resources industry challenges in people, process, technology. I10. What are you able to /not able to do about these issues? I10.P1. Why ? Why questions that lead to leadership, culture, and people skills and motivation I10.P2. Are these actions you are taking sufficient in your mind? – Y/N answer. What else would you want to do? RQ3 & RQ2 Getting to actions being taken to get to TO-BE State I11. If you had a magic wand to resolve three of these issues/challenges that get in the way of you driving digital transformation within your organization – what (three issues) would you wish resolved? I11.P1. Get to priority to issues and which are most important, and why? RQ2, RQ3, RQ4 Getting to prioritize – what’s important and why to see if factors are in top 3. Do they matter or is the focus elsewhere. I12. What would the benefits be, if you were to solve these issues? I12.P1. Probe to see if upskilling of the workforce, saving jobs of blue collar workers in plants and refineries, and energy transition RQ1, RQ2 Outcomes 155 come up as benefits in addition to the growth and survival of business I12.P2. What do you think, if any, is the role of government regulations or policy in helping accelerate digital transformation in resources industries? I13. What may be your plans to address these now? Looking ahead ? I13.P1. Why are you approaching them that way? I13.P2. If you were to look three years into the future, what would the landscape look like? RQ2 Change Transformation program goals. I14. Any other comments that you may want to add in addition to what you already covered? Is there anything I can help you with in terms of sending or referring artifacts, articles, books that I come across in my research that may be relevant to what you are doing to drive digital transformation in your company? I14.P1. Probe based on comments offered. I14.P2. Ask if there are other questions, I should have asked? Close with offer to help and come back with any clarifications and questions. Feedback to process and catch all question for adding anything else in this open-ended question. 156 Conclusion to the Interview: <Name of Participant>. I would like to thank you for your time and the valuable insights that you have provided me with today. Would it be ok for me to reach out to you if I have any clarifications or further questions? Also, if you would like it, I can send you my transcript of our interview and you can read and provide any feedback to ensure that I captured your answers to my questions correctly. Lastly, I would be happy to share my dissertation or other articles and books I have researched that I think may help you on your digital transformation journey. Also, I would love to stay connected. Thank you again and have a great day!

Abstract (if available)

Abstract The purpose of this study was to explore critical external and internal factors and practices promising to accelerate digital adoption in the resource industries. The resources industry, consisting of chemicals, natural resources, energy, and utility companies, has been slower to embrace digital transformation than other industries such as financial services, consumer products, and communications media and technology (CMT), due to the unique challenges of being asset-intensive with large capital outlay, and where technology has not kept pace with the way refineries, plants, and power-grids work. However, in 2023, the industry faces external and internal changes, such as technological advancements, customer expectations, and post-pandemic labor shortages, which make digital transformation essential for business survival, preventing job losses, and to aid in the energy transition. Based on the literature review, and the conceptual framework informed by the Burke-Litwin model of leadership, organization, and performance change, this study was implemented using qualitative methodology via individual semi-structured interviews with C-suite or senior executives within the resources industry who are responsible for leading digital transformation in their organization. Based on data analysis of the interview transcripts of 13 C-suite executives, this study identified 17 emerging themes, and six areas of promising practices for driving digital transformation in the resources industry. The six areas include talent, digital strategy, technology, culture, external factors, and emerging new areas such as the energy transition. Whilst four of these areas, talent, strategy, technology and culture, are also present in other industries undergoing transformation, a few specific practices emerged specific to the resource industry that include ecosystem partnership and focus on energy transition amongst others. This study discusses these key findings and presents recommendations for practice that promise to increase the adoption of digital transformation in the resources industry. Furthermore, the study highlights four new areas of research that emerged as surprise findings or gaps, including building a business case for digital transformation programs, navigating an orderly energy transition, the role of government, and the impact of advances in operational technology on digital transformation in the resources industry.

Linked assets

University of Southern California Dissertations and Theses

Conceptually similar

PDF

Addressing the challenges of employee retention: a qualitative analysis of job satisfaction and perceptions of advancement by marginalized women in the insurance industry

PDF

An improvement study of leading a sustainable electric utility future through organizational change effectiveness

PDF

A methodology for transforming the student experience in higher education: a promising practice study

PDF

Developing and retaining employees: exploring talent management initiatives for enlisted women

PDF

Exploring the practices and experiences of food resource manager in managing food resource rooms to address food insecurity at two-year community colleges

PDF

Educational technology integration: a search for best practices

PDF

Management practices of social wealth funds: an exploratory study

PDF

Gender-based leadership barriers: an exploratory study of the underrepresentation of women of color in technology

PDF

Transformational leadership theory aligned-practices and social workers' well-being: an exploratory study of leadership practices in the context of stress and job burnout

PDF

The failure to attract and hire Millennials and Gen Zs within the U.S. aerospace & defense industry creates workforce scarcity

PDF

The impact of advanced technologies on the workplace and the workforce: an evaluation study

PDF

Sustaining employee engagement and resilience through continuous transformation in digital organizations

PDF

Outside the concrete wall: a qualitative study of Black women persisting in technology

PDF

The role of professional development and certification in technology worker turnover: An evaluation study

PDF

Representative justice for Black males in the energy transition

PDF

Theory-practice gap: MBA curricula as preparation for business practice in marketing

PDF

An examination of the impact of diversity initiatives and their supporting roles on organizational culture: an experiential study from the perspective of diversity personnel

PDF

Preparing for the future of work: exploring worker perceptions of the impact of automation

PDF

An exploratory study of women's advancement in the construction industry

PDF

Mental health disabilities in the workplace: exploring human resource professionals’ practices

Asset Metadata

Creator Panjwani, Manish (author)

Core Title Digital transformation in the resources industry: an exploration of promising management practices

Contributor Electronically uploaded by the author (provenance)

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2023-05

Publication Date 05/04/2023

Defense Date 04/13/2023

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag artificial intelligence,Cloud,compressed transformation,culture,data analytics,digital transformation,energy transition,information technology,OAI-PMH Harvest,operations technology,resources industry,talent,the internet of things

Format theses (aat)

Language English

Advisor Seli, Helena (committee chair), Barcus, Ana (committee member), Phillips, Jennifer (committee member)

Creator Email mpanjwan@usc.edu,panjwaniman@gmail.com

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113099388

Unique identifier UC113099388

Identifier etd-PanjwaniMa-11768.pdf (filename)

Legacy Identifier etd-PanjwaniMa-11768

Document Type Dissertation

Format theses (aat)

Rights Panjwani, Manish

Internet Media Type application/pdf

Type texts

Source 20230504-usctheses-batch-1036 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu