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The organizational impacts of executive technology leadership role proliferation

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The organizational impacts of executive technology leadership role proliferation

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Content The Organizational Impacts of Executive Technology Leadership Role Proliferation
by
Janet Sherlock
A Dissertation Presented to the
FACULTY OF THE USC ROSSIER SCHOOL OF EDUCATION
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF EDUCATION
August 2023
Copyright 2023 Janet Sherlock

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Acknowledgments
First and foremost, I want to thank my husband, Jim, for his unwavering love, patience,
and constant encouragement during my doctoral journey. Your support and belief in me have
been the driving forces behind my ability to complete this program, while juggling a demanding
job. Your sacrifices, understanding, and willingness to shoulder additional responsibilities have
allowed me to dedicate the necessary time and energy to complete this dissertation. Thank you
for always being there for me and for cheering me on every step of the way.
To my precious daughters, Katie and Jessie, you have been my inspiration and
motivation. Your unconditional love, understanding, and empathy have kept me going during the
most challenging times. It was fun sharing our college experiences together and enduring dad’s
complaints about paying for three college tuitions. Thank you for lending your ears during my
struggles. Your smiles and laughter have been the antidote to my stress over the past few years.
You are the greatest blessings in my life, and I am proud to be your mother.
I would like to extend my appreciation to my professors and advisors, who have guided
and shaped my academic journey. Your expertise, passion, and commitment to learning have
been truly inspiring. I am grateful to my dissertation committee members, Dr. Martinez, Dr.
Datta, and Dr. Maddox, for the valuable knowledge, guidance, and feedback you provided on my
dissertation.
A special thank you goes to Dr. Hocevar, who spent countless hours supporting my
quantitative research. I could not have completed this study with the same level of thoroughness,
precision, and deliberation without your expertise and extraordinary patience.

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I am grateful for the invaluable support and constant encouragement from my colleagues
of USC OCL Cohort 19, especially the Thursday night crew. My shared experiences with you
have shaped me into a better researcher and scholar, and a better person.
Lastly, I would also like to express my gratitude to the technology leaders who
participated in my study. Your willingness to share your time and experiences has been
invaluable to my research. The insights you shared provided a deeper understanding of the
challenges and opportunities faced based on the organizational structures in our profession. I am
honored to have had the opportunity to learn from you. I strive to support you and our companies
in advancing our profession and the impact it has on our organizations, customers, and the world
we live in. It is through our collective efforts that we can create positive change and shape the
future of our field.
To all those who have played a role, big or small, in supporting me on this remarkable
journey, thank you from the bottom of my heart. Your belief in me, your encouragement, and
your unwavering support have made all the difference. I am forever grateful for your presence in
my life.

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Table of Contents
Acknowledgments ii
Table of Contents iv
List of Tables ix
List of Figures x
Abstract xi
CHAPTER ONE: INTRODUCTION TO THE STUDY 1
Context of the Problem 2
Purpose of the Project and Research Questions 3
Importance of the Study 4
Overview of Theoretical Framework and Methodology 5
Definitions 6
Organization of the Dissertation 8
CHAPTER TWO: LITERATURE REVIEW 9
Evolution of Technology Leadership Roles 9
History and Progression of Technology Leadership Roles 10
Chief Information Officer Reporting Relationship 11
Proliferation of Technology Leadership Roles 13
Chief Digital Officer Role and Its Effectiveness 13
Chief Data and Analytics Officer Roles 15
Other Technology Leadership Role Proliferation 16
Organization Structure and Role Clarity 17
Significance and Impact of Organizational Structure 17

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Organizational Structure Designs 18
The Reality of Hierarchies and Structure 23
The Impact of Role Clarity 24
Technology Organization Conceptual Framework 24
Burke-Litwin Structural Element 26
Assessing Technology Team Output Via Conway’s Law 27
Summary 28
CHAPTER THREE: METHODOLOGY 29
Research Questions 29
Overview of Design 29
Research Setting 31
The Researcher 31
Data Sources 32
Method 1: Survey 32
Participants 32
Instrumentation 33
Data Collection Procedures 34
Data Analysis 35
Method 2: Interviews 35
Participants 36
Instrumentation 37
Data Collection Procedures 38
Data Analysis 38

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Method 3: Secondary Data 38
Metric and Data Used 39
Instrumentation, Data Collection, and Analysis 39
Validity and Reliability 40
Credibility and Trustworthiness 40
Ethics 41
CHAPTER FOUR: FINDINGS 42
Participants and Secondary Data Collection 42
Survey Participants 43
Interview Participants 43
Secondary Data Collection 45
Analysis Summary by Research Method 46
Quantitative Survey Analysis Summary 46
Qualitative Interview Analysis Summary 50
Secondary Data Analysis Summary 52
Results and Findings 52
Research Question 1: To What Extent Does Having Multiple Executive Technology
Leadership Roles Impact Role Clarity Across Technology Teams? 53
Job Overlap and Shadow Information Technology 54
Common Definitions and Understanding 56
Budgets and Decision-Making Rights 59
Research Question 2: To What Extent Does Having Multiple Technology Executive
Leadership Roles Impact Workplace Climate? 60

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Frustration and Conflict 61
Personalities and Relationships 63
Reputation of Information Technology Departments 66
Research Question 3: To What Extent Does Having Multiple Technology Executive
Leadership Roles Impact the Effectiveness of Technology Output? 69
Speed-to-Market 70
Complexity 70
Quality 71
Impact of Technology Function on Firm Performance 73
Summary 74
CHAPTER FIVE: RECOMMENDATIONS 76
Discussion of Findings 77
Recommendations for Practice 77
External Environment Factors 78
Researcher Actions 79
Recommendation 1: CEO and CHRO Education 80
CEO and CHRO Education on Single-Leader Technology Leadership
Structure 80
Clear Roles and Responsibilities 84
Recommendation 2: CIO and IT Department Reputation Overhaul 85
Title and Department Naming Convention 85
CEO Support and Reporting Structure 86
Technology Leader Characteristics and Persona 87

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Recommendation 3: Lexicon and Context Alignment 88
Technology Department Boundaries 89
Digital Meaning and Primary Title 90
Analytics Structure and Approach 91
Data Management and Engineering 92
Product Management 94
Recommendations Summary 95
Limitations and Delimitations 95
Recommendations for Future Research 96
Conclusion 97
References 101
Appendix A: Survey Instrument 116
Appendix B: Qualitative Interview Question Protocol 138
Appendix C: Secondary Data Collection Protocol 139

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List of Tables
Table 1: Data Sources ............................................................................................................... 30
Table 2: Interview Participants and Criteria ............................................................................... 36
Table 3: Respondent Characteristics .......................................................................................... 44
Table 4: Interview Participant Titles and Reporting Relationships ............................................. 45
Table 5: Descriptive Statistics for Study Measures and Internal Consistency ............................. 47
Table 6: Independent Sample t-Test Results .............................................................................. 48
Table 7: Test for Equality of Variances ..................................................................................... 49
Table 8: Independent Samples Effect Sizes ............................................................................... 49
Table 9: Survey Respondent Comment Themes: Changes They Recommend for Their
Organizations ........................................................................................................................ 50
Table 10: Return on Assets t-Test Results ................................................................................. 53
Table 11: CIO Perceptions of Relationship Strength With Nontechnology Executives ............... 68
Table 12: Responsibility by Technology Domain for Single-Leader Led Technology
Departments .......................................................................................................................... 90
Table 13: Recommendation Summary ....................................................................................... 97

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List of Figures
Figure 1: Number of Publications of the Chief Digital Officer .....................................................3
Figure 2: Multidivisional Organizational Structure .................................................................... 19
Figure 3: Functional Organizational Structure ........................................................................... 20
Figure 4: The Burke-Litwin Model of Organizational Performance and Change ........................ 22
Figure 5: Technology Organization Conceptual Framework ...................................................... 25
Figure 6: Interview Themes ....................................................................................................... 51
Figure 7: Job Overlap ................................................................................................................ 55
Figure 8: Implications of Budget Association to Structure ......................................................... 60
Figure 9: Level of Teams’ Expression of Frustration over Job Overlap or Duplication of
Responsibilities ..................................................................................................................... 62
Figure 10: Self-Ratings of Technology Executives’ Strength of Relationships with Peers .......... 64
Figure 11: Technology Executives’ Relationships with Other Executives .................................. 65
Figure 12: Organizational Structure Impediment to Speed-to-Market ........................................ 71
Figure 13: Organizational Structure Negative Impact to Solution Complexity ........................... 72
Figure 14: Organizational Structure Negative Impact to Solution Quality .................................. 73
Figure 15: Technology Organization Conceptual Framework and Findings Summary ............... 78
Figure 16: Replacement of Overlapping Technology Leadership Roles ..................................... 82
Figure 17: Decision Framework for Executive Technology Leadership Structure ...................... 83
Figure 18: Big Data Skills and Job Families .............................................................................. 93

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Abstract
In today’s corporate environment, there is a trend in the growth of chief titles in the
executive suite, causing overlap, confusion, and role clarity issues in organizations.
Companies are adding C-suite roles to address actual or perceived gaps in capabilities,
respond to business trends, or satisfy the investment community or the public. The executive
ranks of technology departments are impacted most by this proliferation of roles and titles
due to digital transformation efforts. This study was designed to examine the organizational
impacts of potential overlapping roles through the transactional factors of the Burke-Litwin
causal model of organizational change and performance applied to Conway’s law, which
suggests efforts from multiple teams create multiple results. The purpose of this study was to
assess the extent to which multiple leaders in top executive technology capacities impact
role clarity, workplace climate, and team performance versus singly led technology
departments. The research leveraged a quantitative survey of 126 cross-industry technology
executives, qualitative interviews of eight technology leaders, and a secondary data analysis
of return on assets of 96 of the firms represented in the quantitative survey. To evaluate the
differences between the single leader structure versus the multiple leader structure, t-tests
were used. Findings from this study suggest having multiple top-level technology leaders of
companies negatively impacts role clarity, workplace climate, and technology performance
and output. This study provides CEOs and CHROs objective data and information to aid
them in their decisions on how to structure their companies’ technology organizations.

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CHAPTER ONE: INTRODUCTION TO THE STUDY
Technological advancement is the fundamental driver in transforming firms, industries,
and all parts of society (Philbeck & Davis, 2018). Technology has become the foundation of
business and can be an essential driver of the success of companies across industries (Susan &
Novianti, 2019). Consumers expect companies to provide experiences and accessibility to
products and services, and organizations depend on technology for internal productivity (Susan
& Novianti, 2019). Companies’ technology organizations have rapidly expanded over recent
decades to accommodate the increasing mandate for technological advancement. Demand for
technology talent increased 83% between 2020 and 2021, which has resulted in growth and
complexity in technology departments and leadership in most organizations (Stephenson et al.,
2022).
The problem of practice addressed in this paper is the proliferation of executive
technology leadership roles in U.S. public corporations, which results in a lack of organizational
clarity, workplace climate issues, and technology design deficiencies. Since its inception and
broad adoption in the 1980s, the chief information officer (CIO) role has typically been the
highest level information technology (IT) executive role in most organizations (Banker et al.,
2011). The progression of digital transformation, the consumerization of technology, and
extended use of data science have resulted in the proliferation of technology leadership roles,
with many companies creating a chief digital officer (CDO) role, a chief data and analytics
officer (CDAO), or a chief technology officer (CTO), in addition to the CIO (Haffke et al., 2016;
Koh et al., 2021). Multiple technology leadership roles can complicate role clarity, reporting
structures, and responsibilities (Haffke et al., 2016). A company’s organizational structure and
environment directly impact its ability to innovate, transform and manage its strategic
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positioning (Abernathy & Clark, 1985; LaPaz et al., 2019). This problem is essential to address
for most corporations because effective technology executive organizational alignment and
clarity are required to support technology strategy and execution to respond to changes in
competitive market which are largely driven by technology (Li & Tan, 2013).
Context of the Problem
In the corporate environment, there is a trend in the growth of chief titles in the executive
suite, causing overlap, confusion, and role clarity issues in organizations (Gerth & Peppard,
2016; Haffke et al., 2016; Lewnes & Keller, 2019). Organizations are adding c-suite roles, such
as chief customer officer or chief growth officer to address actual or perceived gaps in
capabilities, respond to business trends, or satisfy the investment community or the public
(Lewnes & Keller, 2019). Research indicates the executive ranks of technology departments are
impacted most by this proliferation of roles and titles due to digital transformation efforts (Singh
& Hess, 2020; Tardieu et al., 2020). Systematic literature reviews and research studies have
analyzed the CDO and CIO roles for clarity, overlap, performance, and necessity (Kessel &
Graf‑Vlachy, 2021; Haffke et al., 2016). As indicated in Figure 1, the CDO role has been
researched significantly since 2013, with varying interpretations of the value attainment of those
assignments due to overlap with other leadership roles (Rakovic et al., 2022). Copious variations
of research studies on technology department structures, titles, responsibilities, financial
performance, and overall effectiveness have not established a clear or unambiguous definition of
technology organizations (Peppard, 2018). This study builds on existing literature and research
studies to better understand whether organizations should have all technology ownership and
strategy in one organizational entity.
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Figure 1
Number of Publications of the Chief Digital Officer

Note. With permission from “What about the Chief Digital Officer? A Literature Review” by L.
Raković, S. Marić, L. Đorđević Milutinović, M. Sakal, and S. Antić, S., 2022. Sustainability,
14(8), 46–96. [https://doi.org/10.3390/su14084696]. Copyright © 2022 by Elselvier.

Purpose of the Project and Research Questions
The purpose of this study was to learn the degree to which multiple technology leaders in
an organization impact organizational clarity, workplace climate, and the effectiveness of
organizations’ technological output. The results from the following research questions are
intended to assist human resource (HR) leaders and CEOs in understanding if having a single
executive or multiple executives responsible for technology is advantageous.
1. To what extent does having multiple technology executive leadership roles impact
role clarity across technology teams?
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2. To what extent does having multiple technology executive leadership roles impact
workplace climate?
3. To what extent does having multiple technology executive leadership roles impact the
effectiveness of technology output?
Importance of the Study
Firms increasingly rely on the effectiveness of their IT systems for revenue growth,
customer acquisition, profitability, and competitive advantage (Li & Tan, 2013). Globally, in
2021, companies spent $4.2 trillion, an 8.6% increase over spending in 2020, on technology
(Gartner, 2021). Technology leaders must manage these investments efficiently and effectively
to achieve desired outcomes and return on investment (ROI) results for their firms. Investment in
information technologies and capabilities must be coupled with effective organizational
alignment to drive IT value (Karahanna & Preston, 2013).
Most HR leaders, CEOs, and boards of directors are not equipped or knowledgeable
enough about technology to understand how to structure technology organizations (Krotov,
2015). Therefore, HR leaders and CEOs often rely on external resources to assist them in their
organizational design efforts for technology leadership and structure (Poulfelt & Olson, 2017).
The most prevalent expert resources for organization design and structure available to companies
are executive search firms or management consulting firms (Poulfelt & Olson, 2017; Korn Ferry,
2022). In addition to being very costly, these firms do not have the incentives to help CEOs build
streamlined organizations. Executive search firms benefit from creating additional executive
roles, as they are paid to fill those roles (Korn Ferry, 2022). Management consulting firms
benefit from a lack of clarity in organizational structure, as they often sell engagements focusing
on organizational redesign and operational efficiency (Poulfelt & Olson, 2017). Results from this
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study can furnish CEOs, HR leaders, and boards of directors with affordable, more objective
resources and information for helping them design their organizations.
Overview of Theoretical Framework and Methodology
The impact of the organizational structure of the CIO role and other technology
leadership can be viewed through the organizational structure element of the Burke-Litwin
model. The Burke-Litwin model depicts the interrelationships between 12 aspects in an
organization influencing organizational change, divided into transformational and transactional
factors (Burke & Litwin, 1992). The transformational factors are the external environment, the
company’s mission and strategy, leadership, organizational culture, and performance. The
transactional factors are structure, systems, management practices, working climate, tasks and
skills, individual values and needs, and motivational levels. The structural factor evaluates how
an organization’s size, shape, hierarchy, functional design, and leadership impact individual and
overall performance (Spangenberg & Theron 2013). The effects of the organizational and
reporting structure of the technology functions across companies can be reviewed through the
lens of the structural factor of the Burke-Litwin framework. Organizations in the technology
field can be assessed on their ability to achieve performance goals and influence work unit
climate (Burke & Litwin, 1992).
In addition, Conway’s (1968) law, which states that systems created will always reflect
the organizations that build them, can be used to examine this problem of practice. According to
this hypothesis, products or output mirror the architecture of the group that developed them due
to the communications and governance structure of the organization itself (MacCormack et al.,
2012). Applying Conway’s law to the transactional factors of the Burke-Litwin model will create
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a perspective on the output and performance of technology organizations because of how they
are structured (Yourdon & Constantine, 1979).
Comparisons of role clarity, workplace climate, and technology output effectiveness
across reporting-aligned technology departments, versus unaffiliated technology organizations
reporting to separate technology leaders, were evaluated via a mixed-method research study. A
large-scale quantitative survey was conducted to understand technology executives’ perceptions
of the impact organizational structure has on role clarity, workplace climate, and technology
output effectiveness. A qualitative study with semistructured interview questions provided
further insight into corporate structures’ impact on technology department climate and efficacy.
Results of the studies analyzed against the theoretical frameworks led to recommendations for
the improved structural design of technology departments.
Definitions
The following definitions provide descriptions of key terms associated with this problem
or practice and the theoretical framework being used to examine this problem of practice.
Chief data and analytics officer (CDAO): The CDAO role is an executive leader
responsible for delivering business capabilities based on data, data architecture, data governance,
and data privacy and protection for an organization (Koh et al., 2021).
Chief digital officer (CDO): The CDO role is responsible for a firm’s digital
transformation (Singh & Hess, 2020).
Chief information officer (CIO): The CIO role is the senior executive in the organization
responsible for strategic information systems (IS) planning, technology and information
resources, and the development of new systems capabilities for an organization (Ross & Feeny,
1999).
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Chief technology officer (CTO): The CTO role is often used interchangeably with the
CIO title; however, the position is typically more engineering focused and responsible for
leading the development of new technologies for an organization (Beatty et al., 2005).
Mirroring: Mirroring is a hypothesis that suggests organizational structure elements, such
as colocation, team membership, and communication, correspond to the patterns of the
technology developed by organizations (Colfer & Baldwin, 2016). The concept of mirroring is
often associated with Conway’s law (Conway, 1968).
Organization structure: Organization structure is the composition of people and functions
into specific areas of responsibility aligned to ensure the effective execution of the organization’s
strategy and goals (Burke & Litwin, 1992).
Product management: In context to the field of technology, product management
encompasses the lifecycle of any combination of software, hardware, or services, including
strategy, research, development, sales, marketing, and value creation (Ebert & Brinkkemper,
2014; Gartner, 2023). Product management is primarily intended to serve external customers;
however, technology organizations can also apply the product management model to any
capabilities delivered in a value stream to internal users (Gartner, 2023b).
Technology leadership: Technology leadership is the collection of leaders supporting the
required technology domains in an organization, including CIO, CTO, chief product officer,
CDAO, chief information security officer, and CDO (Koh et al., 2021).
Technology output: Technology output is an implementation of information, processes,
user experiences, and technologies in a distinct system to support a set of business, functional, or
technical capabilities that solve a well-specified business problem (Gartner, 2022).
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Workplace climate: Workplace climate represents the collective feelings and expectations
of members of work functions that impact their relationships with each other and other work
functions (Burke & Litwin, 1992).
Organization of the Dissertation
This study is organized into five chapters. Chapter 1 provides readers with a high-level
summary of the problem of practice, the importance of this study, and the research questions that
informed the study. Chapter 2 presents a review of the existing literature relevant to the problem
of practice. Chapter 3 describes the methodologies used in the mixed methods study, including
the quantitative and qualitative research approaches used. Chapter 4 provides the results of the
sequential mixed methods research conducted. Lastly, Chapter 5 contains proposed solutions and
industry recommendations based on the study’s research findings on the practice problem.

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CHAPTER TWO: LITERATURE REVIEW
This literature review examines the research surrounding the proliferation of technology
leadership roles in organizations. The review begins with the chronological context of
technology leadership, including the contributing technological, historical, and organizational
reasons for the proliferation of technology leadership roles. The review then delves into the
literature on the relevance, effectiveness, and trends of specific technology leadership roles,
including CIO, CDO, and CDAO roles. After examining technology leadership literature, the
review explores the relevance of organization structure and role clarity and their impacts across
organizations. Following the research literature related to the industry problem of practice, the
chapter culminates in a review of the Burke-Litwin theoretical framework in conjunction with
Conway’s law to formulate a conceptual framework to consider the problem of practice.
This study relied on data, statistics, and recent relevant field research by well-known
executive search firms, such as Korn Ferry, Spencer Stuart, and Russell Reynolds, and highly
regarded industry advisory firms, such as Gartner and Deloitte. While studies from these firms
are not peer-reviewed academic research studies, the information is deemed as the foremost
source of reliable industry benchmarking intelligence in the technology industry due to the
access these firms have to relevant cross-industry resources among corporations.
Evolution of Technology Leadership Roles
An examination of technological advancements and the corresponding shifts in the use
and deployment of technology revealed reasons for the evolution of how technology is managed
and how technology departments are structured (Peppard, 2018). Research over the past 50 years
chronicles the creation and advancement of the CIO role as companies’ and society’s appetite for
technology intensified (Peppard, 2018). Researchers have also evaluated the evolution and
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efficacy of technology leadership roles because the complexity of technology definition,
management, and governance continue to change (Hütter & Riedl, 2017; Singh & Hess, 2020).
History and Progression of Technology Leadership Roles
The number of computers installed in the United States increased from 50 to greater than
60,000 from 1955 to 1970 (Gorry & Morton, 1971). This rapid computer and system growth
impelled the creation of a new field entitled IS or IT, transforming beyond its beginnings as a
data processing function (Gorry & Morton, 1971). Early scholars studying the computer industry
recognized and encouraged the focus and attention to organizational structures in the IT field,
forewarning the considerable impact technology operations would have on companies (Gorry &
Morton, 1971; Yourdon & Constantine, 1979). Gorry and Morton (1971) stressed the economic
implications of technology organizations because the cost of developers was rising, and the cost
of hardware decreased while overall demand for technology continued to surge. Yourdon and
Constantine (1979) emphasized the importance of team structure on development projects,
noting project planning, expense, and quality depend greatly on effective team structure,
processes, communication, and culture.
The data processing era that started in the 1960s gave way to the information era of the
1980s and 1990s, and senior corporate executives recognized the importance of IT in their
organizations (Applegate & Elam, 1992). Technological advancements changed IT from a
backroom utility to a strategic resource for corporate performance and organizational change
(Ross & Feeny, 1999). Changes in computing methodologies, intensified business reliance on
technology, and centralization versus decentralization debates emerged in the 1990s and have
continued (Ross & Feeny, 1999; Peppard, 2018).
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Advent and Early Evolution of the Chief Information Officer Role
The establishment of the CIO role became predominant when reliance on technology and
expenditure on technology grew substantially, which warranted the creation of a new executive
position to carry out technology strategy and value creation from technology. For example, in the
1970s, American Airlines’s development of the Semi-Automated Business Research
Environment (SABRE) platform for airline reservations established technology could be used as
a key business enabler and industry differentiator, thrusting technology into the forefront of
firms’ agendas (Jarvenpaa & Ives, 1991). The CIO role was intended to create a link between
data processing and the company’s senior managers to drive technology initiatives for business
benefit (Hunter, 2010).
The 1980s and 1990s brought big, expensive enterprise resource planning (ERP)
initiatives and technology projects, further reinforcing the need for the CIO role and highlighting
its visibility in many corporations (Ross & Feeny, 1999). Unfortunately, many of those projects
were unsuccessful, and CIOs were often blamed for the failures (Ross & Feeny, 1999). While
CIOs were amassing greater responsibilities and visibility, their reputations and credibility often
deteriorated, and relationships with other top executives were not always productive (Ross &
Feeny, 1999).
Chief Information Officer Reporting Relationship
The CIO role has held a long-standing reporting relationship to the chief financial officer
(CFO) because the initial uses of modern computing were primarily used for the benefit of
accounting and finance departments (O’Riordan, 1987). Prior to the creation of the CIO role, the
CFO acted as the CIO, managing the company’s information and financial resources (O’Riordan,
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1987). As technology became more prevalent, CFOs oversaw the significant investments being
made in technology, driving the CIO to CFO reporting trend (Rockart et al., 1982).
While the number of CIOs reporting to CFOs has declined over the years, 28% of CIOs
still reported to CFOs in 2018 (Kark et al., 2018). CIOs reporting to CFOs signals a lack of
strategic relevance to the rest of the organization, positions IT as a cost center, and diminishes
the CIO’s stature in an organization (Krotov, 2015). To establish credibility, authority, and
competitive advantage, the CIO should report to the CEO of an organization (Krotov, 2015).
Perception of the CIO and Information Technology Departments
Misaligned reporting relationships, reputational issues, role ambiguity, and perceived
success of IT delivery plague CIOs and their teams (Gerth & Peppard, 2016; Krotov, 2015).
Based on their research experiments on perceptions of 49 CIOs, Gonzalez et al. (2019)
concluded senior corporate leaders were generally biased against CIOs because of unfounded
stereotypes of their leadership skills and were unnecessarily blamed for performance outcomes in
their organizations. Whether based on personality traits, demographics, or perceptions, CIO
characteristics impact the CIO’s performance in an organization (Gonzalez et al., 2019; Li &
Tan, 2013).
Perception issues are challenging for CIOs, but role clarity issues cause further
disruption, conflict, and performance problems (Gerth & Peppard, 2016; Peppard, 2018).
Because most organizations have no clear definition of what IT entails, IT delivery success often
remains in question (Gerth & Peppard, 2016). Information technology success is often predicated
on positive business outcomes related to technology deployment; however, CIOs typically have
responsibility for the technology deployment only, and not the successful commercial or
business use of the technology (Gerth & Peppard, 2016). The confusion and conflict over the
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technology, its implementation, its successful use by users, and expected business outcomes,
especially in the age of digitization, have caused many organizations to reconsider the nature of
CIO roles (Gerth & Peppard, 2016).
Proliferation of Technology Leadership Roles
Increased pressure and demand due to digitization efforts, lack of value from IT projects,
and diminished confidence in many organizations’ CIOs have caused many companies to
establish an additional technology leadership role: the CDO (Gerth & Peppard, 2016; Singh &
Hess, 2020). Expectations for the CDO vary, depending on the company, industry, and top
executive management composition (Singh & Hess, 2020). Responsibilities can range from
creating new customer-facing digital experiences to managing data analytics to leading the
company’s digital transformation (Tumbas et al., 2020).
Singh and Hess (2020) suggested that in addition to the CIO and CDO roles, leadership
roles, including chief data officer, chief innovation officer, chief strategy officer, or CTO, may
be necessary to perform the technology-related requirements in an organization. Consultants,
executive recruiting firms, and academics have provided varying definitions of these roles (Koh
et al., 2021; Singh & Hess, 2020). Research and literature reviews have also covered the remit,
executive relationships, responsibilities, and effectiveness of these newer technology leadership
roles (Singh & Hess, 2020; Tardieu et al., 2020).
Chief Digital Officer Role and Its Effectiveness
Chief digital officer positions are created in organizations due to market pressures to
transform their companies’ businesses or because the coordination of digitization transformation
efforts across the firm is too complex for the CIO to address (Singh & Hess, 2020)—yet there
can be redundancy between the CIO and CDO roles (Haffke et al., 2016). In addition to potential
14

overlap with the CIO, the hype and lack of clarity around what digital transformation is and what
it entails may harm CDOs’ abilities to be successful (Gong & Ribiere, 2021; Haffke et al., 2016).
Practitioners and academics have debated the necessity and effectiveness of CDOs, yet the role
remains generally adopted among large companies (Kessel & Graf-Vlachy, 2021). In 2018, 17%
of the 2,500 largest international companies had named CDOs (Hiller, 2021).
A study on company financial performance using ROA measurements of the S&P 500
index firms from 2007 to 2019 indicates the presence of a CDO does not positively impact firm
performance (Hiller, 2021). The study suggests a long-term negative impact on company
performance when a CDO is present in an organization (Hiller, 2021). The same research
showed a 14% better ROA for firms with only a CIO, versus firms with both a CIO and a CDO
(Hiller, 2021). Contrary to their initial assumptions when studying 750 cross-industry CDOs,
Berman et al. (2020) found firms achieved greater financial results toward their digitization
efforts when the CDOs reported to CIOs versus CEOs.
Although results are mixed on the effectiveness of the CDO role, and some organizations
are revisiting the CDO role or combining it with the CIO role, the role remains prevalent in many
organizations (Tardieu et al., 2020). Proliferating technology leadership roles, replacing the CIO
with a CDO, or changing the title of the CIO to CDO does not change the underlying issues that
inhibit effective technology strategy and deployment in companies (Gerth & Peppard, 2016).
Better alignment across the top executive management team, improved technology literacy
across top executives, and clearly defined technology objectives from the CEO underpin the
potential for IT success in an organization (Gerth & Peppard, 2016). Lack of top executive
alignment and understanding drives vagueness in technology strategy, which potentially causes
15

role ambiguity and perpetuates IT leadership role proliferation across disciplines, including data
science and analytics (Gerth & Peppard, 2016; Singh & Hess, 2020).
Chief Data and Analytics Officer Roles
Inherent in its title, a CIO’s role is to provide the right information in a timely manner to
the organization (Król & Zdonek, 2020), yet new professional positions related to data analytics
have been created in the last decade, including chief analytics officer (CAO) or chief data
officer, or a combination role of chief analytics and data officer (CADO; Król & Zdonek, 2020).
As investments in data and predictive analytics become vital to many firms’ performance,
establishing structure and stewardship becomes increasingly essential (Earley, 2017; Król &
Zdonek, 2020).
The problem lies with the ambiguity of who is responsible for managing and leveraging
data in business decisions and processes (Earley, 2017). For example, in the field of marketing,
many marketing professionals do not possess the deep analytics skills or education required to
effectively manage customer relationship marketing (CRM) for their organizations (Kaur, 2019).
Educational programs focused on analytics often center on concentrated technical skills and are
not specialized for specific business functions like marketing (Kaur, 2019). Firms need to
determine whether analytics should be fully democratized across departments in the company,
whether it should be centralized under a CAO, or partially or fully managed by IT under the CIO
(Watson et al., 2021; Wiseman, 2017). Some practitioners suggest organizations require a CAO
or chief data officer role to centrally manage the increasingly essential analytics function (Earley,
2017); however, there is a growing opinion amongst industry experts that democratization of
analytics across corporate functions and CIO relationships with functional leaders for data
management is superior to the inevitable analytics triangulation struggles that can be caused
16

between the CIO, CAO, and department leaders (Earley, 2017; Sleep & Hulland, 2019; Watson
et al., 2021). In addition, CIOs manage the systems that create data and fundamentally have
ownership and stewardship of their companies’ data (Chun & Mooney, 2009).
The issues with the democratization of analytics and other aspects of technology
management often stem from the lack of top executive alignment and understanding of
technology (Gerth & Peppard, 2016). Confidence in CIOs’ skills or ability to execute analytics
strategies is often an issue that drives CEOs to consider a CADO or CAO for their organizations
(Earley, 2017). Like CDO role proliferation, CADO proliferation occurs, along with other
technology leadership role proliferation, for the same underlying reasons.
Other Technology Leadership Role Proliferation
Many other top technology-related roles continue to be created, including chief
transformation officer, chief innovation officer, and most recently, chief metaverse officer (Singh
& Hess, 2020; Wilson Schaeffler & O’Connor, 2022). Executive search firm Spencer Stuart
acknowledged the CDO job may be declining but promotes the chief metaverse officer as a
different role for firms to fill (Wilson Schaeffler & O’Connor, 2022). Roles like CDO, CADO,
chief innovation officer, or chief metaverse officer are often associated with hype or the latest
business trends but are grounded in underlying business direction or need (Singh & Hess, 2020;
Tardieu et al., 2020; Wilson Schaeffler & O’Connor, 2022).
Although new and evolving, CDO and CADO roles, like the CIO role, are subject to the
same definition, alignment, relationship, and clarity issues (Singh & Hess, 2020). CDO and
CADO roles, and even new roles like the chief metaverse officer role, are sometimes considered
to be transitory, holding relevance and necessity for only a few years, with eventual plans to be
consumed into other departments or organizations, like IT or marketing (Singh & Hess, 2020;
17

Tardieu et al., 2020; Wilson Schaeffler & O’Connor, 2022). Whether transitory or permanent,
the existence of proliferated technology leadership roles impact organizational structure and role
clarity.
Organization Structure and Role Clarity
Organizational design is a significant company-performance factor based on how people
work together in organizations (Burton & Obel, 2018). Many academic and practitioner business
performance frameworks emphasize the importance of organizational structure in driving
corporate strategy and culture, including the Burke-Litwin model and the widely used McKinsey
7S model (Cooper, 2015; Galbraith, 2014). The degree to which strategic emphasis is placed on
carefully deliberated organization design and leadership role formulation impacts role clarity for
technology leadership and team members (Galbraith, 2014; Peppard, 2018).
Leadership role definition and organizational structure play an essential role in leaders’
and team members’ role clarity and performance (Bauer, 2003; Tubre & Collins, 2000). Role
ambiguity, which the proliferation of executive leadership roles can cause, can negatively impact
employee job satisfaction and intent to stay with an organization (Gerth & Peppard, 2016;
Hassan, 2013). Organizational structure decisions and resulting role clarity are vital byproducts
of having multiple leaders manage a company’s technology (Gerth & Peppard, 2016; Grant,
2021).
Significance and Impact of Organizational Structure
A firm’s organizational structure defines its function, size, shape, degree of
centralization, communication patterns, hierarchies, specializations, and decision-making
authority (Burke & Litwin, 1992; Grant, 2021; Spangenberg & Theron, 2013). Hierarchies and
functional specialization inform strategies and decision-making rights in most organizations
18

(Burke & Litwin, 1992; Grant, 2021). Most companies are designed in one of three fundamental
organizational structures: (a) the matrix structure, (b) the multidivisional structure, and (c) the
functional structure (Grant, 2021).
Organizational Structure Designs
Large, complex, or multinational corporations inherently have cross-functional
relationships across departments due to geography, division, and product diversity (Grant, 2021);
however, starting in the 1960s, some companies formalized their organizations’ functional and
profit center dimensions into prescribed matrix structures that hybridize strategies, resources,
budgets, and authorities (Galbraith, 2014; Grant, 2021). Modern organizations have largely
rebuffed formal matrix organizations due to the conflict, confusion, and proliferation caused by
the complexity of the matrix structure (Galbraith, 2014; Grant, 2021). To support greater
efficiency, HR and IT functions have strengthened their authority and stances in matrix
organizations despite the cross-functional use of their shared services (Galbraith, 2014).
The potential proliferation of functional departments like HR, finance, legal, and IT is a
common characteristic across matrix and multidivisional organizations (Grant, 2021).
Companies with a multidivisional organization structure are typically divided across product
group units, channels, or geographies, with their own functional departments, such as IT or HR,
assigned to each division (Galbraith, 2014; Grant, 2021). As shown in Figure 2, the siloes
associated with a multidivisional structure can impede cross-divisional collaboration among
groups, such as finance, HR, and IT (Grant, 2021; Tardieu et al., 2020). Employees are
intrinsically more comfortable partnering and sharing with people in the same organizational unit
(Tardieu et al., 2020). Unaligned divisional incentives, divergent communication patterns, or
psychological barriers often prevent the use of shared resources, best practices, or efficiencies
19

across functions in the various units of a multidivisional organization (Galbraith, 2014; Grant,
2021; Tardieu et al., 2020).

Figure 2
Multidivisional Organizational Structure

Note. Adapted from Contemporary Strategy Analysis by R. M. Grant, 2021. John Wiley & Sons.

20

Firms typically use functional organizational structures when they have less diverse
geographical or product-related business units (Grant, 2021). As a result, functionally structured
organizations are generally constructed more simplistically, as indicated in Figure 3 (Grant,
2021); however, as many large multinational companies, such as General Motors, mature, they
find they can reap the advantages of economies of scale and efficiency from adopting or
reverting to functional structures (Grant, 2021). While there may be contention for resources in a
functional organization model, shared services like IT, HR, or legal departments can operate
more effectively and efficiently across business units or divisions (Cooper, 2015; Grant, 2021;
Tardieu et al., 2020). The employees that contribute to a specific process or capability, such as
IT, must be situated in the same organizational unit to function effectively (Grant, 2021).
Empirical research across industries has shown that managing the technology function more
centrally and strategically helps companies achieve higher levels of financial performance and
efficiency (Cooper, 2015; Paré et al., 2020).

Figure 3
Functional Organizational Structure

Note. Adapted from Contemporary Strategy Analysis by R. M. Grant, 2021. John Wiley & Sons.
21

The Need and Pace of Change of Organizational Design
Some scholars have suggested the pace of organizational structure transformation needs
to match the speed of change and dynamic nature of evolving business and social complexities
(Shatrevich, 2014). Because innovations and operating conditions shift rapidly, organizational
structures should be flexible to accommodate change (Dyduch, 2019; Johnson McPhail, 2016).
Shatrevich (2014) highlighted the fluidity of the Burke-Litwin model, as shown in Figure 4.
Using the model involves continual evaluation of the 12 elements in the model, as it has no
beginning or end. Therefore, based on Shatrevic’s recommendation, organizational structure
changes should occur as often as necessary to support ongoing change because the organizational
structure element of the model stands as a critical factor in a firm’s successful performance and
competitiveness. Changing business conditions, the aspiration to unlock innovation potential,
contempt for hierarchies, and space required to place proliferated leadership positions support
looser organizational structures (Dyduch, 2019; Leavitt & Kaufman, 2003).
Business leaders and academics predicted hierarchies and tightly architected
organizations would be replaced by more fluid community-based and project-based
organizational structures to support the collaboration and communications necessary in modern
business (Leavitt & Kaufman, 2003). In addition to their success, Silicon Valley startups were
admired for innovation, performance, lack of conformity to traditional office designs and norms,
and perceived lack of hierarchy (Leavitt & Kaufman, 2003). The desire to shed old, antiquated
ideologies and structures and pursue new and seemingly innovative identities drove many top
business executives to reexamine their cultures and structures (Pfeffer, 2013). Conventional
corporations added new or proliferated roles to their organizations to emulate Silicon Valley
firms to invigorate their business models (Haffke et al., 2016). Newer proliferated leadership
22

roles in IT, like CDO, are more easily consumed into looser environments when hierarchy or
clarity are of less concern (Tardieu et al., 2020), yet as Silicon Valley firms like Apple, Google,
and Facebook grew larger and matured, hierarchical forms in their organizational structures took
shape (Grant, 2021; Leavitt & Kaufman, 2003).

Figure 4
The Burke-Litwin Model of Organizational Performance and Change

Note. Adapted from “A Causal Model of Organizational Performance and Change” by W. W.
Burke and G. H. Litwin, 1992. Journal of Management, 18(3), 523–545.
[https://doi.org/10.1177/014920639201800306].
23

The Reality of Hierarchies and Structure
Despite the negative connotations surrounding hierarchies, they remain a necessary and
vital aspect of organizational structure and design (Grant, 2021). Hierarchies are required to
support the organization of complex companies’ functions, strategies, and cultures (Grant, 2021).
Hierarchies are needed to satisfy corporate organization and structure concerns and are a
psychological necessity for most company employees (Leavitt & Kaufman, 2003; Pfeffer, 2013).
While business conditions have significantly evolved, there is a lack of neuroscience
evidence to support that human’s fundamental needs for hierarchy or systems of authority have
changed (Pfeffer, 2013). Hierarchies fulfill an essential need for order and security; hierarchies
provide identity and bearing of stance in an organization; hierarchies motivate achievement; and
hierarchies align with fundamental mental processing of complex tasks (Leavitt & Kaufman,
2003; Pfeffer, 2013). For example, the human brain supports complex tasks, such as assembling
a bicycle or following a recipe, by hierarchically completing subprocesses to create pedals or
sauces as part of building the main or principal product (Leavitt & Kaufman, 2003).
Hierarchies and tight organizational structures are perceived as supporting strategic
planning, while loose organizational structures are perceived as supporting idea generation,
innovation, and creative processes (Dyduch, 2019). Dyduch (2019) studied over 500 companies
with organizational designs to support innovation and creative processes and concluded a
balance of organizational structure elements and other organizational design elements, such as
culture, knowledge, and trust, was required to support innovation in an organization. Especially
for large companies, organizational structure alone does not have as much bearing on creativity
or innovation as the cultural and attitudinal aspects espoused in firms and their leadership
(Dyduch, 2019). Organizational hierarchies and structure are required to enable most companies
24

to function, but culture is what drives cooperation and coordination in an organization (Grant,
2021).
The Impact of Role Clarity
Studies on proliferated IT leadership roles, such as CDO, chief innovation officer, or
chief transformation officer, cite clarity and ambiguity as key issues related to these positions
(Hiller, 2021; Singh & Hess, 2020). Role ambiguity is caused by an incomplete or unclear
understanding of the expectations surrounding a role and can result in role conflict, which
involves the incompatibility of the requirements and demands facing an individual in a given role
(Jackson & Schuler, 1985; Tubre & Collins, 2000). Requirements or expectations of an
employee in a specific role involve explicit responsibilities or tasks and include expected
behaviors. Therefore, conflict occurs between individuals or groups when tasks, actions, or
behaviors are not aligned with each other’s expectations (Jackson & Schuler, 1985). Tubre and
Collin’s (2000) empirical study of the correlation between role ambiguity and job performance
confirmed prior studies, indicating role ambiguity negatively impacts job performance.
Furthermore, role ambiguity more significantly negatively affects job performance in more
complex roles, like technology roles (Tubre & Collins, 2000).
Technology Organization Conceptual Framework
The conceptual framework for this study was used to assess the impacts of potential
proliferation of technology leadership roles in corporations, leveraging the underlying construct
of the Burke-Litwin causal model of organizational performance, focusing on the effects of the
transactional factors of the model, as depicted in the center of Figure 4 (Burke & Litwin, 1992).
While maintaining the integrity of the comprehensive Burke-Litwin model, this framework
concentrates on the organizational structure element as the filter by which to evaluate firm
25

performance (Burke-Litwin, 1992). As depicted in Figure 5, the technology organization
conceptual framework also includes Conway’s (1968) law, which posits multiple technology
organizations create differing solutions that reflect the organization that built them. While
Conway’s law has been tested and used across industries, its roots in the technology
development industry uniquely position it to be leveraged with the Burke-Litwin model for this
conceptual framework (Bailey et al., 2013).

Figure 5
Technology Organization Conceptual Framework

26

The technology organization conceptual framework explicitly views the impact of the
organizational structure on workplace climate, management practices, and, ultimately,
performance. For technology organizations, performance is represented by the quality,
effectiveness, and timeliness of technology output produced for the organization (Gartner, 2022).
The conceptual framework assesses the dimensionality of having multiple technology leaders,
which inherently creates numerous organizations and can create varying workplace climates,
different management practices and policies, and inconsistent performance (Conway, 1968;
Grant, 2021; Tardieu et al., 2020).
Burke-Litwin Structural Element
The Burke-Litwin causal model of organizational performance and change depicts the
interrelationships between 12 elements in an organization influencing organizational
performance, divided into transformational and transactional factors (Burke & Litwin, 1992).
The transformational factors are (a) the external environment, (b) the company’s mission and
strategy, (c) leadership, (d) organizational culture, and (e) performance (Burke & Litwin, 1992).
The transactional factors are (f) structure, (g) systems, (h) management practices, (i) workplace
climate, (j) tasks and skills, (k) individual values and needs, and (l) motivational levels (Burke &
Litwin, 1992).
Most renowned organizational diagnostic models position structure as a fundamental
aspect of each framework (Baharudin & Abdullah, 2020). Weisbo’s six-box model, the
McKinsey 7S framework, the star model, and Leavitt’s model all have significantly fewer
variables than the 12 variables of the Burke-Litwin model, making structure a more predominant
factor in organizational evaluation in other models (Baharudin & Abdullah, 2020); however, as
shown in Figure 4, the Burke-Litwin model is the only theoretical framework of these
27

predominant models that uses its variables to assess an organization’s performance (Baharudin &
Abdullah, 2020). Assessing performance, or technology output, as represented in the technology
conceptual framework, is critical to the study of technology leadership role proliferation. Using
Conway’s (1968) law, layered onto the assessment of the applicable variables of the Burke-
Litwin framework, provides the most comprehensive approach to assessing technology
leadership proliferation in corporations.
Assessing Technology Team Output Via Conway’s Law
When studying the design output of multiple teams in different organizations, Conway
(1968) concluded teams that develop systems produce designs that mirror their organizations,
introducing Conway’s law. Websites, applications, and user-facing technology are intended to
solve problems, fulfill a need, or provide information to users of technology (Bevan, 1997);
however, inconsistencies or incompatibility of websites or technology are often indicative of
issues in the organizational structure of the development organization (Bevan, 1997). Empirical
studies, using Conway’s law, have measured the impact of having multiple organizations on the
quality, interoperability, and future progression of product or output (Colfer & Baldwin, 2010;
MacCormack et al., 2012).
Colfer and Baldwin (2010) analyzed the empirical experiments of 102 cross-industry
organizations, including banking, technology, construction, and others, from 2000 through 2009
to substantiate the mirroring hypothesis, and they determined Conway’s law was supported in
69% of the cases. Wang et al. (2018) assessed the communicative collaboration and output
quality for six technology development projects across teams in an organization. They concluded
communicative collaboration and output quality, measured by the volume of software defects, or
bugs, was superior in organizations than across organizational structures (Wang et al., 2018).
28

Incongruence in communication, approach, and collaboration requires attention from technology
leaders (Wang et al., 2018). The people and processes that create solutions need to be aligned in
the same organizational unit to effectively deliver capabilities for the company (Grant, 2021).
Summary
Especially in technology organizations, there is a trend toward the growth of chief titles
in the executive suite, causing overlap, confusion, and role clarity issues in organizations (Haffke
et al., 2016; Singh & Hess, 2020). The literature has covered the impact, efficacy, and future
predictions of proliferated technology leadership roles, such as CDO and CDAO. Select research
also provides context for the reporting relationship and organizational structure required for these
c-level technology leadership roles. The preponderance of these studies suggests further research
is needed on reporting and organizational structure and alignment. Research studies on
organizational structure and role clarity across industries, fields, and practices indicate the
significance of structure and clarity on workplace climate, employee well-being, and
organizational performance.
Organizational diagnostics leveraging the Burke-Litwin model’s transactional factors can
help determine organizational structure’s impact on workplace climate, management practices,
policies, and, ultimately, organizational performance. Empirical studies have validated Conway’s
(1968) law, which suggests technology output will mirror the organization that built it. The
conclusions and recommendations from the literature review provide context to understand this
study’s problem of practice and research questions. The literature also suggests firms would
benefit from a better understanding of how to structure their top technology leadership, which
this research study endeavors to do.

29

CHAPTER THREE: METHODOLOGY
This chapter outlines the mixed-methods research design for this study, including the
methodology and analysis used, the sampling criteria, and the interview protocols. The
researcher’s positionality and ethics are also included in this chapter. The purpose of this study
was to examine the impact of the structure of corporate technology executive roles on
organizational clarity and climate and on company performance metrics and goals. The research
questions outlined in the following support this study and examination of this problem of
practice.
Research Questions
1. To what extent does having multiple technology executive leadership roles impact
role clarity across technology teams?
2. To what extent does having multiple technology executive leadership roles impact
workplace climate?
3. To what extent does having multiple technology executive leadership roles impact the
effectiveness of technology output?
Overview of Design
The research design for this study was an explanatory sequential mixed-method design
augmented by secondary financial data collection. The quantitative portion of this research study
aided in understanding the broad perception of organizational clarity and climate based on the
structure of top technology leadership roles across U.S. corporations. The qualitative research
phase provided additional context and explanation to research findings, especially related to
detailed perceptions of performance and technology departments (Creswell & Creswell, 2018).
This mixed-methods research approach aligned with the evaluation needed to assess this problem
30

of practice effectively across a broad portion of the subject population and with deeper context
from a smaller, focused group of technology leaders. Secondary financial data was used in
conjunction with the quantitative and qualitative study results to develop a higher level
perspective on firm performance potentially influenced by technology organization structure.
Use of financial metrics from publicly traded U.S. corporations provided objective
measurements to supplement the findings from the qualitative and quantitative surveys on
company performance (Boslaugh, 2010). Financial metrics have been used as the sole
measurement in many research studies on the efficacy of technology leadership (Hiller, 2021;
Zhan & Mu, 2016). As displayed in Table 1, the results from this study represented a
comprehensive analysis of the problem of practice across multiple spectrums, from individual
and specific corporations based on the qualitative research, industry-wide insights based on the
quantitative research, and corporate financial performance measurements from secondary data
sources.

Table 1
Data Sources
Research Questions Survey Interviews Secondary
Data
RQ1: To what extent does having multiple
technology executive leadership roles impact
role clarity across technology teams?
X X
RQ2: To what extent does having multiple
technology executive leadership roles impact
workplace climate?
X X
RQ3: To what extent does having multiple
technology executive leadership roles impact
the effectiveness of technology output?
X X X
31

Research Setting
This research study addressed technology departments in publicly traded U.S. companies
with revenues greater than $2 billion annually in the 12 months prior to April 1, 2023. The total
population of target population was approximately 1,000 technology leaders. Most corporations
have one or more technology functions, and this study focused on the top executive leaders of
those functions, both as the subject of the research and as respondents (Peppard, 2018).
The quantitative research for this study was conducted electronically. The qualitative
interview portion of this study took place via Zoom. Participants were highly engaged in both
portions of the study because the research study subject of technology executive responsibilities
has been a topic of discussion in academic and trade publications and at industry conferences
(Koh et al., 2021; Peppard, 2018).
The Researcher
The researcher is a sitting chief digital and technology officer and long-time CIO, is
intimate with the role proliferation trend that has occurred in technology departments across
industries and has personal experience with the impacts of lack of role clarity. The researcher
believes a single leader should manage technology in an organization and that all technology
strategy and execution should be under the single leader’s remit. Therefore, the researcher holds
bias about the potential outcome of the research results.
At the time of this writing, the researcher plans to retire from the industry in the next 2
years and had no personal or career gain in the outcome of the results of the study. The
researcher’s quest for valid, objective results in a study of this problem of practice outweighed
their personal bias. As described in detail in the validity and reliability section of this chapter,
peer reviews were conducted at several stages of this study to mitigate the risk of personal bias.
32

Systematized feedback from a group of industry leaders and subject matter experts ensured the
validity and objectivity of the overall study (Creswell & Creswell, 2018).
Data Sources
This research study used an explanatory sequential mixed-method design, augmented by
secondary financial data collection. The primary data sources for each research question are
presented in Table 1. The qualitative interviews immediately followed the close of the
quantitative survey. The secondary data was collected following the quantitative study using the
stock trading symbol for the companies represented by respondents of the quantitative survey.
Using integrated data and insights, the mixed method approach to this research study,
accompanied by the secondary data analysis, provided greater insight into the problem of
practice of the proliferation of technology leaders in organizations (Creswell & Creswell, 2018).
Method 1: Survey
The research study began with a quantitative survey administered electronically to
participants. A quantitative survey design was used to gauge the impact between the independent
variables: single executive technology leadership compared to multiple executive technology
leadership (Creswell & Creswell, 2018). In addition, the quantitative nature of this study also
provided the opportunity to obtain broad perspective and feedback on the topic of technology
leadership across the technology field.
Participants
Using the Raosoft (2004) sample size calculator, a target of 139 completed survey
responses was sought to achieve an acceptable confidence level and margin of error. The initial
targeted population was approximately 300 senior technology leaders with specific roles,
including CIO, CDO, CTO, chief data officer, and combination titles, such as chief information
33

and digital officer. The participants were solicited using a single-stage sampling procedure,
leveraging professional technology trade organizations such as T200, World 50, HMG Strategy,
and the National Retail Federation CIO Council (Creswell & Creswell, 2018). A high response
rate was expected due to the reputations of the trade industry groups across the technology field.
The snowball approach was used to obtain relevant participants to reach the required sample size
(Merriam & Tisdell, 2015). By the close of the quantitative study, 145 technology leaders
responded to the survey, resulting in 126 valid responses.
Instrumentation
The quantitative survey consisted of 35 items, including nine demographic questions, 24
five-point Likert scale items, one multipart six-point Likert scale item, and one open-ended
question for respondent feedback. The survey was divided into three sections, associated with the
research question topics. One example item was “There is overlap of responsibilities between my
team and other teams in the organization,” with five responses ranging from strongly agree to
strongly disagree. The nine demographic questions did not include personally identifying
information (PII) or sensitive data, such as age, gender, or race. Answers to demographic
questions were used to correlate responses to address the problem of practice. One of the open-
ended items was the stock trading symbol of the respondent’s companies. This demographic
element was essential for qualifying the respondent’s eligibility for the survey and for providing
the basis for establishing top technology executives in the same firm.
The survey was presented to respondents in block section titles in three core areas: (a)
role clarity, (b) workplace climate, and (c) performance and output. As dependent variables,
these sections correlated to the research questions (Creswell & Creswell, 2018). The final section
34

contained two general questions about the problem of practice, and one of those questions was
open ended, allowing respondents to provide further feedback on the research topic.
One multipart question in the workplace climate section of the survey was created by
adopting a multipart question from an existing tool. The adopted survey question was from a
Deloitte University study on the CIO role and investigated CIO relationships in their respective
organizations (Kark et al., 2015). This Deloitte CIO survey was broader, studying CIO priorities,
reporting, and effectiveness based on variables relating to intercompany relationships (Kark et
al., 2015). The adopted survey question from the Deloitte study was used to understand
workplace climate based on the positivity of relationships for this research survey.
Data Collection Procedures
The quantitative survey was administered through Qualtrics, an online survey platform
(Boas et al., 2020). The use of an online survey, specifically Qualtrics, was an appropriate
method for reaching the targeted respondent population, as this type of survey platform is
commonly used by corporations (Boas et al., 2020). Following the university’s Institutional
Review Board (IRB) approval, the survey was distributed via trade industry groups and
technology leaders through work email addresses. It remained open for 4 weeks. The emailed
survey invitation contained important elements about the study, including a brief description of
the survey, its purpose, its importance, estimated completion time, and confidentiality (Pazzaglia
et al., 2016). Based on pretest results, the estimated survey completion time was 10 minutes.
Email reminders were sent weekly until the target response rate was achieved (Pazzaglia et al.,
2016).
No PII was stored, except email addresses (Pazzaglia et al., 2016). Data was downloaded
from Qualtrics for analysis and was stored on the researcher’s encrypted hard drive. The survey
35

will be deleted from Qualtrics and the researcher’s hard drive 6 months after completion of the
study, allowing enough time for the survey results to be compiled and analyzed.
Data Analysis
Data was extracted from Qualtrics, downloaded into reports for cursory analysis, and
imported to the Statistical Package for Social Sciences (SPSS; Version 28.0) to statistically
analyze the response data (Creswell & Creswell, 2018). Data was evaluated for response bias
from nonresponses and reliability for internal consistency (Creswell & Creswell, 2018).
Response data was then assessed using the demographic survey item responses as key
independent variables, including organizational structure elements, to correlate to the dependent
variables from the research questions. A series of statistical tests was required to determine the
correlations of role clarity, workplace climate, and output performance across single technology
leadership organizations, compared to multiple technology leadership organizations (Creswell &
Creswell, 2018). Additionally, bivariate analysis was used to measure further correlations based
on company demographic data, such as title or company size (Creswell & Creswell, 2018).
Method 2: Interviews
Following the quantitative survey’s close and initial data analysis, participants were
selected to participate in one-on-one semistructured qualitative research interviews. Interviews
provided context for findings from the quantitative study. In addition, insights that cannot be
easily obtained through quantitative research, based on participants’ experiences, perceptions,
and detailed discussion provided a comprehensive data collection to satisfy the study’s research
questions (Merriam & Tisdell, 2015).
36

Participants
Participants for the qualitative interview portion of the research study were selected from
respondents from the quantitative survey who agreed to participate in a follow-up interview.
Eight one-on-one interviews consisted of four pairs of technology executives from four different
organizations. As outlined in Table 2, two pairs had peer relationships in their organizations, and
the other two pairs had manager/subordinate relationships. All participants were top technology
leaders in their organizations who have worked in their position for at least 6 months and have
worked for their company for at least 1 year.

Table 2
Interview Participants and Criteria
Group Criteria Number of
Participants
A 1. Top technology leader in Fortune1000 company
2. Participant’s company revenue must be >$2B for last year
3. CIO, CDO, CDAO, CTO or equivalent title
4. In position for at least 6 months
5. Worked for company for at least 1 year
6. Works in same organization with participants in Groups B or C
4
B 1. Top technology leader in Fortune1000 company
2. Participant’s company revenue must be >$2B for last year
3. CIO, CDO, CDAO, CTO or equivalent title
4. In position for at least 6 months
5. Worked for company for at least 1 year
6. Works in the same organization with participants in Group A
7. Peer to participant in Group A, reporting to different part of
organization
2
C 1. Top technology leader in Fortune1000 company
2. Participant’s company revenue must be >$2B for last year
3. CIO, CDO, CDAO, CTO or equivalent title
4. In position for at least 6 months
5. Worked for company for at least 1 year
6. Works in the same organization with participants in Group A
7. Subordinate to participant in Group A
2

37

The number of participants chosen for interviews was based on convenience and the
practical consideration of time allotment following an extensive quantitative study (Merriam &
Tisdell, 2015). Using four pairs of executives from the same organizations yielded contextual
insights to integrate with the quantitative survey’s results (Creswell & Creswell, 2018). The
recruitment approach, using the criteria listed in Table 2, was purposeful sampling (Merriam &
Tisdell, 2015). Because the purposeful sampling yielded a greater number of potential
participants, additional criteria, such as industry and company size, were used to select
participants. This sampling approach yielded an optimal mix of eight participants who met the
criteria, while ensuring a breadth of industry and company size representation for the interviews
(Merriam & Tisdell, 2015).
Instrumentation
The semi–open-ended research questions encompassed participants’ experiences and
opinions about their technology organization structures, including their views on how the
structures impact role clarity, workplace climate, and output effectiveness. The interview
questions reflected the research questions and the respondents’ responses to the quantitative
survey. The interview protocol had 12 questions and related prompts that aligned with the study
research questions and categories in the quantitative survey. Questions were posed flexibly to
obtain additional information in an exploratory manner (Merriam & Tisdell, 2015). Because the
interview protocol was the most comprehensive method to collect specific information about
organizational output and performance, participants were encouraged to share their experiences
about costs, efficiencies, and the quality of their organization’s technology outputs.
38

Data Collection Procedures
Candidates were contacted via email to confirm their willingness to participate in
interviews. Forty-five-minute interviews via Zoom were scheduled during mutually convenient
times during the business day, evenings, or over weekends. All participants gave consent for
recordings and transcripts from the Zoom calls to be saved, so the recordings and transcripts
were downloaded and stored on the researcher’s encrypted hard drive. In addition, the researcher
took handwritten notes on poignant points the interviewees made during the interviews.
Data Analysis
Data from interview transcripts and notes were coded using a priori coding methodology
based on the research study’s conceptual framework and research questions (Lochmiller, 2021).
The priori themes were (a) individual role clarity, (b) team and process clarity, (c) workplace
climate, (d) architectural or output quality, (e) speed to market, and (f) cost. Priori coding was
supplemented by additional themes that arose from the interviews (Merriam & Tisdell, 2015).
Data was assessed for potential integration with quantitative data sets for further statistical
analysis (Creswell & Creswell, 2018).
Method 3: Secondary Data
Corporate financial metrics were collected for a dimension of analysis on overall
company performance associated with the effectiveness of the technology function and its
leadership. Because companies rely on technology to drive the success of their strategies, studies
commonly use overall corporate financial data to assess the effectiveness of technology
departments or technology leadership (Hiller, 2021; Zhan & Mu, 2016). As indicated in Table 1,
this secondary data analysis was used in conjunction with qualitative and quantitative data to
39

understand the relationship of the number of technology executive leaders to the performance of
the technology department and the company.
Metric and Data Used
The specific financial metric that used for this study was ROA. Return on assets reflects a
company’s effective use of its assets to produce income, including financial investments and
technology investments (Tayeh et al., 2015). Return on assets is net profit before interest and tax,
divided by total assets, then multiplied by 100 (Tayeh et al., 2015). While ROA can vary by
industry, it is one of the most commonly used accounting metrics to evaluate technology
investment and effectiveness across firms and industries (Hiller, 2021; Tayah et al., 2015).
Instrumentation, Data Collection, and Analysis
The trailing 12-month (TTM) ROA for each respondent’s firm was obtained from
Morningstar, an independent service for investment analysis data from publicly available sources
for fund and stock investors, such as regulatory filings and company documents (New York
Public Library, 2023). Trailing 12-month ROA is based on the last consecutive TTM
performance for all firms analyzed. By evaluating TTM numbers, company financials can be
assessed regardless of when the fiscal year-end is and enables more like comparisons while
smoothing inconsistencies (Mastouri & Gilkey, 2021). The ROAs for companies represented in
the quantitative survey were extracted from Morningstar.com based on the stock trading ticker
symbol with the New York Stock Exchange (NYSE) or the National Association of Securities
Dealers Automated Quotations (NASDAQ). The ROA ratio figures were entered and analyzed in
Excel using stock ticker symbol and survey demographic data for correlation analysis and
statistical significance measurement.
40

Validity and Reliability
The researcher employed several strategies to establish validity and reliability of the
quantitative survey (Creswell & Creswell, 2018). To mitigate risk of personal bias and ensure
survey validity, peer reviews were conducted at several stages of this study, which included
feedback from a group of industry leaders and subject matter experts. The industry leaders were
two experienced, recently retired top technology leaders, one CTO and one CIO. Subject matter
experts consisted of one highly regarded technology strategy advisory practice leader and two
technology officers practice leader from top executive search firms. These experts’ thoughts and
reactions reflected the respondents’ opinions, as they are from the same population and field
(Robinson & Firth Leonard, 2019). Expert feedback helped assure questions and responses
would be understood by respondents and provided face validity (Robinson & Firth Leonard,
2019). Peer reviews were conducted on (a) research topic reality, (b) research question validity,
(c) research study question validity, (d) findings, (e) discrepant rationale analysis, or any other
reasons could be contributing to research findings (Merriam & Tisdell, 2016).
Existing tools and research surveys did not align directly with this research study’s
conceptual framework and specific research questions. Except for one adapted multipart survey
item, this quantitative study contained 25 original survey items to understand the research
questions. A Cronbach’s alpha measurement was used to calculate internal consistency reliability
to know whether the newly created questions effectively measure the same variables (Creswell &
Creswell, 2018; Salkind, 2014).
Credibility and Trustworthiness
The researcher used several strategies to establish the credibility and trustworthiness of
research findings (Merriam & Tisdell, 2015). The peer reviewers who agreed to support the
41

efforts to establish validity and reliability also agreed to review the interview framework and
summarized findings. This review contributed to the credibility for the interview protocol and
analysis and aids in regulating the researcher’s positionality on the subject matter, questions, and
findings (Merriam & Tisdell, 2015). Verbatim transcripts were used to ensure participants’
statements and opinions are captured comprehensively and accurately to further establish
credibility and trustworthiness in research findings (Merriam & Tisdell, 2015).
Ethics
Ethics were considered throughout this research study, including the finalization of
survey instruments, data collection, and analysis processes. The research commenced following
IRB approval, which includes review of procedures for ethical research conduct (Merriam &
Tisdell, 2015). The researcher emphasized the voluntary nature of the study, and candidates were
not coerced during the survey or interview recruiting processes (Merriam & Tisdell, 2015).
Informed consent was obtained before the start of the research survey and at the beginning of
each interview (Merriam & Tisdell, 2015). Participants were not solicited from the researcher’s
organization and did not have any subordinate or other relationship subject to influence by the
researcher.

42

CHAPTER FOUR: FINDINGS
This research study evaluated the impacts of having multiple technology leaders, versus a
single leader responsible for technology strategy and execution, in U.S. corporations. As
technology has become increasingly important and complex in corporate environments,
understanding the impacts and dynamics of the organizational structure is increasingly
imperative. The research methodology for this study was a mixed-methods sequential
explanatory approach, augmented by a secondary data analysis to answer the study’s research
questions. This chapter first reviews the participants, provides summary analyses by research
method, and then examines the findings for the research questions:
1. To what extent does having multiple executive technology leadership roles impact
role clarity across technology teams?
2. To what extent does having multiple technology executive leadership roles impact
workplace climate?
3. To what extent does having multiple technology executive leadership roles impact the
effectiveness of technology output?
Participants and Secondary Data Collection
Participants were top technology executives from U.S. publicly traded companies with
over $2 billion in annual revenue. Targeted respondents held the job titles of CIO, CDO, CTO,
CAO, and combination titles, such as chief information and digital officer. Participants were
required to have been employed by their companies for longer than 1 year and in their current
role for over 6 months.
43

Survey Participants
The corporate demographics for the 125 respondents to the quantitative survey are shown
in Table 3. Respondents answered 34 Likert-scaled items and one open-ended item in the
quantitative survey. Respondent demographics largely correspond to the population
demographics for U.S. public companies with greater than $2 billion in annual revenue. The
mean annual revenue across the respondents’ firms was $31.5 billion, and the median was $10.2
billion. Most respondents (57%) had a title of CIO, which aligns with the study’s overall
population distribution. In 2020, 67% of Fortune 500 companies’ top technology executives held
the CIO title (Hopkins & Rickards, 2020). The proportional number of respondents representing
firms with a singular technology leader versus multiple technology leaders (51% and 49%,
respectively) was beneficial for performing the analysis across those two populations of
respondents, as the research questions specifically required the comparative analysis across those
two groups.
Interview Participants
Eight participants from four firms were interviewed in semistructured interviews
following the quantitative survey. Participants were selected based on the criteria specified in
Table 2. In addition, industry sector and firm size were considered in participant selection to
ensure population representation. As stipulated in the pre-established selection criteria (see Table
2), two firms’ technology leaders were peers to one another, and the other two firms’ technology
leaders held manager/subordinate relationships. The titles and reporting relationships of the
interviewees are outlined in Table 4. Other corporate demographic data, such as industry or
company size, were not ascribed to the specific respondents and were provided in aggregate to
maintain the identity confidentiality of the participants.
44

Table 3
Respondent Characteristics
Respondent Characteristics %
Industry
Aerospace and defense
Automotive/automobiles/components
Banking/financial service
Commercial, industrial, or professional services
Consumer goods
Hospitality
Healthcare/healthcare equipment or services
Insurance
Media and entertainment
Pharmaceuticals, biotech, and life sciences
Real estate
Retail/wholesale sales or distribution
Technology hardware, software, or services
Transportation
Utilities and energy
Other

2%
5%
6%
7%
15%
7%
4%
4%
3%
3%
2%
30%
6%
1%
2%
2%
Title
Chief information officer
Chief technology officer
Chief digital officer
Combination title
Chief data/analytics officer or combination
Other

57%
8%
6%
16%
4%
7%
Length of Service
1–4 years
5–10 years
10 years or greater

47%
32%
21%
Reports to
Chief executive officer
Chief information officer
Chief technology officer
Chief operating officer
Chief marketing officer
Chief financial officer
Other

51%
10%
3%
11%
2%
16%
6%
Company Revenue
$2B–$4.99B
$5B–$9.99B
$10B–$19.99B
$20B–$49.99B

25%
23%
20%
13%
45

Respondent Characteristics %
$50B–$99.99B
$100B or greater
11%
8%
Technology leadership structure
Single technology leader
Multiple technology leaders

51%
49%

Note. n = 125.

Table 4
Interview Participant Titles and Reporting Relationships
Firm Participants Reporting Relationship
1 Chief Information Officer ↔ Chief Analytics Officer

Peers
2 Chief Information Officer ↔ Chief Technology Officer

Peers
3 Chief Digital and Technology Officer
↓
Chief Analytics Officer

Manager/Subordinate
4 Chief Information Officer
↓
Chief Digital Officer

Manager/Subordinate
Note. n = 8. Participants represent top technology executives of four firms, two having peer-to-
peer relationships and two having manager–subordinate relationships. The four firms represent
the healthcare, retail/wholesale/distribution, commercial/industrial services, and consumer goods
industry sectors. The average annual revenue of the firms was $13.3 billion.

Secondary Data Collection
In the Qualtrics quantitative survey instrument, respondents were asked to provide their
stock trading symbols for their respective organizations. The researcher extracted stock trading
symbol data and the respondents’ single or multiple technology leadership structure designation
46

from Qualtrics into Excel. The TTM ROA were extracted for all applicable trading symbols from
Morningstar into Excel. ROA was leveraged as an objective measurement to augment the
research findings from the quantitative and qualitative analysis for firms’ technology use
effectiveness.
The secondary data analysis sample included 98 firms. Of the 125 quantitative survey
respondents, 15 were from the same firms as other respondents, and 12 provided invalid
responses for the stock trading symbols. Given the analysis of the single- and multiple-leader
technology leadership structures, respondents from the same firm were anticipated and
welcomed. Invalid responses could be ascribed to typographical errors or the provision of trading
symbols from stock trading platforms other than NYSE or NASDAQ.
Analysis Summary by Research Method
The following section summarizes research analysis by research method, quantitative,
qualitative, and secondary data analysis. These summaries display the research results spanning
the research questions and across the entire respondent populations that participated in each
research method. In addition, data about validity and statistical significance were provided,
where applicable. Interpretations of the research results are conducted in the Results and
Findings section in response to the three research questions.
Quantitative Survey Analysis Summary
The descriptive statistics, including the means, standard deviation, skewness, and internal
consistency measurement using Cronbach’s alpha for this study are displayed in Table 5. This
table shows the results across all survey participants spanning both populations, single-leader-led
technology organizations, and multiple-leader technology organizations. The mean statistics are
47

highly centralized across combined populations, with organizational climate skewing higher in
the five-point Likert scale used in the survey.

Table 5
Descriptive Statistics for Study Measures and Internal Consistency
Topic/Research Question n Mean Standard
Deviation
Cronbach’s
Alpha
Skewness
Statistic Std. Error
Organizational clarity 125 2.2688 .75665 .884 -.750 .217
Organizational climate 114 3.2429 .64860 .752 -.454 .226
Performance and output 113 2.2276 .76065 .816 -.149 .227
Valid n (listwise) 113

Note. n = 125.

Cronbach’s alpha was used to measure the survey’s internal consistency. The higher the
Cronbach’s alpha value, the greater confidence the survey instrument correlates well with itself
and is internally consistent (Salkind & Frey, 2020). The range for Cronbach’s alpha is 0 to 1
(Gliem & Gliem, 2003). The closer Cronbach’s alpha coefficient is to 1, the greater the internal
consistency of the items in the survey or section (Gliem & Gliem, 2003). Alpha values greater
than 0.6 are acceptable, and values greater than 0.8 are considered good (Gliem & Gliem, 2003).
The alpha values across the three sections of the survey that relate to the three research questions
indicate very good internal reliability.
Skewness measures the asymmetry of the distribution of the dataset (Salkind & Frey,
2020). A negative skewness value indicates a larger number of occurrences at the high end of the
distribution and fewer, more spread out data points at the lower end (Salkind & Frey, 2020). The
skewness in the total population’s datasets across all three topics, especially organizational
48

clarity, reflects the variability across the two sample populations, which is further explained in
the results of the t-tests.
As shown in Table 6, a two-sample t-test was used to see if the variations in the two
populations were statistically relevant. The difference between the independent samples of
single- and multiple-leader–led technology organizations was tested for statistical significance at
the .05 level, using the t-test for independent groups, as shown in Table 7 (Salkind & Frey,
2020). The results provide strong support that the difference between the single- and multiple-
leadership organization structure groups was statistically significant at the .05 level across the
three topic areas, clarity, climate, and performance. Because the observed p is less than .05, the
difference is statistically significant with 95% confidence.

Table 6
Independent Sample t-Test Results
Topic/Research Question Structure n Mean Standard
Deviation
Standard Error
Mean
Organizational clarity Single 65 2.5870 .61876 .07675
Multiple 60 1.9241 .74535 .09622
Organizational climate Single 58 3.4100 .53452 .07019
Multiple 56 3.0698 .71291 .09527
Performance and output Single 58 2.4384 .71497 .09388
Multiple 55 2.0052 .74989 .10111

Note. n = 125.

Because statistical significance is a function of sample size, the statistical analysis was
supplemented with an effect size (ES) analysis, as shown in Table 8. Effect size is used to
indicate how significant the difference is between groups (Salkind & Frey, 2020). Effect size is
defined as the ratio of a difference to the pooled population standard deviation. For example, if
49

the difference between two groups is one-half a standard deviation, the ES is .50. Cohen’s (1988)
criteria for small, medium, and large ESs are .20, .50, and .80, respectively. The ESs across the
three topics aligned to the research questions are .68, .63, and .73, all between a medium and
large ES.

Table 7
Test for Equality of Variances

Topic/Research Question

t-Test for
Equality of
t
t-Test for Equality of Means
Degrees of Freedom
(df)
Significance
One-sided p Two-sided p
Organizational clarity 5.426 123 < .001 < .001
Organizational climate 2.890 112 .002 .005
Performance and output 3.144 111 .001 .002

Note. n = 123.

Table 8
Independent Samples Effect Sizes
Topic/Research Question Cohen’s d Point Estimate 95% Lower 95% Upper
Organizational clarity .68242 .971 .598 1.341
Organizational climate .62848 .541 .166 .914
Performance and output .73216 .592 .212 .967

Note. n = 123.

The survey instrument contained one open-ended question about how respondents might
change or reorganize their companies’ top technology leadership structure. Respondents
provided 68 comments in the open-ended survey item. The researcher extracted the comments
50

from Qualtrics and coded them for themes. Table 9 shows common themes that emerged from
the respondents’ comments.

Table 9
Survey Respondent Comment Themes: Changes They Recommend for Their Organizations
Comment Theme Frequency
Recommend single leadership of technology function 21
Create more center-led technology functions to serve business units, subsidiaries, or
regions versus shadow information technology
10
Improve approach and structure for managing data and analytics 5
Better define responsibilities, processes, and accountability, as they matter more than
structure
4
Technology function should report to CEO 4
Product management requires definition and clarification on reporting 3
Adopt agile methodologies to alleviate structural issues 2

Note. n = 68. Table displays themes that were expressed multiple times.

Qualitative Interview Analysis Summary
The eight semistructured interviews reflected the participants’ perceptions and opinions
of how the structure of technology leadership impacts role clarity, workplace climate,
productivity, and the output delivered by their respective organizations. The interview questions
aligned with the study’s research questions. Three key a priori code—(a) organizational clarity,
(b) workplace climate, and (c) performance effectiveness—were key elements of the theoretical
framework constructs and the study’s conceptual framework to establish the coding guideposts.
The study’s central themes, crafted of the a priori codes and comprehensive open codes, address
the study’s three research questions. Using the explanatory sequential approach to this mixed-
methods study allowed for further insights to be captured from the interview participants to
reveal additional factors and nuances surrounding the impacts of technology role proliferation
51

following the quantitative survey. Figure 6 illustrates the themes from the interviews aligned to
the research questions. The figure also depicts the alignment of themes between the research
sample populations representing single- and multiple-technology leader-led organizations.

Figure 6
Interview Themes

Interviewees from both single- and multiple-leader–led technology organizations shared
similar perceptions of the themes surrounding organizational structures on clarity, climate, and
the performance of their departments; however, while they share similar perspectives on the
causes and effects of organizational structure on clarity, climate, and performance, they often
differed in their perceptions of the solutions to organizational problems.
52

Secondary Data Analysis Summary
Return on assets measures how effectively a company uses the assets it owns, including
investments in technology, to generate profits (Tayah et al., 2015). While ROA can vary by
industry, it is one of the most commonly used accounting metrics to evaluate technology
investment and effectiveness across firms and industries (Hiller, 2021; Tayah et al., 2015). Table
10 displays the ROAs of the companies of the technology executives participating in the
quantitative survey separated into single- and multiple-led technology leader organizations. The
difference between the independent samples of single- and multiple-leader–led technology
organizations was tested for statistical significance at the .05 level using the t-test for
independent groups, with a p-value result of .065 (Salkind & Frey, 2020). A p-value of .065
indicates there is some evidence against the null hypothesis, but it is not strong enough to reject
it. The results provide potential support that the difference between the single- and multiple-
leadership organization structure groups affects ROA for this population on firms, but the null
hypothesis cannot be rejected.
Results and Findings
This section details the results of the quantitative survey, the findings of the qualitative
interviews, and the secondary data analysis in response to each research question. Results and
findings are presented in response to the research questions examined by three topic areas that
align to the research questions: organizational clarity, workplace climate, and technology
performance effectiveness. To address the three research questions, the quantitative, qualitative,
and secondary data analyses have been evaluated comparatively across the singular leadership
model versus the multiple leadership model in technology departments.

53

Table 10
Return on Assets t-Test Results
Organization
Structure
n Average Annual Revenue
(in billions)
Average Return
on Assets
Standard
Deviation
Standard
Error Mean
Single 44 $18.46 6.96 % 4.214 0.635
Multiple 54 $35.79 4.88 % 8.737 1.189
Population 98 $28.01 5.81 % 7.149 0.722
Note. Data extraction was conducted on April 1, 2023, from Morningstar.com for all firms
reported based on the last consecutive trailing 12-month (TTM) performance. By evaluating
TTM numbers, company financials can be assessed regardless of when the fiscal year-end is and
enables more like comparisons while smoothing inconsistencies. p = .0653.

Research Question 1: To What Extent Does Having Multiple Executive Technology
Leadership Roles Impact Role Clarity Across Technology Teams?
The first research question focused on understanding leaders’ and teams’ clarity of their
roles, responsibilities, decision-making rights, and accountability in their organizations. Role and
organizational clarity were investigated and measured quantitatively and qualitatively across
technology department leaders, further analyzing singular-led against multiple-leader–led
organizations. Results from the quantitative survey and qualitative interviews suggest having
multiple leaders in a technology organization significantly impacts role and organizational clarity
for leaders and their teams. As indicated in Table 6, the mean for organizational clarity in
organizations with single ownership is 2.58, compared to 1.92 in organizations with multiple
ownership. Thus, executives in single leadership organizations (n = 65) have great organizational
clarity when compared to those working in multiple technology leadership organizations (n =
60). In addition, the organizational clarity differential between single-leader technology
54

organizations and multiple-leader–led organizations was greater than the other two categories,
climate and performance, having a 0.66 difference in the means of the populations (see Table 6).
Issues in the technology organization’s workplace surrounding climate and performance
can stem from clarity issues or have a trickle-down effect from leaders. As one of the
interviewees stated, “Even if those of us sitting in the executive suite are clear on
responsibilities, that gets lost on people 10 layers deep.” Although the research indicates clarity
issues are prevalent in the executive suite among technology leaders, too. The following sections
categorize research themes across modes of research to help further explain potential causes and
effects of clarity issues in technology departments that result from the organizational structure of
leadership.
Job Overlap and Shadow Information Technology
Survey respondents and interviewees were asked about job overlap and whether they felt
others in the organization held responsibilities they felt should be theirs. Interviewees who are
peer technology leaders provided “gray areas” of responsibility but did not necessarily define
those ambiguous areas as overlapping. Peers in one organization stated they were each
responsible for digital, and peers in another stated they were both responsible for analytics and
data science. Reasons for multiple leaders claiming they are responsible for the same function
may be definition alignment, perception, or actual job overlap.
Figure 7 shows the results of a survey item related explicitly to job overlap, comparing
those from single-leader-led organizations to multiple-leader–led organizations. Leaders
representing companies with multiple top technology executives were more than twice as likely
to agree there was an overlap in their responsibilities with others in the organization. Leaders
55

with sole responsibility for technology in their organizations still believed there was overlap in
responsibilities with other leaders.
The concept of “shadow IT” emerged as a theme in both qualitative interviews (see
Figure 6) and in the open-ended item in the quantitative survey (see Table 9). Shadow IT is
defined as solutions used by employees without formal IT department approval and managed by
those outside the IT department (Silic & Back, 2014). In the context of this study, shadow IT can
also be perceived as another technology department like digital, product management, or
analytics. One interviewee, a CAO, said, “I’ve been accused of running a shadow IT
organization.” Technology management can also extend beyond technology-based departments
and reside in business teams, likely accounting for the single-leaders of technology who believe
there is job overlap (see Figure 7). One of the open-ended responses included the statement,
“The technology team should exist in a single org, with no shadow technology teams in the
business units.”

Figure 7
Job Overlap

Note. Respondents who agree or strongly agree (n = 123).
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The complexity of structure in large and complex, multinational organizations can
exacerbate the clarity of roles and responsibilities among technology functions. Overlap between
business units or regional technology departments was referenced as a common theme in
interviews and open-ended survey responses (see Table 9). The opinion provided by a survey
respondent generally reflects the sentiment in other comments and interviewees’ comments:
“Modify the [business unit] IT support structure to reduce independence and drive more
efficiency and consistency through ‘center-led’ strategy and programs (not centralized).”
Overlap and lack of clarity often extend beyond structural lines and into roles and
responsibilities. One survey respondent replied, “Defining responsibilities is key; if this is crystal
clear, the organizational structure does not matter as much.” Definitions of roles and
responsibilities can only be achieved if there is a common understanding of what functions are,
what they consist of, and who is best served to lead them. One of the CIOs interviewed asked,
“What is digital? It makes it hard to agree or disagree where it should report if people don’t align
on what it is.”
Common Definitions and Understanding
A few concepts and terms seem to drive most of the confusion and overlap across leaders
and teams: digital, analytics, and product management. These are the same areas that have the
most significant levels of confusion and overlap across technology teams and business partners.
A comment from the open-ended survey question summed the terminology and organizational
structure issue:
While I think the concepts of technology and digital, and in some cases, transformation
have become a bit interchangeable, some companies have created siloed organizations
57

focused on one or two of these concepts. Often without clear definitions which confuses
the employees in each group.
In addition to the term digital, which sometimes has its own function, “product management”
creates misunderstanding in organizations crossing multiple areas, using many different titles.
Product Management. Product management is somewhat more straightforward in
organizations where technology products are developed and sold to customers (e.g., smart
phones, software packages, digital games, etc.). One interviewee, a CTO, was responsible for the
solutions their company commercially sold to other companies. At that organization, the CTO
was responsible for all the technology that was sold, and the CIO was responsible for the
technology used internally. The CTO and their counterpart CIO had clear lines of ownership and
responsibility, although both had their own chief security officers with roles that sometimes
overlapped.
Other organizations have product owners: business partners with counterpart product
managers in the technology group. For example, one CDO said,
Product owners own the strategy, functionality, features, capability, and roadmap for any
one of the products. But the collection of their agendas causes conflicts with resources,
timelines, and pinch points on my team. So, we’re trying to consolidate the group across
all the related business functions to have one product owner group in the business.
Another CIO, who had both product management and product ownership in their remit, said,
“We have product owner and product manager, and that to me the language is flipped
backwards, because the product manager is the one closer to the business.”
Comments in the open-ended survey question echoed uncertainty and confusion about the
product management area: “Project management and product management functions should be
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clearer;” “Product Management will be better served to keep under tech but matrixed into
respective business owners;” and “The big issue in our organization is the never-ending
discussion around where should Product Management report.” Based on interviews and open-
ended responses, product management is clearly an area driving some clarity issues across
technology organizations.
Data and Analytics. Another area impacting the organizational clarity scores in the
study’s quantitative survey is the area of data and analytics. Interviews and comments in the
survey’s open-ended item suggest this area is causing significant confusion and overlap in
organizations (see Table 9). Chief information officer and CAO peers interviewed for this study
both acknowledged they had competing data and analytics departments. Some companies have
chief data officers and CAOs, while others either combine these roles or do not have them.
Because data is the antecedent to analysis, one open-ended response in the survey suggested,
“The CIO or Tech leader should own data, as the systems they develop generate the data.”
Another technology leader wrote about their relationship with the chief data officer in the open-
ended response: “The Chief Data Officer is a peer in the sense that we both report to the Chief
Administrative Officer, but the CDO has no decision authority over data: architecture,
investment, tools or ways of working outside a formal governance process.”
Analytics connotes the interpretation of data and information into insights and operations,
which can be associated more closely with a business function rather than a technical function
(Earley, 2017). Responses to the open-ended survey item suggest data functions be aligned to
technology departments and analytics be associated with apposite business functions:
I think there needs to be more focus on centralization of key platforms and those areas,
like data engineering, where synergies and effectiveness could be improved. At the same
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time, I think there are certain activities, like data science and analytics, that are best to be
federated out to various parts of the business.
According to the findings in this study, much greater clarity is required in the definitions of data
and analytics for an organization, along with the organizational alignment. Clarity is also
required for decision-making rights over data management and analytics platforms.
Budgets and Decision-Making Rights
Although no quantitative survey questions introduced the topic of financial budgets,
without prompt, budgets and funding were a common theme among the technology leaders who
were interviewed. This study is predicated on the Burke-Litwin theoretical model (see Figure 4),
which associates decision-making rights directly with the organizational structure element;
however, the Burke-Litwin model only slightly alludes to budgets as part of its systems and
policies element along with several other areas, including technology, HR practices, and reward
systems (Burke & Litwin, 1992). Burke and Litwin (1992) admitted this category covers a lot of
ground and that attention and deeper investigation of those topics may be required in the systems
and policies element, including budget.
Interviewee comments surrounding budgets included “It’s not just structure. It’s also
financial processes, you know, decision rights.” Another participant said, “Whoever’s got the
money sponsors it to get it done.” An interviewee commented, “Well, we own this, and we own
the wallet, and you can’t do this XYZ thing because we own it, and it’s our responsibility.”
Another participant provided similar sentiments, “I think this is where the processes get
interrelated to financial allocation models and decision rights, and, well, control, right?” The
interview participants collectively underscored the reality that budgets are intrinsically aligned to
organizational structures in the corporate world, and that impacts behaviors and actions.
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Based on the strength and emotion behind the budget theme across interview participants,
expanding on elements of the Burke-Litwin framework, Figure 8 illustrates the implications of
budget association to corporate structures based on the interview analysis findings. The
consequences of budget alignment not only complicate organizational design and decision-
making rights, but they also can lead to perceptions or reality of control. Control and power
struggles can lead to workplace climate issues (Jackson & Schuler, 1985).

Figure 8
Implications of Budget Association to Structure

Research Question 2: To What Extent Does Having Multiple Technology Executive
Leadership Roles Impact Workplace Climate?
After a review of the literature, the researcher hypothesized workplace climate would be
negatively impacted if structure and role clarity were recognized as an area of concern (Bauer,
2003; Hassan, 2013). Results from the quantitative survey support the hypothesis, as shown in
Table 6. The mean for workplace climate in organizations with single ownership is 3.41,
compared to 3.07 in organizations with multiple ownership. Thus, executives in single leadership
organizations (n = 58) perceived better workplace climates in their organizations, when
compared to perceptions of those working in multiple technology leader organizations (n = 56).
While there is a strong correlation between organizational structure and workplace climate, of
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the three research topics examined (i.e., clarity, climate, and performance), climate was the least
negatively affected by multiple technology leadership structures, with a mean differential of
0.34.
Frustration and Conflict
This study endeavored to assess the frustration and conflict that results from structural
and role ambiguity, versus typical levels and causes of strain between functions. Many teams,
whether business- or technology-related, have natural tension points, as recounted by one of the
CAOs interviewed, “There is always a little bit of friction between your data scientists and your
software engineers.” Sometimes team turbulence can be healthy and lead to creative solutions
(Bauer, 2003); however, high levels of role and structure ambiguity have harmful effects on
behaviors and attitudes in the workplace, causing anxiety, frustration, conflict, and loss of
engagement (Hassan, 2013).
Survey participants were asked about their teams’ levels of dissatisfaction with structural
or role ambiguity. Figure 9 shows the results of the survey item that inquired about overt
expressions of frustration related to job overlap, comparing those from single-leader-led
organizations to multiple-leader–led organizations. The mean for this survey item about
frustration in organizations with single leadership is 3.22, compared to 2.50 (scores inverted to
reflect positivity with higher Likert-scale scores) in organizations with multiple leaders. Teams
in single-leadership technology organizations (n = 62) experience significantly less frustration
with job overlap and duplication of effort when compared to those working in multiple
technology leadership organizations (n = 58).
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Interview participants described conditions that create tension and conflict in their teams
about structure and role clarity. One technology leader described two teams with similar
functions:
The IT department has the global data and analytics group that sits in it, which is a
different organization than enterprise data science and data analytics. So, there’s a rift
between these groups. Because it’s like, who’s doing what, you know?
In the open-ended comment section of the survey, a respondent implied conflict at higher levels
in the organization affects the rest of the teams: “There is tension and frustration getting
consensus among leaders, and it’s felt across the teams.” Certain personality types are more
tolerant of role ambiguity than others (Bauer, 2003). Tension and conflict can be exacerbated or
tempered based on individuals’ temperament, especially in situations with unclear structures and
roles.

Figure 9
Level of Teams’ Expression of Frustration over Job Overlap or Duplication of Responsibilities

Note. Respondents who agree or strongly agree (n = 120).
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Personalities and Relationships
In the semi–open-ended questions, interviewees were prompted to explain what makes
their organizational structure work or not work. Interviewees in the manager/subordinate
interviews did not mention personalities and personal relationships as a theme; however, peers
cited personal relationships as a factor several times in the interviews. One leader described their
relationship with a peer leader and how that animosity filters to their teams:
We try to seem like we work together well. We’re not really friends, and I think that’s
what everybody actually sees because there are deep-rooted difficulties with each other
and each other’s jobs. So, individuals on my team have a really hard time with people on
their team.
Another peer-leader interviewee said, “We all have different personalities, different expectations,
and somebody has turf. That’s where the human aspect of it makes things fall apart unless the
structures are defined well.” It was a common belief among interviewees that personalities and
personal relationships can impact workplace climate and performance, but that structure was a
requisite, foundational element. As one CAO articulated, “If you don’t have the right structure it
doesn’t matter. The best personalities can’t make it work, and when you have difficult
personalities in the mix, it just makes it really hard.”
The strength of the relationships between leaders can sometimes be based on personal
associations or can be grounded on functional or process alignment (Bauer, 2003). Figure 10
depicts the self-reported cross-functional relationship strengths reported by technology
executives in the quantitative survey. Relationships were rated quite high with a mean of 3.93 on
a 5-point scale (n = 114).

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Figure 10
Self-Ratings of Technology Executives’ Strength of Relationships with Peers

Note. n = 114. Survey item scale was provided as 6-point Likert scale to avoid central gravitation
selection. Given the low number of respondents using the rating “very poor” rating (0.24%) on
select roles (CHRO and head of supply chain), very poor ratings were combined with poor
ratings on a weighted scale to evaluate equally across roles to create a 3.93 mean across the
population, based on 5-point scale.

Relationship strength with nontechnology executive peers did not vary significantly
between the populations of single leaders versus those from organizations with multiple
technology leaders, as shown in Figure 11. Although references to business alignment were
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made in both quantitative and qualitative feedback, relationships across technology groups,
regardless of technology title and leadership structure, are generally effective with other business
leaders. Relationships with CEOs were among the highest rated across all technology executives.
The relationship with CEOs may be more significant because more than half the respondents
report to the CEO (see Table 3).

Figure 11
Technology Executives’ Relationships with Other Executives

Note. n = 114. Comparison of technology leaders’ (CIOs, CDOs, CAOs, and CTOs) perceptions
of relationships with other C-level executives in their companies (CEOs, COOs, CFOs, chief
supply chain officers, CHROs, chief marketing officers, and heads of sales) of single-leaders of
technology versus organizations with multiple leaders.

CEO Relationship
In interviews, technology leaders often attributed their companies’ progressive and
strategic use of technology to their tech-savvy CEOs (see Figure 6). According to Chun and
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Mooney (2009), organizations where the CEO supports technology as a business driver and
innovative differentiator are more likely to have the CIO report to the CEO. A single technology
leader reporting to the CEO said,
My CEO is tech savvy. They understand enterprise ERP, analytics, and digital platforms.
They’re savvy in those areas to know that they connect really well and integrate with
each other. In addition, they know that if one leader didn’t manage it all, people would be
walking on each other’s toes.
One CIO who reports to their company’s CFO said, “I think the reporting drives a
different perception and message to the organization about investment, innovation, and
technology enablement.” One common theme in the comments from the open-ended section of
the quantitative survey surrounded the importance of the technology leader reporting to the CEO
(see Table 9). Responses from this study align with Krotov’s (2015) recommendation that to
establish credibility, authority, and competitive advantage, the CIO should report to the CEO of
an organization.
Reputation of Information Technology Departments
Misaligned reporting relationships, reputational issues, role ambiguity, and perceived
success of IT delivery plague IT departments (Gerth & Peppard, 2016; Krotov, 2015). Insights
collected from the qualitative interviews aligned with literature review findings and suggest
persistent negative perceptions of IT departments (see Figure 6). Some opinions were strong and
extreme, as a CAO interviewed said, “Well, I didn’t actually think IT should even exist. I think
it’s archaic.” Other comments surrounded the slowness and lack of agility of traditional IT
departments. These comments and perceptions were shared by both leaders from single- and
multiple-leader–led organizations and by leaders holding different technology leader titles.
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A CTO interviewee said,
IT is traditional. It’s slow. It is more focused around risks. IT isn’t agile, you know?
That’s what people on my team would say. We move fast. IT moves at a different clock
speed. They have projects that have been in progress for 5 years.
A CDO who worked in the IT department took responsibility for their company’s marketing
technology from the marketing department. They stated, “There are so many advantages, but
there’s a perception that we’re not being as fast or as agile.” They explained why: “There’s more
security, compliance, and testing for accuracy and consistency than when it was in marketing.
And that just takes longer. Ironically, those were among the reasons it was handed over to digital
IT to begin with.”
A chief digital and technology officer, who was the single leader of technology in their
organization, acknowledged the divide in their team. They said, “We have the cool kids, and we
have the others. We’ve invested more in digital and analytics, and they get more executive and
board exposure.” A CAO, who reported to the IT organization cited the synergies of having one
technology organization: “The information, technology, data and analytics, and security live
more cohesively. So, there’s a lot more cooperation because we all report to the same leader, and
that leader can drive alignment a bit better.” They also provided the downsides of working in the
IT department: “There are days I wish that I didn’t have to work with the IT systems and
processes. I will be honest. It can be a pain.” They explained their team’s sentiments about
working in the IT department: “If you ask my analytics and data science team whether they’d
prefer to be in a larger technology-oriented organization or outside, their preference would be to
be outside.” The damaged reputation of IT departments that sparked the proliferation of
technology leadership roles persists, based on interviewee perspectives.
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The CIO title is commonly associated with the traditional IT organization (Banker et al.,
2011). Based on survey results, CIOs acknowledged the impact of their standing with the other
executives in their organizations. Chief information officers’ perceptions of their relationship
strengths with nontechnology executives are shown in relation to single- and multiple-leader led
technology organizations in Table 11. Nontechnology executives were defined as CEO, COO,
CFO, CHRO, CMO, chief supply chain officer, head of sales, or like titles. Technology leaders
with the CIO title have more vulnerable relationships with their peers than other technology
leaders, regardless of whether they are the single leaders in their organization.

Table 10
CIO Perceptions of Relationship Strength With Nontechnology Executives
Relationship Strength
Rating
CIO
n = 26
Single Leader
n = 58
Multiple Leader
n = 56
Excellent 30.8% 39.4% 38.0%
Very Good 26.9% 36.5% 29.4%
Good 15.4% 15.9% 17.3%
Average 15.4% 6.1% 12.5%
Poor 11.5% 1.8% 2.8%
Note. n = 114. Survey item scale was provided as six-point Likert scale to avoid central
gravitation selection. Given the low number of respondents using the rating very poor rating
(0.24%), very poor ratings were combined with poor ratings on a weighted scale to evaluate
equally across roles. Very poor ratings were provided only by CIO-titled respondents, increasing
the weighted poor rating to 11.5%.

Whether justified or not, perceptions of IT departments cause issues in relationships,
processes, and alignment in organizations. The analysis of quantitative and qualitative study data
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suggests the perceptions of traditional IT departments and the CIO title are challenging and are
likely leading causes behind the creation of multiple-leader–led technology functions in
companies. Regardless of company demographics, technology leaders’ titles, or traditional IT
versus modern IT, research suggests that the organizational structure of single- or multiple-
leader technology organizations impacts organizational climate.
Research Question 3: To What Extent Does Having Multiple Technology Executive
Leadership Roles Impact the Effectiveness of Technology Output?
As investigated in this study’s first two research questions, the impact of organizational
structure on role clarity and workplace climate culminates in technology team performance and
productivity, affecting output. This research question, related to overall effectiveness of
technology output, is significant for companies, as market competitiveness and financial results
are dependent on technology effectiveness. Results from the quantitative survey support that
organizational structure is essential to technology output and that organizations with multiple
leaders are disadvantaged in their efficacy, as shown in Table 6. The mean for technology output
and performance in organizations with single ownership is 2.44 compared to 2.01 in
organizations with multiple owners. Thus, executives in single leadership organizations (n = 58)
report better output from their organizations when compared to those working in multiple
technology leader organizations (n = 56). Qualitative results in survey comments and interviews
also suggested that organizational structure impacts productivity and output. As summarized by a
CTO in their interview, “Structure can definitely sub-optimize output.”
The conceptual framework for this study was developed based on Conway’s (1968) law
overlaid on the transactional factors of the Burke-Litwin model of organizational performance
and change (see Figure 5). Conway’s law suggests an organization’s structure directly correlates
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to the output it produces. Research studies suggest alignment, quality, complexity, speed, cost,
and productivity impairments to output based on the effects of Conway’s law (Colfer & Baldwin,
2010). This study investigated speed-to-market, technology output quality, and product
complexity of single- versus multiple-leader–led technology organizations. In addition, the study
used objective financial data to measure technology deployment and use effectiveness for firms
objectively.
Speed-to-Market
In alignment with comments made by interviewees about the speed and agility of IT
departments (see Figure 6), leaders of multiple-led technology organizations believed the
organization’s structure impeded speed-to-market for technology delivery. Figure 12 displays the
results of the survey item, “The organizational structure of technology function(s) impedes or
delays our speed-to-market in technology delivery.” On the other hand, leaders of singular-led
technology organizations did not believe their structures impeded speed-to-market. The
discrepancy in perception of speed-to-market for technology delivery between the sample
populations would require input from other leaders in the organization to reconcile the
perception differences.
Complexity
Affirming Conway’s (1968) law, Nagappan et al. (2008) asserted organizational structure
is the most reliable predictor of code complexity and other programming characteristics
associated with software output quality. Multiple teams’ ownership of technology strategy and
approach can cause disorder, redundancy, or misalignment in technology introduced to internal
users or external customers (Conway, 1968; Nagappan et al., 2008). Supporting the concept that
multiple technology teams can increase the complexity of solutions, a survey respondent stated
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in the open-ended question, “Digital technology should be combined with back-office
technology so we can be consistent/seamless to the customer and ensure we do not have
redundancy in tech solutions.” Leaders of technology departments with combined functions
assert they have less undue complexity in their solutions. Figure 13 displays the results of the
survey item, “Technology solutions at my company have additional complexity due to the
organization of technology resources.”

Figure 12
Organizational Structure Impediment to Speed-to-Market

Note. n = 111.

Quality
Aligned with Conway’s (1968) law, the empirical research of Cataldo and Herbsleb
(2012) verified cross-functional software development coordination activities have significant
implications on software quality and subsequent failures. The results of this study’s quantitative
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survey, as shown in Figure 14, support the findings of Cataldo and Herbsleb and Conway, as
unified organizations affirm their organizational structures support solution quality and do not
impede it. Organizations with multiple technology leaders acknowledge their organizational
structures adversely affect the quality of their technology output.

Figure 13
Organizational Structure Negative Impact to Solution Complexity

Note. n = 111.

An IT department’s CDO recounted the reasons for assuming responsibility for their
company’s marketing technology from the marketing department:
There were times when the data from the marketing area conflicted with what the
business units were saying. It was just confusing everyone. So, we took it over so we
could ensure consistency and quality of the data and information.
A CAO shared their organization’s issue about data quality:
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We came into existence about 2 years ago as a combined data and analytics team in the
IT organization because data from many of the applications and business processes
weren’t organized. We became a big source of demand for analytics by addressing data,
standards, and data quality challenges.
Cataldo and Herbsleb’s (2012) research reinforced that high levels of structural congruence,
indicative of alignment of organizational structure, are associated with improved quality and
better team productivity.

Figure 14
Organizational Structure Negative Impact to Solution Quality

Note. n = 111.

Impact of Technology Function on Firm Performance
This study used secondary data analysis to augment the quantitative and qualitative
research to apply a strategic, financial, and objective lens to the problem of practice. Return on
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assets was the secondary data analyzed. It is the most commonly used external accounting metric
to evaluate investments, including technology investments, across publicly traded companies
(Tayah et al., 2015). Based on the t-test results, presented in Table 10, the ROA of companies in
this study with a single technology leader is 43% higher than those with multiple top technology
executives. However, since p =.065, the observed p was not less than .05, the difference is not
statistically significant with 95% confidence. Therefore, other factors, such as company size,
industry type, economic trends, and other internal strategic and investment factors, may have
impacted the ROA analysis (Luftman et al., 2017). Notwithstanding the certitude of the ROA
affiliation between single-led and multiple-led technology organizations, the quantitative study
findings, supported by views extrapolated from the qualitative study, suggest multiple-led
technology organizations can negatively impact technology output effectiveness.
Summary
Research findings support the hypotheses that having multiple top technology executives
has an adverse impact on role clarity, workplace climate, and technology output effectiveness. In
the study’s quantitative survey, respondents were split nearly evenly across the two populations
representing single-leader led and multiple-leader led technology organizations, strengthening
the finding’s validity. Results across all three research areas reveal vastly statistically significant
support that technology organizations with single leadership have better clarity of roles and
functions, less conflict impacting the workplace climate, and greater efficiency and quality of
technology output and products.
As the research literature suggests, the trend toward having multiple technology leaders
surfaced when technology shifted toward more digitally enabled platforms, applications, social
media, and advanced analytics. Due to the reputation of traditional CIOs and IT departments,
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CEOs and CHROs opted to create additional technology executive roles. A decade later, the
quantitative research from this study demonstrated multiple-leader technology organizations are
not as effective as those led by single leaders, yet the qualitative analysis indicated the
reputational concerns of traditional IT departments and CIO roles.
Organizational structure, role clarity, and workplace climate culminate in team
productivity, output quality, and technology performance effectiveness for companies.
Technology performance effectiveness is paramount for most companies. Although the impact of
technology leadership structure on corporate ROA was inconclusive in this study, quantitative
and qualitative results sufficiently support that single-leader technology leadership structures
afford companies higher-quality data, information, and solutions.

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CHAPTER FIVE: RECOMMENDATIONS
Companies increasingly rely on the effective development, deployment, and use of their
information technology systems for revenue growth, customer acquisition, profitability, and
competitive advantage (Li & Tan, 2013). In addition to the increase in dependency on
technology, most companies continue to spend more on technology each year (Gartner, 2023).
Therefore, it is essential for corporations to ensure productivity from their technology
organizations to support strategy and execution to respond to changes in a competitive market
(Li & Tan, 2013). Information technology departments have typically been led by the CIO role,
but digital transformation requirements have caused companies to expand their technology
leadership to include additional technology leadership roles, often reporting to different parts of
the organization (Gerth & Peppard, 2016; Singh & Hess, 2020).
The purpose of this study was to learn the extent to which multiple technology leaders in
an organization impact perceived or actual organizational clarity, work-unit climate, and
effectiveness of the technological output created in organizations. The results from the research
questions are intended to assist HR leaders and CEOs in understanding the impacts of having a
single executive or multiple executives responsible for technology and aid them in their decision
making about organizational design for technology teams.
This chapter provides a summary and discussion of findings detailed in Chapter 4,
recommendations for industry CEOs and CHROs for organizational design for their technology
functions, limitations and delimitations of this study, and recommendations for future research
on this topic.

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Discussion of Findings
This study evaluated two populations of technology leaders: those who singularly lead
their organizations and those who share technology leadership responsibility across executives.
The research questions were designed for understanding the two populations’ impacts on their
teams’ job function clarity, workplace climate, and productivity effectiveness. The quantitative
and qualitative findings suggest strong indications across all three elements that single-leadership
organizational structures are more effective than multiple-leadership structures. A binary
summary result statement could be made that technology organizations should be led by a single
leader versus having multiple leaders. This study further delved into the degree of impact and
nuances behind the leadership structure of technology organizations in U.S. public companies.
This study was predicated on the transactional framework of the Burke-Litwin (1992)
organizational performance model, overlayed by Conway’s (1968) law, to depict a conceptual
model to evaluate organizational effectiveness through the lens of multiple leader structures.
Figure 15 shows the high-level research findings in respect to the technology leadership
conceptual framework that defined this study. The following recommendations are derived from
the results of the quantitative and qualitative research studies and align with scholarly literature
on related research topics.
Recommendations for Practice
Findings from this study suggest single leadership provides the best structure for
technology leadership in corporate settings. Based on the research findings and corroborated by
the literature research, recommendations to address this problem of practice include (a)
education of the corporate CEO and CHRO community regarding technology leadership
structure, (b) addressing the reputational issues surrounding CIOs and IT departments that can
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drive the proliferation of technology leadership roles, and (c) industry alignment on obscuring
context and lexicon related to technology organizational structures. All recommendations
reinforce the overarching findings based on the research questions and support the single
leadership model for technology organizations.

Figure 15
Technology Organization Conceptual Framework and Findings Summary

External Environment Factors
CEOs and CHROs need to understand the adverse implications of creating organizations
with overlapping technology leadership roles and that having single-leader technology
organizational structures can address many of the negative implications. CEOs and CHROs must
realize the resources on which they often rely to determine organizational structures are not
incented to provide the best advice to corporate leaders.
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There is a large ecosystem supporting the multiple technology executive structure in
corporations. This ecosystem, including executive search firms, consulting companies, trade
organizations, software solutions providers, and educational institutions, creates the external
environment influence on leadership as depicted in the Burke-Litwin organizational performance
and change model (see Figure 4).
Executive search firms benefit from creating additional executive roles, as they are paid
to fill those roles (Korn Ferry, 2022). For example, one of the major executive search firms,
Spencer Stuart, has six separate and distinct technology practices and profit centers, each with a
partner leading it: (a) a CDO recruiting practice, (b) a CIO recruiting practice, (c) a CTO
practice, (d) chief data officer executive recruiting practice, (e) chief product officer executive
recruiting practice, and (f) a CISO practice (Spencer Stuart, 2023). Higher education institutions
benefit from multiple technology executive roles. For example, the University of California (UC)
– Berkely (2018, 2023a, 2023b), has at least three executive technology leadership tracks,
including executive CIO, CTO, and CDO programs, averaging $28,000 per program per student.
UC – Berkely and other universities offering multiple executive technology leadership programs
benefit from corporations' multi-title and multirole structures. Management consulting firms gain
from complex organizations, as they also have partners in each self-created tower of technology
leadership to optimize their internal revenues and profits (Boston Consulting Group, 2023;
Poulfelt & Olson, 2017).
Researcher Actions
The recommendations resulting from this study, notably CEO and CHRO education,
involve dismantling the messaging and influence behind the external environmental forces
propagating the pervasive multiple executive leadership structures in corporations. The
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researcher plans to publicize study findings and recommendations in media outlets and
conferences that target CEO and CHRO populations. The researcher is an authorized Forbes.com
contributor and will publish results in an article on Forbes.com. The researcher will also submit
articles to the Wall Street Journal, Harvard Business Review, and Fortune Magazine. They will
also propose educational speaking sessions with the Organizational Design Forum (ODF),
Society of Human Resource Management (SHRM), and other organizational and executive
conferences to discuss research findings and recommendations.
Recommendation 1: CEO and CHRO Education
Education for CEOs and CHROs needs to amplify the recommended single-technology
leadership structure, the systematic forces working against their optimal structure, and the factors
that will help their organizations thrive in the single-leader technology leadership structure.
Those factors include clear roles and responsibilities, reporting configuration, technology
leadership support, and technology skills and development.
CEO and CHRO Education on Single-Leader Technology Leadership Structure
The disseminated information targeted to CEOs and CHROs will include study data
confirming the benefits and rationale. This study’s research comparing the populations of single-
leader technology executives with multiple-leader technology executives demonstrated single-
leader organizations have greater clarity, healthier workplace climates, and higher productivity.
All three areas addressed by the research questions showed that single-leader technology
structures have statistically significant better outcomes than multiple-leader technology
structures (see Table 6). For example, leaders of multiple-leader technology organizations are 2.5
times more likely to believe their responsibilities overlap with other executives in the
organization than single-leader executives (see Figure 7). In addition, 50% of leaders of
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multiple-leader technology organizations believe their organizational structures negatively
impact the speed-to-market, technology output quality, and solution complexity versus 24% of
leaders of single-leader technology organizations.
This study built on the findings of previous research on the proliferation of technology
leadership. As Paré et al. (2020) suggested, a concentrated strategic orientation of technology
management leads to more significant IT contribution to organizational performance. In their
study of 750 CDOs, Berman et al. (2020) learned the optimal reporting structure correlated to
outperformance was for the CDO, chief innovation officer, and chief data officer to report to the
CIO in a single technology unit. Competition among technology leader peers can lead to
unhealthy outcomes (Berman et al., 2020). Data from previous studies, findings from this study,
and graphic models, such as those depicted in Figure 16, demonstrate how the single-leader
technology structure can result in less complexity, reduced costs, and greater clarity in
organizations. Findings suggested multiple leadership models in technology organizations lead to
overlap, conflict, and performance issues. Figure 16 depicts the removal of the overlapping
technology leadership roles, paving the way for more direct connectivity and collaboration with
executive business leaders, which should be bound together with trust, empathy, and
communication (Liu et al., 2023).
CEOs and CHROs should first introspectively consider their existing technology
leadership structure. They should consider whether they were influenced by external
environmental influences, the strength of their technology leadership, and why they have their
current structure. Figure 17 provides a consideration and decision framework to assist CEOs and
CHROs in their high-level assessments of potential existing multiple leadership structures. After
learning the implications of the multiple leadership model, the external factors influencing it, and
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the benefits for single leadership, this framework can help CEOs and CHROs rethink their
organizations toward a more optimized model led by one technology executive leader.

Figure 16
Replacement of Overlapping Technology Leadership Roles

Note. Blue circles signify technology leadership roles and green circles signify business
leadership roles. Titles listed with an asterisk are example titles only. Additional studies are
required to recommend executive titles.
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Figure 17
Decision Framework for Executive Technology Leadership Structure

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Clear Roles and Responsibilities
Leaders’ and employees’ responsibilities need to be clear and well defined for desired
work satisfaction, effectiveness, and performance objectives (Hassan, 2013; Lyons, 1971). The
current study analyzed whether the organizational structure impacted role clarity, workplace
climate, and performance effectiveness. While the study’s findings revealed the organizational
structure of the top leadership executives impacted clarity, climate, and performance, the
findings also indicated clear and specific role definitions could positively impact overall
effectiveness. In the study, 90% of technology executives at single-leadership firms felt there is
clear ownership of technology responsibilities at their companies, compared to 52% at multiple-
leadership firms. This study’s findings align with literature on role ambiguity. According to
Jackson and Schuler (1985) and Tubre and Collins (2000), there is a strong correlation between
role ambiguity and job performance.
When Gerth and Peppard (2016) compared the job descriptions of CDOs and CIOs at
various companies in their studies, they noted the similarities in the roles and responsibilities.
Whether comparing multiple technology leader roles, regional or business unit alignment,
product management responsibilities, or analytics jobs and responsibilities, CEOs and CHROs
should ensure job descriptions do not have overlapping responsibilities. Well-defined job profiles
and descriptions reflect the company's strategic needs and help differentiate the experience and
responsibility demands of each role and layer in an organization (Kesler & Kates, 2010). In
addition to assessing the leadership structure, CHROs can take the actionable step of reviewing
job descriptions for responsibility overlap across executives that may have technology
management responsibilities.
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Recommendation 2: CIO and IT Department Reputation Overhaul
As literature and research findings suggest, persistent negative perceptions of IT
departments plague technology leaders and often lead to the proliferation of technology
leadership (Gerth & Peppard, 2016; Gonzalez & Ashworth, 2021). Findings in this study suggest
CIOs and IT departments’ perceptions and reputational issues remain existent (see Figure 6). The
negative perception of CIOs or top technology leaders and IT departments must be addressed to
ensure the single-leader organization can be positioned for success. There are three suggestions
to address the reputational issues of CIOs and IT departments: (a) title and department naming
conventions, (b) CEO support and reporting structure, and (c) technology-leadership
characteristics and persona.
Title and Department Naming Convention
This study intended to assess the organizational structure and not necessarily the titles
associated with technology leadership; however, this study’s findings suggest IT and CIO have
negative connotations and are related to a lack of agility, focusing on risk rather than innovation,
slowness, and antiquation (see Figure 6). Further, the quantitative survey results showed those
technology leaders with the title CIO had significantly fewer positive relationships with
nontechnology executive leaders than technology leaders with different titles (see Table 11).
Renaming the CIO or top single technology leader and the IT department, while
seemingly superficial, could address a meaningful perception issue. Some organizations have
modernized their CHRO title to chief people officer to reflect the changes required in the HR
field, including talent management, diversity and inclusion, and board-level connections (SHRM,
2020). To reflect the elevated and evolved nature of the technology leadership role, the CIO title
has often been replaced by differing hybrid titles like chief digital and technology officer or chief
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Information and digital officer (Hopkins & Rickards, 2020). Likewise, IT departments can be
renamed technology department or technology enablement department. Relabeling or rebranding
these titles and functions could help enable a perception of this function as more transformative,
innovative, and growth driven rather than a cost-center or risk-management function (Gonzalez
& Ashworth, 2021).
CEO Support and Reporting Structure
A noteworthy theme from the qualitative portion of this study was that CEO support and
alignment for technology and innovation helped drive technology organization success.
Technology leaders cited supportive, tech-savvy CEOs as a key success factor in their companies
(see Figure 6). Organizations where the CEO supports technology as a business driver and
innovative differentiator are more likely to have the CIO report to the CEO and typically achieve
better business results (Chun & Mooney, 2009); however, many CEOs lack involvement and
participation in technology strategies for their firms. Over 50% of CEOs come from financial or
marketing backgrounds and lack the expertise or understanding of how technology should be
used in their organizations (Krotov, 2015). Closing the CEO-CIO gap involves having a shared
vision for technology, creating a culture of technology adoption, and establishing the correct
reporting structure of the CIO (Krotov, 2015).
CIOs or top technology leaders who report to CEOs have the formal power to develop
business technology strategies aligned with top management. In contrast, CIOs who report to
CFOs or other executives may have less formal power and remain in more technology-centric
statuses in their organizations (Carter et al., 2011). Business value creation and firm performance
result from the alignment of the CEO and CIO and business and IT alignment (Luftman &
Kempaiah, 2007). This study’s insights corroborate the findings of previous research and
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literature for the recommendation that CEOs participate and support the structure of technology
organizations, the selection of technology leadership, the strategy of firm technology and
innovation strategy, and provide company-wide advocacy for technology advancement and
adoption (Hiller, 2021; Luftman & Kempaiah, 2007). While over 50% of CIOs and top
technology report to CEOs, a large percentage still report to other executives (Kark et al., 2018).
CEO alignment, support, and reporting are recommended based on the findings and literature
review and this study.
Technology Leader Characteristics and Persona
Executive-leadership and technology-leadership requirements have transformed in
response to business, societal, and technological changes affecting corporations. Given the
recommendation for single top technology leadership, CEOs, CHROs, and boards of directors
must ensure they recruit and retain the right technology leadership to assume all aspects of
technology leadership. If there is a single technology leader, that leader must possess the
experience necessary to lead all facets of the technology portfolio. In addition, leaders need the
leadership and collaboration skills required to drive organizational change and transformation
(Liu et al., 2023). Given the traditional CIO challenges in collaborating with other executives, as
self-reported in this study (see Table 11), communication, influencing, and collaboration skills
need to be present in technology executives.
While this study did not seek to develop the characteristics or persona of a successful
single-leader technology executive, a recent research study by Hillebrand and Westner (2022)
detailed nine critical success factors (CSFs) that can serve as an initial framework for CEOs and
CHROs as they consider their top technology leaders. These CSFs should be augmented by the
needs of each specific company or organization and assess the skills required to be a single
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technology leader, such as data-driven leadership (Gonzalez & Ashworth, 2021). The CSFs
specified by Hillebrand and Westner align with several of the recommendations and findings
from this study, including nuanced perspectives from the study’s interviewees. For example,
study participants discussed the perceptual, skillset, and alignment challenges within the
technology department, referencing the analytics and digital teams as “cool kids” in their groups,
versus the rest of the team, which is more traditional IT. This nuance is addressed in the fourth
CSF enumerated by Hillebrand and Westner: encouraging cross-functional integration of the
technology department. Other CSFs regarding the technology department’s reporting structure
and positioning also align with this study’s findings and recommendations. The CSFs for top
technology leaders, according to Hillebrand and Westner, are
• Anticipating the future through visionary thinking
• Being perseverant in pursuing the company’s long-term goals
• Accepting and embracing change
• Cross-functional involvement and integration of the IT organization
• Being a well-connected and communicative business leader
• Having empathy to deal with uncertainty felt by co-workers
• Positioning and restructuring of the technology organization
• Ability to develop and use a skilled workforce
• Reporting to the CEO
Recommendation 3: Lexicon and Context Alignment
The study suggests single-leader technology organizations yield better clarity, climate,
and productive output. These findings align with previous research studies, yet debates about
technology organization structure and leadership ensue (Paré et al., 2020). Widely used concepts
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and terminology cause confusion and ambiguity that impact the proliferation of technology
leadership and organizations. This study identified five concepts that, if contextualized more
clearly, could provide simplicity and clarity, and assist companies in understanding and adopting
the single-leadership model: (a) technology department boundaries, (b) digital meaning, (c)
approach to analytics, (d) corporate data management, and (e) technology product management.
While additional research could prove helpful, many of these concepts have been debated for
decades and will likely continue to be discussed (Peppard, 2018). The recommendations herein
are not an attempt to exhaustively describe these concepts; they are suggestions for considering
and delineating the concepts for application to the organizational structure of a single-led
technology function. The researcher will include these concept characterizations in the white
papers, articles, and speaking engagements on the findings of this research.
Technology Department Boundaries
According to Peppard (2018), there is no unambiguous description of what a technology
department is. This research study assessed several elements related to how a technology
department should be structured and described the challenges of creating an ideal structure. This
study has primarily described what a technology department should be, based on the
recommended structure for one leader to hold responsibilities for all technology areas. The
demographic data from the study’s survey instrument suggests singly led technology functions
hold responsibility for most technical domains, as shown in Table 12. The recommendation is to
minimize the ambiguity of what a technology department entails by having it be a single
organization encompassing all related domains. If organizations adopt the single-leader
technology model, review outstanding overlap across functions, and review roles and
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responsibilities clearly, the percentages shown in Table 12 should rise to close to 100% across
domains, except product management, discussed in the following.

Table 11
Responsibility by Technology Domain for Single-Leader Led Technology Departments
Technology domain % of remit for single technology
leaders
Analytics/data science 96%
Application management and development 100%
Business intelligence / reporting 96%
Data management and data engineering 99%
Digital/web/e-commerce technology 93%
Enterprise resource planning systems (ERP) 96%
Human resource management information systems 84%
Infrastructure 97%
Marketing technology 88%
Sales technology 87%
Technology products that my company sells* 58%

Note. n = 64. *Technology products that my company sells is discussed under product
management

Digital Meaning and Primary Title
The terms digital, digitization, digitalization, and digital transformation have many
meanings, often conflicting or ambiguous (Gong & Ribiere, 2021; Haffke et al., 2016).
Academics’ and executive recruiters’ efforts to define CDO roles to differentiate the role from
other executive leadership roles have been unable to avoid overlap (Haffke et al., 2016; Singh &
Hess, 2020). According to the Gartner (2023) information technology glossary, digital is
the representation of physical items or activities through binary code. When used as an
adjective, it describes the dominant use of the latest digital technologies to improve
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organizational processes, improve interactions between people, organizations, and things,
or make new business models possible. (para. 1)
Although the concept and definition of digital transformation is highly contested, Gartner’s
(2023) definition aligns more with digital transformations than it does with how the term is used
to describe organization structure. One CIO interviewee described digital in their business as
their e-commerce technology. Another CTO described their use of digital as customer-facing
technology. While further studies can help determine the titling of technology leadership, the
researcher recommends refraining from using the term digital as a primary expression in titles or
organizational units to avoid the confusion associated with the term. Given the ambiguity of the
role and the questions about its effectiveness, some academics and practitioners have suggested
the temporariness of the CDO role and submit the position will disappear over time (Kessel &
Graf-Vlachy, 2021). Based on views expressed in this study and predictions about its viability,
enterprises have reached the time to cease using the term digital as a primary title to provide
clarity in organizations.
Analytics Structure and Approach
All companies represented in the qualitative study were in varying stages of maturity in
relation to analytics and data science; however, a common theme surfaced to create enterprise
platforms and tools and facilitate users’ and business departments’ analysis efforts. The words
democratized and federated were used consistently in survey participants’ comments (see Table
9) and among study interviewees. Many expert practitioners and academics agree with
democratizing analytics, data science, and artificial intelligence (AI; Watson et al., 2021;
Wiseman, 2017). According to Watson et al. (2021), AI will have a presence in the C-suite, not
physically but indirectly, through senior leaders’ adoption of the power of analytics.
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Given the changing landscape of AI with the rapid adoption of generative AI, high-
skilled work efforts will be significantly impacted by new generative AI technologies
(Brynjolfsson & Raymond, 2023). The broad applications of AI and analytics will likely cause
more confusion if there are additional siloes. One CIO who discussed a separate analytics
organization said, “As you might imagine, it’s caused some confusion in the organization, and
titles also impact things.” Based on the changing environment that will directly impact workers
broadly, the expert views on analytics and AI democratization, and results from this study (see
Table 9 and Figure 6), the recommendation is to avoid the creation of a separate analytics
function that sits between business departments and the technology function. This guidance
supports the recommendation to align all technology functions into a singly led technology
department. Separate analytics and CAO functions are not necessarily viewed as technology
functions but as quasitechnology and quasibusiness departments (Koh et al., 2021); however,
democratizing analytics capabilities, leveraging AI for productivity broadly across the
organization, and creating data insights by functional area negates the need for the separate
quasibusiness, quasitechnical analytics function. Democratized business users can be supported
by data engineering, platform support, and technical analytics expertise from the technology
function. Exceptions to this recommendation apply to data and analytics functions supporting
products sold by a company, as detailed in the Product Management section.
Data Management and Engineering
While analysis and analytics may be better positioned in functional business areas
supported by the technology function, data management and engineering should be under the
direction and leadership of the technology leader. Based on the demographics and findings in
this study, data management, and data engineering are typically managed by the technology
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department (see Table 12). According to their study of 2,700 data science-related roles, De
Mauro et al. (2018) asserted data engineers and developers need to be technology focused and
aligned with systems and applications functions, as shown in Figure 18. While there is less
debate over data management in companies, ensuring the difference between the treatment of
analytics and data should be helpful for organizations evolving to a single-leader technology
model and provide clarity for the areas or domains that should be included in the technology
organization.

Figure 18
Big Data Skills and Job Families

Note. Based on four-stage analysis of more than 2,700 data science job descriptions, De Mauro et
al. (2018) categorized roles skill set groups into four job families depicted in an Alluvial
diagram. From “Human Resources for Big Data Professions: A Systematic Classification of Job
Roles and Required Skill Sets” by A. De Mauro, M. Greco, M. Grimaldi, and P. Ritala, 2018,
Information Processing & Management, 54(5), 807–817.
[https://doi.org/10.1016/j.ipm.2017.05.004].
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Product Management
The Chief Product Officer (CPO) role is less common, causing less disruption in the C-
suite; however, the product management function remains highly contested based on this
research study. The CPO was classically known as the CTO in the early Silicon Valley days
(Adler & Ferdows, 1990). Product management entails the lifecycle of any combination of
software, hardware, or services (Ebert & Brinkkemper, 2014; Gartner, 2023). Product
management was primarily intended to serve external customers (Ebert & Brinkkemper, 2014;
Gartner, 2023). In recent years, technology organizations have also applied the product
management model, from strategy to development to marketing, to any internal or external
capabilities (Gartner, 2023). The internal and external dichotomy is the source of much of the
ambiguity and confusion surrounding product management in organizations.
A CTO interviewed in this study held the classic responsibilities for customer-facing
technology, while the CIO was responsible for all internal technology. This organization seemed
to have clarity surrounding product management—it was led by the CTO, who managed all
products that were sold as part of a profit-and-loss business segment. Online customer portals
and cloud technology management were negotiated areas, but all else was delineated by
“customer-facing-for-a-profit” versus “noncustomer-facing” or “sales-enabling.”
If companies assume the same stance as this subject company, which also aligns with the
traditional view of product management, it will drive clarity about product management in their
organizations. Technology or data services marketed outside the company is product
management, led by a CPO (or a similar title) and technology used internally would be managed
under the moniker and leadership of the single-technology leader.
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Recommendations Summary
These recommendations are intended to provide companies, specifically CEOs and
CHROs making decisions about technology leadership, data to make informed decisions. The
first recommendation starts with the overarching findings of this study—that single leader–led
technology organizations are suggested over multiple-leader models for improved clarity,
climate, and performance. The remainder of the recommendations are intended to facilitate and
support single-leader-led technology organizations. Table 13 summarizes the recommendations
from this research study.
Limitations and Delimitations
The proposed methodologies and protocols for this study have been designed to provide
insights into the impact of technology executive proliferation on role clarity, workplace climate,
and team performance or output. Within these methodologies and protocols, limitations and
delimitations exist. Limitations could include the truthfulness of respondents, specifically during
the interviews (Labaree, 2022). Interview respondents may have selective memory, recall
specific situations or incidents more vividly than others, or may attribute events or circumstances
to factors based on personal agency versus external factors (Labaree, 2022).
Delimitations are factors that limit the scope and boundaries of the study (Labaree, 2022).
Although they may face similar technology leadership proliferation decisions, certain
organization types were excluded from the scope of this study. Private, government, nonprofit,
and educational institutions have been excluded from this study. These institutions have been
excluded because governance, funding, and technology strategies in private, government,
nonprofit, and educational institutions can differ significantly from publicly traded companies
(Huang & Karthikeyan, 2015; Laporte et al., 2018). Non-U.S. companies and U.S. publicly
96

traded U.S. firms with annual revenues of less than $2 billion have also been excluded from this
study. Because smaller companies may not have large IT departments or have the need or
funding to support multiple technology leaders, these firms may not face technology role
proliferation situations or decisions. These exclusions ensured a consistent target population to
ensure the validity and reliability of the findings. Although excluded from this research,
nonpublicly traded firms and global firms facing technology leadership proliferation issues or
decisions may apply the results of this study to their technology organizations. Another
delimitation in this study was the exclusion of the CISO in the examination of the proliferation of
executive technology leadership roles. While most CISOs report to CIOs, there is still debate
over governance, reporting and organizational structure of this role (Shayo & Lin, 2019). The
CISO role was excluded from this study because of the reasons and deliberation for separate
reporting typically surround the governing division of responsibilities and potential legal
considerations (Shayo & Lin, 2019).
Recommendations for Future Research
This study has limitations that can serve as avenues for future research. The results of this
study indicate technology functions should have a single leader. While these results were
statistically significant, they were based upon the perceptions, opinions, and experiences of
technology leaders during a limited time over the course of this study. In addition, the secondary
data analysis provided inconclusive results regarding the impact of technology effectiveness on
corporate ROA. Future research could include longitudinal comparative studies of multiple
organizations with single-versus multiple-leader-led technology organizations. Analysis could be
performed with actual workplace climate results, financial analysis, and technology productivity
97

measurements. This research could include private, government, nonprofit, or educational
institutions, which were excluded from this study.
Second, this study’s focus was on structure, not specifically on titles; however, titles are a
critical factor in establishing technology leadership structures. First, the title of the single leader
of technology departments needs to be established. The CIO title has an embattled history and
continues to harbor a negative connotation. Based on the recommendations in this study, the
CDO title should be dissolved. Validation for the worthiest and most appropriate title for the
single leader for technology organizations remains unanswered. In addition to the technology
leadership title, the leader for technology that a company sells, which may be CPO or CTO, also
needs to be resolved.
Related to the topic of titles, future research should also include an understanding of why
the proliferation of c-suite titles occurs within the technology area and beyond. Have
organizations and roles become so complex that a multitude of executives are required when one
used to suffice? Is this trend connected to self-efficacy, ego, or entitlement issues toward the
attainment of c-suite titles? Is the impact of external entities like consulting firms or executive
search firms, as suggested by this study, so influential that organizations succumb to the
demands of external entities? Understanding the cognitive and noncognitive factors behind the
desire and proliferation of C-level titles would prove helpful for planning organizational
structures, hierarchies, roles, and titles across industries.
Table 12
Recommendation Summary
Recommendation Topic Action Research
Question
1 CEO & CHRO
education
Single-leadership
model
Understand variances of single- vs.
multiple-leader models
1 and 3
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Assess organization for single-
leadership potential
Clear roles and
responsibilities
Develop clear roles and
responsibilities for each role
Compare job descriptions to ensure
overlap is minimized
1
2 CIO & IT
department
reputation
overhaul
Leader and
department
naming
conventions
Rename single leader led department
from IT, not digital
2
CEO reporting
and support
Single-technology leader should
report to CEO
CEO needs to provide support for
technology leader and function
2
Technology
leadership
characteristics
Must possess communication,
leadership, and emotional skills
Must possess technical skills across
domain to effectively lead
2 and 3
3 Lexicon &
content
alignment
Technology
development
boundaries
Single leader led should largely
define function
Domains will define next level, all
inclusive, not product management
1
Digital meaning
and primary title
Refrain from using digital for title or
function
Single leader responsible for previous
“digital” technology
1
Analytics
structure and
approach
Democratized and federated model
for analytics
Center-led platforms and core
expertise in technology function
1
Data management Led by technology function 1
Product
management
Products sold or marketed to
customers managed by separate
commercial organization
Technology function supports
commercial product team for shared
technology (e.g., cloud)
1 and 3

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Conclusion
This research study highlights the detrimental consequences of the proliferation of
technology-leadership roles in corporations. The widespread, tentacled organizational model is
fueled by self-serving consultancies, executive search firms, industry trade organizations, and
institutions, which promote multiple technology leaders in organizations. The ecosystem is
robust, with its constituents profiting tremendously by marketing to each proliferated “CXO”
technology leader group and exploiting the latest business or societal trends, such as AI,
customer-centricity, metaverse, or omnichannel; however, this research strongly challenges this
flawed approach to organizational structure.
The findings of this study expose the negative impact on leaders and employees due to
role ambiguity, conflicts, and reduced productivity within technology departments led by
multiple leaders. This unique research examined populations led by single technology leaders
versus those with multiple leaders. Leaders of both types of organizations provided impartial
feedback in quantitative and qualitative surveys. The results are both significant and
illuminating, providing CEOs with invaluable insights into structuring their technology
departments.
Addressing the continually mounting complexity of today’s business environment,
particularly in the technology function, by simply adding new departments or functions
complicates the organizational structure and exacerbates misalignment (Galbraith, 2014). The
recommendations presented as part of this study include actionable suggestions for aligning
functional domains, including digital technology, data, analytics, and product management
within a technology department, aligning to a single-leader model.
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This study’s discerning research serves as a wake-up call to corporations regarding the
negative consequences of role proliferation in technology executive leadership. It challenges the
ephemeral, profit-driven forces perpetuating this flawed model and calls for a reevaluation of
organizational structures. By heeding these findings and adopting a more focused and cohesive
approach, corporations can harness the true potential of their technology departments and thrive
in the dynamic business landscape.

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116

Appendix A
Survey Instrument
Tech Leadership Role Research Study

Start of Block: Introduction

Intro THE STUDY & RESEARCHER
Janet Sherlock is a doctoral candidate at the University of Southern California Organizational
Change & Leadership program. She invites you to participate in her study “The Organizational
Impacts of Executive Technology Leadership Role Proliferation.”

WHAT IS THE PURPOSE OF THIS STUDY?
This study intends to help leaders understand the impact on organizational and role clarity,
workplace climate, and technology output effectiveness based on the number and complexity of
the top leadership roles and their reporting structures.

YOU ARE INVITED TO COMPLETE THIS SURVEY IF: You are a top-level executive leader
of technology, holding titles of Chief Information Officer, Chief Digital Officer, Chief Technology
Officer, Chief Analytics Officer, combination titles (e.g., CIDO, CDTO, etc.), or the equivalent
(e.g., “head of” title) You work for a publicly traded (NYSE or NASDAQ) company that had
greater than $2B annual revenue in the company’s last 12 months You have been
employed at your company for a year or more and in your current role for greater than 6 months
ESTIMATED COMPLETION TIME
This survey should take approximately 10 – 15 minutes to complete.

CONFIDENTIALITY
Any information you provide in this study that could identify you such as your name, email, or
other information will be kept completely confidential. In any written reports or publications, no
one will be able to identify you or your organization.

ADDITIONAL RESPONSE REQUEST
If you have peers or subordinate technology colleagues in your organization holding CIO, CTO,
CDO, CIDO or equivalent (e.g. "head of" title), we invite them to complete this survey, as well.
Please forward the link to them or provide Janet Sherlock (jsherloc@usc.edu) their email
address.

End of Block: Introduction

117

Q1 What is your company's industry?
o Automotive / Automobiles and Components (1)
o Banking / Financial Services (2)
o Commercial and Professional Services (3)
o Consumer Goods (4)
o Hospitality (5)
o Health Care / Health Care Equipment or Services (6)
o Insurance (7)
o Media and Entertainment (8)
o Pharmaceuticals, Biotechnology & Life Sciences (9)
o Real Estate (10)
o Retail / Wholesale Sales or Distribution (11)
o Technology Hardware, Software or Services (12)
o Telecommunication Services (13)
o Transportation (14)
o Utilities (15)
o Other - Please enter (16) __________________________________________________

118

Q2 What is your company's NYSE or NASDAQ stock trading symbol?

________________________________________________________________

Q3 How long have you been employed by your organization
o Less than 1 year (1)
o 1 year - 4 years (2)
o 5 years - 10 years (3)
o Greater than 10 years (4)

Skip To: End of Survey If How long have you been employed by your organization = Less than 1 year

Q4 How long have you been in your current role?
o Less than 6 months (1)
o 6 months to 4 years (2)
o 5 years to 10 years (3)
o Greater than 10 years (4)

Skip To: End of Survey If How long have you been in your current role? = Less than 6 months

119

Q5 What is your current title? (If your title is "Head of" or other top executive title, select closest
commonly known C-level title for your role)
o Chief Information Officer (1)
o Chief Technology Officer (2)
o Chief Digital Officer (3)
o Combination title (CIDO, CDTO, CTIO, etc.) (4)
o Chief Data Officer, Chief Analytics Officer or combination title related to data/analytics
(e.g., CDAO) (5)
o Other - Please enter (6) __________________________________________________

120

Q6 Please indicate the technologies for which you are responsible.

▢ Infrastructure (10)
▢ Security (11)
▢ Application Management & Development (12)
▢ Enterprise Resource Planning Systems (ERP) (13)
▢ Human Resource Management Information Systems (14)
▢ Sales Technology (15)
▢ Marketing Technology (16)
▢ Digital / Web / Ecommerce (17)
▢ Data Management & Engineering (18)
▢ Analytics / Data Science (19)
▢ Business Intelligence / Reporting (20)
▢ Technology products that my company sells (21)
▢ Other - please indicate (22)
__________________________________________________

121

Q7 In addition to your top technology leadership role, the following roles exists in my company
as PEERS. (if the title is "Head of" or other top executive title, select the closest commonly
known C-level title for the role)
▢ Not Applicable - I hold the only top technology leadership role in my organization
(6)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Information Officer
▢ Chief Information Officer (1)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Technology Officer
▢ Chief Technology Officer (2)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Digital Officer
▢ Chief Digital Officer (3)
▢ Combination Title (CIDO, CDTO, CTIO, etc.) (4)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Data Officer, Chief Analytics Officer or combination title related to data/analytics (e.g., CDAO)
▢ Chief Data Officer, Chief Analytics Officer, or combination title related to
data/analytics (e.g., CDAO) (5)
▢ Other - please indicate (7)
__________________________________________________

122

Q8 The following roles exists in my company as SUBORDINATE roles that report into me. (if the
title is "Head of" or other top executive title, select the closest commonly known C-level title for
the role)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Information Officer
▢ Chief Information Officer - Global or Enterprise (1)
▢ Chief Information Officer(s) - Divisional or Regional (8)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Technology Officer
▢ Chief Technology Officer - Global or Enterprise (2)
▢ Chief Technology Officer - Divisional or Regional (9)
Display This Choice:
If What is your current title? (If your title is "Head of" or other top executive title, select clos... != Chief
Digital Officer
▢ Chief Digital Officer - Global or Enterprise (3)
▢ Chief Digital Officer - Divisional or Regional (10)
▢ Combination Title (CIDO, CDTO, CTIO, etc.) (4)
▢ Chief Data Officer, Chief Analytics Officer, or combination title related to
data/analytics (e.g., CDAO) (5)
▢ Other - please indicate (7)
__________________________________________________

123

Q9 Who do you report to?
o Chief Executive Officer (1)
o Chief Information Officer (2)
o Chief Technology Officer (3)
o Chief Operating Officer (4)
o Chief Marketing Officer (5)
o Chief Financial Officer (6)
o Other - Please enter (7) __________________________________________________

End of Block: Demographic Information

Start of Block: Personal Role Clarity Questions

Q10 I am clear about my responsibilities for technology management.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

124

Q11 I have the necessary ownership of the technology platforms within my responsibility.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q12 I know exactly how much authority I have in my role.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

125

Q13 I believe there are other executives with responsibilities that should be in my jurisdiction of
technology leadership.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q14 There is overlap of my responsibilities for technology leadership and another executive in
the organization.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Display This Question:
If In addition to your top technology leadership role, the following roles exists in my company as P...
!= Not Applicable - I hold the only top technology leadership role in my organization

126

Q15 Having multiple top executive leaders for different aspects of technology leadership is
helpful at my company.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)
o Not Applicable - there is a single top executive leadership role at my company (6)

End of Block: Personal Role Clarity Questions

Start of Block: Team and Organizational Clarity Questions
Display This Question:
If In addition to your top technology leadership role, the following roles exists in my company as P...
!= Not Applicable - I hold the only top technology leadership role in my organization

Q16 Other technology teams operate differently than my group.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

127

Q17 Members of my team have expressed frustration regarding overlap or duplication of
responsibilities with other teams in the organization.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q18 My team is aligned to a common technology strategy.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Display This Question:
If In addition to your top technology leadership role, the following roles exists in my company as P...
!= Not Applicable - I hold the only top technology leadership role in my organization

128

Q19 Teams across the organization are aligned to a common technology strategy.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q20 The processes used across teams to deliver technology projects at my company are
effective.
o Strongly agree (6)
o Agree (7)
o Neither agree nor disagree (8)
o Disagree (9)
o Strongly disagree (10)

129

Q21 There is clarity on technology ownership at my company.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

End of Block: Team and Organizational Clarity Questions

Start of Block: Work Relationships and Climate Questions

Q22 My business partners understand who is responsible for the different areas of technology
management at my company.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

130

Q23 The workplace climate of my direct organization is positive.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly Disagree (5)

Q24 Increased clarity of responsibilities across departments would improve the workplace
climate of my direct organization.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly Disagree (5)

131

Q25 The communication across my team and other teams in the organization is effective.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

132

Q26 What is the strength of the following relationships with you? (If combination title like "Chief
Marketing & Digital Officer", choose closest single title selection)

Excellent
(1)
Very
Good
(2)
Good
(3)
Average
(4)
Poor
(5)
Very
Poor
(6)
Not
Applicable
in My Org
(7)
Self
(8)
Chief
Executive
Officer (1)
o o o o o o o o
Chief
Financial
Officer (2)
o o o o o o o o
Chief
Operating
Officer (3)
o o o o o o o o
Chief
Human
Resource
Officer (4)
o o o o o o o o
Chief
Marketing
Officer (5)
o o o o o o o o
Head of
Sales (6) o o o o o o o o
Head of
Supply
Chain (7)
o o o o o o o o
Chief
Information
Officer (8)
o o o o o o o o
Chief
Technology
Officer (9)
o o o o o o o o
Chief
Digital
Officer (10)
o o o o o o o o
Chief
Analytics /
Data
Officer (11)
o o o o o o o o

End of Block: Work Relationships and Climate Questions
133

Start of Block: Performance & Output Questions

Q27 My team is known for its high-quality work.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q28 The organizational structure of technology function(s) inhibits the quality of technology
being deployed to users or customers.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

134

Q29 The organizational structure of technology function(s) impedes or delays our speed-to-
market in technology delivery.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q30 My team is productive.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

135

Q31 My team’s productivity could be improved with better clarity of responsibilities across
departments.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q32 Technology solutions at my company have additional complexity due to the organization of
technology resources.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

136

Q33 Technology solutions at my company have additional complexity due to the organization of
business teams.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

End of Block: Performance & Output Questions

Start of Block: General Questions on Organization Structure of Technology Function

Q34 The organization structure of the technology function(s) in my company is effective.
o Strongly agree (1)
o Agree (2)
o Neither agree nor disagree (3)
o Disagree (4)
o Strongly disagree (5)

Q35 Please describe how you might change or reorganize the structure of top technology
leadership in your company, given the option.
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________
________________________________________________________________

End of Block: General Questions on Organization Structure of Technology Function

Start of Block: Validation & Follow Up
137

Q36 Please enter your email address.

Email address is requested to ensure there are no duplicate responses to this survey and for
follow up purposes only. Your identity is confidential.

________________________________________________________________

Q37 Would you be willing to participate in a 45-minute follow up interview to this survey?
o Yes (1)
o No (2)

End of Block: Validation & Follow Up

138

Appendix B
Qualitative Interview Question Protocol
1. How would you describe your role?
2. How are the top leadership roles’ areas structured?
a. Digital
b. Analytics
c. Product Management
3. How would you describe the level of teamwork and cooperation across technology
teams?
4. Given the structure, what processes are used to align teams, initiatives, and efforts?
5. How would you describe the communications across technology teams?
6. How do you believe the structure impacts the output/product from your companies’
technology departments?
7. How would your business partners rate the effectiveness of technology delivery?
8. Describe how technology strategy is developed in the organization.
9. What makes things work/not work? (Personality, communications, culture)?
10. How do team members feel about the structure and the impact it has on their work?
11. How would you structure?
12. Anything else you’d like to share?

139

Appendix C
Secondary Data Collection Protocol
Technology Leadership Role Proliferation Study

Description:
The specific financial metric that will be extracted for this study will be Return on Assets (ROA). ROA
reflects a company's effective use of its assets to produce income, including financial investments and
technology investments.
ROA = (net profit before interest and tax / total assets) X 100
While ROA can vary by industry, it is one of the most commonly used accounting metrics to evaluate
technology investment and effectiveness across firms and industries.
Data:
• One secondary data element will be analyzed: Return on Assets (ROA) on a twelve-month
trailing basis (TTM). ROA = (net profit before interest and tax / total assets) X 100
o Using TTM will provide a more uniform comparison across companies than fiscal years,
especially in more volatile periods
• RoA will be extracted for the companies represented by the participants of the study
o All U.S.-based firms
o Publicly traded on the New York Stock Exchange (NYSE) or the National Association of
Securities Dealers Automated Quotations (NASDAQ).
• ROA is a publicly available data element and is not a personal identifying data element
• Company revenue will also be used, but only to validate qualification for inclusion in the study.

Data Source & Collection:
• The PI will utilize Morningstar.com for ROA extraction
• Morningstar, Inc. is a U.S.-based investment research and management firm. Their platform
contains syndicated financial data for firms across NYSE and NASDAQ, among other exchanges
and investment types.
• Shown below is an example of the data that will be available through Morningstar.com
(https://www.morningstar.com/).
• The example depicts the data for United Airlines (stock symbol UAL).
140

o First, the stock trading symbols provided by respondents will be validated to ensure the
organization is a US publicly-traded company on the NYSE or NASDAQ
o Next, revenue will be validated to ensure it meets the criteria of >$2B/year
▪ In the example below, UAL is qualified, as its TTM revenue = $40,747 billion,
circled in GREEN in the first screen capture below
o Last, the ROA will be extracted.
▪ In the example below, UAL TTM ROA = -1.09%, circled in RED in the second
screen capture below

141

Data Analysis:
1. Return On Assets (ROA) ratio figures associated with the firms represented by study
participants will be extracted from Morningstar.com on a single day to avoid stock market
variations
2. Data will be entered into an Excel spreadsheet
3. The Excel (CSV) file will be appended with the single- and multiple-leadership designations
from the participants’ firm demographic data collected in the survey
4. The ROA data will be analyzed using the correlation and average to technology leadership
model

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Asset Metadata

Creator Sherlock, Janet (author)

Core Title The organizational impacts of executive technology leadership role proliferation

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2023-08

Publication Date 07/21/2023

Defense Date 06/23/2023

Publisher University of Southern California. Libraries (digital)

Tag Chief Digital Officer,Chief Information Officer,Conway's Law,OAI-PMH Harvest,organization design,role clarity,technology leadership

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Martinez, Brandon (committee chair), Datta, Monique (committee member), Maddox, Anthony Bernard (committee member)

Creator Email janetsherlock@gmail.com,jsherloc@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113288991

Unique identifier UC113288991

Identifier etd-SherlockJa-12134.pdf (filename)

Legacy Identifier etd-SherlockJa-12134

Document Type Dissertation

Rights Sherlock, Janet

Internet Media Type application/pdf

Type texts

Source 20230725-usctheses-batch-1073 (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

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Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA

Repository Email cisadmin@lib.usc.edu