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- Herausgeber: John Wiley & Sons
- Sprache: Englisch
Accessible, thorough guide to merging data analysis and AI with new talent strategies
The Inclusion Equation is a comprehensive, one-of-a-kind guide to merging DEI and employee wellbeing concepts with data analytics and AI. In this book, renowned thought leader and professional keynote speaker Dr. Serena Huang explains exactly how to quantify the effectiveness of new talent strategies by connecting them to a firm ROI estimate, enabling readers to approach and win the favor of higher-ups in any organization with the same effectiveness that marketing and financial departments do.
This book is written in a style that is appealing and accessible to all readers regardless of technical background, but with enough depth to provide real insight and strategies. Dr. Serena H. Huang distills her 10 years of Fortune 500 people analytics leadership experience into tools and framework you can leverage to measure and improve DEI and wellbeing in your workplace. Some of the topics explored in this book include:
- Attract and retain top talent, including Gen Z and Millennials, with tailored DEI and wellbeing strategies
- Quantifying not only a talent strategy's perceived initial effect on an organization, but also its improvement and expansion over time
- Turning DEI and wellbeing from illusive corporate concepts to quantifiable metrics
- Harness the power of AI to create synchronized DEI and wellbeing strategies that maximize ROI
- Getting serious attention from your CEO and CFO by quantifying HR initiatives
- Using data storytelling to demonstrate the business impact of DEI and wellbeing
- Preparing for the future by understanding the role of AI in creating an inclusive and healthy workplace
The Inclusion Equation is a complete guide for DEI and wellbeing, covering getting started in measurement to using storytelling to influence leadership. This is the contemporary playbook for any organization intending to substantially improve their diversity, equity, inclusion, and employee wellbeing by leveraging data & AI. This book is also perfect for any data analytics professionals who want to understand how to apply analytics to issues that keep their CEOs up at night. Whether you are a data expert or data novice, as long as you are serious about improving DEI and wellbeing, this book is for you.
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Seitenzahl: 349
Veröffentlichungsjahr: 2025
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Table of Contents
Cover
Table of Contents
Title Page
Copyright
About the Author
Acknowledgments
Introduction
Chapter 1 The Power of Data and AI in DEI and Well-being
Diversity Measurement
Inclusion and Well-being Measurement
Passive Data
Qualitative Data: Focus Groups and In-depth Interviews
Text Analytics
The Role of AI
Notes
Chapter 2 People Data Storytelling
Why People Data Storytelling Is Different
The Role of Trust
The Three Cs Framework for Successful Data Storytelling
The Process: From Raw Data to a Compelling Story
From Data to Insights: Visualization Dos and Don’ts
From Insights to Action: Recommendations and Influencing
Change Management Pitfalls to Avoid
Change Management for Data Driven Decision-making
Three Biggest Myths Around Storytelling
GenAI as Copilot in Data Analysis and Storytelling
Notes
Chapter 3 The Intersection of DEI and Well-being
The Interplay of DEI and Mental Health
Why Should Leaders Care?
Developing Trauma-informed Leaders
The Role of Age
Right to Disconnect
Synchronize DEI and Well-being Strategies
Organization Structure: Should You Merge DEI and Well-being?
A Discussion on Neurodiversity, Disability, and Accessibility
GenAI Applications: Inclusion and Well-being as an Integrated Effort
A Brief Note on Correlation Versus Causation
Notes
Chapter 4 Quantify the ROI of DEI and Well-being Programs
Program Evaluation Fundamentals
A Discussion on Employee Resource Groups
Running DEI and Well-being as a Business with Clear Metrics
Focusing on Business Questions and Proactive Data Collection
Recognizing the Strong Connection Between DEI and Well-being
Case Studies: Data-informed DEI and Well-being Programs
Notes
Chapter 5 The Impact of AI on DEI and Well-being
The Double-edge Sword: AI’s Potential and Risks to Advancing DEI
Biases in AI Development and Deployment
The Danger of Deepfakes
The Role of AI in Employee Well-being
The Complex Picture of GenAI’s Impact on Productivity
Responsible and Ethical AI Principles for Workplace Well-being
Human-centered AI to Eliminate Bias
Human-centered Versus Traditional AI
The GenAI Journey
Beyond the Framework: People and Process
The Future of AI-driven Inclusion and Well-being
Notes
Chapter 6 The Future of Work: Human-first
Strategic Workforce Planning
Key Skills for the Future Workforce
Organizations of the Future: Human-first Cultures
HR Process Changes to Enable Change
Notes
Index
End User License Agreement
List of Illustrations
Chapter 1
Figure 1.1 Candidate Feedback Data by Gender Across Recruitment Stages
Figure 1.2 Organizational Network Analysis of Gender and Levels
Figure 1.3 Text Analytics Example of Segmentation by Favorable vs. Unfavorable Responses
Chapter 2
Figure 2.1 Satisfaction Level by Gender
Figure 2.2 Gender Distribution by Region
Figure 2.3 Recruitment Funnel
Figure 2.4 Side View of a Simplified Recruitment Funnel
Figure 2.5 Applications per Role from January to June
Figure 2.6 Glassdoor Interview Experience Comparisons
Figure 2.7 Cigarette Usage by Race/Ethnicity (percentage)
Figure 2.8 Cigarette Usage by Race/Ethnicity (percentage)
Figure 2.9 Cigarette Usage by Race/Ethnicity (percentage)
Figure 2.10 GenAI Response Illustrating Python Codes to the Prompt “Can You Identif...
Chapter 3
Figure 3.1 Sample Interconnected DEI and Well-being Program Design
Figure 3.2 Synchronized Program Planning Calendar
Figure 3.3 LinkedIn Search Results for Combined Head of Inclusion and Well-being Roles
Figure 3.4 LinkedIn Search Results for Head of Well-being and DEI Roles Separately
Chapter 4
Figure 4.1 Three-step Process of ROI Quantification
Chapter 5
Figure 5.1 Responsible and Ethical AI Principles by Serena H. Huang, Ph.D.
Figure 5.2 AI Governance Council Process by Serena H. Huang, Ph.D.
Chapter 6
Figure 6.1 Seven Human Skills by Serena H. Huang, Ph.D.
List of Tables
Chapter 1
Table 1.1 Sample Data Access Worksheet
Guide
Cover
Table of Contents
Title Page
Copyright
About the Author
Acknowledgments
Introduction
Begin Reading
Index
End User License Agreement
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The Inclusion Equation
Leveraging Data & AI for Organizational Diversity and Well-being
Dr. Serena H. Huang
FIRST EDITION
Copyright © 2025 by Serena H. Huang. All rights reserved, including rights for text and data mining and training of artificial intelligence technologies or similar technologies.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.
Published simultaneously in Canada.
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About the Author
Dr. Serena Huang is revolutionizing how organizations approach talent, well-being, and DEI through data and AI. As a people analytics executive and chief data officer, Dr. Huang spent more than a decade leading measurement and analytics strategy for DEI and ESG at iconic brands like GE, Kraft Heinz, and PayPal.
A highly sought-after international speaker and one of the 2024 Top AI Keynote Speakers, Dr. Huang’s insightful keynotes and practical workshops have reached leaders across Asia, North America, and Europe. She also energizes the next generation as a guest lecturer at top MBA programs, including Wharton, Haas, and Kellogg.
In 2023, LinkedIn Learning recruited Dr. Huang to develop one of their most popular online courses on using data to drive meaningful progress in DEI and employee well-being. She was also invited to keynote the National Alliance on Mental Illness annual conference on effective workplace mental health strategies.
Dr. Huang recently founded Data with Serena to empower people and organizations through data and AI. Through strategic advisory services, she is helping businesses worldwide actualize a new vision of work where employee well-being and belonging are prioritized alongside profits.
When not traveling, Serena recharges through running, golf, and creating wellness content for her YouTube channel.
Acknowledgments
As I reflect on the journey of writing The Inclusion Equation, I am filled with gratitude for all the individuals who have supported, inspired, and encouraged me along the way.
First and foremost, I want to express my deepest gratitude to my family, who have been my rock throughout this journey. To my parents, Frank, Helen, Conni, and Tom I thank you for instilling in me the values of hard work, perseverance, and compassion. Your guidance and wisdom have shaped me into the person I am today, and I am forever grateful. To my aunt, Sophie, I am grateful for your encouragement since Day 1. To my husband, Naty, I thank you for your unwavering support and patience.
I also want to acknowledge the incredible friends who have been a part of my journey. To Mike Pino, Welu Aningo, Sonny Rivera, Lisa Lee, Karen Eber, Spencer Nicholls, Leonard Green, Holly Lam, Theresia Kurnia, Bas Debbink, Sophia Toh, and Jenny Dunten, I thank you for your friendship, encouragement, and support. Your presence in my life has made a significant impact, and I cherish our relationships.
I had my moment of “I am on the right track” when I started interviewing practitioners and this book would not have been the practical guide I wanted it to be without their experience and insights. A heartfelt thank you to Dawn Klinghoffer, Dr. Alexis Fink, Dr. Stephanie Murphy, Dr. Sanja Licina, Chris Cummings, Shujaat Ahmad, César Lostaunau, Carlo Dela Fuente, Tashi Theisman, Cindi Howson, Dan Riley, and Lani Hall for contributing to The Inclusion Equation.
Throughout my career, I have been fortunate to have had the opportunity to work with and learn from some of the most talented and dedicated individuals in the field of people analytics, DEI, and well-being. To my colleagues, mentors, and peers, I thank you for your expertise, guidance, and collaboration. Your contributions to this field have been invaluable, and I am honored to have had the chance to learn from and work alongside you.
A special thank you goes to Lani Hall, who is the first chief diversity and inclusion officer and HR leader I’ve met who not only believed in data but believed in me. I wouldn’t have started the data analytics work on DEI if it weren’t for her willingness to push the envelope when we worked together at GE.
I would also like to acknowledge the numerous individuals who have inspired me through their work, writing, and advocacy. To Dr. Fei-Fei Li, I thank you for your thought-provoking writing and research in “The Words I See.” Writing a book isn’t easy. Elaine Lin Hering generously provided timely advice that kept me going at a very critical moment. Her work on “Unlearning Silence” also serves as a constant reminder when I think about the important message I want to share with the world.
In writing The Inclusion Equation, I have been driven by a passion to create a more inclusive and equitable world. I hope that this book will inspire and empower others to join me on this journey, and I am grateful for the opportunity to share my thoughts and ideas with a wider audience.
Thank you again to everyone who has supported me on this journey. I am honored to have had the chance to share my work with you.
Introduction
There is no well-being without inclusion.
– Dr. Serena Huang
The phone rang close to midnight—an unknown number I almost ignored. But something made me answer.
“Hi Serena, it’s Sara...,” The voice on the other end was shaky, laced with confusion and fear.
“Hello...Sara? Are you okay?”
“I...I woke up in the ER. I don’t know what happened....”
My heart sank as she apologized profusely about a work deadline she might miss, her biggest concern mere hours after a medical crisis. Sara didn’t report to me directly and was working on a project of mine as a cross-functional stretch assignment.
In that moment, a thousand worries flooded my mind. Had I been so demanding as a leader that she felt compelled to call about work deliverables from a hospital bed? Why didn’t I notice the signs that she was struggling on weekly project team calls?
I assured her that her health was the priority—not the project, not the deadlines. Anything else could wait.
There was a long pause before Sara’s voice cracked again. “Can I...can I ask you something?” I could hear her trepidation.
“Anything, Sara,” I reassured her.
“The doctor said I had a panic attack...,”she said, her voice barely above a whisper. “I didn’t even know what they were. They said I’ve been having them for a while. What should I do?”
My stomach tightened. This wasn’t just a personal struggle; it was a symptom of a broken system. Sara, a talented employee, was suffering in silence, afraid to seek help.
“Sara, you’re not alone,” I said, my voice firming. “Our company has an employee assistance program (EAP)—free confidential counseling. You can talk to licensed professionals and get help there.”
“My manager wouldn’t find out?” she asked, her voice laced with fear.
“It’s confidential, Sara,” I assured her. “Your privacy is protected.”
That call was a turning point. It wasn’t just about Sara; it was about countless others struggling in silence. Sara was the first, but unfortunately not the last, Asian woman who would call me asking for help with a similar challenge at work over the years.
It ignited a fire within me, a burning desire to break the stigma around mental health at work. I started researching, delving into the disparities in access to mental healthcare for BIPOC (Black, Indigenous, and people of color) communities. The stories I uncovered were heartbreaking, highlighting the urgent need for change.
The Problem
After realizing how stigma holds employees back from seeking help and the unique challenges faced by individuals from different backgrounds, I began to wonder why employee well-being and diversity, equity, and inclusion (DEI) are often treated as separate initiatives within organizations.
Traditionally, corporate well-being programs focus on stress management, mental health resources, and work-life balance. Often benefits become the only solution an employer can provide to address these issues. DEI initiatives, on the other hand, address issues of representation, bias, and inclusion. Rather than benefits, various initiatives and programs are created to improve the hiring, development, and retention of employees from diverse backgrounds. Both well-being and DEI impact an employee’s experience at work. This siloed approach fails to recognize the interconnected nature of these two areas.
A truly inclusive and equitable workplace cannot exist without prioritizing employee well-being. Employees from marginalized groups often face unique barriers to accessing support due to stigma, fear of judgment, or lack of culturally sensitive resources. This can lead to underutilization of healthcare services, hindering individual and organizational growth. Furthermore, the experiences of individuals are shaped by the intersection of multiple identities. A Black woman, for example, may face unique challenges related to both race and gender, requiring tailored support and interventions. Veterans transitioning from military into their first civilian jobs, on the other hand, may experience drastically different issues. Because demographic and life experiences create different challenges, treating DEI and well-being as separate programs fails to address this complex reality.
Historical Context and Evolution
The year 2020 hit all of us in different ways. The COVID-19 pandemic and the death of George Floyd brought concerns about DEI, health, and well-being to the forefront.
I remember it was nearly impossible to have conversations about measuring health and well-being at work prior to the pandemic. I started reading about how different organizations would go beyond employee engagement and measure their employees’ well-being in regular surveys back in 2019. When I spoke about the topic at the time, very few organizations were capturing this data in the employee engagement survey. Fast forward to March 2020, the moment the world went into lockdown, the C-suite leadership team reached out asking who could help provide real-time data on the health and well-being of employees. I was the global head of people analytics at one of the largest food companies in the world at the time. Remember when canned food would fly off the shelf in the grocery store? The health of our employees suddenly became critical to the global supply chain of food. Overnight, they became frontline workers. My team ended up creating a COVID-19 dashboard for the senior leadership team, which included both internal and external data by location. We also launched the company’s first-ever health and well-being survey to better understand how to provide the right level of support. We noticed that mental health was an area many employees needed help with and that parents with young children were also having a difficult time. It was some of the most challenging, emotionally taxing yet rewarding work I’ve done in my career. My team ended up reaching an award from the CEO for being “data heroes” in the pandemic.
As companies navigate this post-pandemic world, it’s crucial for businesses to prioritize creating an inclusive and healthy environment for employees. When employees feel seen and valued, they’re more productive and likely to stay with the company long term. In fact, a study by McKinsey found that companies with diverse workforces are 35% more likely to outperform their less diverse peers. On the other hand, the cost of not prioritizing inclusion and well-being can be staggering. A study by the World Health Organization (WHO) found that depression and anxiety disorders cost the global economy more than $1 trillion in lost productivity annually.
The Business Case for Prioritizing DEI and Well-being
There has been a business case for inclusion for quite some time. But after the 2020 protests after the deaths of George Floyd, Breonna Taylor, and Ahmaud Arbery, along with the many Asian hate tragedies, there was a new focus on inequities and injustice leading to a new business case for inclusion. Companies could no longer wait for external or internal situations to spark change. In parallel, the isolation during lockdown, along with the grief of losing family and friends due to COVID-19, made it more acceptable to open up about not feeling okay. Everyone suddenly had a shared experience of being away from loved ones and having to work in drastically different ways.
Can you be productive when you are unwell? Whether it’s a physical issue or an emotional one, you are not operating at 100% when you aren’t feeling 100%. However, stigma holds us back from talking about mental health at work and seeking the help we need.
I recall seeing one social media post from Adam Grant that went viral, and it said, “It’s okay to call in sick. It’s also okay to call in sad.” What a timely reminder. Have you ever needed a mental health day before the pandemic when it was not as acceptable to say out loud? Are you working in an environment where mental health benefits are offered but taboo to talk about?
In my conversations, I’ve heard some executives put discrete personal appointments on their calendar while others openly label their regular therapy sessions to ensure they were protected. There isn’t a right or wrong approach, but the underlying reason for why someone would worry about sharing they are in therapy is worth examining. Some of us have run into managers who are not as understanding of mental health needs, and we naturally want to protect our career. Certain cultures also have open discussions about mental health. Understanding the reason why employees hide their needs can be very helpful to creating programs to address the underlying issues.
Just because the COVID-19 pandemic is over doesn’t mean employees no longer need support. In fact, many employees have continued to need help because of numerous factors that are out of their control, including high inflation and global conflicts. In a recent workshop, I facilitated a debate on who should be responsible for an employee’s mental health. Is it the employees or their manager? The easy answer is both, of course. The manager and employee themselves need to both do their parts. By asking the group to take sides, it forces everyone to think more critically. One side of the room passionately argued that the employer and managers have a responsibility to keep their employees healthy mentally because managers have as much impact on our mental health as a significant other. The other side of the room articulated numerous reasons why managers should not be held responsible for things outside of work or beyond their control, such as illness in the family.
It’s no secret that poor mental health impacts our lives, but many don’t realize how it can also affect our businesses. According to the WHO, an estimated 15% of working-age adults have a mental disorder at any point in time. Depression and anxiety are estimated to cost the global economy US $1 trillion each year, driven predominantly by lost productivity. People living with severe mental health conditions are largely excluded from work despite participation in economic activities being important for recovery.
As reported by the American Psychiatric Association Foundation Center for Workplace Mental Health, employees with depression miss an average of 31.4 workdays each year and lose another 27.9 workdays to unproductivity—or presenteeism—which costs employers an estimated $44 billion annually.
Anxiety and chronic stress can also prevent employees from fully “showing up” to work, leading to reduced effectiveness and costly mistakes. In addition to impacting engagement and productivity, mental health issues can affect our creative efforts and ability to make decisions and solve problems.
Given the high prevalence of mental health conditions globally, your organization is bound to employ people who could benefit from your help.
What about the other employees who do not have mental health conditions? Is there a business case for improving their health and well-being?
Gallup researchers reviewed 736 studies across 347 organizations in 53 industries, with employees in 90 countries. Within each study, they statistically calculated the business-level relationship between employee engagement and business outcomes such as profitability and absenteeism. In total, they studied 183,806 business and work units that included 3,354,784 employees. Comparing top-quartile with bottom-quartile employee engagement, business/work units resulted in the following median percentage differences:
Profitability: 23%
Productivity (sales): 17%
Turnover: 21% to 51%
Safety incidents (accidents): 63%
Absenteeism: 78%
Patient safety incidents (mortality and falls): 58%
Is employee engagement the same as well-being? No, but the two measures are highly correlated in the studies.
The Interconnectedness of DEI and Well-being
It’s easy to think that the DEI movement is losing steam. Social media is filled with anti-DEI sentiments and some US states have even defunded DEI programs. However, a survey of 600 C-Suite leaders of companies with more than 500 employees in 2024 shows 80% remain committed to DEI.1
Some organizations have created new names for DEI functions or combine talent with DEI into one. Inclusion goes far beyond being invited to meetings or team happy hours. It is also being included and having a voice in decisions that impact them.
Plus, the more research I read on employee well-being and mental health, the more obvious is the tight connection between DEI and well-being in the workplace.
Imagine the last time you felt excluded or left out of an important discussion at work. How did that impact your well-being? You likely felt a bit anxious and stressed, wondering why you were not part of the conversation.
Now, imagine having to avoid talking about your family because you weren’t sure how accepting your colleagues would be of your nontraditional setup. Perhaps you are part of the LGBTQ community. Perhaps you have a blended family with stepchildren. Perhaps you are a single parent to adopted children. Perhaps you chose not to have children because of a rare genetic disorder that runs in your family. These are all valid reasons not to share or to cover your identity to avoid unwanted conversations.
Did you know more than 60% of employees engage in covering part of their identity in the workplace? People cover because they want to be included and feel like they belong, and they fear part of their identity prevents them from being accepted. It is not difficult to imagine the negative impact of constant covering on health and well-being.
One essential dimension of workplace well-being is “connection & community” according to the latest framework released by the US Surgeon General’s Framework for Workplace Mental Health and Well-being. Research indicates that feelings of loneliness and inadequate emotional support significantly correlate with a heightened risk of self-harm and suicidal ideation.2 Additionally, insufficient social connections are linked to an elevated risk of various health issues, including a 29% increased likelihood of heart disease and a 32% increased risk of stroke.3
Additionally, demographic background plays a significant role in mental health. The analysis from CARE International shows that 27% of women experienced increased mental health struggles due to COVID-19, compared with 10% of men.4 Reports from Columbia University suggest that a Black adult is 20% more likely to experience a serious mental health concern than a White adult.5
The Solution: AI and Data Analytics
Despite the headlines of backlash on DEI, many organizations are just as committed to their DEI priorities as ever. However, there’s a growing expectation that DEI initiatives must demonstrate a positive return on investment (ROI). This is where data and AI come into play.
We cannot improve what we don’t measure. Measuring diversity is one thing, but quantifying inclusion is far more complex. Until recently, organizations have struggled to clearly quantify the level of inclusion because inclusion is a multifaceted concept. One common theme I’ve noticed in the leaders I’ve interviewed for this book is their focus on demonstrating business impact of DEI and well-being initiatives. Whether it’s the impact of employee resource groups (ERGs) on hiring or promotions or the healthcare cost reduction from implementing specific well-being programs, those who are successful in securing more funding, run their programs like a business. They don’t only focus on attendance for events or participation in programs, but instead, ask the tough questions of what business metric will this program improve and did we achieve that. These leaders either partner with analytics teams internally or external vendors to ensure the metrics are captured on day one.
The advancements in data analysis and AI technology have changed the game for measuring what previously seemed unmeasurable. The AI revolution, sparked by innovations like ChatGPT, has opened up new possibilities for measuring inclusion. By analyzing large amounts of text data from employee surveys, Slack conversations, and other sources, organizations can now gain a deeper understanding of their inclusion dynamics. The question on leaders’ mind is no longer “What can we do?” but “What can’t we do?”
Imagine a workplace where you receive personalized notifications reminding you to connect with a colleague you haven’t spoken to in a while. Or where your calendar suggests alternative meeting times to be mindful of the schedules of your team members in a different time zone. This isn’t the future—it’s already here.
In a 2022 article, researchers at Stanford found that hundreds of firms are using AI to improve inclusion and belonging in the workplace.6 Data analytics tools, which account for 32.3% of the tools in the study, collect real-time information on employee connections, inclusion, engagement, and sentiment. These tools use surveys, pulse checks, and communication metadata to assess belonging. Some tools also leverage sentiment analysis, network mapping, and internal reviews to provide a more comprehensive understanding of employee experiences. Additionally, behavior-change tools, which account for 26.5% of the tools in the study, use digital nudges to encourage inclusive behavior, provide feedback on learning and development opportunities, and offer actionable strategies for improvement. These tools can send reminders, collect feedback, and offer personalized recommendations to enhance employee performance.
Hilke Schellmann describes in her book, The Algorithm, how Alight combines claims, wealth, HR, and search data to predict the needs of employees. Imagine having personalized recommendations based on who you have added or taken off your insurance plan. Recommendations for doctors are based on care quality and cost. The company said it’d be investing even more heavily to predict mental health issues and musculoskeletal problems before claims are filed.
If this seems creepy, some organizations go a step further than Alight: tracking brains for safety. SmartCap is a tool that tracks truck drivers’ alertness and sends an audio-visual signal to the driver when it detects fatigue.7 Additionally, vocal biomarker tools leverage AI to find signals of mental health problems in voices. The underlying biological components rather than words are analyzed. Companies in this space are trying to find an equivalent of heart rate or blood pressure monitoring for psychiatry.
The use of AI-powered tools to enhance workplace belonging and inclusion is an exciting development. As we move forward, it’s essential to prioritize ethical considerations, ensure accountability, and promote transparency. A balanced approach is a must.
Responsible AI and the Role of Trust
When CEOs mandated the return to office, there was constant debate around how to make sure employees are engaged and productive. Many solutions track employees’ activity remotely on not only laptops but also company provided or managed cell phones. Zoom initially offered an attendee attention tracking feature, where if Zoom was not the application in focus on a participant’s computer for more than 30 seconds while someone else was sharing their screen, Zoom showed a clock icon next to the participant’s name in the participant panel.8
If you’ve never heard of this, it’s because the feature was short-lived. This feature received significant backlash after the launch. The Zoom team later apologized for falling short of the community’s privacy and security expectations and decided to remove the attention tracker feature permanently.
During the pandemic, I remember being asked to measure productivity. The debates would almost never end. Is it as simple as revenue per employee on average within a business unit? What about the support function employees like IT and HR? How would you measure the legal team’s productivity? We’d go down a rabbit hole and end up agreeing to focus only on the revenue generating employees in commercial functions because of the ease of obtaining sales-related metrics. For tech companies, engineering teams would use metrics related to code written as a productivity measure. For managers, there might be proxies for manager effectiveness through surveys, but those were not done on a regular basis, so it made for a poor metric. None of these flexible and creative measurements really solved the problem that we couldn’t find a single metric that worked for every employee in the company at all times. At times leaders would start thinking about the other side of the productivity spectrum: what if we instead measure how often employees are unproductive?
Because more people are working from home now, companies that didn’t traditionally feel the need to track workers started to invest in employee monitoring tools. In April 2020, global demand for employee monitoring software more than doubled.9 Online searches for “how to monitor employees working from home” increased by 1,705%, and sales for systems that track workers’ activity via desktop monitoring, keystroke tracking, video surveillance, GPS location tracking, and other digital tools skyrocketed.
What effect do you think monitoring has on employees’ productivity? A 2022 Harvard Business Review article states that employee monitoring can improve productivity when used correctly.10 However, monitoring can also have negative effects on employees, such as reducing their sense of responsibility and agency, which could lead to more rule breaking. In the study, employees who were told they were being monitored were actually more likely to cheat than those who didn’t think they were being monitored. Those who were monitored were more likely to report that the authority figure overseeing their surveillance was responsible for their behavior, while the employees who weren’t monitored were more likely to take responsibility for their actions. To mitigate these risks, Harvard Business Review recommends that leaders treat employees fairly, promote accountability, and present monitoring as a tool to empower employees, not punish them.
If you are new to AI, you might be wondering whether AI is really that different from other technology or traditional software. In certain aspects, the short answer is yes. AI presents a new wave of risks that go beyond traditional software, impacting not just individual companies but entire industries and society as a whole. While AI offers immense potential, it also introduces complexities and uncertainties that current risk frameworks struggle to address.
The biggest challenge lies in the data itself. AI systems are highly reliant on data, but these data can be biased, inaccurate, or outdated, leading to unreliable and potentially harmful output and outcomes. Furthermore, the sheer scale and complexity of AI systems, with millions or even billions of decision points, make it difficult to predict and manage potential problems. Existing frameworks for managing cybersecurity and privacy risks can be adapted to address AI, but they are not sufficient to handle the unique challenges of bias, generative AI, and emerging security threats. Organizations implementing AI need to develop new, comprehensive frameworks that specifically address these risks.
Overall, we must maintain a balanced approach to using AI in the workplace. The next few chapters in this book will provide more detailed discussions on the topic.
Who Is This Book For?
Business leaders and executives who want to create a more inclusive and healthy workplace culture
HR professionals who are responsible for well-being, diversity, equity, and inclusion initiatives and want to leverage data analytics to improve their programs
Data scientists and analytics professionals who want to use data and analytics to drive business decisions and improve workplace culture
AI and machine learning professionals who are interested in using AI-powered tools to support employee well-being and inclusion
Why This Book Now?
As I reflect on my journey, I’ve come to realize the profound impact of data-driven approaches on creating inclusive and well-being focused workplaces. Having spent more than a decade navigating the complexities of large global organizations, I’ve seen firsthand the power of data and AI in driving meaningful change. From my early days at GE to leadership roles at Kraft Heinz and PayPal, I’ve had the privilege of developing and implementing strategies to measure and improve DEI and ESG initiatives.
Beyond my corporate experience, I’ve had the opportunity to share my knowledge through teaching and speaking engagements. I’ve taught courses on people analytics for LinkedIn Learning, focusing on the intersection of DEI, employee well-being, and data-driven talent decisions. Additionally, I’ve personally contributed to the National Alliance on Mental Illness’s efforts to promote workplace mental health.
Throughout my career, I’ve noticed a recurring theme: many DEI and well-being practitioners possess a wealth of experience but may lack the technical skills to leverage data analytics effectively. On the other hand, analytics professionals often have strong technical expertise but may not fully understand the nuances of DEI and well-being. This book aims to bridge this gap, providing a comprehensive guide for organizations seeking to use data and AI to create more inclusive and supportive workplaces.
While there are numerous books on DEI and well-being, few delve into the critical intersection between these two areas. My research and personal experience have shown me that organizations that prioritize DEI often see improvements in employee well-being. This is not a coincidence. When employees feel seen, heard, and valued, they are more likely to be engaged, productive, and motivated.
The rest of the book is organized as follows:
Chapters 1 through 4 will discuss in detail the “how” of measuring what might seem difficult to measure, DEI and well-being; how to tell stories with these data; and the interconnectedness of DEI and well-being. We will also discuss how to demonstrate the ROI of programs to secure additional funding in a corporate setting. Case studies from prominent organizations will provide additional guidance on the most practical path forward.
We can’t talk about data without discussing how AI will impact DEI and well-being. It is a double-edged sword. On the one hand, AI enables quicker analytics and new ways of measuring inclusion and well-being. On the other hand, we have seen headlines around biases in AI that impact hiring, and the AI-created or AI-altered images on social media causing damage for a teen’s body image. Chapters 5 and 6 will provide a balanced view of AI’s long-term impact and address how to stay human-centered in the age of AI.
What Will You Be Able to Do After Reading?
You are about to dive into a book that will elevate your organization’s profitability and productivity. After reading this book, you will have the tools to build a workforce that is not only diverse but also innovative and energized.
First, you will learn how to accurately measure the seemingly “unmeasurable” in the workplace, from inclusion to mental well-being. You will gain skills to quantify the key factors driving inclusion and employee well-being in your organization. With these insights, you will be able to take a data-informed approach to creating a thriving workforce. However, this book is not about crunching numbers. You will also learn how to leverage advanced analytics and AI to uncover opportunities to improve DEI and well-being metrics in meaningful ways that move the needle.
Where it gets more powerful is mapping out integrated strategies that account for the link between an inclusive culture and a healthy employee base. You will use data and AI to finally put a stop to siloed DEI and well-being efforts because there is no well-being without inclusion.
Furthermore, you will gain expertise in quantifying the ROI of your DEI and well-being initiatives. By employing analytical techniques, you will be able to translate the benefits of a diverse and healthy workplace into concrete metrics that resonate with C-level leaders for sustained investment in these critical areas.
Finally, you will see how AI, when used properly, can help you stay ahead of your competitors. In a rapidly changing landscape, building a truly inclusive and well-being-focused workplace and prioritizing human skills that are AI-proof, will be drivers for success. This book is your practical roadmap to positioning your organization for long-term profitability.
Are you ready?
Let’s dive in!
Notes
1
. The New Era of Leadership. (2024).
Chief
. Available at:
https://thenewera.chief.com/research/
2
. Berkel, H. (2023).
The healing effects of social connection and community—The coalition to end social isolation and loneliness
. Available at:
https://www.endsocialisolation.org/the-healing-effects-of-social-connection-and-community/
3
. Valtorta, N.K., Kanaan, M., Gilbody, S., Ronzi, S., and Hanratty, B. (2016). Loneliness and social isolation as risk factors for coronary heart disease and stroke: Systematic review and meta-analysis of longitudinal observational studies.
Heart
102(13), pp. 1009–1016. doi:
https://doi.org/10.1136/heartjnl-2015-308790
4
. CARE Rapid Gender Analysis. (2020).
Filling the data gap to build back equal.
Available at:
https://www.care.org/wp-content/uploads/2020/09/RGA_SheToldUsSo_9.18.20.pdf
5
. Vance, T.A. (2019).
Addressing mental health in the Black Community
. Columbia University Department of Psychiatry. Available at:
https://www.columbiapsychiatry.org/news/addressing-mental-health-black-community
6
. Smith, G. and Rustagi, I. (2022). Workplace AI wants to help you belong.
Stanford Social Innovation Review.
Available at:
https://ssir.org/articles/entry/workplace_ai_wants_to_help_you_belong
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