Index

• Accenture, on Rotation Masters, 136
• action labs (EDO), 5–7, 8
• active foresight, 84, 85–87
• adaptive space, 105
• adhocracies, 143
• advanced vision technologies, 215
• Aetna, 183, 185, 190–91
• Agile Leader Potential (ALP) solution, 225–26
• AI-first companies and org health, 232–55
  • overview, 232–33
  • barriers to scaling and deploying AI, 238–41
  • checklist for agenda setting, 254–55
  • conditions for, 16
  • human-centric work, 242
  • investment in organizational and work design, 239, 244–46
  • investment in risk mitigation and learning, 240–41, 250–53
  • investment in strategy and decision making, 239, 242–44
  • investment in talent, 239–40, 246–50
  • Saxo Bank (case study), 233–36
  • and value-creation, 236–37
  • AI Now Institute (NYU), 217
  • Airbnb, 41, 141–42, 317–18
  • Ally Financial, 10, 33–34
  • Alphabet Inc., 28, 221, 236–37, 334
• Amazon: as AI-first company, 233, 334
  • bias in hiring algorithms, 217
  • gender-biased recruiting algorithm, 163
  • market expectations of, 57
  • use of AI, 10
  • use of integrated strategy machine, 243–44
• Amazon Web Services (AWS), 57, 315
• ambidextrous leadership, 136
• Amdurer, Emily, 204
• American Psychological Association, on lost productivity due to stress, 189
• Andreessen Horowitz, 166
• AngelList, 100, 165, 223
• Anthem, 10, 248–49
• Apple Inc., 130, 315
• Arena, Michael, 105
• Argyris, Chris, 329
• Armstrong, Brian, 154
• artificial intelligence (AI): in agile approach to talent management, 99–101, 103–6, 144–45
  • as foundational building block, 10–12
  • in organizational design, 143–46
  • projected growth of, 10
  • responsible use of, 216–17
  • and strategic direction for purpose over profit, 29–32
  • transparency and EID, 169–70. See also AI-first companies and org health
• Asana, 246
• aspirations, defined, 28
• asset classes of culture: efficiency enhancers, 54
  • risk mitigators, 54
  • strategy enablers, 53
  • talent multipliers, 53–54
• Auckland University of Technology, 178

• Badenoch, Alex, 251
• Bain Capital, 136, 291
• Baldwin, James, 161
• Balwani, Ramesh “Sunny,” 265
• Bank of America, 33
• Baratta, Joe, 166–67
• Barclays, on types of entrepreneurs, 215–16
• Barra, Mary, 162, 319
• “Barriers to AI Adoption” (MIT), 238–39
• BBVA, 253
• BCG, 123, 241
• B Corporations, 138–39
• Beacon, 221
• Beacon Talent, 292
• belonging. See equity, inclusion, diversity (EID)
• Benioff, Marc, 159, 169
• Bennis, Warren, 18, 75, 320
• Bergh, Chip, 157, 320
• Bertolini, Mark, 183, 185, 190–91
• biometric wearables, 186
• Birkinshaw, Julian, 101
• BlackRock, 157
  • culture initiatives of, 50
  • on org health and sustainability, 278
  • Social Impact Challenge, 33
  • tracking of diversity in companies, 169
• Blackstone Group, 99, 166–67
• Blockbuster, 1–2, 71
• Bloomberg Beta, 223
• Bloomberg LP, 223
• Blue Wolf Capital, 155
• BMW, 189
  • Project i, 53–54
• boards of directors. See investors and boards
• Bock, Laszlo, 105
• Boeing, 182
• Boston Scientific, 278
• bottom line, in leadership mindset, 95
• Bridgewater Associates, 146, 168
• Brimmer, Andrea, 33–34
• Brooks Brothers, 134
• Brown, Jeffrey, 33–34
• Business Roundtable (BRT), 30

• California, mandate for female board members, 171
• Cambridge Analytica, 264
• capability building, 141
• Carlyle Group: on diversity and growth, 276
  • investment in Black/Latinx entrepreneurs, 166
  • and org health, 334
  • partnership with Dunkin’ Brands Group, 291
  • talent-first mindset of, 106–7
  • work with portfolio companies, 9, 294
• Carreyrou, John, 265
• CEOs, as change fluent, 313–33
  • overview, 313–15
  • behavioral challenges for, 315–19
  • challenges during COVID-19, 321–23
  • change fluency philosophy, 328–33
  • checklist for agenda setting, 333
  • key actions for scaling and growth, 326–28
  • and organizational learning, 320–21
  • qualifications in age of AI, 323–28
  • reflective questions for, 316–17
• CEO whisperer, 286, 292–94, 309–10
• CEO.works, 226
• Chambers, John Whiteclay, 321–22
• Chandler, Alfred, 122
• change fluency, 328–33
• Chesky, Brian, 317–18
• chief human resources officers
  • (CHROs): as part of golden triangle, 272–73
  • on plans for talent management, 249
  • as value-creation role, 290
• chief performance officers (CPOs), 284–312
  • overview, 284–86, 328
  • as CEO whisperer, 286, 292–94, 309–10
  • checklist for agenda setting, 311–12
  • complicated relationships of, 308–10
  • as due diligence advisor, 286, 288–91
  • four roles of, 286, 288
  • during growth stage, 298–301
  • during maturity/stability stage, 302, 305–6
  • and portfolio operations groups, 286, 287–88
  • qualifications for, 302, 304, 306–11
  • roles during stages, 297
  • during scaling stage, 301–4
  • during start-up stage, 298–99
  • as talent shaper, 286, 291–92
  • as transformation architect, 286, 294–97
• Clockwise, 246
• Coca-Cola Company, 71, 152, 182
• Coinbase, 154
• collective intelligence of groups, 137
• Columbia University, on culture and company value, 201
• company mindset, 91
• Competing in the Age of AI (Insanti and Ikhani), 11
• CompIQ, 227
• continuous change capabilities, 142
• Corwin, Steven, 319, 325
• COVID-19 pandemic: agility and decision making due to, 129, 135
  • and attitudes to well-being, 177
  • boards and revenue decline, 266
  • challenges for CEOs, 318–19, 321–23
  • impact on organizational design plans, 122, 123, 129
  • impact on stakeholder capitalism, 30–31
  • incidence of remote workers, 139
  • org health and agility during, 47, 51
  • remote work operations, 179–80
  • shift to mask and ventilator production, 134
  • and talent management, 102
  • temporary response teams, 80
• Cross, Rob, 99
• Crunchbase, 100, 165, 222
• Crystal, 218
• CSC Group, 222–23
• culture, with shared and adaptive identity, 49–73
  • overview, 49–51
  • asset value of, 52–54
  • challenges to culture change, 69, 71–72
  • checklist for agenda setting, 73
  • common mindsets, 64
  • and developmental stages, 61–63
  • in digital age, 68–69, 72
  • as digital culture, 51, 54–55, 58–60
  • impact of digital advances on, 70
  • leaders and operating models for, 56–58
  • measurement of, 207, 209–10, 224–25
  • shaping healthy, 60, 63–68. See also equity, inclusion, diversity (EID)
• culture audits (EDO), 57–58
• culture clash, 40, 46–47, 128
• culture of psychological safety, 159, 162, 191
• curiosity, in leadership measurement, 225
• CVS Health, 27, 29, 278

• Dalio, Ray, 146, 168
• Das, Payel, 217
• data democratization, 143
• data-driven continuous org health checks, 197–231
  • overview, 197–99
  • building enterprise-wide framework, 200–201, 205
  • and business performance, 201–20
  • checklist for agenda setting, 231
  • HealthCo (pseudonym case study), 203–4
  • investing in analytical talent and technologies, 201
  • measurement of key dimensions, 202, 204–14
  • measurement using digital and AI technologies, 205, 214–17
  • in private equity firms, 205, 218–31
  • subject-matter data experts, 228–30
• data mining, 104
• Daugherty, Paul, 246–47
• decision making: capacity for agility in, 75–79
  • impact of COVID-19 on, 129, 135
  • use of AI, 144–46
• Deep Knowledge Ventures, 45–46
• Deloitte: on ambidextrous leadership, 136
  • Global Human Capital Trends study (2020), 177
  • on multiple scenario planning, 137
• Delta Air Lines, 102
• “Designing the Machines that Will Design Strategy” (Reeves and Ueda), 243
• digital culture. See culture, with shared and adaptive identity Digital Equipment Corporation (DEC), 71, 140–41
• digital nudges, 70
• disciplined agility, 84, 85
• DiVento, Jessica, 177, 178
• diversity bonus, 252
• Domino, 218
• DoorDash, 130
• double-loop learning, 134–35, 329
• dual operating systems, 136
• Duke University, on culture and company value, 201
• Dunkin’ Brands Group, 291

• earnings per share (EPS) growth rate, 171
• eBay, 170
• EBITDA (earnings before interest, taxes, depreciation, and amortization), 117, 136, 171, 287
• Edmondson, Amy, 99, 159
• efficiency enhancers, 54
• Electric Distribution Operations (EDO) (case study), 5–7, 8, 57–58
• emotionally intelligent leaders, 94
• employee burnout, 179–80, 186, 188–89
• employee engagement, 109, 184
• Employee Engagement Series, 179–80
• employee experience, 108–9, 118. See also talent, agile approach to ensemble leadership, 78, 79–81, 87, 90–93
• environmental, social, and governance (ESG): and disruptive global events, 322–23
  • and equity returns, 123
  • impact on board directors, 14, 263
  • investor monitoring of, 25, 276–78
  • Levi Strauss advocacy for strong gun laws, 320
  • in purpose-driven companies, 30, 31–32, 34
  • and social protest, 153
  • in sustainable organizations, 138
  • transparency in disclosure of, 269
• EQT Partners, 222
• EQT Ventures, 222
• equality vs. equity, 156
• equity, inclusion, diversity (EID), 151–75
  • overview, 2, 16, 151–53, 276
  • and adoption of AI, 251–52
  • challenges to, 160–64
  • checklist for agenda setting, 175
  • definitions of, 156–60
  • forensic, evidence-based audits for, 172
  • framework and topical playbooks for, 172–73
  • in investment firms, 106, 164–67
  • measurement of, 213–14, 227
  • reinforcement of mutual accountability, 173
  • reporting capabilities, 173–75
  • and sense of belonging, 157–59
  • and social issues, 153–56
  • from the top-down, 170–71
  • and transparency, 167–70
  • use of digital and AI technologies in, 155–56, 169–70
• ESR, 138
• E2Q (high emotional and ethical intelligence), 307–8
• EU General Data Protection Regulation (GDPR), fines for misuse of data, 240
• Everyday Chaos (Weinberger), 137
• execution data, 235
• Experience Matters, 160

• Facebook: as AI-first company, 10, 219–20, 233
  • and Cambridge Analytica data scandal, 264
  • user gender options, 154
• Farmer, Chris, 221
• Fast Company surveys, on society and environment, 31
• Fidelity, 157
• “Fighting Algorithmic Bias in Artificial Intelligence,” 217
• finance perspective, in digital investment, 92
• financial health, 183, 187, 215
• FinCo (pseudonym case study), 125, 127–29
• Fink, Larry, 33, 278
• FirstEnergy, 24
• First Horizon National Corporation, 227–28
• first principles, defined, 27–28
• First Tennessee Bank, 227–28
• Fitbit, 99, 190
• 5G network, 54, 177–78
• Floyd, George, 23–24, 80, 152
• Ford Motor Company, 134
• foresight. See active foresight
• Fortune 100 companies, culture initiatives of, 50
• Fortune 500 CEOs: on pandemic and stakeholder capitalism, 30–31, 129
  • on purpose over profits, 32
• foundation issues, 1–19
  • overview, 1–5
  • design conditions for effectiveness, 15–16
  • digital advances to scale and adapt, 16
  • Electric Distribution Operations (EDO) (case study), 5–7, 8, 57–58
  • investor perspective, 12–13
  • and key stakeholders, 13–15
  • and leadership, 16–17
  • literature review, 19
  • organizational health, 2, 7–9, 18
  • strategic use of digital and AI, 10–12
• four-day work week, 178, 191
• Freddie Mac, 225
• Friedman, Thomas, 130
• friend a machine concept, 250
• Future Founders list, 223
• Future Workplace, 179–80
• fuzzy accountability, 40, 44–46
• fuzzy priorities, 40, 42–44

• Gallup: on economic impacts of well-being, 184
  • on employee burnout, 180
  • on employee engagement, 109
• Gardner, Howard, 84
• Gartner, on impact of COVID-19
• on organizational design, 122
• GE Global Research, 53
• gender diversity, 152, 154, 165. See also equity, inclusion, diversity (EID)
• General Electric (GE): culture application, 225
  • FastWorks mode, 53
  • GE Digital business unit, 53
• General Motors (GM), 105, 134, 162, 319
• general partners (GPs), 274
• Genome, 144–45, 226–27
• Gen-Z workforce, 107, 108–9, 190
• George, Bill, 37
• gig economies, 163–64
• Glassdoor, 74
• Goizueta, Roberto C., 71
• golden triangle, 272–73
• Goldman Sachs, 167
• Google: as AI-first company, 10, 28, 219–20, 233, 236–37
  • Change and Design Forum, 125, 328–29
  • culture/ subcultures of, 59–60
  • data-driven org health checks, 200
  • first principles of, 28
  • as purpose-driven company, 29
  • transparency in, 47
  • work-life balance, 178, 190
• Google Ventures (GV), 221
• Gottfredson, Ryan, 64
• governance principles: active oversight, 279–80
  • board composition, 281
  • building AI-ready board, 281
  • clarity in governance practices, 280
  • continuous board improvement, 280–81
  • strategy based on shared accountability, 280
• Grant, Adam, 191
• Grotberg, Anna, 277
• G-3, 272–73

• Haas Business School, 223
• Hackett, Jim, 331
• Haier Group, 27–28, 60, 136–37
• Harvard Business School: on agility and sustainability, 17
  • on clarity of purpose and ROA, 32
• Harvard School of Public Health, Nine Foundations of a Healthy Building, 140
• HealthCo (pseudonym case study), 203–4
• healthy buildings, 139–40
• Hededal, Christian Busk, 234–35
• Heidrick & Struggles, Agile Leader Potential (ALP) solution, 225–26
• Helander, Kara, 9, 276
• HERO Employee Health Management Best Practices Scorecard, 183–84
• Heskett, James, 52
• HireVue, 225
• Hitachi, 228
• Holmes, Elizabeth, 265
• Holzemer, Ben, 164–65
• Home Depot, 152
• Hone Capital, 222–23
• Horowitz, Ben, 161
• HosCo (pseudonym case study), 81–90
  • creating fluid leadership ensembles, 90–93
  • enabling transformation in governance and change matter, 89–90
  • ensuring right talent at the top, 83–89
  • Executive Committee Charter, 85, 87
  • goals of, 82–83
  • setting the right tone at the top, 81–83
• hospitality industry, 82
• Hsieh, Tony, 46
• Human + Machine (Daugherty and Wilson), 246–47
• Human Capital Management Coalition, 25
• human-capital practitioners, 229
• Humanyze, 144
• Humu, 105
• Hunger, Patrick, 233–34, 236
• Hurricane Katrina response, 322

• IBM, 185
  • Thomas J. Watson Research Center, 217
• IBM Notes, 218
• idea meritocracy, 146
• Ikhani, Karim, 11
• inclusion. See equity, inclusion, diversity (EID)
• industrial vs. digital enterprise, 314
• Infosys, 170
• Insanti, Marco, 11
• Instacart, 41
• Institute for Ethical AI & Machine Learning, 216
• InsurCo (pseudonym case study), 260–62
• intangible assets, 269
• integrated strategy machine, 243–44
• Intel, 170
• intentional learning, 316–17
• International Classification of Diseases (ICD), definition of burnout, 188
• Internet economy, 237
• intersectionality, 152, 154
• Investor Advisory Committee, 25
• investor mindset, 76, 78, 91
• investors and boards, 259–83
  • overview, 259–60
  • changes in corporate governance, 262–63
  • checklist for agenda setting, 283
  • confidence in org health, 277–79
  • governance and oversight roles, 264–71
  • governance principles, 279–81
  • InsurCo (pseudonym case study), 260–62
  • priorities of PE and institutional investors, 275–77
  • value of investors, 273–75
  • value of PE-backed boards, 266, 267–69, 271–73
• iTunes, 315

• Jetstar Airways, 54
• Johansen, Bob, 324
• Jope, Alan, 39
• JPMorgan Chase, 152, 160, 170, 264
• judgment, art of, 76

• Kashi, 141
• KeenCorp, 224–25
• Kellogg’s, 141
• Kelly, Kevin, 10
• Klick Health, 144–45, 226–27
• Kortright, Holly, 118
• Kotter, John, 18, 52, 136
• KPMG: Board Leadership study, 273
  • report on AI growth, 10
• Kraft Heinz, 101
• Kranz, Ulrich, 54
• Kronos Incorporated, 179–80

• Labx Ventures, 224
• Lancor, 287
• Lattice Performance Management, 106, 246
• Lead and Disrupt (O’Reilly and Tushman), 136
• leadership, as agile and human-centric, 74–96
  • capacity for agility in decision making, 75–79
  • checklist for agenda setting, 96
  • ensemble type, 78, 79–81, 87, 90–93
  • HosCo (pseudonym case study), 81–90
  • measurement of, 206, 210–11, 225–26
  • mindsets, 91
  • qualities of, 94–96
• learning from mistakes, as cultural norm, 168
• Lee, Kewsong, 76, 106–7, 166
• legal issues, misuse of data, 240, 264–65
• Lesser, Rich, 318
• Levi Strauss, 320
• LinkedIn, 99, 111
• location strategy, 139–40
• L’Oréal, 227
• Lucas, Jared, 249

• machine learning (ML), 45
  • algorithms of, 149
  • in deal making, 222
  • ethical use of, 216–17
  • Google’s shift to, 237
  • integration into strategy, 42
  • and psychological profiles, 215
  • software, 100, 144–45, 226–27
• Mackenzie, Mindy, 294, 308, 311
• Malone, Tom, 87, 143
• Mattermark, 222, 223
• Mayo Clinic, 188
• McChrystal, Stanley, 63
• McKinsey & Company, 99
  • on adoption of AI and needed investments, 239–41
  • on agility and sustainability, 17, 134–35
  • on organizational health, 8
  • on org health and TRS, 201
  • on PE-backed boards, 266, 267–69
• MediaTech (case study), 113–18
  • attracting top talent, 115–16
  • comprehensive talent strategy, 114–15
  • improving employee experience, 116–17
  • key actions for org health, 117–18
• mental health, 182, 187
• Mercer, 183–84
• merger failures, 50
• Meta Platforms. See Facebook micro-aggressions, 102
• microenterprises (MEs), 136–37
• Microsoft: as AI-first company, 237
  • bias in hiring algorithms, 217
  • returns from shaping culture, 52
  • ties CEO pay to diversity goals, 24
  • use of virtual assistants, 105–6
  • Work Life Choice Challenge, 178
  • Workplace Analytics, 225
• Millennials, as purpose-driven, 31
• mindsets, 64
• misuse of data, 240, 264–65
• MIT Sloan School of Management: on agile firms, 123
  • on agility and profitability, 202
  • “Barriers to AI Adoption” (MIT Sloan Management Review), 238–39
  • on collective intelligence of groups, 137
  • on executive cultural leadership, 55
  • on systemic AI capabilities, 241
• Monsanto, 162
• MotherBrain, 222
• Moyo, Dambisa, 325–26
• multiple scenario planning, 137

• Nadella, Satya, 11
• Nair, Leena, 60
• Napster, 315
• National Grid utility, 5–7, 8, 39, 57–58
• natural language processing (NLP), 42, 45, 215, 227
• Neal, Annmarie, 290
• Netflix, 24, 52, 71
• New Balance, 134
• Newell Brands, 272
• new markets tax credit (NMTC), 160
• New York-Presbyterian Hospital, 319, 325
• Nokia, 71

• Ogg, Sandy, 75, 99, 226, 284
• Open Table, 141–42
• Organisation for Economic Co-operation and Development (OECD), on corporate governance, 266
• organizational and work design, investment in, 239, 244–46
• Organizational Culture and Leadership (Schein), 56
• organizational design, 120–50
  • overview, 120–23
  • and ability to scale and grow, 129–31
  • for agility and sustainability, 131–40
  • causes of failure, 125, 126–27
  • checklist for agenda setting, 149–50
  • continual evolution of, 140–42
  • FinCo (pseudonym case study), 125, 127–29
  • importance of agility, 123
  • and investment companies, 146–49
  • key performance factors, 147
  • measurement of, 212–13
  • organization building principles, 132–33
  • and org health, 125–29
  • rationales for, 124–31
  • use of AI, 143–46
• Organizational Dynamics (Kotter), 18
• organizational health: and agility during COVID-19, 47, 51
  • definitions of, 2, 18
  • as foundational building block, 7–9. See also AI-first companies and org health
  • data-driven continuous org health checks Organizational Network Analysis, 32
• organizational playbooks, 296–97
• organization building principles, 132–33
• OrgMapper, 227
• Ozy Media, 331

• Page, Larry, 28
• Page, Scott, 252
• parity, defined, 156
• partnerships, in leadership mindset, 95
• Patagonia, 29, 138–39, 334
• Peloton, 243
• People.co, 223
• peopleHum, 106
• people of color, 322
• PepsiCo, 227
• Perception (AI tool), 170
• performance cultures, 52
• performance factors, 147
• Persona, Lucas, 245
• Pettigrew, John, 5–7, 8, 57–58
• Pew, Bob, 331
• Pfeffer, Jeffrey, 25, 179
• physical health, 182, 187, 188
• physics-driven learning, 217
• Pichai, Sundar, 236–37
• Pinterest, 41
• PitchBook, 222
• Polman, Paul, 34–40
• portfolio operations groups, 286, 287–88
• pre-IPO stage. See stages, and culture
• Preqin, on diverse workforce, 9
• private equity firms: approach to strategic direction, 42–43
  • as data-driven, 205
  • examples of continuous measurement, 224–28
  • finding investment opportunities, 222–23
  • measurement of org health, 218–31
  • measurement of pre-deal risk, 220–21
• Procter & Gamble, 152
• Prophet, Tony, 159–60
• psychographic assessments, 174
• psychological contracts, 163, 181, 189–93
• purpose: defined, 27, 29–30
  • in leadership mindset, 94. See also environmental, social, and governance (ESG)
  • strategic direction for purpose over profit

• Qantas, 54
• QuantCube Technology, 215
• Quid, 104

• racial equity, 80, 102
• racial/ethnic diversity, 9, 151–52, 153. See also equity, inclusion, diversity (EID)
• Rainforest QA, 162
• real-time feedback, 99
• Reeves, Martin, 243
• reflective questions, 316–17
• REI, 32
• Reina, Chris, 64
• remote work operations, 139, 177–78, 179–80
• resilience, in leadership mindset, 95
• return on assets (ROA), 32
• return on investment (ROI), 52, 54, 75
• rigid categorical thinking, 324
• risk mitigation and learning, investment in, 240–41, 250–53
• risk mitigators, 54
• robo-coach, 146
• robotics, 233–35
• Ronanki, Rajeev, 248–49
• Rotation Masters, 136
• Ruimin, Zhang, 136

• Saberr, 146
• Salesforce, 153
  • Ethical & Humane Use of Technology initiative, 160
  • hiring of underrepresented groups by, 168–69
  • Office of Equality, 159–60
  • public disclosures on employees, 278
  • wage parity, 169
• Saxo Bank (case study), 233–36
• Schaninger, Bill, 18
• Schein, Ed, 56
• Schlumberger, 250
• Schön, Donald, 329
• Sears, 71
• sentiment analysis, 41, 70
• Sephora, 24
• side-hustles, 109
• SignalFire, 221
• silos, 234–35
• single-loop learning, 329
• social agility, in leadership measurement, 226
• social justice movements, 23–24, 152, 153, 169–70
• social purpose. See strategic direction for purpose over profit
• SoftBank, 166
• Spencer Stuart, 273
• spiritual health, 182
• stages, and culture, 61–63
• stakeholder capitalism, 30–31, 129, 191, 264–65
• startup failures, 1–2
• startup stage and culture, 61
• State Street Global Advisors, 50, 278
• State Street Global Exchange, 54
• strategic direction for purpose over profit, 23–48
  • in age of AI, 29–32
  • checklist for agenda setting, 48
  • elements of purpose in, 26–29
  • examples of purpose implemented by companies, 32–40
  • impact of digital advances on, 43–44
  • measurement of, 224
  • pitfalls to avoid, 40–47
  • Unilever (case study), 34–40
• strategy: defined, 29
  • integrated strategy machines, 243–44
  • and investment in decision making, 239, 242–44
  • and use of digital and AI, 10–12
• strategy enablers, 53
• Stritzke, Jerry, 32, 33–34
• structural inequality, 322
• Sturdy, Laela, 217–18, 274
• SunTrust Bank, 183
• superminds, 87
• sustainability, defined, 121–22. See also organizational design
• synthetic intelligence, 84, 87–89

• Tableau, 218
• talent, agile approach to, 97–119
  • overview, 97–98
  • checklist for agenda setting, 119
  • and core business challenges, 101–6
  • from investment mindset, 106–7, 109–13
  • measurement of, 207–8, 211–12, 226
  • MediaTech (case study), 113–18
  • reallocation of high performers, 99
  • use of digital and AI technologies in, 99–101, 103–6
• talent, investment in, 239–40, 246–50
• talent multipliers, 53–54
• Taraporevala, Cyrus, 278
• Team of Teams (McChrystal et al.), 63, 65
• teams: infusion of AI into, 245–46
  • temporary response type, 80
  • use of AI in coaching of, 145–46
• The Technology Fallacy (Kane et al.), 240
• tenacity, in leadership measurement, 226
• Tencent Holdings, 45
• Tesla, 134
• text analytics, 215
• Theranos, 1, 265
• thinking dexterity, in leadership measurement, 225
• Thomas, Bob, 80
• Thomas H. Lee Partners, 291
• thought exercises, 89
• Tichy, Noel, 75
• time-usage metrics, 225
• T-Mobile, Work from Anywhere (WFX) campaign, 177–78
• total returns to shareholders (TRS), 7–8, 31–32, 99, 201
• Toys “R” Us, 71
• TPG Capital, 164–65
• transparency. See equity, inclusion, diversity (EID)
• TripAdvisor, 141–42
• TrustView, 218
• Twitter, 170
• 2D diversity, 171
• The Tyranny of Change (Chambers), 321–22

• Ueda, Daichi, 243
• Ulrich, Dave, 284
• Ulta Beauty, 24
• Ultimate Software, 227
• unconscious bias training, 162
• unicorns, 265. See also stages, and culture
• Unilever (case study), 34–40, 101, 334
  • approach to business model innovation (UL2020), 37–38
  • Compass Strategy, 35–36, 38
  • continued impact today, 39–40, 60
  • focus on performance and values, 38–39
  • Unilever Sustainable Living Plan (USLP), 35–36, 38
• University of Auckland, 178
• University of California, 153
• Unu Motors, 246
• user experience (UX) perspective, 91, 92
• U.S. Securities and Exchange Commission (SEC), 25, 263, 265

• Vanguard Group, 169
• Venkatesh, Prabhu, 234–35
• Venture Science Capital, 224
• Virgin Blue, 54
• virtual assistants, 105–6
• virtual individual contributors—ops light model, 287
• Vista Equity Partners, 334
• VITAL (AI system), 45–46

• Wadors, Pat, 159
• wage parity, 227
• Warburg Pincus, 148
• well-being, 176–93
  • overview, 176–81
  • and adoption of AI, 252–53
  • checklist for agenda setting, 193
  • digital advances and AI impacts on, 186–88
  • importance of, 181–85
  • measurement of, 214, 227–28
  • organizational assessment for barriers to, 185–86, 188
  • organizational costs and benefits, 188–89
  • and psychological contracts, 181, 189–93
• Whittaker, Meredith, 217
• “Why Healthy Institutional Investors Outperform” (Schaninger), 18
• Wijnhoven, Fons, 51
• Willis Towers Watson, on roles of boards, 272
• Wilson, H. James, 246–47
• workforce strategies: in AI-first enterprises, 242, 245–46
  • diversity in, 9
  • employee engagement, 109
  • employee experience, 108–9, 118
  • four-day work week, 178, 191
  • and investor perspectives, 97–98
  • shorter work days, 191. See also Gen-Z workforce
  • talent, agile approach to
• work-life balance, 109, 178, 179–80, 186, 190, 191–92. See also well-being
• Worley, Chris, 328–29

• YouTube, 24, 59

• Zalando, 104–5
• Zappos, 46
• Zuerl, Michael, 189