Index

ABB Robotics, 102

accountability, 174

adaptive organizations, 18, 78

Aeroflot, 32

after-sale service, 109–110

agility, 18, 19, 21, 26, 38, 69, 78

AI-driven firms

building, 75–92

competition and, 61–72

See also artificial intelligence (AI)

AIG, 43

Airbnb, 11, 16, 18, 22, 33–34

airline industry, 32, 124

algorithms, 62–64, 66, 71–73, 77, 97. See also artificial intelligence (AI)

Alibaba, 3, 22, 61, 62, 70, 72

Alipay, 61, 66

All Traffic Solutions, 107–108

Alpha, 13

Amazon, 3, 6, 7, 8, 10, 22, 36, 62, 66, 72, 107, 139

analytics, 89, 90, 98–99, 115

analytics translators, 80, 88, 89

Ant Financial Services Group, 61–62, 66, 67, 73

Appear Here, 22

Apple, 15, 22, 163–179

collaborative debate at, 171–174

continuous innovation at, 166–167

functional organization of, 163–168, 169

leadership of, 168–178

organizational structure, 163–179

arenas, 10

Arm, 22

artificial intelligence (AI), 18, 61–73

AI factory, 62–64, 70

barriers to adoption of, 79–80

change reinforcement for, 89–91

competition and, 66, 68–72

downsides of, 73

educating about, 87, 89

at firm’s core, 68–69

investment in, 76, 80–81

job losses to, 71–72

leadership and, 72–73

organizational use of, 75–92

organizing to scale, 82–87

oversight and execution of, 86–87

prioritizing, 81

resistance to, 78–79

scale, scope, and learning and, 64–66, 73

strong, 63

successful use of, 78–81

tracking adoption of, 90–91

ways to derail programs, 88

weak, 63

See also AI-driven firms

asset sharing, 18, 19, 25, 26

assumption checkpoint table, 12

assumptions

rethinking, 7

testing, 8, 12–13

AT&T, 159

augmented reality, 102, 110

Auto-ID Center, 106

automatic-execution strategy, 133–136

automation, 62, 155

automotive industry, 71, 143–145

autonomy, 97

Avnet, 37

Badhorn, Dayna, 37

barriers to change, 79–80

Best Buy, 6–7

big data, 18, 21

Bing, 64

blockchain technology, 31

Blue Apron, 131–132

Bonobos, 35

born-digital firms

assumptions in, 3

competition and, 10, 62

IT infrastructure and, 144

See also digital firms

Bosch Group, 122

Brilliant Factories initiative, 104–105

Buffer, 12–13

business models

complexity of, 85

definitions of, 15–16

for digital transformation, 5, 139–150

dominant, 16

platforms, 11–12

smart devices and, 103–104, 108

support for new, 103–104

transformative, 15–27

buy what we have model, 128–130, 137

Canadian Imperial Bank of Commerce (CIBC), 51–52, 56–57

Canon, 22

Casper, 3

Caterpillar, 110, 122

Center for Energy Workforce Development (CEWD), 160–161

centers of excellence, 123

Chalendar, Alice de. See de Chalendar, Alice

Chandler, Alfred, 64, 143, 165, 168

Chanel, 149

change reinforcement, for AI adoption, 89–91

chief analytics officers, 86

chief data officers (CDOs), 43, 45, 48, 52, 56–58, 119

Christensen, Clayton, 10, 66, 139, 143

closed-loop process, 18, 19

cloud technology, 20, 72

coaching behavior, 132–133, 135

Coase, Ronald, 2

collaborative ecosystem, 18, 19, 21, 25, 26

collisions, 66

Collison, Patrick, 149

Comcast, 62, 67

command-and-control model, 116

commodity prices, 20

company culture, 79, 113

compensation models, 113, 167

competition

AI and, 62, 66, 68–72

born-digital firms and, 10, 62

identifying, 10

competitive advantage, 66, 69–71, 115, 137

connected devices. See smart devices

connected strategies, 127–138

automatic execution, 133–136

coaching behavior, 132–133, 135

curated offering, 131–132, 135

repeat dimension of, 136–138

respond to desire, 130–131, 134, 135

consumption patterns, 125

conventional products, 116

Cook, Tim, 165, 174

core competencies, 72

Coursera, 22

cross-business-unit steering committees, 123

cross-functional teams, 76, 86–87, 118–119

culture

company, 79, 114

learning, 156–157

curated-offering strategy, 131–132, 135

customer consumption chain, 11

customer focus, 38–39, 115

customer needs, 129–130, 132, 136–137

customer preferences, 20

customer relationships, 107–108, 136–143

customer success management units, 117, 118, 120–121

customer value proposition, 15–16, 30–34, 108–109

customization, 137

cyberattacks, 111

DalleMule, Leandro, 43–59

Dark, Jill, 161

data

big, 18, 21, 99

customer relationships and, 140–142

defense versus offense, 44–47, 52–57

incremental improvement and, 147

versus information, 46

integration, 68

personal, 111–112, 136

policies, 112

protection of, 147

raw, 46

scalability of, 146

security, 45, 111–112

from smart devices, 97–100

standardization, 46, 47

talent to manage, 182–183

unstructured, 183

data analytics, 89, 90, 98–99, 115

data architecture, 46–52

data breaches, 43

data definitions, 50

data fraud protection, 45

data lakes, 51, 99, 104–105

data-management functions, 43–44, 48, 57–58

data pipeline, 63

data privacy, 44, 69, 111–112, 136

data rules, 50

data strategy, 43–59

data warehouses, 51

Davenport, Thomas H., 43–59, 181–185

de Chalendar, Alice, 151–161

decision making

by AI, 62–64, 75, 77–78, 92

data-driven, 77–78

top-down, 77

Defense Advanced Research Projects Agency (DARPA), 99, 111

DelBene, Kurt, 70

Dell, 22

demand, 20

denial-of-service attacks, 111

detail orientation, at Apple, 169–171

development-operations groups (dev-ops), 117–121

DHL, 107

Didi, 66

Diebold, 110

differentiation, 114, 115

digital economy, 139–140

digital firms

acquisition of, 36–38

advantages of, 139

experimentation by, 3–4

physical businesses of, 35

structures of, 3

See also born-digital firms

digital networks, 69–71

digital operating models, 61–73

digital strategy, incremental approach to, 1–14

digital transformation

defined, 29

discovery-driven, 1–14

key areas for, 181–185

legacy systems and, 139–150

measuring progress on, 8, 10

myths about, 29–42

payoff of, 13–14

physical businesses and, 34–36

talent for, 181–185

digital twins, 99

diminishing returns, 65

Directive on Payment Services (PSD2), 41

direct-to-consumer businesses, 3

discovery-driven digital transformation, 1–14

discovery-driven planning (DDP), 2, 5–13

discretionary leadership model, 175–178

Disney World, 127, 136, 137

disruption, digital technology and, 30–34

disruptive innovation, 66, 152–154

Dragon Innovation, 37

drones, 107

Drucker, Peter, 46

DuPont, 165

economic growth, 125

EdX, 22

employees

adaptability of, 151–161

capabilities needed by, 68–69

change incentives for, 91

educating about AI, 89

engagement of, 157–158

expectations of, 154

optimism about future of, 154–157

resistance to AI by, 78–79

training of, 156–157

ways to support, 156–161

employment, 125–126

energy sector, 36

entrepreneurial firms, 165

environmental stewardship, 125

Etsy, 22

evergreen design, 102, 114, 119

Expedia, 33, 40, 72

Expeditors, 157

experimentation, 3, 12–13, 78, 90

experimentation platform, 63–64

expertise, 112–113, 168–169

Facebook, 62, 63, 70

factories, smart, 104–105

factor prices, 20

Fadell, Tony, 142

failures

fear of, 78

as lessons, 12–13

toleration of, 39

fall-detection sensors, 134

feedback loops, 50, 142

Fidelity Investments, 62, 67–68

Fields, Mark, 148

financial services sector, 41

Ford Motor Company, 119, 148

Fountaine, Tim, 75–92

friction, 72

Fuller, Joseph B., 151–161

functional organization, 163–168, 169

Furr, Nathan, 29–42

G7, 33

Galeries Lafayette, 31, 34–35, 37

Gascoigne, Joel, 12–13

General Electric (GE), 6, 12, 104–105, 113, 123, 141, 146–149

General Motors, 165

gig economy, 153–154

Google, 7, 36, 61, 63, 64, 70, 107

Google AdWords, 22

governance, of digital assets, 69

guardian angels, 37–38

hackers, 111

Hackster.io, 37

Haggerty, Myra, 173

Hamers, Ralph, 39

Handy, 22

Hansen, Morten T., 163–179

Harry’s, 3

HBO, 149

health-care industry, 124

Healx, 25–27

Heppelmann, James E., 93–126

herding cats, 184

Honeywell, 62

hotel industry, 16–17, 33–34

hub-and-spoke model, 82–87

Hubel, Paul, 167

hub firms, 70–71

human resources, 112–113. See also employees; workforce

Iansiti, Marco, 61–73

IKEA, 23

Immelt, Jeff, 113

incumbent firms

incremental advantage of, 2–5, 14

legacy systems of, 139–150

Indigo Ag, 62

industry analysis, 71

information, versus data, 46

information architecture, 46–47

information engineering, 46–47

information technology (IT)

changing nature of, 144

collaboration between R&D and, 116, 118–119, 121

first generation of, 144

talent, 182

infrastructure, 64

ING, 38–39

ING Netherlands, 158

innovation

disruptive, 66, 152–154

technical, 85–86, 154

transformative, 143–145

integration, 114, 115–116

interdependence, 143–145

interdisciplinary collaboration, 76

interdisciplinary teams, 76, 86–87, 118–119

Interface, 23

intermediaries, 11

internet of things (IoT), 20, 106, 134

iPhone, 166, 167, 172–174

iPod, 15, 22

iTunes, 15

job losses, to AI, 71–72

Jobs, Steve, 163, 168–169

Joly, Hubert, 6, 7

JPMorgan Chase, 61

JustPark, 23

Kaiser Permanente, 148–149

Kavadias, Stelios, 15–27

Klöckner, 4–5, 8, 11–12

Kodesh, Harel, 149

labor demographics, 155

Ladas, Kostas, 15–27

Lakhani, Karim R., 61–73

Lawrence, Paul R., 114

leadership

AI and, 72–73, 89–90

at Apple, 168–178

attention to detail by, 169–171

discretionary model of, 175–178

educating about AI, 87, 89

expertise of, 168–169

at scale, 174–178

lean manufacturing, 105

lean start-ups, 2

learning

from failure, 12–13

by firms, 64–66

machine, 18, 20, 71

learning culture, 156–157

legacy systems, 40–41, 67, 139–150, 182

LEGO Factory, 23

Lending Club, 23

Levie, Aaron, 139–150

Levitt, Ted, 10

LiveOps, 23

Loch, Christoph, 15–27

logistics, 106–107

Loop, 161

Lorsch, Jay W., 114

low-cost variability, 101–102

Lyft, 23

machine learning, 18, 20, 71

MacMillan, Ian, 2

Maersk, 31

MagicBands, 127

manufacturing, 20

changes in, 94, 97–100, 114–116

differentiation and integration in, 114–116

lean, 105

organizational structure in, 113–121

skill shortages in, 112–113

smart, 104–106, 113

transitioning to new, 121–123

Manzari, Johnnie, 173

Marineau-Mes, Sebastien, 173

marketing, 107–109

markets, linking technology and, 19, 20

Marriott, 33–34

Mastercard, 38

master data management, 46–47

McCarthy, Brian, 75–92

McDonald, Rory, 66

McGrath, Rita, 1–14

McGraw-Hill Education, 128, 136, 137

McManus, Ryan, 1–14

mechanical engineering, 101, 112

Medicast, 23

metrics

developing better, 148–149

progress, 8, 9

Microsoft, 62, 69, 70

middleware, 40–41

modularization, 143

MP3 technology, 15

M-Pesa, 23

multiple versions of the truth (MVOTs), 47–52

Nadella, Satya, 62, 69, 70

nanotechnology, 20

Natura, 23

Nest, 140–143

Nest Labs, 104

Netflix, 10, 136, 137, 141, 145, 147

networked devices, 93. See also smart devices

network effects, 11, 66, 70–71, 142

networks, digital, 69–71

Nike, 23, 128, 133, 137

Nordstrom, 67

Nwokah, Etugo, 13

Ocado, 62

one-stop service, 109

open-market transactions, 11

operating experience, 6–7

operating models, 61–73

operating performance, 64, 66, 72

optimization, 97

organizational change capability, 184

organizational structures, 67

for AI scale, 82–87

at Apple, 163–179

of manufacturers, 94

smart, connected products and, 113–121

transitioning to new, 121–123

outcomes, identifying, 8

oversight, of AI, 86–87

partnerships, 6–7, 108, 142–143, 145, 149

performance metrics, 148–149

Peri, Guy, 51, 53

personal data, 111–112, 136

personalization, 17, 19, 21, 25–26

personalized medicine, 25–27

pharmaceutical industry, 25–27

Philips (pay per lux), 23

physical businesses, 34–36

pilot programs, in AI, 76

planning, discovery-driven, 2, 5–13

platforms, 11–12, 16–17

Podolny, Joel M., 163–179

Porter, Michael E., 93–126

power generation industry, 5–6

Predix (GE initiative), 12

preventive service, 110

price transparency, 11

pricing, usage-based, 18, 19, 21

process management, 184

Procter & Gamble, 51, 53, 146

product-as-a-service models, 103–105, 114–115, 120

product development, 101–104, 119, 166–167

product-focused mentality, 69

product life cycle, 116

products, smart. See smart devices

progress metrics, 8, 9

project goals, 8

quality management, of smart products, 103

radical disruption, digital technology and, 30–34

radio frequency identification (RFID), 106, 127

Raman, Manjari, 151–161

Randazzo, Ann, 160–161

raw data, 46

Raynor, Michael, 66

Redman, Thomas C., 181–185

regulations, 20, 155

regulatory bodies, 73

remote service, 109

research and development (R&D), collaboration between IT and, 116, 118–119, 121

respond-to-desire strategy, 130–131, 134, 135

return on investment (ROI), 8

return on time invested (ROTI), 8, 10

reverse engineering, 5

Ribau, Jose, 51, 56–57

Ricoh, 23

risk aversion, 78

risk mitigation, 111–112

role models, for AI adoption, 89–90

Rolls-Royce, 23, 108

Rooted, 3–4

Rosner, Roger, 169, 176–178

Rühl, Gisbert, 4, 11

Ryanair, 23

Saleh, Tamim, 75–92

sales, 107–109

Salesforce.com, 23

scale, 64–66, 73, 82–87, 146

Schneider Electric, 112–113

scope, 64–66, 73

search engines, 64

Second Industrial Revolution, 94

security, smart devices and, 110–112, 118, 121

self-driving cars, 144–145

sensors, 18, 29, 98–99, 103–105, 121, 134

service industries, 124

services

after-sale, 109–110

value-added, 110

Shipilov, Andrew, 29–42

shipping industry, 31

showrooming, 6

Shyp, 24

Siegel, Robert, 139–150

Siemens, 149

Siggelkow, Nicolaj, 127–138

siloed structures, 67, 76, 79

Simmonds, Jacky, 40

single source of truth (SSOT), 47–52

smart devices, 20, 36, 93–126

after-sale service, 109–110

autonomy of, 97

broader implications of, 123–126

customer relationships and, 140–141

data from, 97–100

evolution of, 93

human resources and, 112–113

impact on services of, 124

interoperability of, 104, 108

IT and, 118–119

logistics and, 106–107

manufacturing and, 97–100, 104–106

marketing and sales of, 107–109

new capabilities of, 95, 97

organizational structures and, 113–121

product development and, 101–104

quality management, 103

R&D and, 118–119

security and, 110–112, 118, 121

simplified components in, 105

software industry and, 114–115

strategy implications of, 94

technology stack for, 95–97

user interfaces, 102

value chain transformation and, 101–113

smart factories, 104–105

smart thermostats, 93, 104, 142

SmartThings, 108–109

Smoove, 103

software, customer relationships and, 140–142

software development, 69, 113, 114

software engineers, 101, 112

software industry, 114–115

Sorenson, Arne, 33

specialization, 67, 72

speed, of service, 130–131

Spotify, 62

“spot market,” for talent, 159

squads, 38–39

stand-alone business units, 122–123

standard industrial classification (SIC) codes, 10

start-ups

acquisition of, 36–38

incumbents and, 139

leadership of, 5

pivoting by, 3–4

Steelcase, 161

steering committees, 123

Strategic Workforce Architecture and Transformation (SWAT) team, 161

strategy

connected strategies, 127–138

conventional approaches to, 71

data, 43–59

implications of smart, connected products for, 94

reshaping of, 72

Stripe, 149

strong AI, 63

supply chains, 142–143

synergies, 71

Sysmex, 109

system interoperability, 104

talent

attracting, 113, 157–161

collaboration for, 159–161

for digital transformation, 181–185

internal, 159

TaskRabbit, 24

taxi industry, 32–33, 124

teams, cross-functional, 76, 86–87, 118–119

technological innovation, 85–86, 154

technology

advances in, 29–30

blockchain, 31

cloud, 20

linking market and, 19, 20

long-term trends in, 18–20

platform, 16–17

talent, 182

technology adoption, 15

technology hubs, 112–113

technology stack, for smart, connected products, 95–97

Telenor, 39

Tencent, 24, 62, 70

Terwiesch, Christian, 127–138

Tesla, 103, 139, 140, 144–145

test-and-learn mentality, 78

Thermo Fisher Scientific, 119

Thomas, A. Charles, 56

3-D printing, 20

Townsend, Graham, 169, 174

traditional firms

collision between AI-driven firms and, 66

rebuilding, 66–69, 70

training programs, 156–157

transactions, open-market, 11

TransferWise, 41

transformative business model, 15–27

transformative innovations, 143–145

travel industry, 36

TUI UK, 36, 40–41

23andMe, 141

Uber, 21, 24, 32–33, 66, 71, 72, 124, 139, 140

Udacity, 24

uncertainty, managing, 161

unified data organization, 117, 118, 119

unstructured data, 183

Uptake, 122

usage-based pricing, 18, 19, 21

user interfaces, 102

U.S. Food and Drug Administration, 111

value-added services, 110

value chain

constraints of existing, 140

transformation of, 101–113, 145–150

value creation, 15–16, 66, 123, 139–140

value proposition, 15–16, 30–34

van den Boogert, Vincent, 158

variability, in products, 101–102

Ventana Medical Systems, 118–119

venture capitalists, 4

Veon, 1–2

Visa, 67, 149

Vodafone, 67

Wallenstein, Judith K., 151–161

Walmart, 8, 10, 62, 68–69

Warby Parker, 3, 35

Washio, 24

Wayfair, 24, 62

Waymo, 63, 71

weak AI, 63

Wealthify, 41

wearable technologies, 134

WellMatch, 13

Wells Fargo, 56

Wessel, Maxwell, 139–150

work

forces shaping future of, 152–155

transitioning models of, 155

workforce

adaptability of, 151–161

See also employees

Workforce 2020 strategy, 159

workplace skills, 112–113, 125–126, 152, 154

Xerox, 24, 103–104

Zara, 24

Zebra Medical Vision, 62

Zipcar, 24

Zopa, 24