From Data To Profit

Index

A

• AI (artificial intelligence)
  • about, 185–186, 201–202
  • AI evangelist, 321–323
  • best-in-breed solutions, 189–190
  • bottom-up opportunity discovery, 202–205, 212–213
  • business loss of faith in, 30–33
  • feasibility, 198–200
  • hidden components of, 173
  • lack of opportunities, 209–211
  • leveraging data and, 205–206
  • maturity assessment
    • about, 251–252
    • analytics-strategy alignment, 261–263
    • culture, 253–254
    • data monetization catalog, 269–271
    • employee empowerment, 265–269
    • leadership commitment, 255–256
    • operations and structure, 256–259
    • proactive market orientation, 263–265
    • skills and competencies, 259–261
    • starting, 252–253
  • maturity model
    • about, 155–156
    • AI strategy, 97
      • building, 273–286
    • capabilities maturity model, 156–158
    • complexity and rising costs, 161–164
    • data gathering, serving, and experimentation, 158–159
    • data generation maturity model, 167–169
    • expert systems, 159–161
    • product maturity model, 164–167
  • mid-term opportunities, 187–189
  • monetization assessment, 196–197
  • near-term opportunities, 187–189
  • operating systems models, 216–218, 232–233
  • opportunities for, 185–200
  • opportunity discovery, 192–194
  • preparing products for transformation, 190–192
  • product governance framework, 206–209
  • top-down opportunity discovery, 194–196
  • zero-sum game, 186–187
• Accenture, 136
• access to talent
  • about, 296–299
  • as a factor in skills and competencies, 259
• adaptations
  • to technology, 172–173
  • in three-layered framework, 236–238
• adaptive strategy, data-driven, 54–57
• adoption
  • as a factor in culture, ...