Data Without Direction: The Cost of Ignoring the Business Model
summary
Claims that most developed models never reach production, citing 70-75% of models shelved; shows a chatbot rollout that lowered satisfaction because root cause was slow cross-team SLAs not lack of instant replies; recounts a churn project that flagged 4 million vs 200k true monthly churners after teams failed to define churn or business targets; prescribes a working rule Problem first, Solution second, Technology last and stresses aligning goals, definitions and deployment paths before buying AI.
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chapters (13)
- 0:00Introduction
- 1:24Problem framing
- 2:29AI hype and failures
- 4:40Ignoring business problems
- 7:32AI magic vs alignment
- 8:38Business foundation for data
- 9:39Overcomplicating solutions
- 10:45Misdefined churn case
- 12:56Problem-first mindset
- 14:21Cost of tech without direction
- 15:42Data drives decisions
- 17:27Closing remarks
- 18:16Q&A
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