People-Driven Company vs Data-Driven Company
summary
Compares what changes when companies shift from people-driven to data-driven decision making, naming algorithms and metrics used and whether teams produce prototypes or just presentations. Cites failures (Amazon’s biased resume model, automated layoffs driven by Excel-derived metrics) and successes (scalable dynamic pricing algorithms). Recommends a practical path: choose one measurable use case, audit and collect data, build a cheap prototype, run A/B tests, then roll out.
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chapters (13)
- 0:00Introduction
- 1:52Management models
- 5:40People as foundation
- 8:08Processes as foundation
- 10:12Data as foundation
- 12:38People-driven pros/cons
- 14:03Data-driven pros/cons
- 19:45Success/failure cases
- 28:51Why data-driven fails
- 30:56Starting data shift
- 36:52Adoption criteria
- 40:24Where to start
- 42:49Q&A
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