Analytics for Business Strategy
summary
Organizations lose 25–35% of performance without analytics, only 1 in 12 achieves expected returns, and 40% of decisions still ignore data, so the talk prescribes concrete methods: use decision trees for known distributions, predictive models with rolling windows for stationary unknowns, and extreme‑value fits like the Gumbel/Fréchet/Weibull family for non‑stationary tails. A worked example shows analytics raising decision accuracy from 50% to 75%, yielding a net gain in expected value once costs and error rates are accounted for.
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chapters (7)
- 0:00Analytics and intuition in strategy
- 3:37Flaws in data vs intuition
- 11:29Why strategy fails
- 18:52Forecasting in strategy
- 27:31Data to knowledge
- 34:42Valuing analytics projects
- 44:40Q&A
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