Orienting for Outcomes
summary
Shows how to pick measurable outcomes over outputs and test riskiest assumptions first using thin slices, story maps, impact maps and the opportunity solution tree. Gives concrete numbers from other orgs — about a third of experiments harmed metrics, a third helped, a third did nothing; Amazon sees ~50% failures, Netflix ~90% — so expect lots of failure. Describes building a tiny CSV-powered invoice auditor (three rows instead of 20,000) that proves integration and surfaced real business reactions, so iterate or kill early.
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chapters (44)
- 0:00Introduction
- 0:51What happens if we dont think about outcomes
- 2:17But the world moved on
- 2:35It turns out failed
- 4:10Theres no point
- 4:26Are we any better
- 4:53Outcomes
- 7:31Example
- 8:05Understanding the outcome
- 10:10Asking what we might do
- 10:45Thinking about solutions
- 11:32Guard rails
- 11:50Boundaries
- 12:17Options
- 12:33Customer Data
- 13:09The Hippo
- 13:55Experiment
- 14:25Testing Risks
- 15:52Testing at a Scale
- 18:03How can I use this
- 18:25How can I help my organisation
- 20:10Write user stories
- 21:38Ask stupid questions
- 22:48Ask nicely
- 23:24Identify the risks
- 26:41Build a process
- 27:53Build a task
- 28:11Create options
- 28:28Listen to your customers
- 28:39Find out more about the processes
- 29:30Story maps
- 30:16The thin slice
- 32:05Build iteratively
- 33:01Solve customers problem
- 33:52Improve the experience
- 36:21Optimize the metric
- 37:32Communicate
- 38:59Support
- 40:06Funding
- 42:11Second inconvenient truth
- 42:55OKRs
- 43:35Incentives
- 44:16Multiple Teams
- 45:48Expect Failure
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