(2022-02-24) Cutler The Data-informed Product Cycle

John Cutler: The Data-Informed Product Cycle. I recently shared this Tweet: Most teams jump from high level strategy/goals straight to feature ideas (w/ "success metrics") The most successful teams 1. Have a strategy 2. Translate that into models 3. Add minimally viable measurement 4. Identify leverage points 5. Explore options 6. Run experiments

• cf Data-Informed Product Management; OODA

We (hopefully) start with a Strategy (strategic context)

Next we develop/select various context-appropriate Models.

the models you use and socialize are probably AS important as your strategy. Why are models so important? They help orient us, and encourage more effective conversations.

Next we layer in Metrics and Measurement.

Next we identify Leverage Points. (bottleneck)

Donella Meadows describes leverage points as: [The] places within a complex system (a corporation, an economy, a living body, a city, an ecosystem) where a small shift in one thing can produce big changes in everything

Next comes designing and Placing Our Bet, building a feature, or simply “trying something”.

Finally, we Integrate Whatever We Learn back into our strategy, and models. We revisit our approach to measurement, and how we measure impact. And we inform our next bets.