Agile Impact 2018: Feature Experimentation
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The document emphasizes the importance of continuous experimentation in product development, as highlighted by leaders like Jeff Bezos and Satya Nadella. It discusses various experimentation methods, including A/B testing and performance tests, as tools to guide decision making and foster innovation. The focus is on creating a culture of experimentation that embraces failure to validate decisions based on data.
Agile Impact 2018: Feature Experimentation
- 1. FEATURE EXPERIMENTATION For Smarter Products Thomas Rothe
- 2. Agile Practitioner | Workflow Minimizer | Engineering Coach | Technologist Thomas Rothe
- 4. “Our success at Amazon is a function of how many experiments we do per year, per month, per week, per day.” Jeff Bezos “Instead of saying ‘I have an idea’, what if you said ‘I have a new hypothesis, let’s go test it.’” Satya Nadella • Adoption of continuous experimentation to gather data • Complete use of experimentation to guide decision making • Foster innovation and agility
- 5. Discovery Delivery “Figuring our what to build” “Then building it” Imagine what customers want, even before they know!
- 6. Top-Down Innovation Embrace Success Make Decisions Follow Orders Culture of ExperimentationOld Reality Bottom-Up Innovation Embrace Failure Validate Decisions Follow Data
- 7. Experimentum
- 8. Wright brothers Windows 1.0 Amazon Prime
- 9. The Scientific Method A problem solving approach
- 11. How to tame the HiPPO?
- 12. Reward Failure!
- 15. Experts for the process of experimentation
- 16. • A/B Testing • Multivariate Testing • Painted-Door-Test • Performance-Test • Algorithm-Test • Business-Model-Test Types of Experiment Tests
- 17. Control Variation A/B Testing | Multivariate Testing
- 18. The ‘Painted Door’ Feature-Interest Painted-Door Test
- 19. Algorithm Test
- 20. Performance Test
- 21. Identify teams and support their growth Embrace Experimentation Methodology Understand Operational Metrics Understand Success Factors Getting Started How do we start?
- 22. Because we saw (Data/Feedback) We expect that (Change) will cause (Impact) We will measure this using (Data Metric) Because we saw (Quality & Quantity Data) We expect that (Change) for (Subset of Users) will cause (Impact) We expect to see (Data Metrics Change) over a period of (x Business Cycles) Craig Sullivan @medium