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Finding the First Slice
- 1. FINDING THE FIRSTSLICE How to get early value, learning, and risk-mitigation on every project
- 2. THE OUTPUT OFFEATURE MINING It’s designed to get you the first one or two… MINIMUM Marketable Features …for a big idea. Ok. What’s an MMF? MMF = The smallest change in system behavior sufficient to cause a desired business impact
- 3.
- 4. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Business Perspective Technical Perspective+
- 5. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Step 2: Name the thing you're slicing We're trying to find some early slices through ________.
- 6. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Step 2: Name the thing you're slicing Step 3: Brainstorm the lists
- 7.
- 8. Value Where’s the value? Whatmakes this worth doing? What will we get out of it? What will our customers get out of it? How will it make us money?
- 9. EXAMPLE: WEEKLY SALESREPORTING • Stores can respond to changes faster than the current monthly reporting allows • Management can help low-performing stores before problems get too bad • IT won't get requests for ad hoc, mid- month sales reports as often Where’s the value?
- 10. SizeWhat makes this big? Whyisn't this just something we'd knock out in an afternoon?
- 11. EXAMPLE: WEEKLY SALESREPORTING • 1000s of stores • Dozens of regions • Different regions report sales differently • Notifications • Performance—running reports much more often than before What makes this big?
- 12. Risk Where’s the risk? What couldgo wrong that would cause this to fail?
- 13. EXAMPLE: WEEKLY SALESREPORTING • Stores don't get the info they need in the reports so they don't use them • We can't get performance to an acceptable level for weekly runs • We can't handle the differences between the regions in an automated way Where’s the risk?
- 14. Uncertainty Where’s the uncertainty? What questions dowe need to answer in order to be successful?
- 15. EXAMPLE: WEEKLY SALESREPORTING • What sorts of things would happen to sales that stores would want to respond to on a weekly basis? • Where's the performance bottleneck in the current monthly reports? Where’s the uncertainty?
- 16. Revealed by asking aboutrisk Revealed by asking about uncertainty Revealed either way
- 17.
- 18. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Step 2: Name the thing you're slicing Step 3: Brainstorm the lists Step 4: Filter the lists
- 19. Value Size Risk Uncertainty What'sthe value that makes all the others relatively unimportant? What contributes disproportionately to the size of the effort? Which risk is scariest or most likely to derail the project? Which uncertainty seems most critical to resolve?
- 20. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Step 2: Name the thing you're slicing Step 3: Brainstorm the lists Step 4: Filter the lists Step 5: Brainstorm slices
- 21. EXAMPLE: WEEKLY SALESREPORTING • Focus on one region • Focus on one store • Create weekly reports manually for a few weeks and see how stores use them • etc. What are some possible slices that get us value, risk- mitigation, and/or learning without all the size?
- 22. FEATURE MINING STEP-BY-STEP Step1: Get the right people in the room Step 2: Name the thing you're slicing Step 3: Brainstorm the lists Step 4: Filter the lists Step 5: Brainstorm slices Step 6: Name the feature(s) and get started
- 23. YOUR TURN Practice FeatureMining with a work or personal project of your own
- 24. WANT MORE? Check outat agileforall.com/8020-PO Use promo code MHA16 for 20% off through April