HKSM
Affinity Estimation
A rapid, collaborative way to size many user stories at once by grouping them into relative categories. Teams place items into buckets such as small, medium, large, or into story point groupings to reflect comparative effort. The approach is easy to run, highly visible, and promotes shared understanding across the team.
Key Points
- Teams quickly sort user stories into size buckets (small/medium/large or story points) based on relative effort.
- Often begins with a silent sort, followed by brief discussion to reconcile differences and outliers.
- Uses a few reference stories to calibrate consistency; focuses on relative sizing rather than hours.
- Fast and transparent; provides a first-pass estimate for forecasting, roadmaps, and release planning.
Example
During backlog refinement, a product team needs rough sizes for 120 new user stories. The facilitator posts buckets labeled 1, 2, 3, 5, 8, and 13. Team members silently place each story under a bucket, then discuss only the items with disagreements. Within an hour, the backlog has consistent relative sizes that the team will refine later for near-term work.
PMP Example Question
During a backlog grooming session, the team must quickly assign relative sizes to 200 user stories without deep debate on each item. Which technique should the Scrum Master recommend?
- Planning Poker with full discussion for every story
- Affinity Estimation by sorting stories into size buckets
- Wideband Delphi with multiple anonymous rounds per story
- Three-point estimation (optimistic, most likely, pessimistic) for each story
Correct Answer: B — Affinity Estimation
Explanation: Affinity Estimation enables fast, collaborative grouping of many user stories into relative size categories, making it the best fit when speed and transparency are needed.
