Scrum Poker vs. Affinity Estimation: Which One to Choose?

Agile teams have access to a growing toolkit of estimation techniques. Two of the most widely used are planning poker (also known as scrum poker) and affinity estimation. While both techniques aim to help teams size their work relative to other items, they take very different approaches. Choosing between them — or knowing when to combine them — can have a significant impact on your team’s efficiency and estimation quality.

How Planning Poker Works

Planning poker is a structured, card-based estimation technique. Each team member holds a set of cards bearing values from the Fibonacci sequence (1, 2, 3, 5, 8, 13, 21, and so on). The facilitator reads a user story aloud, team members privately select the card they believe represents the story’s complexity, and then everyone reveals their cards simultaneously.

When estimates diverge significantly, the team discusses the reasoning behind each perspective. This continues until consensus is reached or a reasonable compromise is agreed upon. The process is deliberate and thorough, making it particularly effective for teams that need high-confidence estimates for complex or high-priority work.

How Affinity Estimation Works

Affinity estimation takes a more fluid, visual approach. User stories are written on sticky notes or cards, and the team silently sorts them into groups based on relative size — typically labeled with broad categories like “small,” “medium,” “large,” and “extra large,” or using a simple numbered scale.

There is no lengthy deliberation for each individual story. Instead, the team works quickly, moving items around until everyone is satisfied with the groupings. Disagreements are resolved through brief discussion, and the entire backlog can often be estimated in a single session. Affinity estimation trades precision for speed.

Key Differences

Speed and scalability: Affinity estimation is dramatically faster than planning poker. For a backlog of 50 or 100 stories, affinity estimation might take an hour; planning poker for the same set could take several hours across multiple sessions. If you need to estimate a large backlog quickly — such as during a project kickoff or a quarterly planning event — affinity estimation has a clear advantage.

Accuracy and depth: Planning poker encourages deeper engagement with each user story. Because team members must commit to a specific estimate and justify disagreements, the process surfaces assumptions and risks that affinity sorting might miss. For high-stakes features or technically complex stories, this depth is often worth the additional time investment.

Participation and engagement: Planning poker requires every team member to vote independently before the group discussion, which helps prevent dominant voices from anchoring the team’s estimates. Affinity estimation, especially when done silently, also mitigates some of this bias — but the less structured format can allow quieter team members to defer to others without raising their concerns.

Output granularity: Planning poker produces specific story point values for each item. Affinity estimation produces groupings, which must then be translated into point values if the team wants to track velocity. This extra step adds ambiguity that some teams find frustrating.

When to Use Each Technique

Choose planning poker when:

• Accuracy matters more than speed
• Stories are complex or interdependent
• The team needs deep shared understanding of the work
• You are estimating a manageable set of high-priority items

Choose affinity estimation when:

• You need to estimate a large backlog in a short time
• You are in early project planning and rough groupings are sufficient
• The team is comfortable with broad relative sizing
• Sprint planning precision is less critical at this stage

Hybrid Approaches

Many experienced agile teams use both techniques in combination. Affinity estimation is used for initial backlog grooming — quickly sorting a large number of stories into rough buckets. Planning poker is then applied to the stories that are moving into the next sprint or two, adding precision to items that will be worked on imminently.

This layered approach captures the speed benefits of affinity estimation for the broad backlog while ensuring that near-term work is estimated with the rigour that planning poker provides.

Conclusion

Neither planning poker nor affinity estimation is inherently superior. The right choice depends on the size of your backlog, how soon the work will be delivered, and how much precision your team and stakeholders require. Understanding the trade-offs of each method — and being willing to combine them when appropriate — will serve your team far better than committing rigidly to one approach.