T-Shirt Sizing
T-shirt sizing is an agile estimation technique that uses relative size categories (XS, S, M, L, XL) to quickly classify the effort or complexity of work items without precise numerical estimates.
Explanation
T-shirt sizing is a quick, intuitive estimation technique where work items are categorized into relative size buckets using familiar labels: Extra Small (XS), Small (S), Medium (M), Large (L), and Extra Large (XL). Some teams add XXL for very large items. This technique is particularly useful for high-level estimation when precise numbers are not yet needed or practical.
The technique works by having the team agree on a reference item for one size category, then comparing other items relative to that reference. For example, the team might agree that a particular user story is a Medium, then categorize other stories as larger or smaller relative to that benchmark. T-shirt sizing is faster than techniques like planning poker and works well for initial backlog sizing and release planning.
T-shirt sizes are often later converted to story points or other numerical estimates when more precise planning is needed. The technique excels at getting an entire team aligned quickly on relative effort and is particularly useful during product roadmap planning and initial backlog refinement.
Key Points
- •Uses XS, S, M, L, XL categories for relative sizing
- •Faster than planning poker for high-level estimation
- •Uses a reference item as a sizing benchmark
- •Ideal for initial backlog sizing and release planning
Exam Tip
T-shirt sizing is best for quick, high-level relative estimation. If the question describes a need for fast, rough sizing of many items, T-shirt sizing is likely the answer.
Frequently Asked Questions
Related Topics
Agile Estimation Techniques
Agile estimation techniques are lightweight methods used by agile teams to estimate the size, effort, or complexity of work items, including story points, planning poker, T-shirt sizing, and relative estimation.
Wideband Delphi
Wideband Delphi is a consensus-based estimation technique that extends the Delphi method by adding team discussion between anonymous estimation rounds to improve estimate accuracy.
Dot Voting
Dot voting (multi-voting) is a group decision-making technique where participants are given a limited number of votes (dots) to allocate among options, quickly revealing group priorities.
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