Using Planning Poker for Bug Estimation

Your bug backlog is growing. Some issues have been sitting there for months. Others surfaced in production yesterday. Your team needs to decide what to fix, when, and how much capacity to reserve for bug work versus new features.

Estimating bugs presents unique challenges compared to features. Bugs lack context, carry time pressure, and involve unknowns that make traditional estimation difficult.

In this guide, you'll learn when and how to use planning poker for bugs, how to separate severity from complexity, and when to skip estimation and just fix the issue. The goal isn't perfect estimates—it's informed decisions about technical debt while keeping your team moving.

Why Estimate Bugs?

Whether to estimate bugs divides agile teams. Some argue bugs should be estimated like features. Others say bugs are too unpredictable and time-sensitive for estimation.

The truth? Bug estimation serves specific purposes when done thoughtfully.

Capacity Planning and Sprint Commitments

Estimating bugs reveals how much capacity goes to defects versus features. If bugs consistently consume 30% of sprint capacity, that's crucial for roadmap planning and stakeholder communication.

Without estimates, bug work becomes invisible in velocity calculations. Your team completes 15 story points instead of their usual 25—until you realize 10 unestimated bugs ate the difference.

Making Prioritization Decisions

Not all bugs deserve immediate attention. Some are minor inconveniences; others block critical workflows. Estimating lets you weigh effort against severity and business impact.

A severity 2 bug taking 1 point to fix? Easy decision. A severity 3 bug requiring 13 points of refactoring? That deserves strategic consideration—fix now, schedule later, or accept as technical debt?

Building Technical Debt Visibility

Estimated bugs create quantifiable technical debt. Stakeholders can see 89 story points of known issues, supporting conversations about quality time versus new features.

Planning poker discussions surface systemic issues. Consistently high estimates for bugs in one module? That signals deeper architectural problems worth addressing.

Bugs vs Features: Key Differences in Estimation

Estimating bugs requires adjustments from feature estimation. Understanding these differences prevents common pitfalls.

Context Loss and Uncertainty

Feature requirements are fresh; context is clear. Bugs aren't. A bug reported three months ago represents code written six months ago—context has evaporated. The original developer may have left.

Fresh bugs discovered during current work are easy to estimate—the code's in working memory. Older bugs carry exponential uncertainty. Simple logic error or design flaw? Two-line fix or three-module refactor?

These unknowns create divergent estimates. Votes ranging from 2 to 20 points reflect legitimate uncertainty that needs discussion.

Time Sensitivity vs Estimation Overhead

Features can wait for sprint planning. Critical production bugs can't. If payment processing breaks or your app crashes, fix it now—don't schedule a planning poker session.

Teams need judgment about when estimation adds value versus when it delays necessary fixes.

Understanding Severity vs Complexity in Bug Estimation

The biggest challenge? Separating severity from complexity. Research from Microsoft shows these don't correlate as strongly as expected—confusing them leads to poor prioritization.

Severity: Impact vs Effort

Severity reflects the impact a bug has on users and business:

Severity 1 (Critical): Complete system failure, data corruption, security breach. Production is down or severely compromised.

Severity 2 (High): Major feature broken or performing incorrectly. Significant user impact, but workarounds exist.

Severity 3 (Medium): Feature works but has noticeable issues. User experience degraded, limited business impact.

Severity 4 (Low): Minor cosmetic issues, edge cases, or "nice to have" improvements. Minimal user impact.

Severity is about consequences, not effort. A critical bug might take 15 minutes to fix. A low severity bug might need days of refactoring.

Complexity: What Planning Poker Measures

Planning poker measures the effort to fix a bug:

• Diagnostic time to find root cause
• Technical difficulty of code changes
• Testing and regression requirements
• Risk of introducing new issues
• Cross-system dependencies

High-severity bugs don't predict high complexity. Critical bugs can be trivial fixes or architectural nightmares.

Why Planning Poker Helps

Planning poker surfaces the difference between "how bad is this" and "how hard is this to fix"—crucial for smart prioritization.

Consider a severity 2 bug with votes of 2 and 13 points. Discussion reveals the obvious fix is simple but risky, while the proper fix requires refactoring but prevents future bugs.

Without structured conversation, teams assume high-severity = high effort—leading to poor sprint planning.

Bug-Specific Estimation Scales for Planning Poker

Standard planning poker scales work for bugs, but some teams adapt for bug-specific needs.

Modified Fibonacci for Bug Work

Many teams compress the Fibonacci scale for bugs: 1, 2, 3, 5, 8, 13. Anything requiring 21+ points should be broken down or treated as a refactoring project.

Some add "0" or "XS" for trivial bugs—typos, string updates, color changes. An explicit "minimal effort" option streamlines sessions with obvious quick fixes.

T-Shirt Sizing for Rapid Triage

For bug triage processing many defects, t-shirt sizing (XS, S, M, L, XL) offers speed over precision.

Fix XS and S bugs opportunistically during feature work. Schedule M bugs for sprint planning. Treat L and XL bugs as technical debt projects needing scoping.

The "Fix It or Estimate It" Threshold

If a bug takes under 30 minutes to fix, just fix it. Only estimate bugs requiring meaningful sprint capacity. Don't let process overhead exceed fixing effort.

Using Planning Poker for Bug Triage and Prioritization

Bug triage is where planning poker delivers value—helping teams assess backlog, estimate effort, and prioritize.

Structuring a Bug Triage Session

Schedule regular sessions separate from sprint planning—30 minutes weekly or 60 minutes biweekly. The product owner prepares unestimated bugs likely needing fixes.

For each bug, summarize what's broken, user impact, severity, and reproduction steps. Run planning poker as usual: independent consideration, simultaneous reveal, discuss outliers, converge. The key difference? Acknowledge uncertainty—"we need to investigate first" is valid.

Combining Severity and Effort in Prioritization

After estimating, plot bugs on a severity-versus-complexity matrix:

High Severity, Low Complexity: Fix immediately. High-ROI fixes hurting users without requiring significant effort.

High Severity, High Complexity: Need strategic decisions. Temporary workaround? Technical spike? Formal project?

Low Severity, Low Complexity: Opportunistic fixes when already working in relevant code.

Low Severity, High Complexity: Often accepted technical debt unless causing bigger future problems.

Facilitating Productive Discussions

Set time limits—3 minutes per bug. Can't estimate it? Assign investigation and revisit later. When estimates diverge, ask high and low voters to explain. Both perspectives help alignment.

When to Skip Bug Estimation Entirely

The best use of planning poker? Knowing when not to use it. Skip estimation here:

Critical Production Issues

Application down? Database corrupted? Revenue bleeding? Fix it now. Retrospectively estimate for velocity if needed, but don't delay critical fixes for process.

Severity 1 bugs demand immediate response—no estimation changes that.

Obviously Trivial Fixes

One-line change? Typo? Configuration update? Planning poker overhead exceeds fixing effort. Empower teams to fix obvious issues without ceremony.

Many use the "found it while working? Just fix it" rule, preventing small bug accumulation.

Time-Boxed Bug Squashing

Periodic "bug bash" sessions—fixing many small bugs in a timebox—don't need individual estimates. Reserve sprint capacity (maybe 10%) for unestimated fixes and track quality improvements.

When Investigation is Required First

Can't estimate because root cause is unknown? Assign an investigation spike. Time-box 1-4 hours for reproducing, reading code, and understanding. Then run planning poker with real information, not guesses.

Best Practices for Bug Estimation Sessions

These practices maximize value while minimizing time:

Prepare Context Before the Session

Gather relevant information upfront: reproduction steps, error logs, user reports, screenshots, investigation notes. More context = better estimates.

Create a bug template: what's broken, how to reproduce, severity, affected users, known workarounds. Standardization drives efficient discussions.

Include Testing and Verification Effort

Bug estimates should cover investigation, fixing, testing, and verification. Someone must verify the fix across scenarios, run regression tests, and coordinate QA acceptance.

Common mistake? Estimating only the code change. Bugs need thorough testing—you're fixing something already broken once.

Track Estimation Accuracy for Learning

Compare actual effort to estimates after fixing bugs. Five-point bugs consistently taking 2 or 8 points? Calibrate future estimates accordingly.

Teams systematically underestimate (forgetting diagnostic time) or overestimate (too conservative). Tracking reveals patterns.

Use Tools That Support Both Features and Bugs

Planning Poker handles features and defects seamlessly—estimate stories, bugs, technical debt, and spikes with the same collaborative process.

Switching between features and bugs in one session reduces context switching and maintains focus.

Finding the Right Balance for Your Team

Bug estimation isn't all-or-nothing. Effective teams develop nuanced approaches—estimate some bugs, pragmatically skip others.

A reasonable middle ground: estimate bugs consuming meaningful sprint capacity, skip quick fixes, handle critical issues immediately, use planning poker for triage where prioritization matters.

Planning poker's goal? Shared understanding and informed decisions, not perfect estimates. Use it to understand severity versus complexity, identify high-priority fixes, and make strategic technical debt decisions.

Your bug backlog represents quality issues and learning opportunities. Discussions about why bugs happened, their complexity, and whether to fix them build team knowledge and improve practices. For more on getting your team aligned, see how to handle disagreements during estimation.

Start by estimating bugs most important to roadmap decisions. Track whether estimation adds value or creates overhead. Adjust based on what you learn. The right strategy depends on your context, quality requirements, and stakeholder expectations.

According to the Scrum Guide, product backlogs should be ordered by priority, considering value, risk, and dependencies—bug estimation helps teams make these determinations systematically.

Ready to try planning poker for your bug backlog? Planning Poker provides streamlined feature development and technical debt management, with real-time collaboration for in-person and remote teams. Create a bug triage session and see how collaborative estimation improves your quality approach.

Remember: bugs are feedback about system quality. Estimation is one tool for responding. Use it where it helps, skip where it doesn't, and always prioritize fixing important issues over perfectly estimating them.