<h2>Overview</h2>Spades implements a structured estimation process designed to produce accurate, consensus-driven story point estimates:<ol class="steps-list"><li>Independent Voting: Team members vote privately using Fibonacci values</li><li>Statistical Analysis: Automatic calculation of key statistics from all votes</li><li>Result Review: Team reviews calculated results and discusses variance</li><li>Estimate Setting: One-click setting of final estimate in Linear</li></ol><hr><h2>Fibonacci Estimation System</h2><h3>Standard Fibonacci Sequence</h3>Spades uses the modified Fibonacci sequence commonly used in Agile estimation:Available Values: 1, 2, 3, 5, 8<h4>Value Meanings:</h4><ul class="accent-bullets"><li>1 Point: Trivial task, very quick implementation</li><li>2 Points: Simple task, minimal complexity</li><li>3 Points: Straightforward task with some complexity</li><li>5 Points: Moderate complexity, standard development effort</li><li>8 Points: Complex task, significant development effort</li></ul><h3>Abstention Option</h3>Abstain Vote: Available for team members who:<ul class="accent-bullets"><li>Lack sufficient context to provide meaningful estimate</li><li>Are not involved in the implementation</li><li>Prefer not to influence the estimate for other reasons</li></ul>Impact on Results: Abstain votes are excluded from statistical calculations but counted in participation tracking.<hr><h2>Individual Voting Process</h2><h3>Voting Interface</h3><h4>Keyboard Voting (Recommended):</h4><ul class="accent-bullets"><li>Ctrl+1: Vote 1 point</li><li>Ctrl+2: Vote 2 points</li><li>Ctrl+3: Vote 3 points</li><li>Ctrl+5: Vote 5 points</li><li>Ctrl+8: Vote 8 points</li></ul><h3>Voting States</h3><h4>Before Voting:</h4><ul class="accent-bullets"><li>Available Actions: All estimate buttons active</li><li>Issue Context: Full issue description and comments visible</li><li>Team Status: Can see number of expected voters</li></ul><h4>During Voting:</h4><ul class="accent-bullets"><li>Vote Submission: Immediate feedback on successful vote</li><li>Progress Tracking: "X of Y votes received" display</li><li>Wait State: Cannot change vote once submitted (prevents groupthink)</li></ul><h4>After Voting:</h4><ul class="accent-bullets"><li>Vote Confirmation: Visual confirmation of submitted vote</li><li>Waiting for Others: Progress indicator for remaining votes</li><li>Results Pending: Clear indication when waiting for full team</li></ul><h3>Voting Best Practices</h3><h4>Assessment:</h4><ul class="accent-bullets"><li>Encourage Discussion: Make estimate based on team discussion and questions</li><li>Consider Complexity: Think about technical implementation challenges</li><li>Account for Unknowns: Factor in uncertainty and potential complications</li><li>Use Past Experience: Reference similar issues estimated previously</li></ul><h4>Factors to Consider:</h4><ul class="accent-bullets"><li>Technical Complexity: Algorithm complexity, integration challenges</li><li>Requirements Clarity: How well-defined are the requirements</li><li>Dependencies: External dependencies and potential blockers</li><li>Testing Effort: Complexity of testing and validation</li><li>Documentation: Need for documentation and knowledge sharing</li></ul><hr><h2>Statistical Analysis</h2><h3>Automatic Calculations</h3>After all votes are collected, Spades automatically calculates four key statistics:<h4>Lowest Vote</h4><ul class="accent-bullets"><li>Definition: Minimum estimate from all team members</li><li>Use Case: Optimistic scenario, minimum viable implementation</li><li>Consideration: May indicate missed complexity or over-simplified approach</li></ul><h4>Median Vote</h4><ul class="accent-bullets"><li>Definition: Middle value when all votes are sorted numerically</li><li>Use Case: Most balanced estimate, reduces impact of outliers</li><li>Recommendation: Often the best choice for final estimate</li></ul><h4>Average Vote</h4><ul class="accent-bullets"><li>Definition: Mathematical mean of all votes, rounded to nearest integer</li><li>Use Case: Incorporates all team input equally</li><li>Consideration: Can be skewed by extreme outliers</li></ul><h4>Highest Vote</h4><ul class="accent-bullets"><li>Definition: Maximum estimate from all team members</li><li>Use Case: Conservative estimate, accounts for maximum complexity</li><li>Consideration: Good for risk management, may be overly cautious</li></ul><hr><h2>Result Review and Discussion</h2><h3>Analyzing Vote Patterns</h3><h4>Consensus Indicators:</h4><ul class="accent-bullets"><li>Low Variance: Votes clustered around similar values indicate good consensus</li><li>Fibonacci Adjacency: Votes on adjacent Fibonacci numbers suggest minor disagreement</li><li>Clear Clustering: Multiple votes on same values indicate shared understanding</li></ul><h4>Discussion Triggers:</h4><ul class="accent-bullets"><li>High Variance: Large spread between lowest and highest votes</li><li>Outlier Votes: Single votes significantly higher or lower than others</li><li>Bimodal Distribution: Votes split into two distinct groups</li></ul><h3>Facilitated Discussion</h3><h4>When to Discuss Further:</h4><ul class="accent-bullets"><li>Variance &gt; 2 Fibonacci Numbers: Significant spread requires discussion</li><li>Single Outliers: Understand reasoning behind significantly different estimates</li><li>Team Request: Any team member can request discussion before estimate setting</li></ul><h4>Discussion Structure:</h4><ol class="steps-list"><li>Share Reasoning: Each voter explains their estimate rationale</li><li>Identify Differences: Understand different assumptions or approaches</li><li>Clarify Requirements: Resolve ambiguities in issue description</li></ol><h3>Using AI-Generated Questions</h3><h4>Discussion Facilitators:</h4><ul class="accent-bullets"><li>Implementation Questions: AI generates relevant technical questions</li><li>Complexity Factors: Prompts for discussing various complexity aspects</li><li>Assumption Validation: Questions to validate estimation assumptions</li></ul><h4>AI Features:</h4><ul class="accent-bullets"><li>Context Aware: Questions tailored to specific issue content</li><li>Technical Focus: Emphasizes implementation and technical considerations</li><li>Discussion Starters: Helps teams have structured estimation conversations</li></ul><hr><h2>Setting Final Estimates</h2><h3>Estimate Selection Process</h3><h4>Choose From Results:</h4><ol class="steps-list"><li>Review Statistics: Examine lowest, median, average, highest values</li><li>Consider Discussion: Factor in team discussion and identified risks</li><li>Select Approach: Choose result that best represents team consensus</li><li>Click to Set: Single click on chosen result to set estimate</li></ol><h4>Selection Guidelines:</h4>Use Median When:<ul class="accent-bullets"><li>Team has good consensus (low variance)</li><li>Want balanced estimate unaffected by outliers</li><li>Standard estimation scenarios</li></ul>Use Average When:<ul class="accent-bullets"><li>Want to incorporate all team input equally</li><li>Mathematical precision is important</li><li>Variance is relatively low</li></ul>Use Highest When:<ul class="accent-bullets"><li>High uncertainty or risk factors identified</li><li>Conservative estimation approach preferred</li><li>Significant technical unknowns exist</li></ul>Use Lowest When:<ul class="accent-bullets"><li>Team identified overly complex initial assumptions</li><li>Simpler implementation path discovered</li><li>Optimistic but realistic scenario validated</li></ul>

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