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The system automatically calculates and displays the distribution type based on your data. This helps you understand the predictability of your and characterize the delivery process.

Distribution types we support:We distinguish the next distribution types:

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titleRight-Skewed Thin-Tailed Distribution
  • Insight: The process is non-linear but relatively robust, with a thin-tailed distribution. This indicates that while there are some delays, they are not extreme, leading to decent predictability with lower risk of significant delays.

  • Recommendation: Continue monitoring and optimizing processes to ensure delays remain minimal. Focus on maintaining this thin tail by ensuring that minor issues are resolved quickly and do not escalate. Regular retrospective sessions and minor process adjustments can help keep the workflow smooth and predictable.

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titleRight-Skewed Fat-Tailed Distribution
  • Insight: The process is non-linear and fragile, with a fat-tailed distribution. This indicates poor predictability, as a few tasks are taking much longer than expected, significantly impacting overall cycle/lead times and increasing risk.

  • Recommendation: Identify the root causes of these significant delays, such as bottlenecks or resource constraints, and address them directly. Implement strategies like backlog refinement, better resource allocation, and continuous monitoring to reduce the length and impact of the tail, thereby improving predictability and overall process performance.

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titleLeft-Skewed Thin-Tailed Distribution
  • Insight: The process is slightly non-linear but robust, with a thin-tailed distribution. Most tasks are completed in a reasonable time, with minimal risk of delays, though some early stages might cause slight delays that are quickly resolved.

  • Recommendation: Focus on improving the efficiency of early stages to prevent any initial delays from impacting the flow. By refining the early processes and maintaining a strong definition of ready, you can ensure that tasks flow smoothly and consistently, keeping the tail thin and predictability high.

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titleLeft-Skewed Fat-Tailed Distribution
  • Insight: The process is non-linear and fragile, with a fat-tailed distribution. Early-stage delays lead to unpredictability, with some tasks experiencing significantly longer lead times, increasing risk.

  • Recommendation: Streamline and strengthen the initial stages of the workflow by improving collaboration, refining the definition of ready, and ensuring clear communication and requirements from the start. Addressing these early delays is key to preventing them from extending the tail, which will enhance overall process predictability.

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titleGaussian (Thin-Tailed) Distribution
  • Insight: The process is linear and robust, with a thin-tailed distribution, indicating high predictability and stability. Most tasks are completed within a narrow timeframe, suggesting a well-functioning process with minimal risk of delays.

  • Recommendation: Maintain the current level of process control and predictability by continuing regular retrospectives and minor optimizations. Keep focusing on continuous improvement to ensure the process remains robust and capable of handling any minor variations without significant impact on cycle/lead times.

Compact view

Compress those long-tail data points into a single, easy-to-digest area. Keep your charts clear, concise, and clutter-free.

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