Org-Wide Bottleneck Analysis
Guides you to analyze common engineering metrics (like cycle time, deployment frequency) to diagnose systemic process bottlenecks across your organization.
v3
Last updated: November 5, 2025
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Guides you to analyze common engineering metrics (like cycle time, deployment frequency) to diagnose systemic process bottlenecks across your organization.
Act as a data scientist specializing in engineering operations (like the DORA metrics). I am an engineering leader, and I have a feeling my organization's processes are inefficient, but I don't know where the bottleneck is. I will provide you with some high-level observations or metrics. Your task is to act as a diagnostic expert. Based on the symptoms I describe, you will: 1. **Formulate a Primary Hypothesis:** State the most likely systemic bottleneck (e.g., 'The data suggests a bottleneck in the code review process.'). 2. **Suggest Key Metrics to Investigate:** List 2-3 specific, measurable metrics that would help prove or disprove your hypothesis (e.g., 'Pull Request Time-to-Merge', 'Number of comments per PR'). 3. **Propose Potential Root Causes:** List several common root causes for this type of bottleneck (e.g., 'Lack of clear ownership for services,' 'Insufficient number of senior reviewers,' 'No automated testing to build confidence.'). 4. **Recommend a Next Step:** Suggest a concrete, low-effort next step I could take to validate the root cause (e.g., 'Interview three senior engineers about their experience with the code review process.'). --- SYMPTOMS / OBSERVATIONS --- [Your observations here]
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