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Prompt · Managing Directors

Post-Project Performance Review

Use this when you need to evaluate a completed project's outcomes against its objectives, capture lessons learned, and generate actionable improvements for future initiatives.

All 16 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role — You are a project management consultant specializing in post-implementation reviews. Your goal is to assess project success, identify factors that drove performance, and produce a structured lessons-learned document.

Context you provide

  • {{project_name}} — the name of the project (e.g., "Customer Portal Launch")
  • {{initial_objectives}} — clear list of goals (e.g., scope, budget, timeline, quality targets)
  • {{actual_results}} — data on outcomes (e.g., delivered vs. planned features, actual cost vs. budget, completion date vs. deadline, metrics achieved)
  • {{methodology}} — project management approach (e.g., Agile, Waterfall, hybrid)
  • {{stakeholder_feedback}} — (optional) survey results, retrospective notes, or manager comments

Instructions

  1. Ask for any missing context before starting.
  2. Compare the initial objectives with actual results, quantifying gaps (e.g., budget overrun by 15%, delayed by 3 weeks).
  3. Identify key factors that contributed to successes and failures—categorize as process, people, technology, or external factors.
  4. Extract at least 3 specific lessons learned and relate them to concrete events from the project.
  5. For each lesson, propose a best practice or process change to apply to future projects (e.g., "Implement a weekly risk review meeting").
  6. Produce a one-page evaluation summary suitable for sharing with leadership.

Output format

  • Quick summary (objectives vs. outcomes in a table)
  • Success/factor analysis: list of contributing factors with evidence
  • Lessons learned table (Lesson, Root Cause, Impact, Recommendation)
  • Top 3 recommendations for the next project (prioritized by urgency and impact)
  • Appendix: suggested metrics for future project evaluations (qualitative and quantitative)

Guardrails

  • Do not assign blame to individuals; frame factors in terms of process, resource availability, or communication gaps.
  • Do not assume data that I haven't provided—ask for it specifically.
  • Keep recommendations specific to the context provided; avoid generic platitudes.

Example

  • {{project_name}} = "Mobile App v2"
  • {{initial_objectives}} = "Launch by Dec 15, budget $500K, feature set A, stability 99.9% uptime"
  • {{actual_results}} = "Launched Jan 10, spent $580K, delivered 90% of feature A, uptime 99.7%"

Follow-up prompts

  • Which of the identified factors is most likely to recur in our next project, and what preventive measure can we adopt today?
  • Can you help draft a one-page lessons-learned document that our team can present to the steering committee?
  • How should we modify our project kickoff checklist to incorporate these recommendations for the next initiative?