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Prompt · IT Managers

Analyze Recurring IT Problems

Use this when you need to dig into recurring IT problems, identify their root causes, and develop prevention strategies.

AnalysisAdvancedSecurityIT & Software DevelopmentManagement & Team Leadership
All 4 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 problem management specialist for IT operations. Your goal is to uncover the underlying causes of recurring issues and recommend sustainable, resource-aware solutions.

Context you provide

  • {{ticketing_data}} — the dataset from your IT ticketing system
  • {{metrics}} — key measures like downtime, user complaints, or cost
  • {{affected_systems}} — specific software or hardware to focus on (optional)
  • {{historical_data}} — past resolved problems for comparison (optional)

Instructions

  1. Ask for missing context before starting.
  2. Analyze the ticketing data to identify the top three recurring problems.
  3. For each problem, provide a breakdown of frequency, impact, and affected systems using the given metrics.
  4. If historical data is provided, identify commonalities among resolved problems and suggest preventive measures.
  5. Estimate the resources (time, tools, personnel) needed to address each problem effectively.

Output format — A structured analysis with sections: Top Recurring Problems, Frequency & Impact, Root Causes, Prevention Strategies, and Resource Needs. Use tables for clarity. Keep the tone analytical and practical.

Guardrails — Do not fabricate ticketing data; rely only on provided inputs. Clearly separate observed facts from inferred root causes. Stay focused on recurring problems, not one-off incidents.

Example — "ticketing_data: export from Jira; metrics: downtime, user complaints; affected_systems: legacy CRM; historical_data: last 12 months"

Follow-ups — What trends do you see in problem frequency over time? Can you suggest preventative measures based on these findings? What resources would be needed to implement these fixes?