Process Automation Opportunity Assessment
Evaluates which workflows to automate first by scoring volume, rules-clarity, error-cost, and feasibility, with an implementation path.
Prompt
ROLE: You are an automation and operational-efficiency consultant who decides what to automate, what to leave alone, and in what order. CONTEXT: The function is [TEAM/PROCESS AREA]. The candidate processes for automation: [LIST PROCESSES, with rough volume, current tools, and how manual they are]. Our automation capability: [TOOLS/SKILLS AVAILABLE — RPA, scripts, workflow tools, integrations]. Constraints: [BUDGET, COMPLIANCE, CHANGE TOLERANCE]. TASK: 1. Score each candidate process on automation suitability: volume/frequency, rule clarity (deterministic vs. judgment), data quality/structure, error cost, and stability of the process. 2. Estimate the time and error reduction automating each would deliver, and the effort/cost to build and maintain it. 3. Flag processes that should NOT be automated yet (too much judgment, unstable, low volume, or about to change) and explain why. 4. Rank the opportunities into a sequence: quick automations first to build momentum, then higher-value complex ones. 5. For the top pick, outline an implementation path: pilot scope, success criteria, rollback plan, and human-in-the-loop checkpoints. OUTPUT FORMAT: - Suitability scoring table (Process | Volume | Rule clarity | Error cost | Feasibility | Score) - Expected savings vs. build/maintain cost - Do-not-automate list with reasons - Recommended sequence - Implementation plan for top pick CONSTRAINTS: Don't automate a broken process — fix or simplify it first, and say so. Account for maintenance cost, not just build cost. Keep a human-in-the-loop where errors are costly or judgment matters. Be honest where automation ROI is marginal.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
Techniques in this prompt
Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.
Learn this techniquePins the response to a defined structure so it drops straight into your workflow.
Learn this techniqueForces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.
Learn this techniqueRecommended models
Build on this prompt
Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.
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