ThinkWithPrompt by SynotticThinkWithPrompt

Triage and prioritize my team's analytics request queue

A fair, transparent way to rank incoming data requests by value and effort, with replies for the ones you push back on.

Productivity & PlanningFew-ShotStandardData & AnalyticsProductivityAnalyzeFill-in Template

The prompt

Help me triage and prioritize my team's queue of analytics and data requests. Requests: [PASTE list: requester, team, request, date asked, any stated deadline] Team capacity: [people and hours available this week or sprint] Current priorities or OKRs: [company or team goals] Recurring pain points: [e.g. "lots of one-off pulls", "urgent asks from execs", "requests already answered by a dashboard"] Steps: 1. Classify each request: answerable by existing dashboard or self-serve, quick data pull, analysis, new dashboard or pipeline, or unclear. 2. Score each on: decision value (what decision it informs and its size), urgency (real deadline vs. preference), effort (t-shirt size), and alignment with priorities. Show the scoring rule so it is transparent. 3. Spot duplicates and requests that can be bundled. 4. For unclear requests, write the one question that would clarify them. 5. Recommend what to do now, schedule, redirect to self-serve, or decline. Return: - A prioritized table: Request | Type | Value | Urgency | Effort | Score | Action | Notes. - A plan for this week that fits within capacity. - Short, friendly replies for redirected or declined requests that explain why and offer an alternative. - 3 process improvements to reduce repeat requests (e.g. intake form fields, a FAQ of where to find common numbers, office hours). Do not invent deadlines or values; mark unknowns as [ASK].

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • people and hours available this week or sprint
  • company or team goals
  • ASK

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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