System BuildIntermediateGeneralManufacturingEngineering

BI Management Dashboard Planning Prompt

Starts from 'decision questions' to plan a management dashboard, avoiding a pile of useless metrics.

Audience: Executive management, IT · Last updated 2026-07-17
Contents

Scenario

Starts from 'decision questions' to plan a management dashboard, avoiding a pile of useless metrics.

Applicable Industry or Company Size

  • General
  • Manufacturing
  • Engineering

Preparation Before Use

  • Current KPI status.
  • A list of data sources.

Variable Reference

VariableDescription
[Company Name]Your company's official name
[Target Users]e.g., general manager, sales manager, plant manager
[3 Key Decision Questions]e.g., Are we on track this month? Which product line's margin is declining?

Full Prompt

Prompt
You are a BI dashboard design consultant. Plan a management dashboard for the following audience.

[Background]
- Company: [Company Name]
- Target Users: [Target Users]
- 3 Key Decision Questions: [3 Key Decision Questions]

[Output]
1. For each decision question, list 3–5 core metrics and their data sources.
2. Dashboard layering: high-level (1 page), drill-down (3–5 pages).
3. Recommended chart types with rationale.
4. Data refresh frequency (real-time / daily / weekly).
5. Data-quality risks and governance recommendations.
6. An outline of a user-training plan.

[Judgment Criteria] Avoid producing a "show everything" dashboard; every metric must tie to a concrete decision or action.

[Handling uncertain information]
If any of the variables below have not been filled in or the information is insufficient, list the missing fields directly and ask the user — do not assume or fabricate data.

[Prohibited]
- Do not fabricate statistics, regulation numbers, certification names, or client case studies.
- When professional judgment is insufficient, explicitly mark "requires human confirmation" rather than inferring on your own.

[Final self-check]
After producing the output, list a self-check at the end covering: (1) whether any fabricated numbers, regulations, standards, or client names were used; (2) whether any unfilled but important variable was ignored; (3) whether assumptions are clearly labeled.

Usage Steps

  1. Fill in the variables.
  2. Confirm source feasibility with data engineers.
  3. Build an MVP first, then expand.

Example

A sales manager's dashboard typically focuses on pipeline value, projected achievement rate, and top-account activity.

Common Mistakes

  • Moving all ERP reports into BI without redesigning them.

Cautions

  • Data quality is the foundation of dashboard trust.
Last updated 2026-07-17

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