name: measure-dashboard-requirements
description: Specifies requirements for an analytics dashboard including metrics, visualizations, filters, and data sources. Use when requesting dashboards from data teams, defining KPI tracking, or documenting reporting needs.
phase: measure
version: "2.0.0"
updated: 2026-01-26
license: Apache-2.0
metadata:
category: validation
frameworks: [triple-diamond, lean-startup, design-thinking]
author: product-on-purpose
Dashboard Requirements
A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.
When to Use
- When requesting a new dashboard from data/analytics teams
- To define KPI tracking for a product, feature, or team
- When formalizing ad-hoc reporting into a persistent dashboard
- Before quarterly planning to specify what visibility you need
- When onboarding stakeholders who need self-serve analytics
Instructions
When asked to specify dashboard requirements, follow these steps:
Define the Purpose
Start with the questions this dashboard should answer, not the charts it should show. What decisions will this dashboard inform? A dashboard without clear purpose becomes a vanity metrics display.
Identify the Audience
Specify who will use this dashboard, how often, and in what context. An executive weekly review has different needs than a team's daily standup board.
Specify Key Metrics
For each metric, document: name, business definition (in plain language), calculation formula, data source, and baseline/target values. Ambiguous metrics lead to misaligned dashboards.
Design Visualizations
Recommend chart types based on what the data should communicate. Time trends need line charts; comparisons need bar charts; compositions need pie/treemaps. Include dimension breakdowns.
Define Filters and Segments
Specify what drill-downs users need: date ranges, user segments, product areas, geographic regions. Anticipate the "slice and dice" questions users will ask.
Document Data Sources
Identify where data comes from and any known data quality issues. Note latency requirements—does the dashboard need real-time data or is daily refresh sufficient?
Set Permissions and Access
Determine who can view what. Some metrics may need restricted access. Consider both security requirements and organizational politics.
Output Format
Use the template in references/TEMPLATE.md to structure the output.
Quality Checklist
Before finalizing, verify:
Examples
See references/EXAMPLE.md for a completed example.
1---2name: measure-dashboard-requirements3description: <!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->4---5
6<!-- PM-Skills | https://github.com/product-on-purpose/pm-skills | Apache 2.0 -->
7---
8name: measure-dashboard-requirements
9description: Specifies requirements for an analytics dashboard including metrics, visualizations, filters, and data sources. Use when requesting dashboards from data teams, defining KPI tracking, or documenting reporting needs.
10phase: measure
11version: "2.0.0"
12updated: 2026-01-26
13license: Apache-2.0
14metadata:
15 category: validation
16 frameworks: [triple-diamond, lean-startup, design-thinking]
17 author: product-on-purpose
18---
19# Dashboard Requirements
20
21A dashboard requirements document specifies what questions a dashboard should answer, what metrics it displays, and how data should be visualized. Clear requirements help data teams build dashboards that actually inform decisions rather than just displaying numbers.
22
23## When to Use
24
25- When requesting a new dashboard from data/analytics teams
26- To define KPI tracking for a product, feature, or team
27- When formalizing ad-hoc reporting into a persistent dashboard
28- Before quarterly planning to specify what visibility you need
29- When onboarding stakeholders who need self-serve analytics
30
31## Instructions
32
33When asked to specify dashboard requirements, follow these steps:
34
351. **Define the Purpose**
36 Start with the questions this dashboard should answer, not the charts it should show. What decisions will this dashboard inform? A dashboard without clear purpose becomes a vanity metrics display.
37
382. **Identify the Audience**
39 Specify who will use this dashboard, how often, and in what context. An executive weekly review has different needs than a team's daily standup board.
40
413. **Specify Key Metrics**
42 For each metric, document: name, business definition (in plain language), calculation formula, data source, and baseline/target values. Ambiguous metrics lead to misaligned dashboards.
43
444. **Design Visualizations**
45 Recommend chart types based on what the data should communicate. Time trends need line charts; comparisons need bar charts; compositions need pie/treemaps. Include dimension breakdowns.
46
475. **Define Filters and Segments**
48 Specify what drill-downs users need: date ranges, user segments, product areas, geographic regions. Anticipate the "slice and dice" questions users will ask.
49
506. **Document Data Sources**
51 Identify where data comes from and any known data quality issues. Note latency requirements—does the dashboard need real-time data or is daily refresh sufficient?
52
537. **Set Permissions and Access**
54 Determine who can view what. Some metrics may need restricted access. Consider both security requirements and organizational politics.
55
56## Output Format
57
58Use the template in `references/TEMPLATE.md` to structure the output.
59
60## Quality Checklist
61
62Before finalizing, verify:
63
64- [ ] Purpose is framed as questions to answer, not charts to build
65- [ ] All metrics have clear definitions and calculation formulas
66- [ ] Data sources are identified and accessible
67- [ ] Visualization choices match the type of insight needed
68- [ ] Filters enable the drill-downs users will want
69- [ ] Refresh frequency matches decision-making cadence
70
71## Examples
72
73See `references/EXAMPLE.md` for a completed example.
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