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Find the decisions your data product supports
Data products succeed when they help someone make a better decision. Start from the decisions, not the data.
About 3-5 daysEvergreenLast reviewed 5 November 2026
Who this applies to
- Skills it builds
- Data and measurementDiscovery and research
- PM types
- Data
- Product types
- All
- Starting points
- All
- Ways of working
- All
- Experience
- All
- Size of organisation
- All
Steps, by experience
Beginner (under 1 year)
- List who will use the data product and what decisions they make.
- For each decision, ask what information they use now and what is missing.
- Ask how often they decide and how fast they need the data.
- Find out what a wrong decision costs.
- Prioritise the decisions with the most value.
Intermediate (1 to 4 years)
- Map users, decisions and information needs.
- Assess frequency, timeliness and value.
- Prioritise decisions to support.
Experienced (5+ years)
- Link decisions to business outcomes.
- Design for decisions that can be automated.
- Measure success by better decisions, not usage.
Who can do this
Owner: Product manager
Can be delegated to
- User Researcher: Interview decision-makers
- Data Analyst: Map current data use
Reviewed by: Data Analyst
Tool examples
- Miro
- Map each user, their decisions and the data they need.
- Notion
- Keep a decision catalogue with owners and value.
Definition of done
- Users and decisions mapped
- Information needs captured
- Priority decisions chosen
Common pitfalls
- Starting from available data
- Building dashboards nobody uses
- Ignoring how fast data is needed
If you lead the team
What good looks like: Data products start from the decisions people need to make, not from the data that happens to be available.
Ask your PM
- Which decisions will this help, and who makes them?
- How will we know decisions got better?
Warning signs
- The plan is a list of datasets and dashboards.
- No named person is waiting for this to make a decision.