When Everyone Has a Dashboard and No One Decides

More dashboards do not mean more decisions

The democratisation of data analysis has, in many ways, been good news: today any team lead can build their own dashboard without depending on a central department. The problem shows up when that freedom comes with no rules about who decides what, using which data, and under which criteria.

• The more dashboards an organisation has, the easier it becomes for none of them to translate into an actual decision.
• Data self-service without governance doesn't distribute power, it distributes confusion.
• Democratising access to data isn't the same as democratising good judgement about how to read it.

Every area with its own version of the truth

It's common to find organisations where every area head has their own panel of indicators, built with a different tool, using different definitions for the same metrics, with nobody quite sure who's responsible for acting on what. The result is a leadership meeting where everyone defends their own number, and none of them quite match the one next to it.

Dashboard proliferation was sold as a way to bring data closer to decision makers. In practice, without clear rules, it's produced the opposite effect: every area has its own version of the truth, and meetings turn into debates about which panel is correct instead of conversations about what to do with what it shows.

• Leadership meetings where every area presents a different number for the same indicator.
• Personal dashboards that nobody else in the organisation knows how to read or update.
• Decisions delayed because nobody can agree on which data point is the right one.

Freedom to explore, discipline to decide

We don't think the answer is re-centralising all analysis into a single team, that would undo exactly what democratisation was meant to achieve. We think what's needed is governance: clear rules on shared definitions, ownership of each indicator, and who has the authority to decide with it.

A good self-service data system combines freedom and discipline: anyone can explore and build their own views, but there's a shared layer of definitions and key indicators nobody can reinterpret on their own, and one accountable owner for every important decision that leans on that data.

Four rules to govern data self-service

Bringing order to data self-service doesn't mean restricting access, it means agreeing on the rules of the game before handing out the ball.

1. Define a shared dictionary of key indicators
   • Agree on a single definition for the metrics that genuinely matter at organisational level.
   • Allow customised views on top, but never different definitions of the same indicator.
2. Assign an owner to every critical indicator
   • Someone needs to make sure that data point is reliable, up to date and consistently interpreted.
   • Without an owner, every indicator ends up with as many versions as people looking at it.
3. Separate exploring from deciding
   • Anyone can use a dashboard to explore and ask questions.
   • Important decisions should always rest on the shared source, not a personalised view.
4. Periodically review which dashboards are still useful
   • Retire panels nobody consults or that have become outdated.
   • Fewer, well governed dashboards generate more decisions than many scattered ones.

Before celebrating how many panels you have

Before celebrating how many dashboards your organisation has today, it's worth asking:

• Do all your area heads use the same definition for your most important indicators?
• Could you say who is responsible for the reliability of each key data point you use to decide?
• How many meetings have been spent arguing over which number is correct instead of what to do with it?
• Are there dashboards nobody else would know how to read if that person left tomorrow?
• Do you have more indicator panels than real decisions being made from them?

Clarity on who decides and on what basis

This isn't about having less data or fewer tools. It's about making sure access to information always comes with clarity about who decides, and on what basis.

If you'd like to review how data access is currently governed in your organisation, let's talk. Sometimes simply sorting out the definitions is enough to get decisions flowing again.