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Data & AnalyticsMarch 20266 min read

Beyond Dashboards: Building a Data-Driven Operating Model

The companies pulling ahead aren't the ones with the most dashboards. They're the ones whose decisions changed because of them.

Nikola Ristic

Partner · Digital & Data Practice

A dashboard nobody's decision changed because of is a sunk cost in green text.

Most data programs we audit deliver more dashboards than the company can read. The leadership team is not under-served by reporting; they are drowning in it. The interesting question is not how to build more — it is how to make any of it change a decision.

The dashboard fallacy

There is a quiet assumption in most data investment cases: if we surface the number, the right behaviour will follow. It almost never does. We have walked into companies with 400+ Power BI reports, and into companies with two well-built dashboards. The latter group is consistently making faster, better decisions.

Reporting is a means. The thing being measured by a serious data program is not coverage. It is decision velocity.

What 'data-driven' actually means at the operating-model layer

When we say a company is data-driven, we mean three specific things. First, every recurring executive decision has a number attached to it that the team agrees is the right number. Second, that number lives in one place that everyone trusts. Third, when the number moves the wrong way, somebody is on the hook to explain it within the same week.

Notice what is not on that list: machine learning, real-time streaming, modern data stack, lakehouse architecture. Those are sometimes useful. They are not the definition.

Three diagnostic questions

Before we recommend any new investment in a data program, we ask the leadership team three questions about every existing dashboard:

  1. 1Whose decision changes when this number moves? If the answer is 'nobody's', the dashboard is a sunk cost and should be retired.
  2. 2When was the last time you actually used this number to choose between two paths? If you cannot remember, the dashboard is theatre.
  3. 3Who is accountable when this number is wrong? If the answer is 'the data team', the operating model is broken — accountability for a number cannot live downstream of the people who consume it.

Accountability for a number cannot live downstream of the people who consume it.

The operating-model shift

Companies that get this right tend to make a structural change in how they consume data. Instead of a central data team that produces reports for everyone, they organize around decision domains. The pricing team owns the pricing scoreboard. The supply chain team owns the supply chain scoreboard. The data team enables — it does not produce.

This sounds obvious until you try it. The hard part is not the technology. It is the political move of telling the central reporting team they are now infrastructure, not output.

What good looks like

In a healthy operating model, the executive team can name the five numbers that run their business without looking. There is one place those numbers live. Every recurring meeting starts with them. When one of them is wrong, somebody is uncomfortable in the next 24 hours.

Everything else — the platforms, the lakehouse, the AI initiatives — is in service of that. If your data investment cases cannot be traced back to a specific decision that will change because of it, the investment is not yet ready.

Written by

Nikola Ristic

Partner · Digital & Data Practice

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