Shadow BI is a Coping Strategy

The Good News: Every Data Team I’ve encountered in over a decade in the data space is motivated to quickly and reliably deliver useful data products to their stakeholders.

The Bad News: Despite this, there are unsatisfied stakeholders everywhere. The most common complaint? It’s difficult—especially with centralized Data Teams—to get the necessary priority for analyses and reports. The demand for insights almost always exceeds the capacity of the teams, leaving important tasks unaddressed.

This problem cannot be solved through prioritization alone. Good prioritization ensures that more important tasks take precedence. But what happens to the tasks that never make the cut? They don’t automatically become irrelevant just because there isn’t enough capacity to address them!

When stakeholders start building their own solutions—often using Excel or Power BI—they create the inefficient and data-governance-unfriendly structures we know as Shadow BI.

Seeing Shadow BI as an Opportunity

Shadow BI is not the problem—it’s a symptom of genuine needs. Those who take the time and effort to manually create reports and dashboards clearly have important goals in mind.

Instead of fighting Shadow BI, Data Teams should view these solutions as an invitation to engage in dialogue. For instance, an existing Excel tool can serve as the perfect briefing for a report that can be incorporated into the central system with minimal effort. Alternatively, the Data Warehouse could provide quality-assured tables that act as verified sources for existing Excel solutions, ensuring their reliability.

Conclusion

With understanding and pragmatism, Data Teams and business units can collaborate to find better solutions together. Shadow BI isn’t the enemy—it’s an opportunity to identify real needs and foster data-driven collaboration.