Self-service BI: smart outsourcing to your own key users (or not)

Self-service BI brings knowledge literally close to the source: key users know their own process better than an external developer, allowing them to ask sharper questions, iterate faster, and create analyses that precisely match the reality on the floor. As the queue of BI tickets disappears, the time-to-insight drastically shortens. Questions are answered in hours or minutes instead of days, making the entire process cheaper and less frustrating. At the same time, dependence on outsiders decreases: minor changes and ad-hoc questions can now be handled internally, making teams more agile and able to adjust more quickly when the situation demands it. 

The downside of self-service BI often begins with definition chaos: terms like “revenue,” “margin,” or “OEE” turn out to be defined slightly differently by each team, resulting in the same topic leading to different outcomes in multiple reports.  

On top of that, there can easily be uncontrolled growth of different reports: when ten people in Finance each publish their own version of a report, the distinction between draft, test, and “official” version blurs, and no one knows which figures are authoritative. Although tools like Power BI are becoming increasingly accessible for non-developers, certain cases can still prove challenging as the questions become more complex. Especially when using a large and complex data warehouse, certain scenarios can be a challenge for less technical users. 
Additionally, management and permissions require maturity; without a clear authorization structure, audit logging for changes, and an assessment of data sensitivity, information may be unintentionally shared, or shadow reports may continue to circulate. Finally, there is the risk that knowledge rests on one person: if a key user leaves, definitions, context, and working methods leave with them, resulting in stagnation, rework, and loss of trust.