Self-service analytics for a foodtech platform

The client is a French food-delivery platform whose analysts were bottlenecked behind a small central BI team. Fast, data-driven decisions are core to how the platform competes.

Every data question queued behind the BI team, so analysts waited days for answers they needed in minutes.

Every question queued behind a small central BI team, so analysts waited days for data they needed in minutes. The bottleneck slowed decision-making across the whole business.

The queue buried the BI team in repetitive request-handling, leaving no time for higher-value work. Both sides of the bottleneck were losing.

The platform needed to let analysts serve themselves without sacrificing consistency or trust in the numbers. Self-service could not be allowed to fracture the metrics.

We built governed self-service models with a shared metric layer, so analysts explore certified data directly instead of filing tickets. A governed self-service layer is what removes the bottleneck without losing control.

Because the metrics are defined centrally, self-service does not fracture into conflicting numbers. Consistency is preserved even as access widens.

Guardrails kept the exploration safe and consistent, and freed from repetitive requests, the BI team moved to higher-value modelling and enablement work. Everyone moved up the value chain.