Building the operating model behind the product.

One product serving several client partners has a problem a single-client product never has: every partner experiences their priority as the product's priority.

That is the structural tension. A dedicated team can simply work the queue. A shared product cannot — because the queue is the negotiation. Without an explicit way to sequence across partners, prioritization defaults to whoever escalated most recently, and the product stops having a direction of its own.

Underneath that, the delivery chain was long and crossed disciplines. Strategy, engineering, analytics, QA and multiple client-partner teams each owned a critical link. Analytics work fails quietly in those gaps: a definition drifts, an event is instrumented against a stale assumption, and nobody discovers it until a number is already in front of an executive. Every team can be locally correct while the output is not trustworthy.

So the mandate was dual, and the harder half was the second one: lead delivery, and build the operating model that delivery needed — while the work was already moving and could not pause to be organized.

I designed the model around the handoffs where enterprise analytics work most often loses clarity. Every stage needed an owner, a decision, an entry condition, and a definition of ready.

The model became useful because it was built around real product-delivery friction—not around a generic methodology.

The product gained a common way to see the work: what is moving, what is blocked, who owns the next move, and what “ready” means.

The most important result was not another layer of process. It was a calmer delivery environment with clearer ownership, earlier signal, more useful leadership conversations, and a route from business requirements to trusted analytics.