Lean analytics

Lean analytics applies the lean manufacturing idea of eliminating waste and focusing on flow to how a team chooses and uses metrics, rather than to a physical production line. Instead of tracking dozens of dashboards at once, it argues for identifying the one actionable number that matters most at the company's current stage.

The approach ties recommended metrics to a business's stage and model — for example, an early-stage product focuses on engagement and retention signals before it has meaningful revenue, while a later-stage business shifts focus toward growth and revenue metrics. This differs from Six Sigma and statistical process control, which reduce variation in a well-defined, repeatable manufacturing process; lean analytics deals with the much higher uncertainty of product and growth decisions, where the "right" metric itself is often unclear.

Lean analytics matters because it pushes teams to act on a single, well-chosen focus metric rather than getting lost in vanity numbers that look good but don't drive decisions, an idea closely related to a north star metric. A common pitfall is choosing a metric because it's easy to measure rather than because it reflects real progress, or keeping the same metric long after the business has moved past the stage it was meant for.