Attribution is often framed as a modeling problem. Define the right entities, apply the right logic, and insight is expected to follow.
In practice, this framing fails early.
Attribution does not succeed or fail based on analytical rigor alone. It succeeds or fails based on whether the underlying systems are stable enough to tolerate real work—loss, delay, correction, and drift included. When those conditions are missing, attribution models either go unused or quietly lose credibility.
This series takes a different position:
Attribution is an outcome of stable systems, not an abstract design exercise.
Attribution works best when it stays out of the way. It should not require new rituals, new habits, or sustained attention from the organization. Instead, it should emerge gradually as systems become consistent enough to support it.
Each post in this series focuses on a different domain—operations, revenue, and marketing—but all examine the same pattern. Attribution becomes useful only after systems stop fighting reality and start absorbing it.
Operational attribution is rarely discussed first. It should be. Operations are where attribution systems encounter reality early. Inventory is lost. Counts drift. Corrections accumulate. If an attribution system cannot tolerate those conditions, it will not survive long enough to be…