PlatformsPerspective
Design the operating model before you automate the workflow.
07 August 20268 min read→
Operating modelsExplainer
Choose service metrics that change a decision.
A compact measurement system is more useful than a comprehensive dashboard when every signal has an owner and a response.
Reading note
Three ideas to take away.
- Begin with the decision, then choose the signal.
- Pair averages with distribution and exception views.
- Retire measures that no longer trigger learning or action.
Simplify
More visibility can still produce less clarity.
Dashboards tend to accumulate because adding a measure feels safer than removing one. The result is a wall of accurate information with no shared rule for what should happen next.
Reverse the design. Name the operating decision, its owner and the time available to make it. Then select the smallest signal set that makes that decision better.
Contract
Give each metric an operating contract.
A metric contract names the definition, source, period, population, owner, threshold and intended response. This prevents teams from debating the number only after it becomes uncomfortable.
- Definition and calculation method.
- Data source, quality caveats and reporting period.
- Named owner and review cadence.
- Threshold that prompts investigation or action.
- Decision or behaviour the measure is intended to influence.
Review
Review the measurement system itself.
A measure can outlive the question it was created to answer. Quarterly, ask which signals changed a decision, which created useful investigation and which were simply copied into the next pack.
Removing inert measures creates space for explanation — and explanation is where operational learning becomes visible.
Occasional notes
One useful idea, when we have one.
No weekly quota. No recycled headlines. Just new Aevis thinking and practical field notes worth keeping.