Aglet

Learn why customer feedback became stale over time

Staleness often reflects a missing owner, changing product, weak reporting coverage, or a legitimate decline in demand. Learning should identify which condition applied, compare the state decision with later evidence, and improve one mechanism that keeps useful requests current. The useful lesson is a maintenance change that keeps relevant requests visible without preserving obsolete work.

Keep the lesson for the next incident

  1. Classify the staleness cause

    Review the record and current-state check to identify whether age came from no decision, no recent observation, a product change, or reduced customer relevance. Tie the classification to dates and evidence, not a generic stale label.

  2. Compare later signals

    At the next review, compare new reports, workflow observations, and product changes with the original state decision. Note whether the request resurfaced, stayed resolved, or became a different problem. Preserve uncertainty where source coverage remains limited.

  3. Adjust the maintenance practice

    Choose one improvement such as a review cadence, ownership field, freshness trigger, source coverage check, or merge rule. Assign an owner and define the evidence that will show whether fewer useful requests become stale without hiding quiet demand.

What to carry forward

The learning output connects staleness to a concrete process condition and a testable maintenance adjustment. Stop when the change has a responsible owner and follow-up evidence; keep historical requests intact so future reviews can assess the lesson.

Keep the decision with the work.

Use a Work Item in Aglet to record the problem, the evidence you have, and the next decision. Add an owner and priority, then keep updates in the discussion so the next person can follow the reasoning.

Create an account See the product workflow