A support team closes more tickets this month. The dashboard improves, yet customers keep returning with the same unresolved problem. The measure has changed more clearly than the service.
Name the intended outcome
Before choosing a target, write what the organisation wants to improve in ordinary language. “Customers can complete the task after receiving help” is an outcome. “Tickets closed per day” is one possible activity measure. The relationship between them needs checking.
In a fictional example, a team is rewarded only for fast closure. Complicated cases may be closed prematurely or moved elsewhere. The numbers can improve without anyone consciously deciding to provide worse service; the process makes the counted action easier to prioritise than the uncounted result.
Add a balancing view
Pair speed or volume with an appropriate quality check, such as repeat contacts for the same issue, a reviewed sample of resolutions or another measure tied to the actual task. No single companion metric solves every problem. Define it carefully and check whether it introduces a new incentive to manipulate the record.
Talk to the people doing the work. Ask which cases the measure handles badly and what important effort disappears from it. Distinguish an inconvenient finding from an attempt to avoid accountability; both deserve evidence rather than assumptions.
Review a small set of real cases before changing rewards or judging individuals. A rising repeat-contact rate may reflect a product defect or a more complex workload, not just the support team’s behaviour. Keep the context beside the number.
A useful metric helps people notice and improve the work. When the team spends more effort protecting the score than understanding the outcome, revisit the definition, incentives and review process. The dashboard should remain a tool for judgment rather than a substitute for it.