KPI Design & Behavior Review: What Does the Target Encourage?

KPI Design and Behavior: What Does the Target Encourage?

A KPI can report that a team has met its target while leaving an important business question unanswered. A useful review connects the measure to its objective, the decisions people can influence, and the evidence of the intended outcome.

Consider an original fictional customer-support team. Its objective is to resolve customer issues reliably and promptly. The primary KPI counts tickets closed within the agreed service time. In a fixed cohort of 100 eligible tickets, 90 were closed within that time. The reported result is 90%.

Read the measure in its business context

Assume every ticket in this cohort has now passed a complete seven-day observation window. Of the 90 timely closed tickets, 20 distinct tickets were reopened in that window. Seventy were not observed reopening.

The timely-closure rate is 90 divided by 100, or 90%. A companion measure, timely closures without a recorded reopening in the window divided by the same eligible cohort, is 70 divided by 100, or 70%. Reopened tickets as a share of timely closed tickets are 20 divided by 90, or approximately 22.2%.

These measures answer different questions. The 70% measure is a limited proxy for sustained resolution. It does not establish that all those customers were satisfied or that their underlying issue was resolved. Some may not return, may use another channel or may raise a new ticket. Reopening can also reflect a new issue rather than a poor original resolution. Those distinctions require investigation.

Review the behavior before rewarding the number

If the primary target rewards fast closure alone, one possible incentive is premature closure. This is a design risk, not evidence that this fictional team or any real employee manipulated a record.

Ask what people can do to improve the measure without improving the objective. Could difficult tickets be excluded? Could a closure timestamp be reset? Could a reopened issue be logged under a new ID? Could work move to another team after the reporting cut-off?

Then identify the checks that would expose those possibilities. Useful controls might include a documented eligibility rule, reconciled source counts, retained status histories, review of unusual closure or exclusion patterns, and evidence-based discussion of repeat contacts. A companion KPI helps only if its own definition and data can be trusted.

Keep the denominator and observation window stable

Define the cohort before measuring it. In this example, eligibility is tied to tickets due for resolution in the period. Count each eligible ticket once. Link reopen events to the original ticket and count distinct reopened tickets, rather than multiple events against one ticket.

Do not compare a fully matured cohort with a newer cohort that has not yet completed the same observation window. An apparent improvement may simply reflect less time for problems to reappear. Changes in case complexity, customer mix and service channels can also affect comparability.

The seven-day window and example targets of 90% for timely closure and 80% for the companion proxy are illustrative design inputs. They are not professional standards or recommended targets for every support operation.

Use the toolkit to document the decision

The KPI Review sheet captures the objective, metric, formula definition, data source, target, owner, desired behavior, unintended behavior, control and review frequency. It also records a companion measure, evidence reference, review decision and follow-up action with its owner.

The review form accepts a target expressed in the unit appropriate to the KPI. The Worked example sheet demonstrates percentage calculations using editable fictional counts. It marks missing or inconsistent counts and incomplete observation windows instead of presenting an unsupported result as zero.

A calculated status of Review recorded means required fields are populated. It does not certify the evidence, approve a reward or conclude that a KPI is well designed. The reviewer must explain the decision in context and retain the evidence supporting it.

Make the measure useful for learning

Pilot revised definitions before using the results for consequential decisions. Compare what changed in the underlying work, data capture and customer experience. Document exclusions, limitations and alternative explanations. A rise in one percentage does not, on its own, establish that a redesigned incentive caused improvement.

Northern Ireland Audit Office's 2018 guide provides public-sector context on outcomes, data quality and unintended incentives. This toolkit, its formulas and customer-support example are original Inside Assurance work. They are not a reproduction of the guide's framework or a requirement imposed on private companies.

A practical review question is simple: if someone improves the KPI, what evidence would show that the intended business outcome improved too?

Inside Assurance — Beyond the numbers. Inside the business.