A dashboard tells you that the service is meeting its targets. At the same meeting, the business describes delays, avoidable effort or a poor customer experience. The first question is whether the measures and the business are discussing the same outcome.
My doctoral research examined KPI reliability through three dimensions: relevance, iteration and corporate culture. For a service leader, relevance begins with a practical test: identify the decision a measure is intended to support.
Start with the decision
Consider this illustrative situation: a support service reports a high proportion of calls answered. That is useful evidence about access to the service. It does not, by itself, tell the CIO whether users received an effective resolution or whether the service can sustain its staffing model.
Those are different decisions. Improving call coverage may require a roster change. Reducing repeat contacts may require a change to knowledge, diagnosis or escalation. A staffing decision may require demand patterns and handling effort. One favorable percentage cannot answer all three questions.
For each executive KPI, write one sentence: “We use this measure to decide whether to…” If the sentence ends with “monitor performance,” make it more specific. What resource, priority, service commitment or intervention could change?
Connect the measure to a business objective
In the thesis, relevance is explored through focus, responsibility and alignment. The management implication is to examine the chain from a business objective to a service outcome, then to the action a team can take.
A useful review asks whether the measure still reflects the current objective, whether an accountable owner can act on it, and whether improving it could undermine another service outcome. An aggressive handling-time target, for example, may deserve a joint review with resolution quality. That is an illustrative trade-off, not a result established by the survey.
Use a decision-to-measure review
| Question | What to record |
|---|---|
| What decision does this support? | The specific choice, its owner and review frequency. |
| What outcome matters? | The customer or operating objective behind the target. |
| What can the team change? | An action within its authority or an escalation route. |
| What could the metric miss? | A countermeasure, contextual explanation or known limitation. |
| When did we last test relevance? | The review date and any change to the service or strategy. |
This worksheet is a practical adaptation of the research framework. It has not been validated as a diagnostic scoring instrument. Its value is in making the management discussion explicit.
Keep the evidence proportional
The study collected perceptions about KPI-system characteristics. It did not demonstrate that a green dashboard causes poor decisions, or that a relevance review produces a particular financial return. Its findings support a discussion about how measures are designed and used; they do not replace analysis of the service itself.
For your next service review, choose one important KPI and trace it back to a decision. If the connection is unclear, resolve that connection before adding another measure.
Source and interpretation
Hany Taha Badawy Saqr, Key Performance Indicator’s KPIs Reliability in Decision Making: In People Management, Process Optimization and Marketing, DBA dissertation, International Business School of Scandinavia, 4 March 2022.
Relevant PDF pages: 38–45, 50–59, 73–78. Examples and operating routines in this article are practitioner adaptations; they are not additional survey findings. The dissertation is not presented here as a peer-reviewed journal publication.