From a business question to a measured outcome

The core idea

Our practical workflow is business question → relevant data → analysis → insight → intervention → measured outcome. It is an editorial synthesis, not a proprietary assessment. Begin with the decision that needs support and end by checking what the action changed. An interesting chart is an intermediate result. The workflow should be proportionate: a small, well-defined comparison may answer the question better than a complex predictive system.

Using it in practice

Name the decision owner and agree a population, outcome and time window. Collect only information relevant to the purpose, with appropriate access and handling. Inspect quality before analysing patterns. Separate what the data shows from your explanation of why. Discuss the finding with people who understand the work, then choose a feasible action and an evaluation design. Keep a record of definitions, assumptions and changes so the work can be updated.

What to watch for

Do not turn the question into a search for which employees are likely to be disloyal. Avoid collecting sensitive or intrusive data without a justified purpose and appropriate legal assessment. A plausible insight is not yet evidence that an intervention works. Keep the distinction between prediction, explanation and causal evaluation visible throughout.

1 · Write a decision brief

State the problem, who is affected, what choice is available and when it must be made. Replace “build a turnover dashboard” with a question such as whether a change to the first-month scheduling process is worth testing. Define what evidence would change the decision.

2 · Build a data specification

List the minimum fields, definitions, source, period and access permissions. Record missingness and how rehires or inactive casual workers are handled. Use aggregate outputs where they answer the question. A data dictionary is part of the analysis, not an administrative afterthought.

3 · Analyse and challenge

Begin with counts, denominators and comparable cohorts. Investigate whether the pattern changes with role or contract mix. Invite alternative explanations from employees and managers. Use a more advanced technique only when it answers a question the simpler analysis cannot.

4 · Design a useful action

Describe the mechanism: what will change in work, why that could improve the outcome and which resources it needs. Set fair eligibility and practical boundaries. Plan the evaluation before rollout so that a suitable comparison is not lost accidentally.

5 · Report and maintain

Record the outcome, uncertainty, unintended effects and remaining questions. Assign an owner for follow-up. If the finding changes a process, review whether the effect persists. If it does not support the preferred explanation, publish that conclusion internally with the same clarity as a positive result.

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