Summary: People analytics can make HR decisions more measurable, but variables moving together does not prove that one caused the other. Reliable analysis combines definitions, timing, alternative explanations, and appropriate tests.
Correlation and causation
Correlation describes a tendency for two variables to change together. Causation is a stronger claim that an intervention in one variable produces change in another. A dashboard relationship is often a hypothesis, not a verdict.
Five causal questions
- Are the definitions and time order sound?
- Could a third factor affect both variables?
- Is there a baseline or comparison group?
- Does the result hold across segments?
- How will the proposed action be measured?
Responsible workflow
Define the decision, state a hypothesis, check data quality and selection effects, examine alternatives, pilot at small scale, and evaluate against pre-defined metrics. A model may provide a signal; managers must validate context and choose a fair action.
Conclusion
The value of people analytics lies in better questions and controlled decision loops, not more charts. Avoiding causal overclaiming protects scientific quality and employee trust.
Sources
This article is for general information and is not legal advice.
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