ACCA Strategic Professional · Strategic Business Leader · Enabling success: disruptive technologies
Orlan Pharma's analysts mined a large dataset and found a strong correlation between a clinic's use of a particular supplier and higher patient recovery rates. Management proposes to force all clinics to switch to that supplier immediately. Which limitation of data analytics is most relevant to the proposal?
The key limitation is that correlation does not prove causation. Better recovery might stem from patient mix or clinic resources rather than the supplier. Forcing a switch without testing causal links risks a poor decision, whereas the other options misstate what analytics can do.
- ACorrelation does not prove causation, so other factors such as patient mix may explain the resultCorrect
- BBig data cannot be analysed unless it is structured
- CVelocity of data makes any historical finding unreliable
- DAnalytics can only be applied to financial data
Explanation
The finding is a correlation. Clinics using the supplier may differ in patient profile, location or resources, which could explain recovery rates. Acting without testing causality risks a costly wrong decision. The other options are incorrect: unstructured data can be analysed, and analytics is not limited to financial data.
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