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Broken HR advice #9: 'Be data-driven about people decisions'

People data has the lowest signal-to-noise of any business data. 'Data-informed' is honest. 'Data-driven' is a hiding place.

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60-Second Summary
  • Most HR datasets have sample sizes too small for the inferences leaders try to draw — a 200-person company has 8 promotion decisions a year, not a statistically meaningful population.
  • The 'data-driven' framing is often used to defer judgment calls and to absorb accountability for a decision made for political reasons.
  • Use the term 'data-informed' — it preserves the role of judgment and assigns the accountability where it belongs.

If you have 200 employees, you do not have a dataset. You have anecdotes arranged in a spreadsheet.

The sample-size problem

n=8
Promotion decisions per year, 200-person company
Below threshold for statistical inference
n=18
Annual attrition events at 200 ppl
Too small to segment meaningfully
12 months
Time before a hiring decision shows true quality signal
Most 'hiring data' is pre-signal

Data-informed vs data-driven

Two postures
Data-driven (overclaim)
  • The data showed X, so we did X.
  • Decision authorship hidden behind dashboard.
  • Hard to overturn even when the data is wrong.
Data-informed (honest)
  • Here's the data, here's the judgment we layered on it, here's who decided.
  • Decision authorship explicit.
  • Easy to revisit when context changes.
Written by Pawan Joshi.Sources cited inline.
First published 10 Feb 2026See site changelog →