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A large body of research in behavioral economics and psychology has highlighted systematic mistakes we can make when looking at data. We tend to seek evidence that confirms our preconceived notions and ignore data that might go against our hypotheses. We neglect important aspects of the way that data was generated. More broadly, it’s easy to focus on the data in front of you, even when the most important data is missing. As Nobel Laureate Daniel Kahneman has said, it can be as if “what you see is all there is.”
I think we all know this, but we still constantly claim to be “data-driven” and “wanting to see what the data says,” which in 97% of orgs still means “want to see a spreadsheet and then make a decision based on my gut anyway.” We actually live in a belief-driven world, and we try to ascribe it to being a data-driven world.
The problems with “data” in organizations are many and diverse, including:
- Executives, whose egos are massaged by everyone, tend to trust their guts.
- When you collect too much data, you slow down decision-making.
- No one is totally sure which C-Suite silo gets to “own” it.
- It runs counter to human emotion, which is more palpable around decisions.
- We don’t explain what the data is saying…
