Monday Myth: More Data Means Better Decisions
This myth refuses to die.
Dashboards multiply. Metrics expand. Confidence rises. Decision quality does not.
Modern organisations proudly claim to be data-driven. In reality, most are data-soothed. Data does not sharpen judgement. It often dulls it. It reassures. It calms. It creates the impression that uncertainty has been handled.
More data rarely delivers more understanding. It mostly delivers more comfort.
The comforting lie of numbers
Data feels objective. Clean. Scientific. It gives the impression that ambiguity has been tamed.
Yet most organisational data does not explain reality. It describes the past, filtered through assumptions that are rarely explicit and almost never revisited.
When outcomes are good, numbers are presented as proof. When outcomes are bad, the same numbers are reinterpreted until failure appears inevitable, external, or miscategorised.
This is not learning. It is narrative repair.
Antifragility says the opposite
In Antifragile, Nassim Nicholas Taleb makes a point that modern organisations consistently ignore: we learn far more from what fails than from what appears to work.
Antifragile systems do not seek certainty. They seek exposure.
They improve through stress, error, and disconfirmation. Progress comes from discovering what does not work, not from refining increasingly confident predictions about what might.
Data-heavy organisations do the reverse:
- They optimise forecasts instead of preserving options
- They suppress volatility instead of learning from it
- They reward confidence rather than intellectual humility
The result is a system that looks informed but collapses the moment its assumptions are tested.
This is epistemic fragility: apparent knowledge that disappears under stress.
When measurement turns into distortion
At some point, a critical transition occurs. Metrics stop serving observation and become targets. This is where Goodhart’s Law stops being theory and becomes mechanics:
When a measure becomes a target, it ceases to be a good measure.
Once this line is crossed:
- Teams optimise the proxy rather than the outcome
- Local success accumulates into systemic failure
- Numbers turn into shields instead of signals
The dashboard turns green. The system quietly becomes brittle.
The watermelon effect nobody admits
Many organisations already know their metrics are lying. They just prefer the lie.
Everything looks green on the outside. Inside, it is red.
This is the watermelon effect: KPIs signal health upward while problems accumulate downward. Risks are contained locally, softened in reporting, and reframed until escalation feels unnecessary or politically dangerous.
The more status depends on numbers staying green, the more aggressively reality is filtered. Dashboards become instruments of reassurance, not detection. By the time red finally surfaces, it is no longer a signal. It is an incident.
Why more data often makes decisions worse
- Volume replaces judgement
When everything is measured, thinking atrophies. Sense-making is delegated to charts. - Metrics become defensive tools
Numbers are used to justify decisions, not to challenge them. Learning stops without announcement. - Models lose falsifiability
If no one can state what would prove a model wrong, it is not a model. It is belief presented with precision. - Systemic risk hides behind local optimisation
Each team hits its targets while the organisation accumulates unseen failure modes.
The leadership reality nobody wants to name
There is an uncomfortable factor behind all of this: title inflation.
Many people carrying senior titles today did not earn them through mastery of systems, mathematics, or engineering discipline. They inherited scope, survived reorganisations, or accumulated headcount.
Expecting mathematical literacy, statistical intuition, or an understanding of uncertainty from such roles is optimistic at best.
Numbers become attractive precisely because they remove the need to understand what they represent. When status is inflated and foundations are thin, dashboards replace competence.
Why IT is especially exposed
Other industries learned to distrust clean numbers early.
Manufacturing, aviation, and medicine separate measurement from incentives. Signals are protected because lives, machines, and capital depend on them.
IT largely ignored this lesson.
Velocity became productivity. SLAs became reliability. Output was mistaken for outcome. Dashboards were equated with health. The result is metric theatre: impressive displays with little operational truth behind them.
The uncomfortable pattern
Organisations that consistently make sound decisions tend to:
- Track fewer, more deliberate metrics
- Accept short-term volatility
- Encourage small, contained failures
- Value people who say “we do not know yet”
Organisations obsessed with data tend to:
- Add dashboards
- Add process
- Add confidence
- Add explanations
Until reality bypasses all of it.
The real role of metrics
Metrics are not there to decide. They exist to inform judgement, not replace it.
The moment a metric must be defended, it stops telling the truth.
The moment success depends on a number remaining green, learning has already ended.
Final cut
If your decision quality improves only when the dashboard looks calm, you are not data-driven. You are reassurance-driven.
And reassurance does not fail gradually.
It fails all at once.
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