If you can track every activity but still lack clarity about where you’re heading, the problem isn’t missing data. It’s missing meaning.
Data has authority. A number looks clean, decisive, and immune to argument. In many organisations, it now carries more weight than judgement, experience, or a well-reasoned narrative. That shift feels modern and disciplined. It also creates a hidden vulnerability: the moment data is mistaken for meaning, interpretation is pushed to the margins as optional rather than essential.
Without interpretation, data doesn’t produce clarity. It simply increases the amount of information in circulation.
Research on information overload shows that more data doesn’t automatically lead to better decisions—especially when people are expected to process more signals than they can realistically absorb. The issue isn’t intelligence; it’s cognitive bandwidth. Overload shows up as scanning, snap judgements, taking shortcuts and false confidence—the belief that you’re on top of the numbers, while lacking a coherent view of what they mean in terms of action.
This is where the trouble begins: modern dashboards are excellent at showing movement, but poor at explaining meaning. A red indicator says something is “off”. It rarely says why. A green indicator says something is “on track”. It rarely shows what was traded away to get there. Over time, organisations become efficient at tracking performance and surprisingly clumsy at interpreting it.
KPI-heavy environments accelerate this drift because they reward what can be counted and penalise what cannot be summarised in a chart. The less visible work—judgement calls, pre-emptive risk insight, context gathering, dissent, nuance—starts to feel like “opinion” rather than operational intelligence. People learn the rules of the game: If it isn’t measurable, it struggles to move beyond the report. And if it doesn’t move through the organisation, it rarely changes behaviour.
Then, reporting becomes ritual.
You see it in briefing packs that grow fatter month after month, in meetings that start with dashboards and end with “we need to move the needle”, in targets that cascade until teams spend more time managing the metric than the reality. At that point, the organisation isn’t just measuring performance. It is being governed by its instruments.
Social science has warned about this for decades. Goodhart’s Law captures the dynamic bluntly: “When a measure becomes a target, it ceases to be a good measure.” Campbell’s Law goes further, arguing that the more a quantitative indicator is used for decision-making, the more it becomes vulnerable to corruption pressures—and the more it distorts the very process it is intended to monitor.
This is not an abstract academic worry. It is what “gaming” looks like when dressed in respectable clothing.
When a KPI becomes high-stakes, people optimise for it—sometimes ethically, sometimes not, often unconsciously. They reshape work to fit what is measured, not what is true. They compress complexity into cleaner narratives that fit the metric. While interpreting ambiguity in the direction that protects the metric. The organisation doesn’t necessarily become dishonest. It becomes selectively articulate. The dashboard stays reassuring. The underlying reality grows more volatile.
And that volatility is often human.
Most dashboards struggle to carry lived context: friction between teams, quiet operational workarounds, eroding trust, talent fatigue, customer confusion, risk that sits between categories. These do not show up neatly in month-end variance charts. Yet they are precisely the things that determine whether performance is actually sustainable. When those realities are excluded, leaders don’t just miss information—they miss meaning.
So people fill in the blanks.
This is where sensemaking becomes essential. In organisational research, sensemaking refers to how people interpret signals and piece them together to understand what is happening—particularly when the information is partial or ambiguous. When explanation is missing, people don’t wait; they infer. They generate stories that help them understand what is happening and what it means for them. The irony is that a “data-driven” culture can increase speculation, because the numbers move while the organisation fails to explain what those movements signify.
At that point, the organisation has two narratives running in parallel: the official story (the dashboard) and the unofficial story (what people believe is really happening). The gap between them is not a communications problem in the cosmetic sense. It is a governance problem.
Because governance depends on traceability: what was seen, what was prioritised, what assumptions were made, what trade-offs were accepted, and why. Numbers alone cannot supply that chain. They can signal. They cannot justify. They cannot contextualise. They cannot show competing interpretations and the reasons why one interpretation was chosen over another.
This is why authentic narrative is not “marketing decoration”. It is interpretative infrastructure.
In a mature organisation, narrative is how data becomes usable: it connects indicators to causes, connects causes to decisions, and connects decisions to consequences. It makes the implicit explicit. It forces clarity about what the metric is actually standing in for—and what it is not capturing. It also restores accountability. “The data shows…” stops being a shield and becomes a starting point: what do we think this means, and what are we willing to do about it?
The tension, of course, is that interpretation slows things down—and KPI cultures worship speed. But speed without sensemaking is not agility. It is drift with good charts.
If you want one practical test: ask whether your reporting changes behaviour or merely documents it. If dashboards are mainly used to prove performance, they will encourage compliance theatre. If they are used to explain performance—including uncomfortable context and trade-offs—they can support real decision-making.
The organisation becomes rich in signals and poor in shared meaning. And without shared meaning, coordination is guesswork rather than strategy.
The competitive advantage, in the next phase of “data maturity”, won’t belong to the organisations with the most metrics. It will belong to the organisations that pair metrics with genuine interpretation—and treat narrative as a governance function rather than an afterthought.
Because data has authority. But authority without understanding is fragile.
And when metrics replace meaning, the organisation doesn’t become more rational.
It simply becomes more measurable—and arguably less wise.