Modern organisations are accumulating increasing volumes of data, while at the same time experiencing a form of decision-making paralysis. This situation creates a paradox: the more sophisticated the measurement tools become, the more the ability to make decisions seems to be diluted. The question is not whether data is useful, but why it sometimes produces the opposite of the desired effect.
Why data is becoming an organisational refuge
In many structures, data has emerged as a form of collective protection. Asking for figures means postponing a decision, avoiding a confrontation or diluting responsibility. This dynamic does not reflect analytical rigour, but rather an aversion to decision-making risk.
The belief that a decision based on objective data would be less open to challenge than an assumed choice by an individual or a team is one of them. This illusion of neutrality masks a simple reality: all data is based on measurement conventions, arbitrary perimeters and implicit assumptions. A KPI never measures reality; it measures a proxy that we have chosen to consider relevant. In some teams, data has even become a form of religion. They consult it before taking action, they invoke it when in doubt, they quote it to protect themselves. It is no longer used to understand: it is used to justify.
It's no coincidence that the “data culture” is taking hold everywhere. It has the almost magical virtue of making people believe that we're making progress, even when we're going round in circles. Every project has its dashboard, every initiative its indicators. When something doesn't work, you don't question it: you change the KPI. Do we not end up confusing the activity of measuring with the action of transforming? As if observing the weather were enough to change the climate.
And finally.., data allows us to maintain a posture of non-committal observation. Multiplying studies, prolonging measurement phases or waiting for a threshold of statistical significance offers an acceptable justification for not making a decision. This form of active passivity gives the impression of a rigorous approach, when in fact it is an avoidance strategy. The courage to decide, on the other hand, cannot be measured. It can be observed in the silences of a meeting, in unpopular choices, in those moments when you have to say: we're going, even if everything is not certain.
The structural limits of the data-driven approach
A number of situations reveal the shortcomings of excessive dependence on data. Disruptive or innovative contexts are a first critical case.. When an organisation explores new territory, historical data loses its predictive value. Established models no longer work, and the signals available become too noisy to guide a decision. In these situations, strategic intuition once again takes centre stage.
Another pitfall arises in situations where measurement modifies the behaviour being measured. This phenomenon, which has been well documented, produces perverse effects: teams optimise indicators rather than results, pathways conform to expected metrics and management systems generate systematic biases. The data then ceases to be a reflection and becomes a normative framework that distorts observation.
The question of temporality also poses a problem. The data available reflects the past, sometimes the present, but never the future. Yet all strategic decisions are about future developments in an uncertain environment. Statistical extrapolation cannot capture discontinuities, regime changes or emerging dynamics. Hindsight is not enough to anticipate.
Data is not the problem, it's what we do with it, or rather what we no longer do with it. A good indicator should not replace human judgement; it should feed it, question it and sometimes contradict it, but never paralyse it.
How is excessive data dependency diagnosed?
There are a number of signs that can be used to identify an organisation where measurement has taken precedence over decision-making. When arbitration decisions are systematically postponed on the grounds that additional data is lacking is one of them. And when this pattern is repeated cycle after cycle, without the additional level of information substantially altering the situation, it reflects an inability to make decisions in the face of uncertainty.
Delegating decision-making responsibility to tools is also a real scourge within organisations. When trade-offs are systematically attributed to an algorithm, a predictive model or a scoring system, this often reflects a lack of accountability that makes it possible to avoid taking responsibility for choices and consequences.
The continual addition of KPIs, dashboards and tracking tools is also a sign of the company's commitment to its customers.’confusion between monitoring and steering. The more indicators are multiplied, the more the hierarchy of priorities becomes illegible. This proliferation often masks a lack of clear vision of what really counts.
Testing minor variants of an interface or a route is a legitimate practice, but it is not the only one. when any design decision, even a fundamental one, is subject to experimental validation, it reveals an inability to accept a bias editorial or strategic.
A mature organisation regularly questions the validity of its measurement conventions and challenges established metrics. When an indicator becomes sacred, when it structures management rituals without ever being questioned as to its relevance or its induced effects, it ceases to be a tool and becomes a dogma.
A number of levers can be used to correct the imbalance when data too often takes precedence over strategy and intuition. For example: limiting the number of indicators monitored to three or five critical dimensions clarifies priorities and reduces information noise. Defining explicit decision windows ensures that waiting for additional data does not become an excuse for inaction. Clarifying who decides what and within what framework strengthens the ability to act. The data can be shared, but the decision must be made by the people.
The initial question as to whether data and intuition should be opposed poses a false dilemma. Data and intuition are not opposites, they complement each other in a coherent decision-making process. Data is objective, intuition is guiding, decision making is decisive. The problem lies not in the use of measurement, but in transforming it into an organisational refuge that avoids commitment.
Decision-making maturity is not measured by the volume of data mobilised, but by the ability to make decisions in a context of imperfect information and to assume the consequences of its choices.