Why Public Administrations Struggle with Data

When someone in a project meeting asks what a decision is actually based on, the answer is often silence. The response is usually: experience, judgement, common sense.

In public administration, that is not the exception, it is the norm. Anyone who has worked in a public authority for years develops a fine instinct for which processes work and which do not. That instinct is valuable. It does not replace a robust basis, however, when far-reaching decisions are at stake: a new organisational structure, the allocation of scarce posts, the prioritisation of digitalisation projects. It is precisely with these decisions that it becomes clear how rarely administrations today can draw on a systematic data basis.

The problem is not a lack of goodwill

In most administrations, the problem is not a lack of willingness to decide on a data basis. What is missing is the infrastructure for it. Case figures sit in different specialist systems that do not talk to each other. Processing times are recorded, if at all, in spreadsheets that nobody consolidates. Staff surveys disappear into folders instead of feeding into decisions. The data often exists, but scattered, inconsistent, and with nobody to bring it together and analyse it.

There is also a structural problem: anyone who has learned over decades that decisions above all have to be legally sound and politically defensible rarely asks whether they are also backed by figures. Legal soundness and evidence are two different standards. A decision can be formally correct and still miss the mark in practice, because nobody checked what the available data actually shows. This gap usually only becomes visible once a measure fails to produce the expected effect after implementation, and nobody can explain why, for lack of comparative figures.

What evidence-based decision-making means in practice

Evidence-based decision-making starts with something modest: before a measure is decided, one looks at what robust information is available. How many cases of a given type occurred in the last three years? How long does a process take on average, and where do the biggest delays arise? What feedback exists from day-to-day practice, and can it be analysed systematically rather than cited anecdotally?

These questions sound simple, but applying them demands discipline. It is not enough to collect a figure and then present it as proof of one’s own prior assumption. Evidence-based decision-making also means taking results seriously when they contradict the original expectation. This is exactly the point where many initiatives fail: the data collection goes ahead, but its result changes nothing about the decision that had already been made. The analysis then becomes a formality that no longer changes the outcome, because the actual decision was made long before.

Complexity as a counterforce

A second reason why evidence-based decision-making is difficult in public administration lies in the sheer complexity of the organisations. A local authority has dozens of departments, each with its own processes, responsibilities and historically grown arrangements. Anyone who tries to capture and analyse everything at once overwhelms themselves and the organisation. The analysis therefore has to be limited to what is actually relevant to the decision at hand. This complexity reduction is anchored as a separate application principle alongside evidence-based decision-making in the VESPRA approach, which I describe in my book Verwaltungsmodernisierung mit Methode. The two principles work together: only by sensibly limiting the scope of investigation can the data basis be prepared in a way that actually supports robust conclusions, instead of drowning in a flood of unwieldy figures.

This limitation is not a sign of incompleteness, it is a methodological necessity. An organisation that tries to examine every process at once with the same depth ties up resources needed elsewhere, and ends up with results that are too superficial to derive concrete measures from. The skill lies in deciding in advance which question is genuinely relevant to the decision, and directing the data collection consistently towards it.

A practical starting point

Senior managers who want to take this path do not have to start with a large data project. The first step is often to pick a single, clearly defined question, for instance the processing time for a particular type of application, and build a clean, traceable data basis for exactly that question. This experience teaches which data is actually available, where gaps exist and how to close them. This small-scale approach builds trust in the method before it is applied to bigger decisions.

It is important here to involve from the start the staff who work with the processes concerned on a daily basis. They often know the weak points precisely, but rarely have access to a systematic analysis that backs up their observations. Bringing their experience together with the collected data produces a considerably more complete picture than a purely figures-based view or a purely subjective judgement on its own.

In the end, the attitude of leadership is decisive. When a senior manager routinely asks what a proposal is based on, and makes this question a habit, the way staff work gradually changes too. Evidence-based decision-making is then no longer felt as an extra burden, but becomes part of normal decision preparation. It starts with a single recurring question that becomes a habit: how do we actually know that?