Decision-making quality in ministries and governments: Why government investment and structural decisions can be structurally suboptimal from a mathematical perspective

The federal and state governments have extensive data sets at their disposal.
They work with budget plans, economic feasibility studies, impact assessments, subsidy programmes, impact analyses and medium-term financial planning.
They use specialist procedures, controlling systems, interdepartmental coordination processes and parliamentary budget procedures.

And yet, even at ministerial and government level, suboptimal allocation decisions are systematically made.

The cause is rarely a lack of data or technical expertise.
It lies in the structure of highly complex government decision-making processes.

The structural misunderstanding: more data does not automatically mean better government decisions

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Government budgets are formalised, rule-bound and data-based. Programmes are calculated, prioritised and politically legitimised. Nevertheless, a central question often remains unanswered. :

Is the chosen combination of programmes, investments and measures really the best possible one, given all the legal, fiscal and strategic restrictions?

In the political arena, decision quality is often assessed normatively or politically. In mathematical terms, however, it means :

• Maximum overall government impact per euro spent
• Minimisation of opportunity costs in the federal or state budget
• Strict compliance with all constraints (debt brake, EU requirements, funding logic)
• Transparent and reproducible prioritisation

This is not primarily a question of political evaluation.
It is a formal optimisation problem.

Why even ministries do not make mathematically optimal decisions under complexity

Ministerial decision-making processes rarely fail due to a lack of competence, expertise or commitment.
However, they operate in highly complex decision-making spaces with multiple conflicting goals.

For decades, modern behavioural economics has shown that decisions made under uncertainty, time pressure and political considerations are not entirely rational in the mathematical sense. Complexity leads to heuristics, simplifications and structural distortions.

Key empirical contributions to this field include those by :

• Daniel Kahneman – Analysis of systematic decision-making errors
• Robert J. Shiller – Investigation of collective valuation dynamics
• Richard Thaler – Fundamentals of behavioural economics

The core thesis is :

Suboptimal allocation decisions are not the result of individual failure on the part of individual officials.
They are a structural feature of human decision-making processes in complex systems.

The structural core: the exponential decision space of government programmes

Suppose that at the federal or state level there are :

• 50 programmes or investment projects that can be prioritised
• €81 billion in available budget
• €220 billion in aggregate financing requirements

Then there are not 50 options to choose from.
There are 2⁵⁰ possible combinations of government measures – over 1,125 quadrillion variants.

No cabinet committee.
No budget committee.
No classic table model.

can evaluate this entire decision space simultaneously.

In practice, programmes are developed on a departmental basis, negotiated sequentially and designed to achieve political consensus. Priorities arise from coalition logic, eligibility for funding, urgency or media visibility.

The result is often a politically viable, locally plausible optimum –
but most likely not the combination with the greatest global impact.

Typical structural distortion mechanisms in government decisions

1. Funding and co-financing logic

Measures are prioritised because they are co-financed or funded by the EU – not necessarily because they have the greatest overall impact on the national economy.

2. Path dependency and political escalation

Programmes that have already been initiated are continued even though the framework conditions have changed or alternative measures would be more efficient.

3. Legislative period logic

Measures that are visible in the short to medium term are given structurally higher priority than long-term transformation projects (e.g. digitalisation, infrastructure modernisation, resilience building).

4. Departmental optimisation instead of overall optimisation

Each ministry optimises within its area of responsibility. The overall impact across departmental boundaries is rarely modelled simultaneously.

5. Sequential evaluation instead of portfolio modelling

Programmes are evaluated individually. Interdependencies, synergies and opportunity costs between measures often remain implicit.

6. Political compromise as a substitute for formal optimisation

Decisions are made in the negotiation process. Consensus becomes the dominant criterion – not necessarily mathematical impact maximisation.

These mechanisms are structurally determined and inherent in the system.
They result from institutional logic, incentive systems and limited information processing.

Multidimensional constraints increase complexity exponentially

Government investment and funding decisions are simultaneously subject to :

• Constitutional budget restrictions (e.g. debt rules)
• European legal requirements
• Climate targets and CO₂ budgets
• Funding deadlines and earmarking
• Capacity restrictions (personnel, administration, implementation)
• Strategic objectives (transformation, competitiveness, social stability)

Each additional restriction expands the scope of decision-making.
With each additional measure, the combinatorics grow exponentially.

From locally viable to globally effective optimum

The central question of government decision-making quality is therefore not :

Which individual programme makes sense?

But rather: :

Which combination of all programmes generates the maximum possible overall government impact under all fiscal, legal and strategic constraints?

A structural increase in the quality of decision-making requires: :

• Formal modelling of all measures as an overall portfolio
• Explicit definition of quantifiable target values (impact, sustainability, fiscal stability)
• Simultaneous consideration of all restrictions
• Systematic evaluation of possible combinations of measures
• Transparent derivation of an optimal initial constellation

Political decision-making authority remains fully intact.
However, it is based on a formally analysed decision-making space rather than on implicit assumptions.

Transparency, traceability and legitimacy

A mathematically sound portfolio analysis at the state level enables :

• Explicit presentation of opportunity costs
• Visualisation of synergies between policy areas
• Objective prioritisation under restrictions
• Traceable justification of parliamentary decisions
• Increased transparency towards the public and audit offices

Democratic decision-making processes are not replaced.
They are made more precise in structural terms and analytically sound.

Conclusion

Ministerial and government investment decisions are not irrational.
However, they are made in exponentially growing decision-making spaces.

As long as measures are prioritised in isolation and negotiated sequentially, there remains a high probability that :

• the overall effect will remain below the theoretically achievable level
• combination advantages will remain undiscovered
• opportunity costs will remain implicit and invisible

Decision-making quality at government level is therefore less a question of political integrity or professional competence –
but rather a question of structured mastery of complex, combinatorial decision-making spaces.

Do ministries and governments inevitably make suboptimal decisions? The mathematical explanation in the videos :

Order
: 1. Intro video – Understanding the problem and the decision space
2. Deep dive video – Modelling, constraints and optimisation logic

Video 1 :

We calculate the national budget ex ante – before political decisions are made

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Government decisions should not only be evaluated after the fact. The decisive factor is the optimal starting point before cabinet decisions, interdepartmental coordination or parliamentary budget approval. By simultaneously taking into account budget restrictions, debt rules, CO₂ targets, capacity limits, funding logic, European legal framework conditions and strategic objectives, the entire scope of government decision-making is systematically analysed.

The result is a transparent, reproducible and mathematically sound prioritisation of all programmes, investment and funding options – providing a reliable basis for decision-making by ministries, state secretariats, budget committees and the government.

Request ex-ante analysis of the national budget