Why companies reject the solution
When the same mechanisms that cause bad decisions also block corrections
Many companies recognise that investment decisions are not always optimal.
Budgets are exceeded, projects deliver less value than planned, and portfolios are created based on historical priorities rather than calculated overall logic.
And yet structured optimisation, external decision support or formal reassessment are often rejected.
As part of our analysis of decision quality, we examined this pattern as a separate phenomenon: the rejection of the solution.
The key finding is that the same cognitive and organisational mechanisms that cause suboptimal decisions often prevent their correction from being accepted.
The paradox
A company can simultaneously :
- observe suboptimal results
- recognise the need for improvement
- and yet stick to existing decision-making routines
This paradox is rarely rationally justified.
In many cases, it is a combination of bias, governance logic and psychological defence mechanisms.
1. Overconfidence and illusion of knowledge
Managers often overestimate the robustness of internal models and forecasts.
Existing processes seem familiar, established and "proven" – even if their results reveal structural weaknesses.
If you believe you are already making good decisions, external optimisation seems unnecessary.
2. Illusion of control
Decision-makers experience control as part of their role and identity.
Formal optimisation logic can then be perceived as a restriction: not as support, but as a loss of autonomy.
This is particularly true in situations where experience and political control have previously served as substitutes for formal evaluation logic.
3. Confirmation bias and cognitive dissonance
An external analysis can call existing priorities into question.
This creates cognitive dissonance: psychological pressure that must be reduced.
In such situations, information that confirms the existing approach is preferred.
Deviating models or recommendations are viewed with greater scepticism, questioned more closely or devalued.
4. Status quo bias and process comfort
A key driver is mental and organisational inertia.
Existing decision-making processes generate :
- Familiarity
- Predictability
- Internal legitimacy
- Role and power stability
A new decision-making architecture means change.
And change creates uncertainty, additional work and internal reframing.
5. Sunk cost fallacy at the process level
Many companies have invested years in existing control logic :
- Excel models
- ERP reports
- Budget routines
- Evaluation standards
Psychologically, these investments are treated as an argument for continuing with existing procedures.
A change would imply that previous decisions or structures were suboptimal.
This is often avoided emotionally and politically.
6. Short-termism and immediate costs
Structured optimisation has short-term costs :
- Modelling effort
- Transparency about conflicting goals
- Reprioritisation
- Possible correction of "cherished" projects
The benefits often become apparent later.
In organisations with strong pressure to deliver results or report, this cost-benefit timeline is systematically distorted in favour of short-term stability.
The structural core
Rejecting the solution is often not a "no to improvement".
It is a "yes to stability".
Stability of identity, processes, roles and decision-making narratives.
But it is precisely this stability that keeps organisations stuck in the local optimum.
Why this is particularly relevant in the portfolio context
As soon as several projects have to be evaluated simultaneously, a combinatorial decision space arises.
In this context, isolated individual evaluations and heuristic routines are not sufficient to determine the best combination under constraints.
If optimisation is rejected, capital allocation remains trapped in historical patterns:
- Continuation of existing priorities.
- Political stabilisation.
- Incremental adjustments.
The result is not only inefficient.
It is structurally suboptimal.
Conclusion
Companies rarely reject the solution because it is objectively bad.
They reject it because it is perceived as a threat cognitively, organisationally or politically.
If you want to improve decision-making quality, you therefore need to do more than just offer better models.
You need to understand the mechanisms that block change – and design decision-making architecture in such a way that optimisation is accepted as a support measure.
