Decision quality: Why companies make suboptimal investment decisions
Six structural mechanisms that systematically limit decision quality
Nobel Prize-winning research has shown for decades that decision quality under complexity is subject to structural limits. In particular, the work of Daniel Kahneman (Nobel Prize 2002), Richard Thaler (Nobel Prize 2017) and Robert Shiller (Nobel Prize 2013) shows that real decisions systematically deviate from mathematically optimal solutions - not due to a lack of competence, but due to the structural properties of complex decision-making systems.
Building on these scientific findings, we have identified six central mechanisms that measurably influence the quality of decisions in companies and institutions:
1. The WACC Fallacy
The WACC evaluates projects in isolation rather than as part of an overall portfolio. Portfolio effects are not taken into account, which means that value-maximizing combinations can be structurally overlooked.
2. Escalation of commitment
As Kahneman showed, decision-making systems tend to continue existing decisions. New, superior alternatives are structurally underweighted.
3. Heuristics instead of optimization
Kahneman's research on bounded rationality shows that complex decisions are simplified heuristically. This enables stable, but not necessarily optimal results.
4. Experience bias in the management board
Experience is based on historical patterns. As Thaler showed, past experience systematically influences decisions - even if the global solution space contains new, superior alternatives.
5. Earnings pressure and short-term decision-making logic
Robert Shiller showed that expectations and short-term evaluation mechanisms influence decisions. Optimal long-term investments are structurally underprioritized as a result.
6. Structural rejection of new decision-making models
New, mathematically superior decision-making processes are often initially rejected. This effect is a well-known structural property of stable decision-making systems.
The central finding of Nobel Prize research
Kahneman, Thaler and Shiller unanimously show that decision quality is structurally limited - not by a lack of data, but by the complexity of the decision space.
With increasing complexity, decision quality becomes a mathematical optimization problem. Without systematic modeling of the decision space, global optima remain structurally invisible.
