
Building on our previous discussion of rational decision-making frameworks, let's explore how our minds create and use cognitive models to navigate complex choices. Consider two pharmaceutical companies with similar strategic decisions about developing new drug candidates. Company A relied solely on traditional financial metrics, while Company B incorporated sophisticated mental models considering multiple interconnected factors. This scenario exemplifies what researchers describe as the difference between single-strategy and adaptive decision-making approaches.
The Power of Mental Models in Organizational Decision-Making
Recent research by Kahn and Daw (2025) reveals that our brains use multiple decision-making systems simultaneously. Their study demonstrates how the brain dynamically adjusts between different approaches based on their effectiveness in different situations, a finding that has profound implications for organizational decision-making.
Understanding Our Brain's Decision Toolkit
Viale et al. (2023) and Kahn and Daw (2025) identify three key mechanisms:
Model-Based Planning
Detailed evaluation of potential outcomes based on structured analysis
Step-by-step analysis of consequences and potential pathways
Flexible but computationally intensive
Successor Representation (SR)
Efficient prediction of future outcomes
Balance between flexibility and computational cost
Particularly effective in stable environments
Quick Response Systems
Rapid decision-making based on embodied experience
Most efficient but least flexible
Best suited for routine decisions
Making This Work in Organizations
Strategic Framework Implementation:
Decision Classification
Identify and categorize decision types by complexity and frequency
Match decision approaches to environmental stability
Create clear protocols for different decision categories
Implement systematic review processes
Model Development
Build comprehensive mental models for key decision areas
Include feedback mechanisms for continuous refinement
Integrate multiple perspectives and data sources
Create dynamic adjustment capabilities
Systematic Review Process
Regular evaluation of decision outcomes against objectives
Adjustment of models based on environmental feedback
Documentation of lessons learned and best practices
Real-World Application
Environmental Awareness
Monitor and assess decision environment stability
Recognize significant condition changes
Adapt models to environmental shifts
Feedback Integration
Implement robust feedback mechanisms
Measure both immediate and long-term outcomes
Adjust strategies based on performance data
Common Pitfalls to Avoid
Over-complication
Not every decision requires complex modelling
Match model complexity to decision importance
Maintain efficiency in routine operations
Rigid Thinking
Avoid single-strategy lock-in
Build adaptability into decision models
Regular review and update of approaches
Isolation
Incorporate multiple stakeholder perspectives
Establish cross-functional collaboration
Foster collective intelligence in decision-making
In our next post : We will delve into the social dimensions of rationality and explore how organizational culture shapes decision-making processes.
Remember: As Pinker (2021) emphasizes, the goal isn't to eliminate uncertainty but to create better frameworks for managing it effectively.
References:
Daw, N. D., Niv, Y., & Dayan, P. (2005). Uncertainty-based competition between prefrontal and dorsolateral striatal systems for behavioral control. Nature Neuroscience, 8(12), 1704-1711. https://doi.org/10.1038/nn1560
Kahn, A. E., & Daw, N. D. (2025). Humans rationally balance detailed and temporally abstract world models. Communications Psychology, 3(1), 1-11. https://doi.org/10.1038/s44271-024-00169-3
Pinker, S. (2021). Rationality: What It Is, Why It Seems Scarce, Why It Matters. Viking Press.
Viale, R. (2021). Embodying Bounded Rationality: From Embodied Bounded Rationality to Embodied Rationality. Frontiers in Psychology, 12, 710607. https://doi.org/10.3389/fpsyg.2021.710607
Viale, R., Gallagher, S., & Gallese, V. (2023). Bounded rationality, enactive problem solving, and the neuroscience of social interaction. Frontiers in Psychology, 14, 1152866. https://doi.org/10.3389/fpsyg.2023.1152866
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