Why Leaders Make Bad Decisions? Herbert Simon's Theory on Leaders' Decision-Making: A Comprehensive Analysis

Or Bar Cohen
Mar 3
4 min read

Introduction

Herbert Simon (1947) introduced the concept of bounded rationality, which suggests that decision-makers operate within the limits of available information, cognitive limitations, and time constraints. His work revolutionized the understanding of decision-making by recognizing that leaders cannot consistently achieve optimal decisions but must instead rely on satisficing, choosing an option that meets an acceptable threshold of satisfaction rather than the absolute best choice (Simon, 1979). This article examines eight common decision-making scenarios leaders face, analyzing them through Simon’s framework and providing recommendations for improvement based on academic research.

1. Decisions Under Information Overload

Leaders frequently encounter overwhelming information, leading to cognitive overload and poor decision quality (Eppler & Mengis, 2004). Simon’s bounded rationality explains that humans can only process a limited amount of data effectively.

Example:

A CEO of a multinational corporation must analyze extensive market reports, financial forecasts, and industry trends to decide on an international expansion strategy. The overload of data results in analysis paralysis, delaying critical decisions.

Improvement Strategy:

Prioritize Key Data: Implement decision-support systems to filter out non-essential information and focus on critical insights (Davenport & Harris, 2007).
Delegate Information Processing: Assign specialized teams to analyze specific data aspects, providing summarized insights to leadership.
Adopt AI and Automation Tools: Utilize machine learning algorithms to streamline data analysis and highlight actionable insights.

2. Satisficing Instead of Optimizing

According to Simon, decision-makers often settle for the first acceptable option rather than exhaustively evaluating all possibilities (Gigerenzer & Goldstein, 1996).

Example:

A startup founder selects a software provider without thoroughly comparing alternatives, leading to long-term inefficiencies and higher operational costs.

Improvement Strategy:

Use Decision Matrices: Implement structured frameworks such as weighted decision matrices to compare multiple options systematically.
Set Clear Evaluation Criteria: Define key performance indicators (KPIs) before making selections to ensure objective decision-making.
Encourage Multiple Perspectives: Consult team members with diverse expertise to identify potential blind spots.

3. Heuristic Biases in Decision-Making

Heuristics, or mental shortcuts, can lead to systematic errors in judgment (Tversky & Kahneman, 1974). Leaders may rely on intuition rather than evidence-based analysis.

Example:

A hiring manager selects a candidate based on first impressions rather than an objective evaluation, leading to suboptimal hiring decisions.

Improvement Strategy:

Implement Structured Interviews: Use standardized questions and scoring rubrics to reduce bias in hiring (Schmidt & Hunter, 1998).
Promote Data-Driven Decision-Making: Encourage leaders to base decisions on empirical evidence rather than intuition.
Train on Cognitive Biases: Conduct workshops on recognizing and mitigating heuristic biases.

4. Decision-Making Under Time Constraints

Leaders often make high-stakes decisions under pressure, leading to rushed or poorly thought-out choices (Eisenhardt, 1989).

Example:

A marketing director must decide on a last-minute advertising campaign but lacks sufficient time for thorough market research, leading to ineffective messaging.

Improvement Strategy:

Develop Contingency Plans: Prepare pre-approved strategic responses for common scenarios to reduce the burden of last-minute decisions.
Utilize Decision Trees: Employ decision-making frameworks to evaluate trade-offs quickly.
Delegate Authority: Empower mid-level managers to make real-time decisions within predefined guidelines.

5. Group Decision-Making Challenges

Decision-making in groups can be hindered by issues such as groupthink, conflicting interests, or dominance by certain individuals (Janis, 1982).

Example:

A boardroom discussion is dominated by a senior executive’s opinion, preventing alternative viewpoints from being considered.

Improvement Strategy:

Encourage Devil’s Advocacy: Assign team members to challenge prevailing opinions to foster critical discussions.
Use Anonymous Voting Systems: Enable confidential input to minimize social pressure and bias.
Promote Psychological Safety: Create an open culture where employees feel comfortable voicing dissenting opinions.

6. Escalation of Commitment to Failing Decisions

Leaders sometimes continue investing in unsuccessful projects due to sunk costs and ego involvement (Staw, 1976).

Example:

A technology company persists with a failing product launch despite clear market signals indicating poor reception.

Improvement Strategy:

Set Clear Exit Criteria: Define measurable benchmarks for reassessing failing initiatives.
Encourage Adaptive Learning: Promote an iterative approach where strategies can be adjusted based on real-time feedback.
Separate Personal Ego from Decisions: Foster a culture where acknowledging failure is seen as strategic wisdom rather than weakness.

7. Limited Consideration of Alternative Solutions

Time constraints and cognitive limitations often lead leaders to overlook potential alternatives (Bazerman & Moore, 2013).

Example:

A CFO considering cost-cutting measures immediately opts for layoffs rather than exploring process optimization or automation alternatives.

Improvement Strategy:

Adopt the “5 Whys” Technique: Encourage deeper exploration of problems before selecting solutions.
Brainstorm Multiple Scenarios: Use structured ideation methods such as the Delphi technique to generate diverse solutions.
Consult External Experts: Engage industry specialists to provide fresh perspectives on challenges.

8. Intuition vs. Analytical Decision-Making

While intuition can be valuable, overreliance on gut feelings can lead to errors (Dane & Pratt, 2007).

Example:

A venture capitalist invests in a startup based on a charismatic pitch rather than due diligence, resulting in financial losses.

Improvement Strategy:

Use Data Analytics: Incorporate predictive modeling and risk assessment tools.
Combine Intuition with Analysis: Balance instinct with empirical validation through A/B testing and pilot projects.
Develop Reflective Thinking: Encourage leaders to review past decisions to refine their judgment.

Conclusion

Herbert Simon’s work on decision-making remains highly relevant for modern leaders navigating complex environments. Organizations can enhance leadership decision-making effectiveness by acknowledging bounded rationality and integrating structured frameworks, decision-support tools, and cognitive bias training. Implementing these strategies ensures more rational, inclusive, data-driven choices that drive sustainable success.

References

Bazerman, M. H., & Moore, D. A. (2013). Judgment in Managerial Decision Making. Wiley.
Dane, E., & Pratt, M. G. (2007). Exploring intuition and its role in managerial decision making. Academy of Management Review, 32(1), 33-54.
Davenport, T. H., & Harris, J. G. (2007). Competing on Analytics: The New Science of Winning. Harvard Business Review Press.
Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal, 32(3), 543-576.
Eppler, M. J., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting, marketing, MIS, and related disciplines. Information Society, 20(5), 325-344.
Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103(4), 650.
Simon, H. A. (1947). Administrative Behavior. Macmillan.
Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.