Questions for you:
- When making decisions under uncertainty, do I acknowledge the full range of possible outcomes or focus only on most likely scenarios?
- How comfortable am I with probabilistic thinking rather than seeking single “right” answers?
- Do I understand the limitations of predictions about rare but high-impact events?
Organisational applications:
- Monte Carlo scenario analysis for strategic decisions:
Replace single “most likely” forecasts with probabilistic range modelling for major decisions. Run thousands of simulations incorporating uncertainty in multiple variables (market demand, regulatory changes, competitor responses, economic conditions) to generate distribution of possible outcomes rather than point estimates. This reveals which strategies remain robust across diverse futures versus those optimised for specific assumptions that may not hold. Apply particularly to capital allocation, market entry timing, and long-term investment decisions where single forecasts create false confidence. - Wargaming critical business scenarios:
Implement regular wargaming exercises where teams role-play responses to crisis scenarios with uncertainty explicitly modelled through randomisation. Unlike conventional planning which assumes single scenarios, wargames force decision-making under evolving conditions where “dice rolls” determine external developments (regulatory decisions, market shifts, competitor actions). Participants learn to make adaptive decisions rather than follow predetermined playbooks. Document which decision frameworks prove robust across multiple scenario variations versus those that only work under specific conditions. - Portfolio approach to uncertainty management:
Structure initiatives as portfolios of bets with different risk-return profiles rather than committing fully to single predicted futures. Maintain multiple simultaneous approaches to major challenges, accepting that some will fail whilst others succeed in ways that couldn’t be predicted. Deliberately include high-uncertainty, high-potential initiatives alongside safer options. This requires tolerating apparent inefficiency—maintaining capabilities that may not be needed—but provides resilience when unpredicted scenarios materialise. - Premortem analysis with probabilistic thinking:
Before major decisions, conduct premortems that explicitly quantify failure probability ranges rather than binary success/failure predictions. Teams imagine the initiative has failed and work backwards to identify what went wrong, then assign probability ranges to different failure modes. Unlike conventional risk assessment that produces single probability estimates, this generates uncertainty distributions around risks. The exercise forces acknowledgment that you cannot predict which specific problems will emerge, only that some will.
Further reading
On uncertainty and unpredictability:
The Black Swan: The Impact of the Highly Improbable by Nassim Nicholas Taleb (Random House, 2007). Examines why we systematically underestimate rare, high-impact events and why prediction-based planning fails for “Black Swan” scenarios. Argues for building robustness rather than attempting prediction.
Antifragile: Things That Gain from Disorder by Nassim Nicholas Taleb (Random House, 2012). Extends Black Swan thinking by exploring systems that improve under stress and uncertainty. Directly applicable to organisational resilience and designing systems that benefit from unpredictability.
The Logic of Failure: Recognizing and Avoiding Error in Complex Situations by Dietrich Dörner (Basic Books, 1996). Psychological research on why planning fails in complex systems with multiple uncertainties. Examines how humans systematically misjudge interconnected risks.
On scenario planning and futures thinking:
The Art of the Long View: Planning for the Future in an Uncertain World by Peter Schwartz (Currency, 1996). Classic text on scenario planning methodology, explaining how to develop multiple plausible futures rather than single predictions. Written by Shell’s former head of scenario planning.
Scenario Planning: Managing for the Future by Gill Ringland (Wiley, 2006). Comprehensive guide to scenario planning techniques with corporate case studies demonstrating how organisations use multiple scenarios for strategic decision-making.
Thinking in Time: The Uses of History for Decision-Makers by Richard E. Neustadt and Ernest R. May (Free Press, 1986). How historical analysis improves decision-making under uncertainty by revealing patterns and breaking assumptions about inevitable outcomes.
On wargaming and simulation:
Wargaming for Leaders: Strategic Decision Making from the Battlefield to the Boardroom by Mark Herman and Mark Frost (North Atlantic Books, 2009). Practical guide to using wargaming techniques for business strategy, crisis planning, and decision-making under uncertainty.
The Complete Wargames Handbook by James F. Dunnigan (William Morrow, 3rd edition, 2000). Comprehensive examination of wargaming methodology across military and civilian applications, with focus on modelling uncertainty through simulation.
On Monte Carlo methods and quantitative risk analysis:
How to Measure Anything: Finding the Value of “Intangibles” in Business by Douglas W. Hubbard (Wiley, 3rd edition, 2014). Accessible introduction to quantifying uncertainty using Monte Carlo simulation and probabilistic methods for business decisions. Directly challenges claims that certain risks are “unmeasurable.”
The Flaw of Averages: Why We Underestimate Risk in the Face of Uncertainty by Sam L. Savage (Wiley, 2009). Explains why planning based on average scenarios systematically fails and how probability distributions reveal true risk exposure. Includes practical Monte Carlo techniques.
Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein (Wiley, 1996). Historical examination of how humanity developed tools for managing uncertainty, from ancient gambling to modern risk management. Provides context for current methods.
On organisational resilience:
The Resilience Dividend: Being Strong in a World Where Things Go Wrong by Judith Rodin (PublicAffairs, 2014). Rockefeller Foundation president on building organisational and system resilience to unexpected shocks. Emphasises adaptive capacity over prediction.
Resilient Organizations: How to Survive, Thrive and Create Opportunities Through Crisis and Change by Erica Seville (Kogan Page, 2016). Practical frameworks for building organisational resilience based on disaster recovery research. Focuses on capabilities that work across multiple crisis types.
On decision-making under uncertainty:
Superforecasting: The Art and Science of Prediction by Philip E. Tetlock and Dan Gardner (Crown, 2015). Research on why some people make better probabilistic predictions than others and how organisations can improve forecasting accuracy whilst acknowledging irreducible uncertainty.
Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts by Annie Duke (Portfolio, 2018). Professional poker player on decision-making under uncertainty, emphasising probabilistic thinking and acknowledging what you cannot know.
On dealing with complexity:
Managing the Unexpected: Sustained Performance in a Complex World by Karl E. Weick and Kathleen M. Sutcliffe (Wiley, 3rd edition, 2015). Research on “high reliability organisations” that operate safely in uncertain, high-risk environments. Examines how they build resilience through culture rather than prediction.
Team of Teams: New Rules of Engagement for a Complex World by General Stanley McChrystal (Portfolio, 2015). Military leader on adapting organisational structures for rapid response to unpredictable threats. Emphasises adaptive systems over predetermined plans.
Interactive exhibit
You can play around with the idea of Monte Carlo simulators and how they might be used to predict your commute time here.
About the image
I spotted this soap dispenser in a shopping mall on the Malaysian island of Penang last summer. The double-entendre of the message amused me, because I’m easily amused like that.
Photo Matt Ballantine 2025 Photo montage Matt Ballantine 2026.
Random the Book 