About this Topic
This technical day addresses the critical question: when does quantification improve decisions versus when does it create false precision? Participants learn to distinguish between decisions that benefit from sophisticated modeling and those that require only structured thinking about key uncertainties.
The proportional risk analysis framework helps participants match analytical approaches to decision complexity. Simple operational decisions might need only structured uncertainty discussions, while complex strategic investments may require sophisticated Monte Carlo simulations. We explore the dangerous middle ground where organizations either over-analyze routine decisions or under-analyze critical strategic choices.
Hands-on workshops cover Monte Carlo simulations for business decisions, teaching participants to model correlated uncertainties and interpret probability distributions for decision-making. Scenario planning sessions focus on developing plausible future states that inform strategic planning, moving beyond generic "best/worst/most likely" approaches to scenarios that actually challenge strategic assumptions.
The expected value versus risk distribution workshop addresses a critical misconception - why focusing only on expected outcomes can lead to catastrophic decisions that ignore tail risks. Participants learn to communicate uncertainty to decision-makers in ways that improve choice quality rather than creating analysis paralysis.
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