Short Abstract

In the face of risk (likelihood of an unfavorable outcome) and uncertainty (range of possible outcomes), how well do you perform at decision-making? Do you strive to make good decisions or to make the right decisions? If the right decision is the descriptive result of the knowledge of an event that has already occurred, a good decision can be defined as logically consistent, defensible, transparent, and prescriptive. In the face of risk and uncertainty, the webinar addresses why you should strive to make good decisions which may lead to favorable or unfavorable outcomes.
     While organizations tend to provide rewards for the right decisions, in reality, one can only make good decisions when the path ahead is unclear and the minefields that lie along one or other path are shrouded by the fogginess of uncertainty. Beginning with an overview of the different mental models of decision-making and examining hidden traps that prohibit good decision-making, this webinar provides a structured methodology for making difficult and complex decisions by first decomposing them into phased elements and applying proven analytic techniques that facilitate good, informed decision-making. Decision Tree analysis is employed to decompose complex, sequential decisions while Expected Monetary Value (EMV) is described as the common currency to evaluate decision options and to value information before committing to expensive investments. Because prioritization is utilized so widely in organizations, utility theory is introduced as a means of incorporating both quantitative and qualitative decision criteria in an attempt to bring together the often conflicting objectives of multiple stakeholders on Governance committees.

This presentation will cover the following areas :

• Decision framing and decision modeling.
• Probability and risk analysis.
• Uncertainty forecasting.
• Data integrity, cognitive and emotional biases.
• Decision Tree analysis.
• Risk preference.
• Utility theory and Multiple Objective Decision Analysis (MODA).