Regardless of the setting, management decisions are necessarily made under conditions of risk and uncertainty.  The broad objective of this course is to enable the participants to embrace and manage risk and uncertainty, rather than be blindsided by it.  The course highlights the overarching challenges in assessment of risk and uncertainty and our susceptibility to illusion of control, some fundamental concepts of probability and statistics, strengths and weakness of quantitative models, some common cognitive biases in human intuition, and a prescriptive approach of combining quantitative models with judgment. While the course uses some technical concepts of probability and statistics, the emphasis is on sharpening intuition related to risk and uncertainty for a management career.

Nominated for Outstanding Teacher Award MBA Core Course every year except one since 1993, and won the award fourteen times:  1993, 1996, 1998, 1999, 2001, 2003, 2004, 2005, 2012, 2013, 2016, 2017, 2019, 2020.

This course introduces philosophy and methods of Bayesian inference and prediction, with emphasis on the general approach of modeling real-world problems of interest to data analysts and decision makers.  Topics include subjective probability, evaluation of probabilities, modeling data-generating processes, development of priors, inference and prediction for various processes, Bayesian estimation and hypothesis testing, and comparisons with classical/frequentist methods.

This includes a variety of combinations based on the three modules below.

A. Data, Models, and Illusion of Control

A senior management team along with the board of directors regularly look into the future and create a vision and subsequently craft a strategy towards that vision.  A home team of a nation must continuously view the existing and the future world through multiple windows and then allocate limited resources to various initiatives for the security of that nation.  The financial industry is the quintessential context for management of risk and uncertainty.  However, there often exist severe limits to predicting the future, be it in the context of business, investments, policy, health, or even personal pursuits such as happiness. We then look for shelter in “engineered models” to accurately predict future outcomes.  In doing so, we frequently go too far and often end up underestimating the role of chance and what we don’t control, we overestimate our ability to predict the future, underestimate risk and uncertainty, and hence fall prey to Illusion of Control with all its potential costs.  A counterpart to this is the Paradox of Control:  if we don’t try to control what we can’t control, we often end up with more beneficial outcomes. 

Key Learnings:
Understanding and embracing uncertainty as an opportunity, developing options and flexibility in the face of uncertainty, role of a leader.

B. Discernment: Cognitive Biases, Emotional Barriers, and Barriers to Learning

Stemming from our illusion of control, while making decisions, we are susceptible to cognitive biases, emotional barriers (such as greed, fear, and hope), and obstacles to learning (such as self-serving attribution, lack of experimentation).  Such distortions in individual decision making are illustrated with a variety of interactive online tools and some nudges are outlined to mitigate such distortions.

Key Learnings:
Budgeting and projections, performance reviews, evaluating downside/upside for risk management, stopping losing projects, alleviating inaction, fostering innovation and experimentation, defining organizational culture through leaders.

C. Diversity and Inclusiveness: A Judgmental View

Abundant theories exist on the importance of diversity and inclusiveness (D&I) at an organizational and societal level.  Yet, the effectiveness of such initiatives despite heavy investments and good intentions remains an open question.  This module highlights a value proposition for D&I as a fundamental aspect of improving the quality of judgments at an organizational level.  It is well known that individual judgments, including judgments of experts in their domains, are susceptible to a variety of cognitive biases, emotional barriers and obstacles to learning.  While such unconscious distortions in individual judgments can be mitigated through a variety of nudges, group-based judgments can be a powerful way to improve the quality of judgments.  And, in leveraging the full potential of group judgments, D&I is a key factor. A tangible and constructive meaning of diversity and inclusiveness in a group judgment process is proposed.  The practical implications cover various types of organizational and societal decision-making processes, the role of experts and leaders, and making the D&I initiatives effective with the correct messaging, with an overarching goal of improving judgments.

Key Learnings:
Individual judgments vs. group judgments, defining diversity, creating and managing a diverse team, defining and managing experts, the role of leaders and creating personal impact.

Some representative executive programs in which the Judgment modules are taught:

Open Enrollment Programs:

AMP (Advanced Management Program)
IDP (International Directors Program)
LEAP (Leadership Excellence through Awareness and Practice)

Company Specific Programs:

Raytheon Technologies
Singapore Home Team (various organizations of the Ministry of Home Affairs in Singapore)
Mizuho
Citibank
Tata Consulting Services
Pernod Ricard
Otsuka
Hitachi

1. Judgment Survey. The purpose of this tool is to highlight a variety of biases in human judgment in different real-life contexts, and to allow the possibility of benchmarking those biases for different population groups (for example, by demographics, culture, and institutions) against a reference population of interest.  For example, we can benchmark different departments in an organization against a reference population (for example, another organization).
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2. Game of Experts Trivia. The purpose of this tool is to highlight the overconfidence bias in assessments of uncertainty, and to create a learning experience towards reducing the overconfidence bias.  The tool enables an interactive exercise in several groups simultaneously, where participants engage in a game akin to a prediction market based on interval forecasts (rather than point forecasts) of trivia questions. The tool then generates a group-level report for participants.
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3. Game of Experts Real-Life. The purpose of this tool is to highlight the overconfidence bias in assessments of uncertainty, and to create a learning experience towards reducing the overconfidence bias. The tool enables an interactive exercise in several groups simultaneously, where participants engage in a game akin to a prediction market based on interval forecasts (rather than point forecasts) of real-life quantities. The tool then generates a group-level report for participants.
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4. Wisdom of Crowds. With this tool, the participants provide subjective estimates of unknown quantities, individually and in groups, in a variety of ways administered by the facilitator. The results provide an extensive platform for discussion of individual vs. group judgment.
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