What is the best strategy in a bidding situation? How does this strategy depend upon the auction type? Why do winners sometimes lose? Professor Howard demonstrates how decision analysis brings clarity of action to complex, highly-competitive auctions.

How much is it worth to gather additional information before making a choice? Professor Howard explains how decision diagrams can be used to represent information gathering opportunities, such as market research or testing programs.

Perhaps the single most important decision-making mistake is obtaining an excellent answer to a different problem. Before we can analyze our choices, we must frame the decision appropriately. Professor Howard will introduce the concepts of decision quality and the decision hierarchy. These concepts and their associated tools ensure that our efforts are focused in the right direction.

High-quality decision analyses require high-quality probabilistic assessments. How good are we at probability assessment, and how can we improve our performance? Professor Howard will demonstrate the pitfalls of probability assessment and how to overcome them. This includes careful modeling through the use of knowledge maps and systematic assessment procedures.

How do we incorporate risk aversion into our decision making procedures? How risk averse should you be? How about your company? Professor Howard will expand upon the risk preference modeling introduced during the DA course, to more directly tie risk preference to wealth. In addition, he will discuss the history of risk preference modeling and demonstrate its use.

How do we incorporate time and risk preference? How to we account for multiple value measures? Professor Howard will demonstrate how to account for joint time-risk preference and how the concept of dominance can simplify decision analyses. In addition, he will introduce the concept of direct and indirect values, which brings clarity when trying to achieve multiple objectives.

Suppose we face multiple information gathering opportunities or tests. How do we choose the best single test or combination of tests? Building on the Experimentation section, Professor Howard shows how to model multi-testing situations and demonstrates the effect of relevance between tests.

Most decision situations include downstream contingencies or future decision opportunities. How do we model and value such "options?" Professor Howard will discuss the fundamental importance of options in decision analyses. He will argue that our failure to include options in some decision analyses greatly reduces decision quality.

Suppose you face an investment that is too large for you individually, but you can form a syndicate comprised of other individuals who will purchase and share the investment. How should the syndicate be structured? What is your optimal share? In this section, Professor Howard will demonstrate how decision analysis can be used to optimally structure joint investments or partnerships.

The course concludes with a series of experiential exercises that unify understanding of key concepts.