Assignment 2: Banking on a Beard Award Decision trees are models which allow you to both visualize and quantify a range of possible outcomes when faced with complex choices. These models incorporate the timing and estimated probability of outcomes along branches on a tree to help you identify the most promising path forward. Review the following: Real Options and the Value of Information Did you know that roughly 60 percent of new restaurant businesses fail within the first three years of operation (Abrams, 2004)? Suppose you have a close friend who is employed in a high-paying position in the banking industry with tremendous potential for her professional and financial growth. However, your friend wants to leave this position and start a little restaurant. It is your job to help your friend make a sound decision. What do you do? Often, the valuations on which decisions are based require the input of information neither easily deduced nor accurately available. There are so many options and so little time. The values of these options can be clouded in uncertainty. The likelihood of each outcome—both those that are dependent and those that are independent—is shrouded in a variety of likely scenarios. Like your friend, you must assess the value of certain options, including those choices foregone. If your friend, the restaurateur, leaves her job, what is the income she has given up? What is the probability that her business will flourish for a year or two years? What is the likelihood today that she will be in business three years from today (you would immediately think 40 percent)? What if she creates a great restaurant that is widely acclaimed, but the market, well beyond her control, suddenly crashes? How might you have incorporated that information in your forecast of probabilities? As you can see, decision points combine with scenarios, including events beyond the chooser’s control, to increase the complexity of choosing. Fortunately you have a tool,...
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