Coming from a mathematical background I can appreciate the beauty of the equations shown in this chapter, however, I believe that math has a place in everything but may not hold the entire answer. Equations can answer questions involving risk, profit and other measurable aspects, but they may not show the entire picture. When making dynamic decisions one must weigh all the options and look at them in different ways.
The first step in solving problems for me is to gather information and lots of it. I like to have as much information as possible in order to make an informed decision; sometimes I might go overboard and gather too much information, which can send my mind into overload. Once I have gathered information, I need to sort through it to eliminate that which may not be relevant to the specific problem at hand. Hoch, Kunreuther, and Gunther (2001) described this as accumulation of knowledge.
Once I have gathered and sorted through all the information, I will try to form two options and weigh them against each other. This is similar to what Hoch et al (2001) described in decision policies, this is where math equations can be helpful. When I am making a decision with two outcomes I prefer to use a simple T-chart to help me weigh the options. A T-chart is a graphic organizer, which compared pros and cons, advantages and disadvantages, or facts for both sides. Once I fill in the chart I can weigh which option will be right for me. Sometimes the decision is obvious sometimes it’s not such a clear choice.
Two points Hoch et al (2001) made that resonated with me were complete forward planning and optimal learning. With complete forward planning all aspects, possible choices, and outcomes are considered. This is very similar to the way that I make decisions, I look at all the possible outcomes no matter how unlikely they may be to happen. This not only offers multiple options for decisions but can also rule out any options that don’t fit into the plan. Optimal learning is about using past information to make future decisions. This is along the same lines as excepting and learning from feedback. Ever experience is a process in learning no matter the outcome, positive or negative. If we are able to look back on our past choices and learn what went right and what didn’t then we are better prepared for future decisions.
The combination of looking forward and learning from the past are the keys to making dynamic decisions. Where we can’t predict the future we can learn from the past and use it to make better decisions. Feedback is one of the most powerful tools we have to help us make better choices and learn from our mistakes. Feedback isn’t always easy to take but it is important. If the old adage “history always repeats itself” is true then the more we learn from the past the more we will succeed in the future.
Hoch, S., Kunreuther, H., & Gunther, R. (2001). Wharton on making decisions.
Hoboken, New Jersey:John Wiley & Sons, Inc.
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