A632.1.4.RB - Multistage Decision-Making

                        Decision making is a challenging process and requires confidence in one’s decision as a leader. Jonsson, et al (2005) stated that decision confidence is the feeling of having done something correctly or incorrectly and is an important aspect of subjective experience during decision making; this also increases for correct decisions and decreases for error decisions as the task become easier. There are several options for leaders in order to make decisions about future situations; these include, formulas for multistage problems, complete forward planning, and optimal learning.  

            In order for researchers to solve multistage problems, they need simplifying assumptions, which Hoch, Kunreuther, & Gunther (2001) described as an accumulation of knowledge and decision policies. The accumulation of knowledge is expanded knowledge about the situation over an extended period of time. The decision policies are how one will make a decision over the time period. In order to reach a conclusion based on the information at hand, a mathematical formula is used to determine the best possible outcome.  The process for this situation is called dynamic programming, which Hoch, Kunreuther, & Gunther (2001) described as a process for solving multistage decision problems that are widely credited to the mathematician Richard Bellman.

            Forward planning is described by Hoch, Kunreuther, & Gunther (2001) as when maximizing total utility over the horizon, decision makers are assumed to look ahead to all future periods and anticipate all possible choices and outcomes. Forward planning may be hindered by myopic thinking, which is defined by Myopia (n.d.) as a lack of foresight or discernment; or a narrow viewing of something. One must be able to see beyond roadblocks when planning for the future in order to make a clear and decisive decision. Forward planning is a great tool to utilize to plan for the future, however; myopic thinking may hinder forward planning because one may narrow their future path rather than expand their abilities.

            Optimal learning (n.d.) is defined as addressing the challenge of how to collect information as efficiently as possible, primarily for settings where collecting information is time consuming and expensive. This is supported by Hoch, Kunreuther, & Gunter (2001) who stated that optimal learning is assumed to fully utilize past information to update both current beliefs and future predictions.

Based on the information in the text, as well as additional research, I would say the formula for future problem solving in my future is very unlikely to be effective. Forward planning is the approach I use in order to make effective decisions because I observe all avenues of approach in order to rule out any unforeseen possibilities. However, I need to work on creative thinking and expanding my horizons in order to improve forward planning abilities and not allow myopia to hinder the decision-making process. Although this practice and mindset is not effective for everyone, I find that it works best for me because I have the opportunity to prepare mentally for the circumstances beyond my control.

Overall, when making a decision, there are multiple methods for making future predictions to solve problems. This can be done with mathematical equations, analysis from past situations, and comparative data to assist with decision making. However, one must ultimately decide which method works best for them in order to make a decision.  

Jonsson et al., (2005). Jonsson FU, Olsson H, Olsson J. Odor emotionality affects the confidence in odor naming. Chem Senses 30: 29–35, 2005

Hoch, S. J., Kunreuther, H. C., & Gunther, R. E. (2001). Wharton on Marking Decisions. Hoboken, NJ: John Wiley & Sons Inc.

"Myopia." Merriam-Webster.com. Merriam-Webster, n.d. Web. 16 Jan. 2016.

Optimal Learning. (n.d.). Retrieved January 17, 2016, from Princeton.edu website:

     http://optimallearning.princeton.edu/