Albright, S. C., & Winston, W. L. (2017). Business analytics: Data analysis and decision making (6th ed.). Stamford, CT: Cengage Learning.Chapter 6, “Decision Making Under Uncertainty”Chapter 7, “Sampling and Sampling Distributions”Ekin, T., Kocadagli, O., Bastian, N. D., Fulton, L. V., & Griffin, P. M. (2015). Fuzzy decision making in health systems: A resource allocation model. JEuro Journal on Decision Processes, 1–23.Note: Retrieved from the Walden Library databases.
Discussion: Fuzzy Decision Making
When uncertainty exists, how does one evaluate the universe of possible outcomes?
Unfortunately, there is no one steadfast rule on how to anticipate what a correct decision might be. However, there are a set of tools and practices that healthcare administration leaders can use to help make the best decision possible given data for a particular set of circumstances. One such example is that of fuzzy decision making, wherein a healthcare administration leader attempts to wrap human expertise around a set of guidelines to enhance workflow and performance. While not all circumstances may lend themselves to fuzzy decision making, understanding what these tools are is a useful practice when managing a health services organization.
For this Discussion, review the resources for this week. Reflect on the concept of fuzzy decision making for healthcare administration practice. Consider how you, as a current or future healthcare administration leader, may engage in fuzzy decision making for your health services organization.
Post a description of how you would define fuzzy decision making for healthcare administration practice. Then, explain how you might implement fuzzy decision making to evaluate decisions when uncertainty exists. Provide an example where fuzzy decision making might be important for your work or life, and explain why. Be specific and provide examples.
Palisade [PalisadeCorp]. (2014b, January 29). Introduction to PrecisionTree—Palisade webcast [Video file]. Retrieved from