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Piedmont Airlines Case Study

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Piedmont Airlines Case Study
Executive Summary

Piedmont Airlines recently invested over $1 million in state of the art equipment and employee development in order to forecast and analyze the appropriate amount of discounted fares to offer per flight. The company discovered that by offering several discounted flights to consumers willing to book their travel well in advance of their departure date left many options available for the business traveler who needed to book much closer to the actual departure date. The analysis was the task of the Revenue Enhancement Department (RED) managed by Marilyn Hoppe. While this state of the art equipment was a step in the right direction, Marilyn believed that there were still a lot of subjective decisions being made and automation was not as prevalent as she would have liked. She wanted the process to be more scientific in nature and leave less up to chance or human interpretation.

Smart Choices and Proactive Decision Making
The decision for the Revenue Enhancement Department to change the current process of allocating discounted seats is definitely a complex one. There are numerous factors and variables to evaluate before making an informed decision or even begin the decision-making process. Some pertinent things that come into play in making this decision include the reports of historical and forecasted data that the seven analysts built, the judgment of the analyst team, competitor activity, and economic trends. Marilyn is in a key role to guide proactively throughout this process, but it will be important to involve the appropriate stakeholders to provide information to help make the decision. This creates the most constructive environment to ensure the right questions are being asked based on the objective that is given. In order for Piedmont to benefit the most from these findings, the company should first look at the core decision-making process and how it applies.
Objective- The objective for this case is to decide how the Revenue



References: Anderson, D. R. (2008). Essentials of statistics for business and economics. (5th ed.). Mason, OH: Thompson Higher Education. Bodily, S. E., Carraway, R.L., Frey, Jr., S.C. & Pfeifer, P.E. (1998). Quantitative business analysis: Text and cases: Irwin/McGraw-Hill. Hammond, J., Keeney, R., & Raiffa, H. (199). Smart choices: A practical guide to making better decisions. Harvard Business School Press, 8(3), 150. Predicting consumer behavior [Web log message]. (2012, March 05). Retrieved from http://distributedmarketing.org/2012/03/05/predicting-consumer-behavior/ Stevenson, W. (2005). Introduction to Operations Management. Operations Management (8th ed.) (pp. 12-14). Irwin/McGraw-Hill

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