Analytics has become a new source of competitive advantage for many corporations. Today’s work force therefore must be cognizant of its power and value to effectively perform their jobs. In this paper, we define the appropriate skill level and breadth of knowledge required for business school graduates to be successful. An undergraduate course of study in analytics is proposed for students with average to above-average analytical skills. Implementation guidelines are also addressed to ensure a successful program.

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The primary goal of the accompanying case study, "You Can't Take It with You," is to help business students develop better problem-solving skills. Teaching quantitative courses to students not in a STEM (science, technology, engineering, mathematics) discipline can be a challenging task. Using concrete examples with spreadsheets is an effective teaching strategy that appeals to many business students. This case study offers a concrete and relevant exercise using the base package of Excel. It is multidisciplinary and flexible in its delivery, allowing instructors to effectively integrate it into their course(s). Topics that may be covered include simulation, data analysis, and the time value of money. Advanced Excel functions that may be used include PMT, NORMINV, VLOOKUP, Scenario Manager, Data Table , and Goal Seek. Overall, students believed the case was challenging and that it was a valuable learning experience.

Many of the skills that define analytics are not new. Nonetheless, it has become a new source of competitive advantage for many corporations. Today's workforce, therefore, must be cognizant of its power and value to effectively perform their jobs. In this chapter, the authors differentiate the role of a business analyst by defining the appropriate skill level and breadth of knowledge required for them to be successful. Business analysts fill the gap between the experts (data scientists) and the day-to-day users. Finally, the section on Manufacturing Analytics provides real-world applications of Analytics for companies in a production setting. The ideas presented herein argue in favor of a dedicated program for business analysts.

The objective of this research is to produce a simple tool to assist health care management in quantifying the tradeoffs between different resource allocations. In many cases, intuition results in an appropriate selection; the quandary, however, is typically over the magnitude of improvement. The problem addressed herein uses queuing theory in the context of a hypothetical walk-in clinic. Different resource allocations are compared on the basis of the expected number of patients in the waiting room. Without comparative numbers, managers are forced to guesstimate the difference in expected queue lengths. Fact-based decisions not only improve quality but give the decision maker a sense of comfort.