Dear Club Geographer:

 

For your information – this can be a good option for those of you who are interested in business applications with quantitative and computational analysis.

 

Since Club Geography List does not permit attachments, I have copy-and-pasted the flyer to the end of this message.

 

Best,

 

Shih-Lung

 

 

Dr. Shaw:

Please share this information about our new program in Business Analytics with your students. It is a program ideally suited for geography majors who would like to further develop their quantitative skills and learn how to apply them in a business environment. There is a strong demand in industry for problem solvers with training in business intelligence, data mining, applied statistics or process optimization.

The Department of Statistics, Operations, and Management Science in the College of Business Administration at the University of Tennessee will begin offering a new M.S. degree in Business Analytics beginning in the Fall of 2010.  The program provides an alternative to the M.B.A degree for students that are interested in advanced mathematical and statistical tools and how they can be applied in modern business.  The duration of the program is 3 semesters and offers a tuition waver and 10 hours of assistantship for students that qualify.

Our faculty have years of experience in teaching analytical techniques such as Statistical Process Control, Lean Manufacturing, Operations, and Data Mining to executives.  These topics are an integral part of our program.  Students will also attend courses that are part of the MBA curriculum in order to gain managerial training and familiarity with business processes.
As currently designed the program offers four tracks focusing on various career paths: Business Intelligence, Data Mining, Business Process Optimization and Applied Statistics.  More details are given below, as well at the weblink: Business Analytics at UT Knoxville <http://bus.utk.edu/soms/analytics/index.htm> .  

Prerequisites are also provided on the website and include a minimum GPA of 3.0, three semesters of Calculus, and knowledge of at least one programming language.
Please feel free to contact me by phone (865-974-1738) or via email: [log in to unmask]">[log in to unmask] <[log in to unmask]">http:[log in to unmask]>  and we will be happy to address any questions.  I look forward to hearing from you.

Kenneth Gilbert

Department Head

Statistics, Operations and Management Science

 

Are you a student in mathematics, economics, computer science, or another quantitative field interested in applying your quantitative abilities in the real world?

If so, we have the perfect graduate degree for you, a Master’s in Business Analytics at the University of Tennessee, in beautiful Knoxville, TN.

Please visit our website for more information at http://bus.utk.edu/soms/analytics/index.htm

Why Business Analytics? To solve real-world quantitatively-oriented problems at some of the most successful businesses in the world . . .

“People who can do high level math are practically a commodity. People who can figure out which problem is the right one to solve and then apply high level math are both expensive and elusive.  Those who can communicate effectively the answer in such a way managers can understand, priceless.”  Dave Clark, Vice President North American Fulfillment, Amazon.com, and University of Tennessee MBA graduate

What is Business Analytics at the University of Tennessee?

The goal of business analytics is to help managers achieve better business performance.  Students in our program develop an understanding of business; they develop the skills needed to work effectively in a business environment and they learn the analytic skills to solve business problems. These analytic skills encompass four overlapping areas: business intelligence, data mining, process optimization and applied statistics.

The goal of business intelligence is better decision making in business. For example, in order to know how to improve business performance, a retail manager may need to objectively compare the performance of several different retail outlets. This comparison is difficult because the retail outlets are different in terms of inputs, e.g. floor space, advertising budget, population of the neighborhood, number of employees. It is made even more complex because there are many different measures of performance such as total sales, profit margin, gain in market share, customer satisfaction.  The tools of business intelligence help perform such complex comparisons. As another example, a company may need to decide what mix of products to produce. In order to understand this decision, the company must take into account how these products compete for capital, manufacturing capacity, warehouse space shipping capacity and marketing efforts. 

Data mining involves gleaning information from a company’s database of historical records. For example, which customers are most likely to respond to a coupon promotion?  Are there common attributes of those customers who cancel their insurance policy? What set of variables are best at predicting whether a potential customer’s visit to a web site will actually result in a sale?  What distinguishes those transactions in which the customer returns the purchase for a refund?

Business process optimization is aimed at making processes more efficient. For example, it may be discovered through data mining that customers who request a price quote on property insurance are much more likely to buy if they receive a response within twenty four hours.  Then the job becomes that of improving the process for quoting prices so that the response time is consistently less than twenty-four hours.

Applied statistics involves collecting and analyzing data to gain business insights.  It sometimes involves specifying business experiments necessary to answer important questions. For example, suppose a retailer plans to launch a coordinated advertising campaign and in-store display to boost sales of a particular line of products. Before the company launches the campaign nationwide it may first conduct experiments in selected locations. These experiments will help the retailer better understand the impact of the mix of advertising media used and the type of ad used.  At the same time, the effect of the attributes of the display such as size, color and placement will also be studied. Since the WWW is such a prolific interface between businesses and prospective customers, it has become the primary venue for experimentation. Every day, web users unwittingly participate in experiments designed to provide business insight.

 

Find out what business is up to and join the innovation!  Earn an M.S. in Business Analytics.