The document discusses the Master's in Business Analytics program at the University of Tennessee. It describes how business analytics focuses on using data and statistics to gain insights and aid decision making. It provides examples of how companies are using analytics to improve customer retention, recruitment, and business decisions. The program teaches students to ask the right questions, use analytics to answer them, and clearly communicate results.
2. Business Analytics: No Longer an
Option for Success in 21st Century
• Focus is on developing new insights and
understandings of business performance
based on data and statistical methods
– Analyzes past performance to aid in better
decision making
• Companies must embrace this because their
competition is
msanalytics@utk.edu
(865) 974-4116
3. Answers
Big (Holy Grail) Questions
• 5% of my customers contribute 105% of my
profits. Who are they and how do I create more
of them?
• One third of my new sales people fail. How can I
do a better job of recruiting the right people?
• Are we capturing all the relevant costs to our
outsourcing decisions? How can I identify those
choices that save a dime in cost, but sacrifice a
quarter in revenue?
• How can I double the amount my customers
spend on each visit to my store?
msanalytics@utk.edu
(865) 974-4116
4. The Tennessee
Business Analytics Model
• Apply big picture thinking to ask the right
question
• Use analytics to answer the question
• Communicate the results in a clear and
concise manner
msanalytics@utk.edu
(865) 974-4116
6. The Standard Question in Major
League Baseball
How can we maximize
Quality of Players/ $ Dollar Spent
Conventionally answered using four measurements
Running
Fielding
Throwing
Hitting
msanalytics@utk.edu
(865) 974-4116
7. The Oakland A’s
Asked the Right Question
How do we Maximize
Wins/ $ spent?
msanalytics@utk.edu
(865) 974-4116
8. The Oakland A’s Used Analytics to
Answer the Question
Statistical Analysis (guided by process
knowledge) revealed that:
– Runs lead to wins
– Getting on base leads to runs
– Walks, on-base percentage and slugging
percentage are better predictors of a
player’s value than stolen bases, rbi’s, and
batting average.
msanalytics@utk.edu
(865) 974-4116
9. They Communicated the Answer in a
Format Everyone Easily Understood
Question - Why do we want that player?
Answer - He gets on base.
Question - How can we replace Giambi, our
best individual player?
Answer - We can’t . But we can create a
winning TEAM.
msanalytics@utk.edu
(865) 974-4116
11. Asking the Right Question
• How does a customer’s target.com
browsing pattern influence them to make
an in-store Target purchase?
• If they browsed, would they then make an in-store
purchase?
• If they made an in-store purchase, how much were they
expected to spend?
• Is this something we can predict?
msanalytics@utk.edu
(865) 974-4116
12. The Data-Driven Process to Answer
the Question
• Because we are trying to predict customer
behavior, must use statistical method called predictive
analysis.
• Need to determine what browse factors influence store
purchases and sales amounts.
• Merge 2 datasets:
• Guest online browse data
• In-store purchase data
?
msanalytics@utk.edu
(865) 974-4116
13. Findings
• Successful model that predicts how groups of
customers will behave based on their
target.com browse behaviors
– Whether or not they made a purchase
– How much we expect them to spend if they DO
make a purchase
• Results can be put into action in many ways
– Online personalization, coupons, etc.
msanalytics@utk.edu
(865) 974-4116
15. Asking the Right Question
• Is it possible to predict the accuracy of a
line picker in the warehouse?
• Will the Hays Aptitude Test accurately predict how an
associate will perform?
• How can we go about determining this?
msanalytics@utk.edu
(865) 974-4116
16. The Data-Driven Process to Answer
the Question
• Needed to find correlation between test results and
associate performance
• Two Possible Methods
• Run longitudinal test to determine how new hires perform
at line picking positions
• Have current line picking associates take tests and
calculate correlation value
msanalytics@utk.edu
(865) 974-4116
17. Findings
• Not 1 of the 4 sections of the test had any
correlation with associate performance
– Saved company $75 per new associate hire
– Started new project to determine what factors
have strongest influence on performance
msanalytics@utk.edu
(865) 974-4116
20. Why number of companies and
salaries will significantly increase
1. CEOs recognize business analytical talent is
critical to success and are demanding this talent
in their organizations
msanalytics@utk.edu
(865) 974-4116
21. Why number of companies and
salaries will significantly increase
1. CEO’s are demanding this talent in their
organizations
2. Supply and Demand
msanalytics@utk.edu
(865) 974-4116
22. Business Analytics
By 2018, the U.S. will face a shortage of
1,500,000 managers who can use data to shape
business decisions
May, 2010 McKinsey and Co. Study reported in Wall Street Journal 8/4/11
msanalytics@utk.edu
(865) 974-4116
23. UT’s Business Analytics Master’s is a
Path to a Promising Career
• High and Increasing interest by top companies
• Very attractive starting salaries
• Recognition by CEO’s of importance to
maintain competitive advantage
• Projected high demand and low supply
msanalytics@utk.edu
(865) 974-4116
24. Contact Us
• Please reach out to us with any questions.
• Department of Statistics, Operations and
Management Science
• Email: MSAnalytics@utk.edu
• Phone: 865-974-4116
• Web: soms.utk.edu/analytics
msanalytics@utk.edu
(865) 974-4116
