1. Kirk Karwan Department of Business & Accounting Furman University
Analytics II: Elevating the Quantitative and Qualitative Decision Making Skills of Undergraduates
Kirk Karwan
Department of Business & Accounting
Furman University

2. Furman University Private, liberal arts, all undergraduate
In Greenville, SC along I-85
Business program, Economics dept.,
no statistics department
Division I Sports

3. Our new toy…

4. Two+ Business Analytics Classes
BUS 337 – Predictive Analytics
BUS 338 – Descriptive & Prescriptive Analytics
Each course, juniors and seniors, heavily Business Administration majors.
Background primarily limited to calculus and an introductory economics-based statistics course
Complemented by a qualitative course, BUS – 230, entitled
Problem Solving & Decision Making for Management

5. Experiment #1 – The Predictive Analytics Course
I worried about the statistical aspects
Student experience with statistics
Student capabilities
Accommodation of both methods AND interpretation/understanding
I was wrong
They appreciated learning EXCEL better and loved some applications – sports data, forecasting financial outcomes, etc.
Word of mouth now carries course

6. Experiment #2: A Course in Prescriptive Analytics
The original plan:
Give it the college try with optimization and simulation tools
In part, selfish on my part
Enhance student abilities to describe data AND results
-overcome preconceptions about ‘complex’ tools
Simultaneously, I wanted to deal with comments from employers and recent graduates in business analysis positions – telling the story

7. Course Specifics A course about descriptive and prescriptive analytics
Evans Business Analytics text and Frontline Systems (Analytics Solver) platform as needed
Decided to ‘wade’ into Tableau during early part of the course
Optimization and simulation in second half

8. Issues… A goal: to dismiss the instinct that ‘this is just math/stat’
A second: keep the experience away from: “Did I get the right answer?”
I like to think that: liberal arts students are more open to ‘uncertainty in exams, approaches, etc.’.
Possibly true in that most disciplines teach something about the decision making ‘process’ (history, political science, etc.)
…but I doubt it as often as I believe it

11. Krishna Dhir (Decision Line, 2005)
What is needed is:
Applied math with some
drama

12. Some Thoughts…
Most of our students do not think like we do… Then again, neither do most decision makers.
Re-learning the significance of ‘WHAT IF’
Consultants know this
Adding complexity to establish relevance
Larger problems – e.g, scheduling airlines, routing, etc.
Perhaps two-stage problems

13. Mathematical Model (Cont’d)

14. 2015 NFL PLAYING SCHEDULE Completed schedule
Scheduling process begins immediately after the regular season ends once all opponents are known. Input is solicited from all 32 Clubs (stadium blocks, travel considerations, competitive factors, key initiatives, etc.) and from all 5 Network partners regarding the 6 different television packages (key games, dates, markets, etc.). Entire process takes about 3 months with the computers (and humans!) working 24 hours a day.

15. PARTIAL LIST OF 2015 RULES & CONSTRAINTS
Teams playing in London home the week prior, on BYE the week after
Two teams must play Thursday of Week 13 after playing Thanksgiving Day
No team plays more than two road games against team coming off their BYE
No team plays consecutive road games involving cross-country trips unless requested
All teams playing road Thursday games are home the previous week
All teams playing home Thursday games have limited travel the previous week
All teams playing Thursday games cannot play Monday night the previous two weeks
No team has earliest BYE in consecutive seasons
Maximize separation between each teams’ Thursday game and their BYE
Minimize non-division games during hurricane season (enabling us to “swap” sites)
Minimize 3-game road trips (and 3-game home stands for teams with ticket issues)
Minimize number of teams playing road game after road MNF
Minimize number of division series that end in first half of season
Minimize number of division series that are played less than 3 weeks apart
Minimize number of teams that play two consecutive road games to start or end season
Minimize number of games that would have conflicts with MLB postseason
Maximize number of late-season division games
Manage the number Pacific time zone teams play at 1:00pm ET in the Eastern time zone
Minimize early-season 1pm games for teams with weather concerns
CBS/FOX have at least three 1pm games every week, preferably geographically diverse
CBS/FOX have at least five total games, preferably six or more when doubleheader network
CBS and FOX shouldn’t “lose” their key teams or an entire division all on same weekend
Teams can play no more than 6 primetime games, and only 3 teams per year can play 6
All other teams can play no more than 5 primetime games (max 4 NBC)

16. The Two Phase Method: Second Phase
Second phase assigns Thursday games and venues for all games
Thursday games and venues of games for the same area teams are assigned in the second phase
3514 constraints, 1024 binary and 1122 continuous variables
schedules are generated from the second phase
Second phase simultaneously minimizes:
The maximum number of games played by any team against teams coming off a Thursday game (LMTE)
Number of teams that play the maximum number of such games

17. Examples: In predictive analytics In prescriptive analytics
Predicting the NCAA Basketball brackets
Who survived the Titanic
In prescriptive analytics
The annual schedule of the National Football League
Winning the electoral college
In either case, ‘telling the story’ is essential. Students need practice in presentation of results to others/decision makers