1. Rick Burnette, Ph.D. Florida State University
Using Business Intelligence to Gain a Strategic Advantage in College Admissions
Rick Burnette, Ph.D. Florida State University
Rick Burnette – FSU

2. Using Business Intelligence to Gain a Strategic Advantage in College Admissions
Florida State University has used business intelligence to reengineer much of our admissions processes, including decision processing, back-office workflow, data auditing, and reporting. Leveraging data gives us a strategic advantage in managing head count, quality, and diversity. We will discuss data uses, as well as organizational and process change.
Rick Burnette – FSU

3. Strategic Enrollment Management
It has been 10 years since FSU adopted a formal enrollment management model
During that time, the Freshman student profile has changed dramatically
Fall SAT average was 1146 now 1218
Freshman Enrollment was 4510 now 6133
Minority enrollment has increased over 60%
First-year retention was 84% now 90%
Rick Burnette – FSU

4. What Changed?
Enrollment Management established clear goals which identified the need to:
Improve data granularity
Improve data access
Establish targeted strategies
Make process changes
Make organizational changes
Rick Burnette – FSU

5. 1. Improving Data Granularity Good Data = Good Results
1998 data limitations prevented modeling
We needed:
More granular data
Historical data
Earlier predictors
Database extensions
Operational changes to get more data
contact cards, web forms, telecounseling
Rick Burnette – FSU

6. 2. Data Access Empowerment
Malleable data vs. fixed reports
Decision-maker empowerment vs. reliance on programmer resources
Business Intelligence Software
Business Objects
SPSS/SAS
Excel (believe it or not)
Data Warehouses and Data Marts
Data Access Policies
Rick Burnette – FSU

7. 3. Generating Targeted Strategies
Initial strategies focused on global marketing
Cost efficiencies were actualized by using data to guide targeted strategies
More effort on those likely to attend, less on those who wouldn’t
Later, strategies shaped the entering class by focusing on subpopulations
Rick Burnette – FSU

8. 4. Strategic Process Changes
All processes have to focus on useable data
Collect more data up front
Adding outcomes to communications
Capturing dates for all interactions
Using data to focus processes
Using data for targeted communications
Focusing on ROI, accuracy, and efficiency
Rick Burnette – FSU

9. 5. Organizational Change
The Student Information Management Team was developed to strategically integrate business intelligence within these areas:
Communication and Marketing
Research
Technology Integration
Systems
Data Administration
Rick Burnette – FSU

10. The Admissions Funnel
Rick Burnette – FSU

11. One Funnel or Many? AKA – Know Thy Data
What populations are important to you?
Define target populations
Create funnels for each
What populations have different funnel shapes?
What student characteristics affect yield?
How do you define them?
Rick Burnette – FSU

12. Finding Meaningful Variables
Step 1 – Identify your meaningful data
Geodemographic data – gender, race, age, in-state vs. OOS, counties, geomarkets
Academic indicators – test Scores, GPAs, curricular differences (Units, AP/IB, etc.)
Other indicators – interest, legacy, non-cognitive variables, major
Separate these by student types – FTIC, Transfers, Graduates, Non-degree
Rick Burnette – FSU

13. Identify your Unique Challenges
Distance From Home
Identify your Unique Challenges
Distance From Home
FSU Natl.
0-100
>500 9%
68%
23%
50%
42% 8%
Rick Burnette – FSU

14. Finding Meaningful Variables
Step 2 – Generate simple comparisons
Geodemographic data – gender, race, age, distance from home, in-state vs. OOS, counties, schools, geomarkets,
Academic indicators – test Scores, GPAs, curricular differences (Units, AP/IB, etc.)
Other indicators – interest, legacy, non-cognitive variables, major, special programs.
Rick Burnette – FSU

15. Finding Meaningful Variables
Step 3 – Yields and Crosstabs
Single and multivariate comparisons
Crosstabs
Single variable funnel and yield
Multivariate yield examples ->
Crosstabs and multivariate comparisons show relationships among data. The first rule of statistics is binocular analysis. Sometimes it is better to represent data graphically to see relationships.
Rick Burnette – FSU

16. Statistical Modeling Step 4 – Statistical Modeling
First, know your data. Doing regression analyses are valuable only after you understand your student population.
Use more complex statistics to determine combinations of variables that cannot be defined by single variables or simple combinations of variables.
Focus on future performance/retention in addition to profile data.
Rick Burnette – FSU

17. Establish Baseline Data
Track your data and trends
Step 1 – Collect baseline data at different points in time. Weekly Stats
Step 2 – Compare this year’s data with last year’s as a measure of how you are doing. Final Stats ->
2 year Point in Time (PIT) comparison
Rick Burnette – FSU

18. Predictive Model Convergence
Probabilistic models rely on your sample being consistent with the prior year.
I read from several possible models
The simple model is to compare acceptances with prior yield rates
A better way is to subset different populations based on your most predictive variables ->
Rick Burnette – FSU

19. Processing Applications
Capture data and updates electronically
Automate acknowledgement using data
Target strategies for file completion
Validate data looking for inconsistencies
Systematically identify files for review
Record 25 decision elements in database
Run 25 audit reports just before decisions
Rick Burnette – FSU

20. Making Decisions
We use a multi-scale, multi-variate, matrix decision model – complex methodology
Open to errors if done manually
Now we record data and evaluations
We then do extensive error checking
Then we do a decision dry run
We run another ten audits on those data
We adjust the model and then execute
Rick Burnette – FSU

21. Tweaking the Model
Each year we tweak the admissions standards and that forces us to change our models because we are dealing with better classes each year.
We model each year’s admissions standards on demographic trends and modeling of prior year data on the next year’s standards
Rick Burnette – FSU

22. Summary
Our goal is to accept the most qualified mix of students who will also be retained.
To do so requires matching the right people with the right tools to guarantee we meet our goals while assuring efficiency, accuracy, and a good return on our investment.
Rick Burnette – FSU

23. Questions? Thanks for Attending
Rick Burnette, Ph.D. Director of Student Information Management
Florida State University
Rick Burnette – FSU

24. Copyright Statement
Copyright Rick Burnette, 2007 This work is the intellectual property of the author. Permission is granted for this material to be shared for non-commercial, educational purposes, provided that this copyright statement appears on the reproduced materials and notice is given that the copying is by permission of the author. To disseminate otherwise or to republish requires written permission from the author.
Rick Burnette – FSU