Higher Education Conference

enrollment management

The Role of Data and Playful Experimentation in Enrollment

Management

A Look at Campuses and the State

Don Hossler

Indiana University Bloomington

Hossler@Indiana.Edu

An Advanced Organizer

• Common understanding of EM

• Your challenges, expectations, and goals

• The science of EM – information not data

Purposes of Enrollment Management

• Institutional PurposesInstitutional Purposes1. Number of students

2. Characteristics of students

3. Budget strategy

4. Institutional Image

• State PurposesState Purposes1. Educated citizenry2. Efficient use of

state resources3. Effectiveness4. Economic

development

Defining Enrollment ManagementDefining Enrollment Management

Organized by strategic planning & research and supported by research, enrollment management

activities concern student college choice, the transition to college, student retention, & student outcomes.

These processes are studied to guide campus practices in the areas of new student recruitment and

financial aid, student support services, curriculum development, & other academic areas that affect

enrollments

• Information Resource Management

Information Development - research, analysis, evaluation, assessment

Information & Systems Management - data processing, MIS, DSS - the networked campus, web-enabled processes

Information Dissemination & Use : - knowledge management systems; intellectual capital - processes of organizational learning

D. Kalsbeek, 2004

The Incentive Structures

• Graduation & degree completion

• Transfer • Credit hours earned• Retention

Science of Enrollment Management

• A caveat – information will not fix organizational structure, lack of expertise, or bad decisions

• Data transformed into information are essential

Relevant State Policy Trends at the National Level

• Constrain demands for state resources going to postsecondary education– Appropriations to institutions– Support for student financial aid

• Seamless transferability– Encourage transfer & articulation agreements– Mandate them

• All of these are likely to increase the social acceptability of starting at Two-Year Colleges

Number of High School Graduates, 1994-2018:Southern, Southwestern, & Western Regions

Source: WICHE/The College Board, Prepared by Andre Bell, 2005

0

150,000

300,000

450,000

600,000

750,000

900,000

94 96 98 00 02 04 06 08 10 12 14 16 18

Non-Public White Black Asian Hispanic American Indian

South

0

150,000

300,000

450,000

600,000

750,000

900,000

91 93 95 97 99 01 03 05 07 09 11 13 15 17

Non-Public White Black Asian Hispanic American Indian

Southwest

0

150,000

300,000

450,000

600,000

750,000

900,000

94 96 98 00 02 04 06 08 10 12 14 16 18

Non-Public White Black Asian Hispanic American Indian

West

Market Research

• No dramatic compelling advantage

• From a large campus…Personal attention, small classes, not fr. seminars, not theme residence halls

• A complex message, uncertain results, not easily implemented

The Playfulness of EM

• Information delimits choices but seldom produces - the choicethe choice

• Seldom a sure thingSeldom a sure thing

Yet, senior administrators often want, uncertainty reduction—a sure thing.

Examples of the Intersection of Science and Playfulness

• Using financial aid to affect access, diversity, quality, or revenue

• Academic success

• Persistence

• Rankings

• Information systems

• Looking across campuses for effectiveness and efficiency

Academic Rating (Based on ACT, HS Class Rank, HS GPA) / (Median ACT shown)

1 2 3 4 5 6

Expected Family Contribution

Average Enrollment Yield by Level of Family Resources and Strength of Academic Profile:

24%

45%

45%

57%

59%

60%

17%

39%

41%

53%

52%

51%

18%

48%

35%

40%

58%

42%

18%

35%

33%

40%

41%

41%

14%

31%

32%

39%

43%

44%

12%

32%

34%

34%

37%

40%

Non-AidApplicant

Highest

Mid

Lowest

Academic Rating (Based on ACT, HS Class Rank, HS GPA) / (Median ACT shown)

1 2 3 4 5 6

Expected Family Contribution

Managing the Mix

129

45

39

57

74

100

72

40

42

56

64

68

99

65

50

60

85

75

70

45

47

52

67

57

67

50

47

58

61

58

51

63

64

61

46

31

Non-AidApplicant

Highest

Mid

Lowest

Market Merit

Mission

Margin

Always keep in mind, can our staffs and our systems handle this new initiative?

When Working with Aid Models

• Need good data, which is no easy task• Need multiple years• Need to carefully examine your our own past

practices• Need to realize that you can never predict

exactly• Sunk costs are largest problem• Can your systems handle your plan?• Can never predict your competitors’ behavior

• What drives student rankings?

• In your cluster of institutions – really not much

variance & strategies easy to copy

• In your cluster of IHEs – not much variance & most are easy to copy

Look Under the Hood

% of Ranking Variance Factor Explained

• Teaching quality 3%

• % students with jobs at graduation 0

• Responsiveness of the program 2%

• Career services support 42%

• Post-MBA salary 30%

“The Quality of International Students is Declining”

Fr to Soph Retention

00 01 02 03 04

Internatl 90% 84% 83% 92% 89%

Domestic residents

82% 82% 83% 83% 84%

Domestic non-residents

86% 86% 87% 86% 86%

These New Programs at the Community College are Hurting our

Regional Campus Enrollments!

Actual data indicated they were enrolling students who simply had not been attending any postsecondary

This Transfer Program Is a Model Program

• Get our data

One Final Problem in a System Environment

• It’s a unit of analysis question.• Always a temptation to make the results fit our

beliefs or political expediency.• Who controls the results?

Higher Education Conference

enrollment management