Enrollment Goals: Last Year
1.
Understanding the primary drivers that impact enrollment & revenue outcomes
2.
Analyzing current trends
3.
Understanding new tactics deployed which may influence past trend lines y p and future projections.
4 4.
Using this information to influence future strategy & resource decisions.
Enrollment
Budget F Factors
Enrollment forecasting requires balancing multiple factors to achieve institutional goals.
Prospect & applicant pool – P & li l knowing who is k i h i most likely to make commitment to come & to stay Effective communication plan throughout recruitment & admission phase Affordability – sticker price vs. out of pocket costs Connections to your institution
New student key performance indicators
# applications # li ti
% completed applications
Admit rate
Yield rate
By Segment critical to achieve institutional goals By Segment –
Student type – high school, transfer
Academic ability ‐‐ merit / non‐merit
Need category – high, medium, low, no need
Mix – gender, diversity, special target groups
Program
Enrolled headcount by total; by student type; class level
By program or unique tuition rates Residential vs. commuters Headcount
Term to term retention rates (by class level; program)
Persistence rate for fall entering cohort nd ( t (return for 2 f
f ll t fall term) )
Retention rate to junior year (return for 3rd fall term)
Graduation rate by cohort Ability to pay (financial aid)
Registration Activity
AACRAO 2010 Forecasting Enrollment
Historical Trends to Project Future Graduation Rates
Data not based on FT‐FT FR (IPEDS definition), but on all FR enrolled in the cohort. Freshman Cohort ‐ 1st Year Graduation Rate Chart How to use information for forecasting future continuing student enrollment, retention rates, graduation rates. Fall FR Cohort Fall HDCT
2004 635
2005 710
2006 622
2007 716
2008 712
# Lost
537 85% ‐98
615 87% ‐95
535 86% ‐87
585 82% ‐131
618 87% ‐94
Additional # Lost
452 71% ‐85
544 77% ‐71
458 74% ‐77
524 73% ‐61
548 77% ‐70
419 66% ‐33
513 72% ‐31
424 68% ‐34
494 69% ‐30
337 86 25
414 95 20
335
Graduation Rate‐4‐YR Graduation Rate‐5‐YR Graduation Rae‐6‐YR
53% 67% 71%
58% 72% 75%
54%
6 YR Goal
71%
75%
70%
Fall YR 2 Persistence
Fall YR 3 Retention
Fall Year 4 Retention Additional # Lost
Graduation Information 4‐YR Graduation 5‐YR Graduation 6‐YR Graduation
Projection
Projection
2009 682 586 Projection 86% ‐96
Shared goals
Establish timeline with stakeholders; on‐going Establish timeline with stakeholders; on going communication
Determine critical benchmarks & track progress towards goals at specific points in time
Know where opportunities exist to adjust pp j strategy
Build trend lines for key performance indicators
Refine models overtime (change)
By program New student applications enrolled headcount goal Awarding scholarships Connecting financial aid & headcount goals
Challenges:
Price
Net Revenue
New Student Headcount
Average credits per student g p
Prior quarter continuing student flow pattern
Program capacity – total students and new students d t d t ◦ facilities ◦ faculty resources ◦ services
g q Programs are unique Competition Market sensitivity tied to adult learners Resources Longer timeline in admission funnel Front end data is essential
Program projection model
AACRAO 2010 Forecasting Enrollment
Program Projection Model Enrollment Projection by Program
rate increase 1.05 2010-11
A 2009-10 Program Capacity
Actual Summer
Program Name
B
C D E
Credits $PerCr Revenue Total Headcount New Students Continuing Students Avg. Cr per HC Prior Q. Cont. Std. Flow
74 30
199 $459 $91,341 40 0 40 4.98 0.57971
Actual Actual Fall Winter Total Proj. Revenue
Projected Spring $898,263
Total Proj. Credits
1957
600 $459 $275,400 66 32 34 9.09 0.85000
611 $459 $280,449 68 1 67 8.99 1.01515
547 $459 $251,073 64 0 64 7.62 0.96297
Projected Summer
217 $482 $104,583 42 0 42 5.18 0.65139
Projected Projected Fall Winter Total Proj. Revenue
Projected Spring $931,609
Total Proj. Credits
1933
609 $482 $293,508 69 30 39 8.83 0.93039
612 $482 $294,953 68 0 68 9.01 0.99194
495 $482 $238,565 65 0 65 7.62 0.9630
D: Average Credits per Headcount -- based on 3-YR average E. Continuing Student Flow Pattern -- based on 3-YR average
A. B. C. D. E.
Enrollment Drivers: Program Capacity -- maximum number of total students; maximum number of new students Price -- per credit tuition rate New students -- some programs admit students once per year (cohort); others admit new students each term Average Credits per Headcount -- of all students enrolled, what is the average credits per students per quarter Prior Quarter Continuing Student Flow Pattern (ex: spring term: What % of the total winter students enroll in spring)
New student application - model
AACRAO 2010 Forecasting Enrollment
New Student Projection Model Applications through Yield
What if I want to enroll
750
Freshmen -- how many applications are required? Projection
New Students Applications % Change
2005
2006
2007
2008
2009
2010
2,000 2,230 2,210 2,500 2,600 6.2%
11.5%
‐0.9%
13.1%
4.0%
Model
Multi‐YR Avg
2,850
A
9.6%
5.41%
Completed Apps 1,900 2,100 2,120 2,350 2,420 2,679 % Completed
Admits
95.0%
94.2%
95.9%
94.0%
93.1%
94.0%
1,576 1,597 1,753 1,808 1,830
2,036
% Admit Rate
82.9%
76.0%
82.7%
76.9%
75.6%
76.0%
Registered
715
685
716
725
732
750
% Yield
45.4%
42.9%
40.8%
40.1%
40.0%
36.8%
94.0%
94.4%
B
76.0%
78.8%
C
If the projected yield rate is too high or low --- adjust one of the following: A
Total Number of Applications
B
% Completed
C
% Admitted
What influences the variations in the Yield Rates? What do historical trends suggest? Options: Chart for New Transfer Students Chart for Early Action Students
41.8%
Start with what happened last year. Check what is happening with 2010 incoming class. Determine if shift in the line might improve yield rates or increase other enrollment goals – gender, diversity, etc. ◦ Set goals ◦ Check benchmarks at specific points in time Under Missing 900 Missing Below 3.00
1000900-990 1040
10501090
11001140
11501190
12001240
12501290
13001340
13501390
14001440
14501490
15001600 Missing Below 3.00
7
3.00-3.09 3.10-3.19 3.20-3.29
3.00-3.09 3.10-3.19 3.20-3.29
6 5
3.30-3.39
3.30-3.39
3.40-3.49
HS
3.40-3.49 GPA
4
3.50-3.59
3.50-3.59
3
3.60-3.69 3.70-3.79 3.80-3.89 3.90-3.99 4.00
2 1 Under Missing 900
1000900-990 1040
10501090
11001140
11501190
12001240
SAT Score
12501290
13001340
13501390
14001440
14501490
15001600
3.60-3.69 3.70-3.79 3.80-3.89 3.90-3.99 4.00
AACRAO 2010
Academic Ability -- By High School GPA and SAT Score Question: How to determine where to apply merit aid scholarships? What history is needed?
Yield -- All FR by Cell. Compare Cells with larger number of Admits yet with lower Yield Rate and seek an explanation to inform future strategy decisions.
Missing
Under 900
no admits no admits
Missing Below 3.00 3.00-3.09 3.10-3.19 3.20-3.29 3.30-3.39 3.40-3.49
1000900-990 1040
10501090
100% no admits no admits 57%
11001140
11501190
12001240
0% no admits 75%
0%
no admits
75%
57%
50%
67%
no admits
100%
83%
36%
20%
25%
56%
40%
no admits no admits
57%
43%
50%
38%
10%
38%
12501290
13001340
13501390
14001440
14501490
15001600
0% no admits no admits no admits no admits no admits
50% no admits 50%
100%
0%
0% no admits no admits
0% no admits no admits no admits
100% no admits
0%
100% no admits no admits no admits
no admits no admits
44%
42%
27%
38%
44%
0%
0%
0%
no admits
100%
57%
29%
38%
63%
33%
64%
63%
0%
no admits no admits
71%
36%
57%
50%
27%
44%
50%
20%
50% no admits
no admits no admits
50%
44%
36%
50%
31%
40%
30%
38%
60%
3.50-3.59 3.60-3.69 3.70-3.79
no admits no admits
44%
17%
45%
35%
38%
19%
33%
40%
33%
38%
0% no admits
no admits no admits
29%
8%
39%
38%
41%
36%
45%
23%
67%
33%
50% no admits
no admits no admits
33%
14%
50%
26%
29%
27%
54%
29%
43%
0%
3.60-3.69 3.70-3.79 3.80-3.89
3.80-3.89
no admits no admits
78%
29%
37%
35%
48%
32%
36%
32%
65%
0%
20%
0%
3.90-3.99
3.90-3.99
no admits no admits
30%
0%
46%
36%
27%
36%
29%
43%
52%
57%
17%
43%
4.00
4.00 Missing
Under 900
1000900-990 1040
10501090
11001140
11501190
12001240
SAT Score
12501290
13001340
67% no admits no admits no admits
Missing Below 3.00 3.00-3.09 3.10-3.19 3.20-3.29 3.30-3.39 HS 3.40-3.49 GPA 3.50-3.59
0%
13501390
100% no admits no admits 0% no admits
100% no admits no admits
100% no admits
14001440
14501490
15001600
Why segment?
Model Segmentation – by:
Different rate for moving through the process h h h
1. Student type
Different completion rates
3. Gender
2. Merit vs. non‐merit
4. Ethnic students vs. all Different yield rates Identify more clearly where to influence students
5. Intended major
Project Model-Segmentation
AACRAO 2010 Forecasting Enrollment
A
Segmenting Data Early Action + Regular ADM = All Freshmen
B
U
V
W
X
Y
1
New Student Projection ‐ Segments
3 4
All Freshmen
5
Academic Ability ‐‐‐‐ by Grid 1
6 7
Z
AA
AB
AF
AG
AH
AI
AJ
Total
2
3
4
5
6
7
3,500
% Change
Three Years Past
20
400
460
645
615
600
185
2,925
9
Two Years Past
10
Last Year
50 35 40
450 460 499
505 495 559
635 630 758
635 620 734
580 600 691
195 180 219
3,050 3,020 3,500
1.1% 14.3% 16.0% 21.7% 21.0% 19.7%
6.3%
100.0%
0.7% 1.6% 1.2% 1.2%
6.3% 6.4% 6.0% 6.2%
Projection %
12 13 14 15 16 18 19
AE
enrollment mix (gender, ethnicity), other target groups ‐‐ visit program, communication strategy, etc.
Applications
A
AD
Similar models could be created for transfer students,
8
11 A.
AC
Application Goal: 125
Distribute by percentage of Merit category
‐30 480
calculation‐ row 11 Adds cells ‐‐ e.g in Column 1 =C11 + L 11
History ‐ % of Total Three Years Past Two Years Past Last Year 3‐YR Avg
13.7% 14.8% 15.2% 14.6%
15.7% 16.6% 16.4% 16.2%
22.1% 20.8% 20.9% 21.2%
21.0% 20.8% 20.5% 20.8%
20.5% 19.0% 19.9% 19.8%
20 45 30 38 95%
380 410 450 486 97%
435 490 470 537 96%
600 580 615 732 97%
575 600 610 703 96%
550 540 585 656 95%
155 2,715 165 2,830 145 2,905 149 3,301 68% 94.3%
100% 90% 86% 92%
95% 91% 98% 95%
95% 97% 95% 96%
93% 91% 98% 94%
93% 94% 98% 95%
92% 93% 98% 94%
84% 85% 81% 83%
92.8% 92.8% 96.2% 93.9%
Two Years Past Last Year
20 45 30
380 410 450
435 490 470
550 540 570
450 435 445
200 195 210
6 5 7
2,041 2,120 2,182
Projection
38
486
537
609
430
178
5
2,283
100% 100% 100%
83%
61%
27%
3%
69.2%
100% 100% 100% 100%
92% 93% 93% 92%
78% 73% 73% 75%
36% 36% 36% 36%
4% 3% 5% 4%
75.2% 74.9% 75.1% 75.1%
20 21 22 23 24
Completed Applications Three Years Past Two Years Past Last Year
25 26 27 28 B. 29 30 31 32
Projection %
B
Compl Rate 93% 93% 96% 94%
Completed Application Goal:
Review percentage completed by Merit category
History ‐ % Completed Three Years Past Two Years Past
33 34 36
Last Year
3‐YR Avg
37 38 39 40 41 42 43 44
Admits Three Years Past
45 46 C. 47 48 49 50 51 52 53 55 56
C
ADM Rate Projection
ADM Rate 75%
Admits and Admit Rate
75% 75%
Review admit rate by Merit category Identify where may choose to increase / decreaes admits
69%
History ‐ Admit Rate Three Years Past Two Years Past Last Year 3‐YR Avg
100% 100% 100% 100%
100% 100% 100% 100%
57 58 59 60
Goal ‐ Hold HDCT to 880
61 62
Headcount ‐ Enrolled 165 185 190
205 235 225
130 125 145
90 110 105
1 0 1
783 850 876
38.4%
Last Year
180 175 190
HDCT ‐ Projection
20
220
202
241
129
89
0
901
39.5%
Yield Rate ‐ Proj
53% 60.0% 44.4% 66.7% 57.0%
45% 47.4% 42.7% 42.2% 44.1%
38% 37.9% 37.8% 40.4% 38.7%
40% 37.3% 43.5% 39.5% 40.1%
30% 28.9% 28.7% 32.6% 30.1%
50% 45.0% 56.4% 50.0% 50.5%
0% 16.7% 0% 14% 10.3%
39.5% 38.4% 40.1% 40.1% 39.5%
Three Years Past
64
Two Years Past
65 66 D. 67 68 69 70 72
D
Yield Rate
12 20 20
63
Three Years Past Two Years Past Last Year 3‐YR Avg
Headcount Goal and Yield Rate
Review yield rate by Merit category
40.1% 40.1%
What if model shows too many or not enough enrol
Financial aid strategy to achieve net revenue goals headcount p p need levels of student population financial aid strategy (merit & need based)
Financial aid used to influence new student entering class as well as support student outcomes increase persistence & graduation rates improve student satisfaction
Need analysis‐model
AACRAO 2010 Forecasting Enrollment
A
Need Analysis - Projection Model B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
1 2 3 4 5 6 7
Need Distribution Projection What percentage of new and continuing students are projected to fall within need categories?
Consider past trends. Consider impact as new students move into continuing student categories.
8
Enrolled Student ‐ % of Fall Headcount
9 10 11
Segment by Student Type
12 13
High Need
29%
35%
41%
34.5%
230
295
357
304
14 15
Medium Need
17%
15%
15%
16.4%
133
125
135
144
16 17
Low Need
19%
17%
14%
14.6%
145
145
125
128
18 19
No Need
35%
34%
30%
34.9%
275
285
259
307
20 21 22 23
Total
100%
100%
100%
100%
783
850
876
880
Prev YR
Prev YR
Last YR
Fall Headcount Projection
Prev YR
Prev YR
Last YR
Projection
Steps:
24
Review history and determine 'break points' for each category by "student segement" -- eg. continuing, new
2 25
Review admit, registered and yield rates
26
Establish baseline goal and use this information to create a model that tracks goals by Need and Merit category
27
Monitor this information throughout spring/summer to determine in baseline projection is on target
Proj = $Total HDCT$ x % by Need Category 304 =round($K$20*F12,0)
AACRAO 2010 Forecasting Enrollment
Model Connecting Headcount and Need Projections
Projection Model ‐New Freshmen ‐ Enrollment and Financial Aid Model: Merit and Need This report provides an overview by Merit Scholarship and Need Categories. Final Data ‐ History
Goal
Academic Ability ‐ GRID. Linked to New Student Model
3 Years Two Years Ago Ago Last YR Projection Enrollment Goals: 2,041 2,120 2,182 2,283 Admits Enrolled 783 850 876 901 Yield 38.4% 40.1% 40.1% 39.5%
This section summarizes the Need Groups below the bar
Proj F10 2283 852 37.3% Prev Avg Yield Rate
F09
1
3
4
5
6
7
38 486 537 609 430 178 5 20 220 202 241 129 89 ‐ 52.6% 45.3% 37.6% 39.6% 30.0% 50.0% 0.0% Summary Chart Below based on Assumptions by Need Distribution
1 38 20 52.6% 57.0%
1
F10
2
2 486 177 36.4% 44.1%
2
3 537 188 35.0% 38.7%
3
4 609 245 40.2% 40.1%
4
5 430 141 32.8% 30.1%
5
6 178 79 44.4% 50.5%
6
7 5 2 40.0% 10.3%
7
F07
F08
570 230 40.4% 27.9% 29.4%
615 295 48.0% 29.0% 34.7%
745 357 47.9% 34.1% 40.8%
614 294 47.9% 26.9% 34.5%
10 8 100.0% 26.3%
135 61 44.9% 27.8%
147 67 45.5% 27.4%
153 75 48.9% 25.1%
115 53 45.9% 26.7%
54 30 55.0% 30.3%
0.0%
360 133 36.9% 17.6% 17.0%
350 125 35.7% 16.5% 14.7%
342 135 39.5% 15.7% 15.4%
375 140 37.3% 16.4% 16.4%
5 1 100.0% 13.2%
88 33 38.0% 18.1%
92 29 32.0% 17.1%
80 36 45.0% 13.1%
75 26 34.5% 17.4%
33 14 42.0% 18.5%
2 1 33.0% 40.0%
351 145 41.3% 17.2% 18.5%
370 145 39.2% 17.5% 17.1%
365 125 34.2% 16.7% 14.3%
358 123 34.4% 15.7% 14.4%
8 4 100.0% 21.1%
85 25 29.5% 17.5%
85 30 35.7% 15.8%
95 38 40.5% 15.6%
65 18 28.0% 15.1%
20 8 40.4% 11.2%
0 0
310 130 41.9% 18.5% 16.6%
360 150 41.7% 17.4% 17.6%
335 140 41.8% 13.1% 16.0%
359 132 36.8% 15.7% 15.5%
10 5 85.0% 26.3%
90 32 35.0% 18.5%
80 29 36.8% 14.9%
80 32 40.3% 13.1%
75 23 30.2% 17.4%
24 11 45.0% 13.5%
0.0%
5 2 66.7% 13.2%
88 26 29.0% 18.1%
133 33 25.0% 24.8%
201 64 31.9% 33.0%
100 21 21.4% 23.3%
47 16 33.6% 26.4%
3 1 33.0% 60.0%
1. High Need Admits Registered Yield % of Total FR Admits % of Registered
History ‐ Yield rate by category
2. Medium Need Admits Registered Yield % of Total FR Admits % of Registered
3. Low Need Admits Registered g Yield % of Total FR Admits % of Registered
0.0%
4. No Need Filer Admits Registered Yield % of Total FR Admits % of Registered
0 0
5. No Need Non Filer Admits Registered Yield % of Total FR Admits % of Registered
450 145 32.2% 20.9% 18.5%
425 135 31.8% 21.8% 15.9%
395 119 30.1% 19.2% 13.6%
577 163 28.2% 25.3% 19.1%
% of "full pays"
53.6%
50.6%
43.8%
49.1%
2Project Model-Segment SPU 2010 Model 2-42%fullpay
Net revenue drivers Headcount by student type # Instit. Scholarships $ Instit. Scholarships I i S h l hi # Institutional Gift Aid % Institutional Gift Aid $ Institutional Gift aid Average $ Scholarship Average $ Gift aid f d Total Net Revenue Discount Rate
| Enrollment Goals: Continuing Student Goal Discount Rate Discount Rate Headcount # Scholarship $ Scholarship # Gift Aid # Gift Aid % Gift Aid $ Gift aid Average SPU Scholarship A Average SPU Gift aid SPU Gift id Total Net Revenue Discount Rate
Last Year 1,589 38 2 38.2 1,520 1,200 $6,543,278 1368 90% $15,432,180 $5,453 $11 281 $11,281
| | | | | | | | | | | | $26,724,475 | 36.2% |
This Year 1,615 38 80 38.80 1,503 1,035 $7,012,035 1237 82% $11,502,930 $6,775 $9 299 $9,299 $23,461,715 35.8%
Summary data. Next level of analysis aggregates data by need levels – high, medium, low, no need filer, no need non‐filer , , f , f
Determine critical information needed and begin data collection Excel, access, frozen data tables/information system, data warehouse
Verify data quality Enrollment
Budget Factors
accurate, complete, shared definition & metrics
Identify key benchmarks points in time when data must be gathered and compared to build historical trends
Data segmentation start with macro then identify sub‐sets
pp g Holistic approach to data management requires buy‐in from “data managers” (create / manage data)
Build baseline year assess effectiveness and refine over time
Forecasting Enrollment to Achieve Institutional Goals, 2007 article in College & University (Volume 82, No. 3).
Data‐Driven Decisions: Using Data to Inform and Influence Decision‐makers, 2006 article in College & University (Volume 81, No. 3).
Enrollment Management: Key Elements for Building and Implementing an Enrollment Plan, 2005 article in College & University (Volume 80, No. 4).
Understanding the Business of Higher Education: Building Context for Your Staff Development Plan; 2008 article in College & University (Volume 84, No. 1). ; g y( 4, )
Let's Get Organized: Your Personal GPS to Improving Organizational Skills; March 2010 article in SEM Source, found online at http://www.aacrao.org/sem/ .
When Enrollment Strategies Cross Traditional Boundaries: Opportunities and Challenges, April 2008 article in SEM Source, http://www.aacrao.org/sem/ ‐‐ (listed under archives).
Understanding the primary drivers that impact enrollment & revenue outcomes
2.
Analyzing current trends
3.
Understanding new tactics deployed which may influence past trend lines y p and future projections.
4 4.
Using this information to influence future strategy & resource decisions.
Enrollment
Budget F Factors
Enrollment forecasting requires balancing multiple factors to achieve institutional goals.
Prospect & applicant pool – P & li l knowing who is k i h i most likely to make commitment to come & to stay Effective communication plan throughout recruitment & admission phase Affordability – sticker price vs. out of pocket costs Connections to your institution
New student key performance indicators
# applications # li ti
% completed applications
Admit rate
Yield rate
By Segment critical to achieve institutional goals By Segment –
Student type – high school, transfer
Academic ability ‐‐ merit / non‐merit
Need category – high, medium, low, no need
Mix – gender, diversity, special target groups
Program
Enrolled headcount by total; by student type; class level
By program or unique tuition rates Residential vs. commuters Headcount
Term to term retention rates (by class level; program)
Persistence rate for fall entering cohort nd ( t (return for 2 f
f ll t fall term) )
Retention rate to junior year (return for 3rd fall term)
Graduation rate by cohort Ability to pay (financial aid)
Registration Activity
AACRAO 2010 Forecasting Enrollment
Historical Trends to Project Future Graduation Rates
Data not based on FT‐FT FR (IPEDS definition), but on all FR enrolled in the cohort. Freshman Cohort ‐ 1st Year Graduation Rate Chart How to use information for forecasting future continuing student enrollment, retention rates, graduation rates. Fall FR Cohort Fall HDCT
2004 635
2005 710
2006 622
2007 716
2008 712
# Lost
537 85% ‐98
615 87% ‐95
535 86% ‐87
585 82% ‐131
618 87% ‐94
Additional # Lost
452 71% ‐85
544 77% ‐71
458 74% ‐77
524 73% ‐61
548 77% ‐70
419 66% ‐33
513 72% ‐31
424 68% ‐34
494 69% ‐30
337 86 25
414 95 20
335
Graduation Rate‐4‐YR Graduation Rate‐5‐YR Graduation Rae‐6‐YR
53% 67% 71%
58% 72% 75%
54%
6 YR Goal
71%
75%
70%
Fall YR 2 Persistence
Fall YR 3 Retention
Fall Year 4 Retention Additional # Lost
Graduation Information 4‐YR Graduation 5‐YR Graduation 6‐YR Graduation
Projection
Projection
2009 682 586 Projection 86% ‐96
Shared goals
Establish timeline with stakeholders; on‐going Establish timeline with stakeholders; on going communication
Determine critical benchmarks & track progress towards goals at specific points in time
Know where opportunities exist to adjust pp j strategy
Build trend lines for key performance indicators
Refine models overtime (change)
By program New student applications enrolled headcount goal Awarding scholarships Connecting financial aid & headcount goals
Challenges:
Price
Net Revenue
New Student Headcount
Average credits per student g p
Prior quarter continuing student flow pattern
Program capacity – total students and new students d t d t ◦ facilities ◦ faculty resources ◦ services
g q Programs are unique Competition Market sensitivity tied to adult learners Resources Longer timeline in admission funnel Front end data is essential
Program projection model
AACRAO 2010 Forecasting Enrollment
Program Projection Model Enrollment Projection by Program
rate increase 1.05 2010-11
A 2009-10 Program Capacity
Actual Summer
Program Name
B
C D E
Credits $PerCr Revenue Total Headcount New Students Continuing Students Avg. Cr per HC Prior Q. Cont. Std. Flow
74 30
199 $459 $91,341 40 0 40 4.98 0.57971
Actual Actual Fall Winter Total Proj. Revenue
Projected Spring $898,263
Total Proj. Credits
1957
600 $459 $275,400 66 32 34 9.09 0.85000
611 $459 $280,449 68 1 67 8.99 1.01515
547 $459 $251,073 64 0 64 7.62 0.96297
Projected Summer
217 $482 $104,583 42 0 42 5.18 0.65139
Projected Projected Fall Winter Total Proj. Revenue
Projected Spring $931,609
Total Proj. Credits
1933
609 $482 $293,508 69 30 39 8.83 0.93039
612 $482 $294,953 68 0 68 9.01 0.99194
495 $482 $238,565 65 0 65 7.62 0.9630
D: Average Credits per Headcount -- based on 3-YR average E. Continuing Student Flow Pattern -- based on 3-YR average
A. B. C. D. E.
Enrollment Drivers: Program Capacity -- maximum number of total students; maximum number of new students Price -- per credit tuition rate New students -- some programs admit students once per year (cohort); others admit new students each term Average Credits per Headcount -- of all students enrolled, what is the average credits per students per quarter Prior Quarter Continuing Student Flow Pattern (ex: spring term: What % of the total winter students enroll in spring)
New student application - model
AACRAO 2010 Forecasting Enrollment
New Student Projection Model Applications through Yield
What if I want to enroll
750
Freshmen -- how many applications are required? Projection
New Students Applications % Change
2005
2006
2007
2008
2009
2010
2,000 2,230 2,210 2,500 2,600 6.2%
11.5%
‐0.9%
13.1%
4.0%
Model
Multi‐YR Avg
2,850
A
9.6%
5.41%
Completed Apps 1,900 2,100 2,120 2,350 2,420 2,679 % Completed
Admits
95.0%
94.2%
95.9%
94.0%
93.1%
94.0%
1,576 1,597 1,753 1,808 1,830
2,036
% Admit Rate
82.9%
76.0%
82.7%
76.9%
75.6%
76.0%
Registered
715
685
716
725
732
750
% Yield
45.4%
42.9%
40.8%
40.1%
40.0%
36.8%
94.0%
94.4%
B
76.0%
78.8%
C
If the projected yield rate is too high or low --- adjust one of the following: A
Total Number of Applications
B
% Completed
C
% Admitted
What influences the variations in the Yield Rates? What do historical trends suggest? Options: Chart for New Transfer Students Chart for Early Action Students
41.8%
Start with what happened last year. Check what is happening with 2010 incoming class. Determine if shift in the line might improve yield rates or increase other enrollment goals – gender, diversity, etc. ◦ Set goals ◦ Check benchmarks at specific points in time Under Missing 900 Missing Below 3.00
1000900-990 1040
10501090
11001140
11501190
12001240
12501290
13001340
13501390
14001440
14501490
15001600 Missing Below 3.00
7
3.00-3.09 3.10-3.19 3.20-3.29
3.00-3.09 3.10-3.19 3.20-3.29
6 5
3.30-3.39
3.30-3.39
3.40-3.49
HS
3.40-3.49 GPA
4
3.50-3.59
3.50-3.59
3
3.60-3.69 3.70-3.79 3.80-3.89 3.90-3.99 4.00
2 1 Under Missing 900
1000900-990 1040
10501090
11001140
11501190
12001240
SAT Score
12501290
13001340
13501390
14001440
14501490
15001600
3.60-3.69 3.70-3.79 3.80-3.89 3.90-3.99 4.00
AACRAO 2010
Academic Ability -- By High School GPA and SAT Score Question: How to determine where to apply merit aid scholarships? What history is needed?
Yield -- All FR by Cell. Compare Cells with larger number of Admits yet with lower Yield Rate and seek an explanation to inform future strategy decisions.
Missing
Under 900
no admits no admits
Missing Below 3.00 3.00-3.09 3.10-3.19 3.20-3.29 3.30-3.39 3.40-3.49
1000900-990 1040
10501090
100% no admits no admits 57%
11001140
11501190
12001240
0% no admits 75%
0%
no admits
75%
57%
50%
67%
no admits
100%
83%
36%
20%
25%
56%
40%
no admits no admits
57%
43%
50%
38%
10%
38%
12501290
13001340
13501390
14001440
14501490
15001600
0% no admits no admits no admits no admits no admits
50% no admits 50%
100%
0%
0% no admits no admits
0% no admits no admits no admits
100% no admits
0%
100% no admits no admits no admits
no admits no admits
44%
42%
27%
38%
44%
0%
0%
0%
no admits
100%
57%
29%
38%
63%
33%
64%
63%
0%
no admits no admits
71%
36%
57%
50%
27%
44%
50%
20%
50% no admits
no admits no admits
50%
44%
36%
50%
31%
40%
30%
38%
60%
3.50-3.59 3.60-3.69 3.70-3.79
no admits no admits
44%
17%
45%
35%
38%
19%
33%
40%
33%
38%
0% no admits
no admits no admits
29%
8%
39%
38%
41%
36%
45%
23%
67%
33%
50% no admits
no admits no admits
33%
14%
50%
26%
29%
27%
54%
29%
43%
0%
3.60-3.69 3.70-3.79 3.80-3.89
3.80-3.89
no admits no admits
78%
29%
37%
35%
48%
32%
36%
32%
65%
0%
20%
0%
3.90-3.99
3.90-3.99
no admits no admits
30%
0%
46%
36%
27%
36%
29%
43%
52%
57%
17%
43%
4.00
4.00 Missing
Under 900
1000900-990 1040
10501090
11001140
11501190
12001240
SAT Score
12501290
13001340
67% no admits no admits no admits
Missing Below 3.00 3.00-3.09 3.10-3.19 3.20-3.29 3.30-3.39 HS 3.40-3.49 GPA 3.50-3.59
0%
13501390
100% no admits no admits 0% no admits
100% no admits no admits
100% no admits
14001440
14501490
15001600
Why segment?
Model Segmentation – by:
Different rate for moving through the process h h h
1. Student type
Different completion rates
3. Gender
2. Merit vs. non‐merit
4. Ethnic students vs. all Different yield rates Identify more clearly where to influence students
5. Intended major
Project Model-Segmentation
AACRAO 2010 Forecasting Enrollment
A
Segmenting Data Early Action + Regular ADM = All Freshmen
B
U
V
W
X
Y
1
New Student Projection ‐ Segments
3 4
All Freshmen
5
Academic Ability ‐‐‐‐ by Grid 1
6 7
Z
AA
AB
AF
AG
AH
AI
AJ
Total
2
3
4
5
6
7
3,500
% Change
Three Years Past
20
400
460
645
615
600
185
2,925
9
Two Years Past
10
Last Year
50 35 40
450 460 499
505 495 559
635 630 758
635 620 734
580 600 691
195 180 219
3,050 3,020 3,500
1.1% 14.3% 16.0% 21.7% 21.0% 19.7%
6.3%
100.0%
0.7% 1.6% 1.2% 1.2%
6.3% 6.4% 6.0% 6.2%
Projection %
12 13 14 15 16 18 19
AE
enrollment mix (gender, ethnicity), other target groups ‐‐ visit program, communication strategy, etc.
Applications
A
AD
Similar models could be created for transfer students,
8
11 A.
AC
Application Goal: 125
Distribute by percentage of Merit category
‐30 480
calculation‐ row 11 Adds cells ‐‐ e.g in Column 1 =C11 + L 11
History ‐ % of Total Three Years Past Two Years Past Last Year 3‐YR Avg
13.7% 14.8% 15.2% 14.6%
15.7% 16.6% 16.4% 16.2%
22.1% 20.8% 20.9% 21.2%
21.0% 20.8% 20.5% 20.8%
20.5% 19.0% 19.9% 19.8%
20 45 30 38 95%
380 410 450 486 97%
435 490 470 537 96%
600 580 615 732 97%
575 600 610 703 96%
550 540 585 656 95%
155 2,715 165 2,830 145 2,905 149 3,301 68% 94.3%
100% 90% 86% 92%
95% 91% 98% 95%
95% 97% 95% 96%
93% 91% 98% 94%
93% 94% 98% 95%
92% 93% 98% 94%
84% 85% 81% 83%
92.8% 92.8% 96.2% 93.9%
Two Years Past Last Year
20 45 30
380 410 450
435 490 470
550 540 570
450 435 445
200 195 210
6 5 7
2,041 2,120 2,182
Projection
38
486
537
609
430
178
5
2,283
100% 100% 100%
83%
61%
27%
3%
69.2%
100% 100% 100% 100%
92% 93% 93% 92%
78% 73% 73% 75%
36% 36% 36% 36%
4% 3% 5% 4%
75.2% 74.9% 75.1% 75.1%
20 21 22 23 24
Completed Applications Three Years Past Two Years Past Last Year
25 26 27 28 B. 29 30 31 32
Projection %
B
Compl Rate 93% 93% 96% 94%
Completed Application Goal:
Review percentage completed by Merit category
History ‐ % Completed Three Years Past Two Years Past
33 34 36
Last Year
3‐YR Avg
37 38 39 40 41 42 43 44
Admits Three Years Past
45 46 C. 47 48 49 50 51 52 53 55 56
C
ADM Rate Projection
ADM Rate 75%
Admits and Admit Rate
75% 75%
Review admit rate by Merit category Identify where may choose to increase / decreaes admits
69%
History ‐ Admit Rate Three Years Past Two Years Past Last Year 3‐YR Avg
100% 100% 100% 100%
100% 100% 100% 100%
57 58 59 60
Goal ‐ Hold HDCT to 880
61 62
Headcount ‐ Enrolled 165 185 190
205 235 225
130 125 145
90 110 105
1 0 1
783 850 876
38.4%
Last Year
180 175 190
HDCT ‐ Projection
20
220
202
241
129
89
0
901
39.5%
Yield Rate ‐ Proj
53% 60.0% 44.4% 66.7% 57.0%
45% 47.4% 42.7% 42.2% 44.1%
38% 37.9% 37.8% 40.4% 38.7%
40% 37.3% 43.5% 39.5% 40.1%
30% 28.9% 28.7% 32.6% 30.1%
50% 45.0% 56.4% 50.0% 50.5%
0% 16.7% 0% 14% 10.3%
39.5% 38.4% 40.1% 40.1% 39.5%
Three Years Past
64
Two Years Past
65 66 D. 67 68 69 70 72
D
Yield Rate
12 20 20
63
Three Years Past Two Years Past Last Year 3‐YR Avg
Headcount Goal and Yield Rate
Review yield rate by Merit category
40.1% 40.1%
What if model shows too many or not enough enrol
Financial aid strategy to achieve net revenue goals headcount p p need levels of student population financial aid strategy (merit & need based)
Financial aid used to influence new student entering class as well as support student outcomes increase persistence & graduation rates improve student satisfaction
Need analysis‐model
AACRAO 2010 Forecasting Enrollment
A
Need Analysis - Projection Model B
C
D
E
F
G
H
I
J
K
L
M
N
O
P
1 2 3 4 5 6 7
Need Distribution Projection What percentage of new and continuing students are projected to fall within need categories?
Consider past trends. Consider impact as new students move into continuing student categories.
8
Enrolled Student ‐ % of Fall Headcount
9 10 11
Segment by Student Type
12 13
High Need
29%
35%
41%
34.5%
230
295
357
304
14 15
Medium Need
17%
15%
15%
16.4%
133
125
135
144
16 17
Low Need
19%
17%
14%
14.6%
145
145
125
128
18 19
No Need
35%
34%
30%
34.9%
275
285
259
307
20 21 22 23
Total
100%
100%
100%
100%
783
850
876
880
Prev YR
Prev YR
Last YR
Fall Headcount Projection
Prev YR
Prev YR
Last YR
Projection
Steps:
24
Review history and determine 'break points' for each category by "student segement" -- eg. continuing, new
2 25
Review admit, registered and yield rates
26
Establish baseline goal and use this information to create a model that tracks goals by Need and Merit category
27
Monitor this information throughout spring/summer to determine in baseline projection is on target
Proj = $Total HDCT$ x % by Need Category 304 =round($K$20*F12,0)
AACRAO 2010 Forecasting Enrollment
Model Connecting Headcount and Need Projections
Projection Model ‐New Freshmen ‐ Enrollment and Financial Aid Model: Merit and Need This report provides an overview by Merit Scholarship and Need Categories. Final Data ‐ History
Goal
Academic Ability ‐ GRID. Linked to New Student Model
3 Years Two Years Ago Ago Last YR Projection Enrollment Goals: 2,041 2,120 2,182 2,283 Admits Enrolled 783 850 876 901 Yield 38.4% 40.1% 40.1% 39.5%
This section summarizes the Need Groups below the bar
Proj F10 2283 852 37.3% Prev Avg Yield Rate
F09
1
3
4
5
6
7
38 486 537 609 430 178 5 20 220 202 241 129 89 ‐ 52.6% 45.3% 37.6% 39.6% 30.0% 50.0% 0.0% Summary Chart Below based on Assumptions by Need Distribution
1 38 20 52.6% 57.0%
1
F10
2
2 486 177 36.4% 44.1%
2
3 537 188 35.0% 38.7%
3
4 609 245 40.2% 40.1%
4
5 430 141 32.8% 30.1%
5
6 178 79 44.4% 50.5%
6
7 5 2 40.0% 10.3%
7
F07
F08
570 230 40.4% 27.9% 29.4%
615 295 48.0% 29.0% 34.7%
745 357 47.9% 34.1% 40.8%
614 294 47.9% 26.9% 34.5%
10 8 100.0% 26.3%
135 61 44.9% 27.8%
147 67 45.5% 27.4%
153 75 48.9% 25.1%
115 53 45.9% 26.7%
54 30 55.0% 30.3%
0.0%
360 133 36.9% 17.6% 17.0%
350 125 35.7% 16.5% 14.7%
342 135 39.5% 15.7% 15.4%
375 140 37.3% 16.4% 16.4%
5 1 100.0% 13.2%
88 33 38.0% 18.1%
92 29 32.0% 17.1%
80 36 45.0% 13.1%
75 26 34.5% 17.4%
33 14 42.0% 18.5%
2 1 33.0% 40.0%
351 145 41.3% 17.2% 18.5%
370 145 39.2% 17.5% 17.1%
365 125 34.2% 16.7% 14.3%
358 123 34.4% 15.7% 14.4%
8 4 100.0% 21.1%
85 25 29.5% 17.5%
85 30 35.7% 15.8%
95 38 40.5% 15.6%
65 18 28.0% 15.1%
20 8 40.4% 11.2%
0 0
310 130 41.9% 18.5% 16.6%
360 150 41.7% 17.4% 17.6%
335 140 41.8% 13.1% 16.0%
359 132 36.8% 15.7% 15.5%
10 5 85.0% 26.3%
90 32 35.0% 18.5%
80 29 36.8% 14.9%
80 32 40.3% 13.1%
75 23 30.2% 17.4%
24 11 45.0% 13.5%
0.0%
5 2 66.7% 13.2%
88 26 29.0% 18.1%
133 33 25.0% 24.8%
201 64 31.9% 33.0%
100 21 21.4% 23.3%
47 16 33.6% 26.4%
3 1 33.0% 60.0%
1. High Need Admits Registered Yield % of Total FR Admits % of Registered
History ‐ Yield rate by category
2. Medium Need Admits Registered Yield % of Total FR Admits % of Registered
3. Low Need Admits Registered g Yield % of Total FR Admits % of Registered
0.0%
4. No Need Filer Admits Registered Yield % of Total FR Admits % of Registered
0 0
5. No Need Non Filer Admits Registered Yield % of Total FR Admits % of Registered
450 145 32.2% 20.9% 18.5%
425 135 31.8% 21.8% 15.9%
395 119 30.1% 19.2% 13.6%
577 163 28.2% 25.3% 19.1%
% of "full pays"
53.6%
50.6%
43.8%
49.1%
2Project Model-Segment SPU 2010 Model 2-42%fullpay
Net revenue drivers Headcount by student type # Instit. Scholarships $ Instit. Scholarships I i S h l hi # Institutional Gift Aid % Institutional Gift Aid $ Institutional Gift aid Average $ Scholarship Average $ Gift aid f d Total Net Revenue Discount Rate
| Enrollment Goals: Continuing Student Goal Discount Rate Discount Rate Headcount # Scholarship $ Scholarship # Gift Aid # Gift Aid % Gift Aid $ Gift aid Average SPU Scholarship A Average SPU Gift aid SPU Gift id Total Net Revenue Discount Rate
Last Year 1,589 38 2 38.2 1,520 1,200 $6,543,278 1368 90% $15,432,180 $5,453 $11 281 $11,281
| | | | | | | | | | | | $26,724,475 | 36.2% |
This Year 1,615 38 80 38.80 1,503 1,035 $7,012,035 1237 82% $11,502,930 $6,775 $9 299 $9,299 $23,461,715 35.8%
Summary data. Next level of analysis aggregates data by need levels – high, medium, low, no need filer, no need non‐filer , , f , f
Determine critical information needed and begin data collection Excel, access, frozen data tables/information system, data warehouse
Verify data quality Enrollment
Budget Factors
accurate, complete, shared definition & metrics
Identify key benchmarks points in time when data must be gathered and compared to build historical trends
Data segmentation start with macro then identify sub‐sets
pp g Holistic approach to data management requires buy‐in from “data managers” (create / manage data)
Build baseline year assess effectiveness and refine over time
Forecasting Enrollment to Achieve Institutional Goals, 2007 article in College & University (Volume 82, No. 3).
Data‐Driven Decisions: Using Data to Inform and Influence Decision‐makers, 2006 article in College & University (Volume 81, No. 3).
Enrollment Management: Key Elements for Building and Implementing an Enrollment Plan, 2005 article in College & University (Volume 80, No. 4).
Understanding the Business of Higher Education: Building Context for Your Staff Development Plan; 2008 article in College & University (Volume 84, No. 1). ; g y( 4, )
Let's Get Organized: Your Personal GPS to Improving Organizational Skills; March 2010 article in SEM Source, found online at http://www.aacrao.org/sem/ .
When Enrollment Strategies Cross Traditional Boundaries: Opportunities and Challenges, April 2008 article in SEM Source, http://www.aacrao.org/sem/ ‐‐ (listed under archives).
