Lycoming College Findings and Recommendations

Lycoming College Findings and Recommendations

Using Data and Information to Drive Enrollment Planning and Decision-Making Kevin Crockett, Senior Executive July 17, 2018 1 Agenda for our time together Survey the major categories of enrollment research (marketing and recruitment focus) Provide examples of actual institutional data to provide additional insight Assist participants in thinking about how to expand/augment their current research efforts and create a data-driven culture Will not cover the logistics of conducting various kinds of enrollment research 2 In God we Trust, all others must bring data Edwards Deming 3 If you dont count it, it didnt happen Peter Bryant Ruffalo Noel Levitz 4

Enrollment management A systematic, holistic, and integrated approach to paradigm achieving enrollment goals by exerting more control over those institutional factors that shape the size and characteristics of the student body. It encompasses all activities associated with attracting and retaining students, including marketing, recruitment, financial aid, orientation, advising, and instruction. Involves examining institutional mission, program and service offerings, organizational structure, and resource allocation. The enrollment management process relies heavily on the use of pertinent data and information for informed decision-making. Ruffalo Noel Levitz 5 Research categories Historical trend data Market share analyses Strategy impact research (including predictive analytics) Cost-benefit studies Market research Secondary data mining Student price response research 6 Historical Trend Data 7 Tracking prospects, inquiries, applicants, accepts, deposits, and Geographic market

area Academic enrolled students by: profile Academic and co-curricular interest (are certain majors rising and falling within your pool?) Race/ethnicity First-year versus transfer Resident/commuter Financial aid status Etc. Provide three to five years of data whenever possible and make certain you are reporting on all your Key Performance Indicators 8 Historical trend data What has our history been? Provides benchmark for comparison On this day last year, we had 221 applications from Los Angeles County. This year, we have 277 applications from LA County. Applications from LA county are up 26%. 9 Tracking student interest by major field of study Major 2013

2014 2015 2016 2017 2,207 2,407 2,620 2,694 2,635 186 164 138 146 125 43 38 32 29 31 763 867 1,344

1,755 2,101 Apps 79 67 107 134 141 Enrolled 21 14 32 37 42 Business Inquiries Apps Enrolled Biology Inquiries This institution was tracking growing interest in biology and declining interest in busin 10 Utilize historical funnel data in your planning process

Fall 2017 funnel report: first-time-in-college (FTIC) students Stage Prospects 2017 (as of July 15) 2017 (goals) 2015 final 2014 final 2013 final 2012 final 15,681 15,000 14,222 14,222 14,139 12,678 2,598 2,500

2,355 2,388 2,142 2,042 Conversio n 15.1% 16.0% 14.5% 15.6% 17.1% 16.6% Applicatio ns 391 400 342 373 366 339 85.2% 85.0% 89.8%

86.1% 85.2% 87.0% 333 340 307 321 312 295 47.1% 48.5% 46.6% 47.4% 47.8% 49.5% 157 165 143 152 149 146

Inquiries Admit rate Admit Yield rate Enrolled 11 Develop separate funnels for each new student enrollment goal 12 Segment analyses are increasingly used to understand the unduplicated Athlete Y/ Financial of students Segment Distance Admits Enrolled Yield Click icon Ntosources add chart Tier Segment 1 Athlete Has Need NA 546 262 48% Segment 2 Athlete

No Need NA 378 76 20% Segment 3 Nonathlete Has Need <50 440 150 34% Segment 5 Nonathlete Has Need 51-100 519 125 24% Segment 7 Nonathlete

Has Need 101-499 767 138 18% Segment 9 Nonathlete Has Need 500+ 359 43 12% Segment 4 Nonathlete No Need <50 460 83 18% 13 Market Share 14

Common sources of market share data ACT and the College Board High school graduate projections (WICHE) Community college enrollment/graduates data State commissions and higher education planning boards IPEDS (degree production by academic program, student import/export data, and share by school) Federal and state population projections for share of adult students by age cohort 15 Market share of degree-granting institutions by control and type of institution: 19704-Year through 2016 4-Year Public 2-Year Public Private 2-Year Private 60% 49% 50% 40% 42% 42% 36%

36% 44% 40% 37% 29% 25% 30% 26% 24% 20% 38% 34% 26% 22% 20% 20% 2% 2% 2% 2% 1% 1980 1990 2000 2010 2016

10% 1% 0% 1970 Source: Digest of Education Statistics, table 303.25 16 Total U.S. public and private high school graduates Copyright 2016. Knocking at the College Door. Western Interstate Commission for Higher Education 17 Projected change in high school graduates Public and non-public, 2017-18 to 2022-23 Copyright 2016. Knocking at the College Door. Western Interstate Commission for Higher Education 18 Projected change in high school graduates White, non-Hispanic, 2017-18 to 2022-23 Click icon to add chart Copyright 2016. Knocking at the College Door. Western Interstate Commission for Higher Education 19 Projected change in high school Students ofgraduates color, 2017-18 to 2022-23 Click icon to add chart

Copyright 2016. Knocking at the College Door. Western Interstate Commission for Higher Education 20 Sample institutional enrollment (Total FY students assuming constant market projection share) 350 300 318 Primary Market Tertiary Market 312 306 Secondary Market 300 295 289 283 139 136 133 127 127 124 79

78 76 75 74 73 2014 2015 2016 2017 2018 2019 250 200 143 150 100 5079 0 2013 21 Strategy Impact Research 22 Are you tracking your essential marketing and recruiting strategies to Source code

analysis determine their effectiveness? Student-initiated contacts Campus visit programs Student search (at the market level) Travel (high school visits, college fairs, offcampus receptions, hotel interviews, etc.) Impact of student contact team Conversion rates for ACT/SAT score reports received (any contact) Search engine optimization Scholarship programs And the list goes on and on ... 23 Sample inquiry source analysis Value A05 A11 ZZ A99 A01 A12 A08 A49 A04 A07 A26 A13 A75 A74 A92

A88 A86 A91 A02 A78 A17 A96 A44 A20 A80 A23 A03 HPU A06 A42 A41 Description Electronic Mail Request SAT Results Description Not Provided JC Day/Night ACT Results Campus Vist Private Coll & Uni. Spring Srch Telephone Request Trnspts Received Athletic Ref NRCCUA--Srch NRCCUA Declared Choice Senior HS Visit High INC Srch Summer Srch Snr-Coll Day/Night Junior HS Visit Children of Alum HS Guidance Ref Jr. Fall Srch NRCCUA My Coll Guide Zinch.com Parent Ref Student Ref

Church Contact HPU Faculty/Staff Letter Request Soph Private Visit Soph Coll Day/Fair Total Number 13643 2969 1602 1462 13478 2717 1517 26887 25188 490 1024 683 7783 935 786 5110 12787 1609 536 175 515 144 7740 411 2 7 20 1 37 50 211 Applicants 3256 1267

1379 1462 778 702 412 539 358 192 363 62 102 83 85 86 100 49 50 13 35 13 38 16 2 3 8 1 6 7 9 Admits 2944 1115 998 999 649 612 380 421 338 171 303 51

87 72 78 78 88 41 44 13 27 11 28 12 2 3 8 1 5 5 8 Confirmations Enrollees 1501 988 379 221 303 211 345 197 280 163 203 113 159 106 167 88 112 73 95 68 82 51

28 27 29 18 23 17 20 16 36 16 25 16 15 13 17 12 8 6 12 5 5 4 9 4 6 3 2 2 2 2 5 2 1 1 2 1 1 1 1 1 Application Admission Confirmation Enrollment Rate

Rate Rate Rate 23.9% 21.6% 11.0% 7.2% 42.7% 37.6% 12.8% 7.4% 86.1% 62.3% 18.9% 13.2% 100.0% 68.3% 23.6% 13.5% 5.8% 4.8% 2.1% 1.2% 25.8% 22.5% 7.5% 4.2% 27.2% 25.0% 10.5% 7.0% 2.0% 1.6% 0.6% 0.3% 1.4% 1.3% 0.4% 0.3% 39.2% 34.9% 19.4% 13.9%

35.4% 29.6% 8.0% 5.0% 9.1% 7.5% 4.1% 4.0% 1.3% 1.1% 0.4% 0.2% 8.9% 7.7% 2.5% 1.8% 10.8% 9.9% 2.5% 2.0% 1.7% 1.5% 0.7% 0.3% 0.8% 0.7% 0.2% 0.1% 3.0% 2.5% 0.9% 0.8% 9.3% 8.2% 3.2% 2.2% 7.4% 7.4% 4.6% 3.4% 6.8% 5.2% 2.3%

1.0% 9.0% 7.6% 3.5% 2.8% 0.5% 0.4% 0.1% 0.1% 3.9% 2.9% 1.5% 0.7% 100.0% 100.0% 100.0% 100.0% 42.9% 42.9% 28.6% 28.6% 40.0% 40.0% 25.0% 10.0% 100.0% 100.0% 100.0% 100.0% 16.2% 13.5% 5.4% 2.7% 14.0% 10.0% 2.0% 2.0% 4.3% 3.8% 0.5% 0.5% 24 Tracking student-initiated

contacts # of Contacts 1 2 3 4 5 6 7 8 Inquiries 13,24 4 3,972 1,744 1,013 637 410 259 172 Applications 1,131

970 820 629 477 333 228 154 354 320 291 240 200 151 106 70 Apps/Inqs % 8% 24% 47% 62% 74% 81%

88% 89% Enr/Inqs % 2% 8% 16% 23% 31% 36% 40% 40% Enrolled Students with 2+ contacts represent 30% of inquiries, 86% of apps, and 90% o 25 Evaluating search at the EPS market level Marke t Name s Inq Resp % Apps

Conv % Enrl Yield % purchas ed IL-96 20,388 2,186 10.7% 68 3.1% 16 0.7% Market 998 124 12.4% 3 2.4% 0 0.0% 1 Market 1,804 170 9.4% 4 2.3% 0 0.0% 2 Market 2,324 266 11.4% 5 1.9% 0 0.0% 3 IL - 95 20,191 2,175

NA 55 2.5% 12 0.5% Market NA 100 NA 2 2.0% 0 0.0% 1 They purchased approximately 10,252 names in two years, which generated Market NA 144 NA 4 stopped 2.8%searching0these0.0% 21 applications and one enrolled student. They three 2 IL markets. 26 Market Evaluating your student search coverage Prospect Progression Rates Funnel Counts Yield Rates Prospect 51531 Inquiry 5519 10.71%

Applicant 455 0.88% Admit 433 0.84% Confirm 152 0.29% Enroll 149 0.29% Coverage Rates (CR%) by Source Source Purchased Names Traditional Inquiries Applications, First Source Total Prospect Inquiry Applicant Admit Confirm Enroll CR % 51531

5519 455 433 152 149 34.98% 0 4935 281 217 37 34 7.98% 0 51531 0 10454 790 1526 578 1228 246 435 243 426

57.04% 100.00% Coverage Rates (CR%) by Source: This table breaks down Sample University's funnel stages between purchased names, non-purchased inquiries, and students whose first source of contact was an application. Coverage Rate for each source is the number of enrolled students divided by the total enrolled. Purchased names produced 34.98% of Sample University's enrollees. 27 Evaluating high school visits Contact s Inqs Apps Conv. % Enrolled Yield 1 2 3 4 5 6+ Total 566 260 138 94 64

101 1,223 33 46 30 31 24 52 216 5.8% 17.7% 21.7% 33.0% 37.5% 51.5% 17.7% 16 31 2.8% 11.9% 11 15 12 24 109 8.0% 16.0% 18.8% 23.8% 8.9% This institution also found significant differences by market area 28 Evaluating SEO results Number of keywords ranking on pages 1, 2, 3, and 4-10

This institution has a big opportunity to increase its rankings for many keyword searches 29 Evaluating student contact team results Late-Winter Program Completed Contact To Inquiries 2,593 Number Who Applied Conversion Rate 38 1.5% Number Who Enrolled Conversion Rate 6 0.2% Why did only 38 apply? They eventually concluded the target group was very weak 30 Strategy impact research Target group selection One outcome of good operations research is the ability to effectively grade and qualify the inquiry pool Understanding past student behavior and the effectiveness of various strategies enables an institution to focus scarce resources on those

students who are most likely to apply and enroll The newest technology in this area is predictive modeling, which enables an institution to forecast a prospective students likelihood of enrolling at the inquiry or prospect stage 31 A known fact about student choice, interest, and behavior 32 Means of qualifying and grading your funnel Research findings Tracking student contacts Student contact team Personal contact on-campus and in the field Reply mechanisms in emails and direct mail Predicitive modeling 33 Goal of predictive modeling Focus marketing resources on individual prospective students who collectively are the most likely to enroll Marketing to the individual 34 Sample model Relative Strength of Model Variable

4.90% 9.70% Initial 28.70% Source Code First Major as Inquiry 6.40% Acxiom Net Worth Profile Primary County Code of Student 14.30% No. of Days as Inquiry (Quartiles) Primary State of Student 36.00% 35 Predictive modeling: Sample results Four-Year University Enrollment 9,900 Model Score Inqs .00-.09 .10-.19 .20-.29 .30-.39 .40-.49 .50-.59 .60-.69 .70-.79 .80-.89 .90-1.0

Total 206 1,026 4,313 10,088 12,485 5,827 2,563 2,344 2,143 2,164 43,159 Apps Conv. % 7 43 222 490 587 473 391 559 728 1,082 4,582 3.4 4.2 5.1 4.9 4.7 8.1 15.3 23.8 34 50 10.6 Four-Year College Enrollment 2,800 Inqs 204

1,203 2,091 2,769 1,974 1,617 1,189 976 970 549 13,542 Apps Conv. % 3 17 79 161 187 182 179 212 230 224 1,474 1.47 1.41 3.78 5.81 9.47 11.26 15.05 21.72 23.71 40.8 10.9 36 Common uses of predictive modeling data

Develop the most productive inquiry pool possible Target admissions travel/staff time Develop segmented written communication plans Develop targeted student contact team plans Target limited financial aid dollars Identify new markets Save recruitment dollars by focusing resources on those students most likely to enroll 37 Cost-Benefit Studies 38 Cost benefit studies Provide additional insight about the relative effectiveness of various strategies Attempts to link budget data to activities such as travel and investments in SEO Solid strategy impact research is an essential prerequisite Detailed, line-item budgeting is very helpful 39 Cost benefit studies Evaluating admissions travel Cost/Benefit Analysis Of Three Primary Travel Programs Students Program Seen Applicants Enrolled College Fairs

2,250 122 38 High School Visits 971 211 85 Off-Campus 1:1s 203 117 47 3,424 450 170 Totals Average Cost* * 9 $68.74 $181.96 Based Upon $30,933 in travel expenditures 40

Market Research 41 Market research Common target populations Prospects Inquiries Lost applicants (pre-accept) Lost admits and deposited students Alumni High school counselors Clergy or other influencers Parents Feeder businesses/employers 42 Market research General observations Can and should segment these groups

(racial/ethnic category, academic profile, income level, geography, etc.) Populations further down the funnel will have stronger attitudes and beliefs about your institution; therefore, most schools start at the bottom However, focus market research to address your problems; slumping yield demands different research than declining conversion rates Should have comparison groups whenever possible (e.g., enrolled versus non-enrolled students) 43 Market research Importance of starting at the bottom Results of a Lost Inquiry phone survey Impressions of the admissions/recruitment process Item Campus visit experience Contact w/faculty Interaction w/current students Admissions representatives The admissions office in general The college web site Publications and mailings Percent Dont Know or Did Not Use 93% 92% 71% 66% 57% 26% 11% On average, two-thirds of the students also could not answer the general attitude and belief questions 44

Market research Common studies Image and perception studies Academic program demand analyses Pricing studies Competition studies (secret shopper studies, program characteristics) Environmental scans Lost admit studies 45 Which of these schools do you think is best for . . . ? STUDENTS 100% 90% 80% 70% 60% 53% 52% 51% 48% 44% 50% 43% 39% 39% 42% 37% 40% 32% 30% 28% 29% 29% 29% 29% 29% 30% 22% 20%

19% 18% 17% 16% 15% 15% 15% 11% 11% 20% 12% 13% 13% 12% 14% 11% 11% 15% 11% 11% 10% 11% 10% 10% 9% 9% 8% 8% 8% 8% 8% 8% 10% 7% 7% 7% 6% 6% 10% 0% s s k e u le ts ip rs in m es es es es d)

es ch am or ice d yo vic iti rc am iti ab sh se en he ar nc liti oo v r r e w gr r i n u c n a d e d r e r t o t

e g c i a o r a t s e s e r tu o tu -b ss so tu es fa ol te re pr rs ffo in ng pe re or or pr ed er ity rs cla al ch

e a n st t x ti n st p p e c n s o e e ti t i e s o e n o e t u m t l B (n d at B op m ar op re

ti os en ty m in en ar na b id alu te tc id du M ip de os ul e m m a o s s o t w n a c a c h j i o l m a

o n c t t re fa es gr ati Be ac ia ns es to es et in st os rie st rn st ng th er nc ti i b e e t e s i e e m o a

le y m t t B p r b w B ti in n ve tiv in fin ty St ik ex to rk st ke ac de ni ha d st tl e o d n a r i l u r s

t u o s B t a w t o s la o m m or te ge M to aw m of gt -w icu rs ua s s l o r t o e n d e c e a t

r t a e ti lli en ly in Off au ni -cu Gr tr m wi d a d s u e t il ke t r a e o v t t t os or ol Gr Ex ca m gm os

pp nv Lo i ir n M o tl y t st b cu es te ty a B l Fa e cu Gr Fa Public Competitor Private Competitor Sample College 46 Sample competitor grid Institutions Program Type Competitor 1 Ed.D. Competitor 2 Ed.D. Competitor 3 Ed.D. (Organizational Leadership) Competitor 4 Ed.D. Ed.D. (Educational Administration Competitor 4 or Teacher Leadership) Competitor 5 Ed.D. Competitor 6 Ed.D. (Educational Leadership) Competitor 7 Ed.D. (Educational Leadership)

Competitor 8 Ed.D. (Leadership Studies) Price Credit Hours Modality $825 47 Blended $875 48 80/20 ground-based $875 57 On-ground Blended online/on-ground using Blackboard; late afternoons and $857 60 weekends $870 $885 $1,340 $1,420 $1,320 53 54 56-60 43 63 Online Blended online/on-ground 60/40 online/on-ground On-ground On-ground 47 Secondary Data Mining 48

Secondary data Demographic information for the primary, secondary, and tertiary market (from service area school districts and census information) Characteristics of the college-bound population (e.g., racial/ethnic diversity, academic qualifications) Data from ACT, the College Board, RNL, etc. Association, Federal, and State/local data (e.g., NACUBO, Bureau of Labor Statistics, Department of Education, School Districts) IPEDS/National Student Clearinghouse/HERI/NCES data Competition data (number of institutions, price, endowments, financial aid trends, programmatic offerings) 49 Miles from home: 2015 vs. 1980 40.0% 33.9% 35.0% 29.4% 30.0% 24.1% 21.4% 25.0% 20.0% 15.0% 20.6% 17.6% 17.4% 15.1% 12.0% 11.3%

10.0% 5.0% 0.0% 10 or less 11 to 50 2015 HERI: The Regents of the University of California. All Rights Reserved. 51 to 100 101 to 500 Over 500 50 The National Student Clearinghouse reported a 1.3% drop in spring 2018 enrollments 2018 National Student Clearinghouse. Current Term Enrollment Estimates fall 2017. Reprinted with permission. This material may not be posted, published, or distributed without permission from National Student Clearinghouse. 51 Only two states had public enrollment growth of 5 percent or more between 2011 and 2016 (FY) Source: SHEEO: State Higher Education Executive Officers Association Finance FY16 52 Average tuition and fee charges in constant dollars 1987-88 to 2017-18 (enrollment weighted) Private four-year Public four-year Public two-year

$40,000 $33,180 $34,100 $34,740 $9,670 $9,840 $9,970 $2,700 $3,490 $3,530 $3,570 2007-08 2015-16 2016-17 2017-18 $35,000 $30,000 $25,000 $27,520 $21,020 $20,000 $15,160 $15,000 $10,000 $3,190 $5,000

$1,590 $0 1987-88 $4,740 $2,390 1997-97 $7,280 Source: Data derived from 2017 Trends in College Pricing. Copyright 2017, the College Board. www.collegeboard.org. Reproduced with permission. This data may not be posted, published, or distributed without permission from the College Board. 53 Purchasing power of Federal Pell Grant Four-year private and Stafford Loan Average P+S Year 2009-10 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16 2016-17 2017-18 Maximum Pell Maximum Stafford Pell + Stafford

Tuition and Fees Tuition and Fees $5,350 $5,550 $5,550 $5,550 $5,645 $5,730 $5,775 $5,815 $5,920 $3,500* $3,500* $3,500* $3,500* $3,500* $3,500* $3,500* $3,500* $3,500* $8,850 $9,050 $9,050 $9,050 $9,145 $9,230 $9,275 $9,315 $9,420 $26,273 $27,293 $28,500 $29,056 $30,094 $31,231 $32,405

$33,480 $34,740 34% 33% 32% 31% 30% 29% 29% 28% 27% * Dependent students eligible for $2,000 unsubsidized Stafford Loan so long as parents were not denied a PLUS loan. Source: Data derived from 2017 Trends in College Pricing. Copyright 2017, the College Board. www.collegeboard.org. Reproduced with permission. This data may not be posted, published, or distributed without permission from the College Board. 54 55 Real-time labor databases are a powerful new tool 56 Student ROI is also an important consideration 2015 The National Association of Colleges and Employers Salary Survey: Starting Salaries for New College Graduates, 57 Student Price Response Research 58 The cost/selectivity matrix is a useful tool for understanding your current market Net Price position High Cost

Low Selectivity High Cost High Selectivity Selectivity Low Cost Low Selectivity Low Cost High Selectivity 59 Student price response research Financial aid leveraging is the strategic investment of financial aid funds to: Enroll the desired number of students Enroll students with the desired characteristics Achieve a targeted net revenue goal Control the institutions discount rate 60 Two important considerations Students ability to pay Students willingness to pay Financial aid strategy must address both

criteria Both elements must be present for a student to enroll 61 Academic achievement as a proxy for willingness to pay Academic Tiers Fall 2017 50% 43% 45% Yield Rate (%) 40% 35% 28% 30% 25% 25% 20% 18% 15% 10% 5% 0% T1 T2 T3 T4

Tier 1 has the highest/strongest academic credentials 62 The strategic financial aid By definition, segments contain students that share matrix similar financial and academic characteristics Willingness to Pay Quality groups Ability to Pay Need criteria 63 64 Key metrics Yield (and retention) rates by cell Percentage of need met and need met with gift aid for need-based students Yield by institutional gift offer for low-need and merit-aid-only students 65 Measuring price-sensitivity of selected need-based students by percentage of need met Need Met <75.6% 75.6%87.0% >87.0% Total Enrollment Number of Rate

Cases 25.9% 54 Cases 48.2% 83 Cases 49.2% 42.6% 65 Cases 202 Cases Yield rates in selected cells of a client subpopulation 66 Measuring price-sensitivity of selected need-based students by percentage of need met with gift aid Need Met w/ Gift Aid <53.16% 53.16%61.7% >61.7% TOTAL Enrollment Number Of Rate Cases 24.4% 78 Cases 47.9% 73 Cases 62.7% 42.6% 51 Cases 202 Cases Yield rates in selected cells of a client subpopulation 67 Measuring price-sensitivity of selected merit-aid only students by examining the gift aid offer

Merit Offer Enrollmen Number Of t Rate Cases 6% 30 Cases 42% 53 Cases <$3,000 $3,000$4,999 $5,00060% 30 Cases $6,999 >$6,999 75% 12 Cases Total 39.2% 125 Cases Yield rates in low-need and merit-aid-only segments (ability level 3) of a clients first-year population 68 Price Scenario Response Curves STUDENTS 100% 90% 80% 70% Pct to enroll = 9 or 10 60% 50% 40%

30% 20% 10% 0% al iti n I w Lo T: /A :L id ow w Lo T: /A m iu ed :M id w Lo T: /A ig :H

id h T Public Competitors m iu ed :M /A :L id ow m iu ed M T: m iu ed :M id A / Private Competitors m iu ed M T: /A

ig :H id h g Hi T: h /A ow :L d i g Hi T: h /A m iu ed :M id g Hi T: h /A ig :H id

h Sample College 69 Net Revenue Optimization (Students) $10,000,000 $9,000,000 $8,000,000 $7,000,000 $6,000,000 $5,000,000 $4,000,000 $3,000,000 $2,000,000 $1,000,000 $0 $4 0, 00 $4 0 1, 00

$4 0 2, 00 $4 0 3, 00 $4 0 4, 00 $4 0 5, 00 $4 0 6, 00 $4 0 7, 00 $4

0 8, 00 $4 0 9, 00 $5 0 0, 0 $5 00 1, 00 $5 0 2, 0 $5 00 3, 00 $5 0 4,

00 $5 0 5, 00 $5 0 6, 00 $5 0 7, 00 $5 0 8, 00 $5 0 9, 00 0 TOTAL COST (Sticker Price) Aid = $10000

Aid = $15000 Aid = $20000 Aid = $25000 70 Getting Started 71 Getting started Seek staff who... Have research interests and are unafraid of evaluation Possess high-level analytical skills and can interpret data Will constantly seek new and better ways to do things Are well-organized and detail-oriented Understand and appreciate advanced computer systems 72 Getting started Additional thoughts Identify problem areas and start there Understand how you plan to use research before you undertake a project

Obtain good hardware and software systems A need for senior staff appreciation for the value and importance of database management Develop periodic reporting schedules that are linked to the planning cycle Create a well-organized, central depository that is easy to access (e.g., a directory on the network) Link the EM database to an institutional database that is used by all divisions of the institution Demand office-wide computer training/orientation Beware of over-reliance on data, paralysis by analysis 73 Questions 74 KEVIN CROCKETT Senior Executive [email protected] com 800.876.1117 | toll free 303.910.8838 | mobile 303.714.5656 | office All material in this presentation, including text and images, is the property of Ruffalo Noel Levitz. Permission is required to reproduce information. 75

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