Compression / Inversion Report

UFF Summary/Interpretation

In CBA 2007-2010◦ “C & I student completed by Feb. 1, 2009”◦ Started by Joint Committee. Completed by UFF-FGCU to make

an offer for bargaining. No agreement. In CBA 2009-11 Supplement

◦ 23.8 Compression and Inversion Study. Recognizing that the University and the UFF-FGCU Chapter did not jointly complete a Compression and Inversion (C&I) Study as outlined in the 2007-2010 Collective Bargaining Agreement, the parties acknowledge that the parties will commission an external consulting firm having a regional and/or national reputation and experience in performing compensation studies to conduct a C&I Study to inform bargaining.

C & I History

Salary Compression occurs when newly hired, or junior faculty members receive a rate of pay that approaches, or is approximately equal, to the rate paid to faculty of higher, or senior, professional rank.

Salary Inversion arises when junior faculty members earn higher salaries than senior faculty.

Within rank and between ranks.

What are Salary Compression and Inversion?

Study because individual faculty members saw newer faculty getting salaries the same as, or more than, experienced faculty members.

Faculty members felt this was unfair -- Climate Study, turnover, lower morale, less willingness to serve the college, less willing to mentor new faculty, had completed an external study (Market Study) several years before and had discussed doing the internal study in the future at that time.

Compression and inversion exists across the university. For example:

Why?

Examples of C&I: Actual Salaries

CIP Coll Subj Rank Yr Hire

Salary

03 CAS Ecology Asst 09 49,980

Prof 02 88,900

09 CAS Communication Assoc 97 64,460

Prof 05 64,666

Prof 06 71,735

14 Eng Engineering Asst 06 70,754

Asst 10 75,000

Assoc 06 79,400

Assoc 08 96,900

Examples of C&I: Actual SalariesCIP Coll Subject Rank Yr

HireSalary

22 CPS Justice Studies Asst 04 50,330

Asst 07 50,480

51 Hlth Nursing Asst 06 66,813

Physical Therapy Asst 08 70,086

Health Sciences Assoc 96 68,290

52 COB COB Asst 09 105,060

Assoc 99 88,400

Prof 96 92,527

27 CAS Science Inst 1 03 35,800

Inst I 09 36,720

Inst II 06 38,990

Even though the C&I report states that there is no C&I in the university, except for Health and Business (H&B). This conclusion is WRONG—it needs to be understood in light of the statistics used.

C&I is particularly large in H&B, but there is also C&I in the rest of the University.

Let’s understand what the report does and does not say, especially in light of the statistics we needed to use.

Report Findings

The study provided an extra analysis requested by administration that compares our average JUMPS between ranks with other universities’ average jumps◦ This is NOT a market survey of salary levels.

Rank Ratio — compares average salaries between ranks and compares to other universities. Mean salary/rank by mean salary/ discipline. Time in rank not included.◦ “Do our salary jumps between ranks look like those of other

universities?” Yes, in all but 2 disciplines. ◦ Based on salary averages by rank

Methods

Average salaries by rank ◦ Instructor; Jr. Asst. Professor/less than 3 years; Asst.

Professor; Assoc. Professor, Professor ◦ Progressively increase as faculty rise through ranks

Average jumps, not including seniority The jumps are similar to peer schools. However,

FGCU has larger jumps between levels . Not true in:

◦ Heath Professions (Instructors higher than Asst.)◦ Business (Assistants almost = Associates)

Rank Ratio Analysis

Predicts what salary “should be” ◦ What would salaries be if we paid everyone consistently, on the same basis.◦ Taking into consideration: discipline, rank, years-at-rank, and market

conditions at time of hire to predict “should be”◦ There are variation within rank

Develops different regression equations to predict salaries for different disciplines and different “ranks” There are 23 disciplines using CIP at 2-digit level “Ranks:” Instructor, Jr. Asst. Professor, Asst. Professor, Assoc. Professor, Professor.

Also, Library, Advisors. Regression compared to rank-ratio

◦ Considered in the C&I literature (and by the consulting firm) to a better method than rank-ratio.

Looks at salaries internal to FGCU only, not compared to other universities.◦ Not a market study, we have done two of those previously

Regression Analysis

Considered: 9 month salaries, CIP code for discipline, rank, years of service at rank

Most of university paid in a similar manner◦ University-wide rank and years at rank◦ Identified the university’s “policy” for paying people◦ Created a “line of best fit” for predicted salaries

Some paid differently◦ CIP 51 (mostly Health Professions) and CIP 52 (most of Business

faculty) not paid on the same policy as rest of University◦ Multipliers differ◦ Two groups in business identified as having high pay premium in

equation (finance and accounting) Developed equations for calculation of predicted

salaries for all individual faculty members

Regression

Dispersion around “Best Fit” for Most Disciplines

Salary

Time in Rank

Assistant

Associate

NOTE: Observations “fit” the regression model, because they are close to the line. But some people are

underpaid, others overpaid according to the line

Dispersion around “Best Fit” Problems

Salary

Time in Rank

Assistant

Associate

NOTE: Observations do NOT “fit” the regression model, and so the model is “significant”. But some people are underpaid,

others overpaid according to the line

Regression Equation Predictions using average salaries New assistants make $12,739 more than Inst. New associates make $18,934 more than Inst.

◦ $6195 more than assistants New professors make $30,355 more than Inst.

◦ $17,616 more than assistants◦ $11,421 more than associates

Not compressed when experience is not considered. Additional years of experience are rewarded at an

increasing rate as rank increases.

University-Wide Faculty Salaries Compared to New Instructors

Regression Equation Predictions using average salaries Additional pay to new assistants, associates, and

professors in Health is negative, means increased salary for higher ranks are less than for average faculty.

Average salary for instructors $64,027 New assistants $ -3255 (less) than instructors New associates $3463 more than instructors

◦ $6720 more than new assistants. New professors $7236 more than Inst.

◦ $3772 more than new associates

Health Professions

Regression Equation Predictions using average salaries Avg salaries for instructors $57,588 New assistants earn $32,268 more than instructors New associates earn $27,505 more than instructors

◦ $4763 less than new assistants New professors earn $46,724 more than instructors

◦ $19,219 more than new associates Faculty in finance and accounting earn $20,375 more

than other business sub-disciplines.

Business

Estimate predicted salaries at the individual faculty member level. Identify discipline (CIP). $ CIP Intercept Identify current rank. + $ Rank modifier If accounting or finance add + $ hi-business Multiply years at rank

times years at rank modifier + years*rank mod Predicted Salary Predicted Salary Actual current salary - current salary Desired adjustment $

Predicted vs. Actual Salary Comparisons for an Individual Person

Example of How to Compute, NOT Actual Salaries

Predicted salary

Cip intercept

Rank Modifier Hi-Bus

Yrs at Rank

modifier

Your years at

rankTotal

Predicted ActualDifferen

ce

Assistant Professor in CIP 1 (Agriculture), 5 years of experience at Assistant level

Y =

39,606

14,177 (484)

5

51,363

50,000

1,363

Professor, CIP 1 (Agriculture, 10 years of experience as Professor

Y =

39,606

30,355 1,266

10

82,621

80,000

2,621

Sample Predictions and Differences between Predicted and Current Salary

CIP Coll Subj

Rank Yr Salary Predict Diff

03 CAS Asst 09 49,980 55,374 5,394

Prof 02 88,900 91,675 2,773

09 CAS Asso 97 64,460 64,850 390

Prof 05 64,666 70,366 5,700

14 Eng Asst 06 70,754 75,325 4,570

Asst 10 75,000 75,822 822

Asso 07 88,442 84,900 ---

Is the study perfect? ◦ NO, but it can be informative as long as we understand what it shows and

doesn’t. ◦ We must also understand the statistics and limitations of the study.

Should we have done it a different way◦ We reviewed the literature on C&I to find the way that other universities

have handled this issue. Regression is what they used.◦ Previous internal C&I committees have tried to develop “better”

approaches, but these were not agreed to by both sides.◦ We want something done now—finally--rather than wait for a perfect

study. By all means, continue to identify and report to UFF and

Administration your concerns with your experience with C&I. ◦ I hope that these reports will influence FGCU NOT to sweep the issue under

the unexamined findings of the study.◦

Final Note