This document provides an overview of performance evaluation and benchmarking using data envelopment analysis (DEA). It discusses how DEA can be used to evaluate the performance of multiple units by establishing an efficient frontier and identifying benchmarks. DEA allows for the inclusion of multiple inputs and outputs in a single model and provides targets for inefficient units to improve performance. Examples of using DEA for benchmarking bank branches and new business processes are also presented.

1. Performance Evaluation
and Benchmarking Using
DEA
Joe Zhu
Department of Management
Worcester Polytechnic Institute
Worcester, MA 01609
jzhu@wpi.edu
www.deafrontier.com

2. Data Envelopment Analysis
Joe Zhu
2
Outline
• What is DEA?
• New Models/Uses
• Two-Stage Model
• Context-dependent DEA
• Benchmarking
• Books

3. Data Envelopment Analysis Joe Zhu 3
DEA & Banking
 The Banking industry has been the subject of DEA
analysis by researchers in various areas and
probably is the most heavily studied business
 Branches
 Banks across countries
Bank
Branch
Inputs
FTE in dollars
Premise/IT expenses
Other Expenses
Outputs
Loan Balances
Deposit Balances
Securities Balances
Gross Revenue
Bank
Branch
Inputs
FTE in dollars
Premise/IT expenses
Other Expenses
Outputs
Loan Balances
Deposit Balances
Securities Balances
Gross Revenue
Source: Paradi et al. 2004

4. Data Envelopment Analysis Joe Zhu 4
DEA
 Deals with multiple performance measures
(inputs and outputs) in a single integrated
model
 Includes any necessary measures related to the
characterization of banking performance
 Identifies a “base-line” for comparisons in
continuous improvement program
 Provides specific targets for improvement
(over time)

5. Data Envelopment Analysis Joe Zhu 5
- Regression can accommodate
Multiple inputs or
outputs but not both
- Regression requires a
functional relationship
between in/outputs
- Regression provides only
average relationships
not best practice
Why DEA?
DEA Best-Practice
Frontier
Input
Output
6
6
6
6
6
6
6
6
6
6
6
6
6
predicted
average
behavior

6. Data Envelopment Analysis Joe Zhu 6
Basic DEA Benchmarking Information
 DEA gives
 Efficiency rating, or score, for each DMU
 Efficiency reference set: peer group
 Target for the inefficient DMU
 Information on how much inputs can be
decreased or outputs increased to make the
unit efficient – improving productivity &
performance

7. Data Envelopment Analysis Joe Zhu 7
DEA & Performance Improvement
DEA Best-Practice
Frontier
Input
Output
6
6
6
6
KInput reduction
6
D
Output
augmentation
D
D

8. Data Envelopment Analysis Joe Zhu 8
Benefits
 The establishment of the efficient frontier
consisting of the best performing DMUs
 A projection to the efficient frontier - a guide
to “what to do” for the DMU managers
 The identification of the peer group, a
reasonable argument why it is a FAIR
comparison
 An indication of how important a particular
DMU is as a role model

9. Data Envelopment Analysis Joe Zhu 9
How DEA works?
 5 branches
 Three (B1, B2 & B3 are efficient – best practice frontier)
 B4 and B5 are inefficient
 Target for B4 is T1 (decrease inputs)
B4
B5
B1
B2
B3
T1
0
50
100
150
200
250
300
350
400
450
0 20 40 60
Teller Hours
SupplyDollars

10. Data Envelopment Analysis Joe Zhu 10
H4
H5
H1
H2
H3
T2
0
50
100
150
200
250
300
350
400
450
0 100 200 300 400 500
Sales
MarketShare
 5 branches
 Three (H1, H2 & H3 are efficient – best practice frontier)
 H4 and H5 are inefficient
 Target for B4 is T2 (increase outputs)
How DEA works?

11. Data Envelopment Analysis Joe Zhu 11
More Information on DEA
 Web
 www.deafrontier.com
 …
 Books
 Cooper, W.W., Lawrence M. Seiford, and K. Tone. 2000. Data
Envelopment Analysis: A Comprehensive Reference Text with
Models, Applications, References, and DEA-Solver Software.
Kluwer Academic Publishers, Boston
 Zhu, J. 2002. Quantitative Models for Performance Evaluation
and Benchmarking: Data Envelopment Analysis with
Spreadsheets. Kluwer Academic Publishers, Boston
 …
 Softwares
 DEA Excel Solver (DEAFrontier)
 …

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Joe Zhu
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DEA & IT
• Indirect impact of IT on productivity
• Two Stage DEA Model
• Chen, Y. and Zhu, J., Measuring information technology’s indirect
impact on firm performance, Information Technology &
Management Journal, Vol. 5, Issue 1-2 (2004), 9-22.

13. Data Envelopment Analysis Joe Zhu 13
What is Benchmarking?
... a process of defining valid
measures of performance
comparison among peer
units, using them to determine
the relative positions of the peer
units and, ultimately, establishing
a standard of excellence.

14. Data Envelopment Analysis Joe Zhu 14
Acceptance System Decision Rule
 Trout et al. (1996, COR, Vol 23, 405-408)
– acceptance/rejection of credit risks
 Seiford & Zhu (1998, COR, Vol. 25, 329-
332)
Benchmarking

15. Data Envelopment Analysis Joe Zhu 15
Approach
DEA Best-Practice
Frontier/Benchmarks
Input
Output
T
6
6
6
6
T
T
6
T
6

new
activities

16. Data Envelopment Analysis Joe Zhu 16
Business Process Re-
engineering
s s s
s s
s s
traditional
best practice
performance
time
• Compare new bank branches to the
traditional best-practice frontier.

17. Data Envelopment Analysis Joe Zhu 17
Benchmarking results
 Overall, new
branches’
performance is
improving
New branch best-practice
traditional branch best-
practice
Cook, W.D., Seiford, L.M. and Zhu, Joe, Models for
performance benchmarking: Measuring the effect of e-
commerce activities on banking performance, OMEGA,
Vol.32, Issue 4 (2004), 313-322.

18. Data Envelopment Analysis
Joe Zhu
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Context-dependent DEA
• Context-dependent
DEA
• Consumer’s choice
is influenced by the
context
• The performance of
DMUs should also
reflect “context”

19. Data Envelopment Analysis
Joe Zhu
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Journal of Marketing
Research
• Book Review
– context-
dependent DEA
(identifying
possible
moderating
results) intriguing
and, conceivably,
breathtaking.

20. Data Envelopment Analysis Joe Zhu 20
Service Productivity
• D. Sherman and J. Zhu, Service
Productivity Management: Improving
Service Performance Using Data
Envelopment Analysis (DEA)
Springer, Boston, 2006, ISBN 0-387-
33211-1.

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Joe Zhu
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DEA Handbook
W.W. Cooper, L.M.
Seiford and J. Zhu
Handbook on Data
Envelopment
Analysis, Springer,
Boston, 2004, ISBN
1-4020-7797-1

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Zhu
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Modeling Issues
 W.D. Cook and Joe
Zhu, Modeling
Performance
Measurement:
Applications and
Implementation
Issues in
DEA, Springer, Bo
ston, 2005, ISBN
0-387-24137-X.

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Joe Zhu
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DEA & Finance
• Mutual funds
• CTAs
• Hedge Funds
G. Gregoriou and Joe Zhu, Evaluating
Hegde Funds and CTA Performance:
Data Envelopment Analysis
Approach, John Wiley & Sons, New
York, 2005, ISBN 0-471-68185-7 .

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Joe Zhu
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