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)
 …

12. Data Envelopment Analysis
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.

21. Data Envelopment Analysis
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

22. Data Envelopment Analysis Joe
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.

23. Data Envelopment Analysis
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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