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Data Envelopment Analysis (DEA). Which Unit is most productive?. DMU labor hrs. #cust. 1 100 150 2 75 140 3 120 160 4 100 140 5 40 50. DMU = decision making unit. - PowerPoint PPT Presentation
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Data Envelopment AnalysisData Envelopment Analysis(DEA)(DEA)
Which Unit is most productive?Which Unit is most productive?
DMU = decision making unit
DMU labor hrs. #cust. 1 100 150 2 75 140 3 120 160 4 100 140 5 40 50
DEA DEA (Charnes, Coopers & Rhodes ‘78)
A multiple-input, multiple-output productivity measurement tool
Basic intuition(DMU = decision making unit)
DMU labor hrs. #cust. #cust/hr. 1 100 150 1.50 2 75 140 1.87 3 120 160 1.33 4 100 140 1.40 5 40 50 1.25
#cust.
labor hrs.
x x
50 100
100
200
x
x
x
slope = 1.87
DMU’s 1,3,4,5 are dominated by DMU 2.
Extending to multiple outputs ...Extending to multiple outputs ...Ex: Consider 8 M.D.’s working at Shouldice Hospital for the same 160 hrs. in a month. Each performs exams and surgeries.
Which ones are most “productive”?
Note: There is some “efficient” trade-off between the number of surgeries and exams that any one M.D. can do in a month, but what is it?
Doctor #Exams #Surgeries1 48 682 12 803 35 764 31 715 20 706 20 1057 36 538 15 65
0
20
40
60
80
100
120
0 10 20 30 40 50 60
#Exams
#S
urg
eri
es
Scatter plot of outputs: Efficient M.D.’s: These two M.D.’s (#1 and #6) define the most efficient trade-off between the two outputs.
efficient frontier
#6
#1
These points are dominatedby #1 and #6.
“Pareto-Koopman efficiency” along the frontier - cannot increase an output (or decrease an input) without compensating decrease in other outputs (or increase in other inputs).
0
20
40
60
80
100
120
0 10 20 30 40 50 60
#Exams
#S
urg
eri
es
How bad are the inefficient M.D.s and where are the gaps?
73.4% of distance to frontier
Efficiency score = 73.4%
Performance “gap”#5
0
20
40
60
80
100
120
0 10 20 30 40 50 60
#Exams
#S
urg
eri
es #5
Reference set for #5is {1,6}
#1
#6
“Nearest” efficient points define a reference set and a linear combination of the reference set inputs and outputs defines a hypothetical composite unit (HCU)
HCU
DEA summary so far: DEA summary so far: DEA uses an efficient frontier to define multiple I/O productivity
Frontier defines the (observed) efficient trade-off among inputs and outputs within a set of DMUs.
Relative distance to the frontier defines efficiency “Nearest point” on frontier defines an efficient
comparison unit (hypothetical comparison unit (HCU)) Differences in inputs and output between DMU and
HCU define productivity “gaps” (improvement potential)
How do we do this analysis systematically?
A real-word example: A real-word example: NY Area Sporting Goods StoresNY Area Sporting Goods Stores
ProductivityProductivity
Conceptually ...
Productivity = OutputsInputs
Reality if more complex ...
Technology+
Decision Making
Inputs Outputs
equipment
facility space
server labor
mgmt. labor
#type A cust.
#type B cust.
quality index
$ oper. profit
Operating Units DifferOperating Units Differ
Mix of customers served Availability and cost of inputs Facility configuration Processes/practices used Examples
– bank branches, retail stores, clinics, schools, etc.
Questions:– How do we compare productivity of a diverse set of operating units
serving a diverse set of markets?– What are the “best practice” and under-performing units?– What are the trade-offs among inputs and outputs?– Where are the improvement opportunities and how big are they?
Some approachesSome approaches Operating ratios
– e.g. Labor-hrs/transaction, $sales/sq.-ft.– Good for highly standardized operations– Problem: Does not reflect varying mix of inputs and outputs found in more
diverse operations Financial approach: Convert everything to $$$!
Problems?– Some inputs/outputs cannot be valued in $ (non-profit)– Profitability is not the same as operating efficiency (e.g. variances in
margins and local costs matter as well)
$Inputs $Outputs
Profitability vs. effeciencyProfitability vs. effeciency
Profitability is a function of 3 elements …– Input prices (costs)– Output prices– Technical efficiency (How much input is required to generate
the firms output.)
Improving operations requires understanding technical efficiency not just overall profitability.
LP Formulation:LP Formulation:
N
iiki
M
jjkj
k
k
j
i
ik
jk
Iv
Ou
E
E
ju
iv
kiI
kjO
MjM
NiN
KkK
1
1
100%)-(0 DMU of efficiency
output on weight
input on t weigh
DMU from input of level observed
DMU from output of level observed
,...,1 outputs#
,...,1 inputs #
,...,1 (DMUs) units operting# Data
Model variables
To evaluate a give unit, e, choose nonnegative weights tosolve ...
KkE
ts
E
k
e
,...,1 ,100
..
max
Niv
Mju
KkIvOu
Iv
ts
Ou
i
j
N
iiki
M
jjkj
N
iiei
je
M
jj
,...,1 ,0
,...,1 ,0
,...,1 ,100
1
..
max
11
1
1
Which can be formulated
Normalize weighted input of
e to one
Output analysis
e setreferencek
k
k
k
DMU of in the is DMU 0
DMU with associated variabledual
NiII
MjOO
ik
jk
,...,1 ,ˆ
,...,1 ,ˆ
K
1kki
K
1kkj
These dual variables can be used to contruct an efficient hypothetical composite unit (HCU) with
Input i of HCU
Output j of HCU
Satisfying
NiII
MjOO
ie
je
,...,1 ,ˆ
,...,1 ,ˆ
i
j
HCU can be used to measure excess use of inputs and potential increase in outputs
NiII
MjOO
ie
je
,...,1 ,0ˆInput
,...,1 ,0ˆ Output
i
j
Refer to spreadsheet examples.
Using the results: Eff.-Profit MatrixUsing the results: Eff.-Profit Matrix
High Profit
Low Profit
LowEff.
HighEff.
Under-performingpotential leaders
Best practice comparison group
Under-performingpossibly profitable
Candidates forclosure
Designing DEA StudiesDesigning DEA Studies
#Inputs/OuputsK > 2(N+M)
“Ambivalence” about inputs and outputs - all should be relatively important!
“Approximate similarity” among DMUs– objectives– technology
Provides relative efficiency only– choice of units to include matters– inclusion of “global leader” unit may be desirable
Experimenting with different I/O combinations may be necessary
DEA SummaryDEA Summary
Addresses fundamental productivity measurement problems due to ...
– complexity of service outputs– variability in service outputs
Takes advantage of service operating environment– large numbers of similar facilities– diversity of practices/management/environment
Provides useful information– objective measures of productivity– reference set of comparable units– excess use of inputs measure– returns to scale measure
DEA Summary (cont.)DEA Summary (cont.)
Role of DEA– “data mining” to generate hypotheses– evaluation/measurement– benchmarking to identify “best practice” units
Caveats– “black box” - No information on root causes of inefficiency– Be aware of assumptions (e.g. linearity)– Can be sensitive to selection of inputs/outputs