DEAB-P10

DEAB-P10
PGDM 2020-12: Term-VI

DEA for Benchmarking

Course Instructor : Biresh Sahoo, PhD
No. of Credits : Three
Nature of Course : Elective
Area : Economics

OBJECTIVE
The quest for greater efficiency is never ending as managers are always under pressure to improve the performance of their organizations. In the public sector, governments are constantly seeking better value for tax payers’ money, while the emergence of a more global economy has intensified competitive pressures on commercial companies. The onus is therefore on managers to achieve better results from the resources available to them. Furthermore, for businesses organizations seeking to gain the edge over their competitors, benchmarking is an increasingly popular tool that has been used to compare operations and performance over years. This course elegantly presents the techniques and theory to empirically explain how performance indices and rankings are developed and how they can be used to improve efficiency, productivity and profitability. Data envelopment analysis (DEA) is a powerful benchmarking technique to assist you in achieving these objectives. DEA is a linear programming based benchmarking technique to measure the relative performance of the comparable organizations where the presence of multiple inputs and outputs makes their comparison difficult. This technique has been internationally acclaimed as a leading-edge method of performance measurement that supports benchmarking, continuous improvement and strategic analysis. One can use this technique to assist managers in performing comparative efficiency analysis studies that will offer more accurate and richer insights than purely financial measures of performance. Finally, what the students will gain from this course is an appreciation of the principles underlying benchmarking tool, issue arising in using it and some familiarity with DEA-Solver software for implementing comparative assessments.

WHO SHOULD OPT FOR
Students from various areas of management such as General Management, Finance and Accounting, Risk Management, Marketing, Operations Management, and Strategy.

POTENTIAL BENEFITS
Students will learn how to:
Ų Measure performance in a multi-input, multi-output industry.
Ų Decompose performance measures into components (e.g., technical and allocative efficiency).
Ų Identify role models that can serve as benchmarks for programs of productivity improvement.
Ų Identify the output and input changes necessary for an organization to achieve best practice.
Ų Estimate various measures of performance such as customer satisfaction efficiency, consumer welfare index, credit rating/risk, audit risk, bankruptcy, stock selection, ratio analysis, human development index, macroeconomic policy performance, socio-economic performance, ecological (environmental) performance, etc.
Ų Measuring the overall efficiency of a company in terms of both profitability and marketability (Here, one will get to know by how much each of these two factors contributes to the overall efficiency of the company).
Ų Decompose total factor productivity into its various factors such as efficiency and technology.
Ų Decompose profit (cost) change into its various drivers such as efficiency, technology, resource-mix, output-mix, scale and price.
Ų Decompose technological capacity utilization into various meaningful components such as efficiency, economic capacity utilization and optimal capacity idleness.
Ų Critically evaluate a performance study

There are two modules in this course
Ų MODULE 1: DEA methodology in performance measurement
Ų MODULE 2: Application of DEA methodology.

MODULE 1 offers in-depth training drawn from the latest research developments in DEA methodology, as applied to comparative efficiency assessment and more generally to performance management.
This module reviews
Ų The concept of relative efficiency in broader and specific contexts.
Ų Basic economic concepts needed for a proper understanding of productivity and efficiency measurement. Students learn how the production possibilities facing firms can be summarized using input and output sets (i.e., input and output isoquants), production functions, cost functions, revenue functions and profit functions.
Ų Basic DEA models for measuring efficiency in multi-input multi-output situations.
Ų Introducing to recent development in DEA including weights restrictions, assessment under variables returns to scale and target setting.

CONTENTS OF [MODULE 1]
[MODULE 1 (A)] THEORETICAL PART [6 sessions]
a) BASIC ECONOMIC CONCEPTS for understanding efficiency and productivity. The concepts include: Technology, Input Isoquant, Output Isoquant, Production Function, Cost Function, Revenue Function and Profit Function
b) TYPES OF EFFICIENCY - Technical Efficiency (TE), Cost Efficiency (CE), Revenue Efficiency (RE), Allocative Efficiency (AE), and Profit Efficiency (PE)
c) BASIC DEA MODELS – CCR, BCC, ADDITIVE, SBM and FDH for the estimation of efficiency (input efficiency and output efficiency)
d) RETURNS TO SCALE
e) DEA MODELS with restricted multipliers: Assurance Region Method, and Cone-Ratio Method
f) DISCRETIONARY, NON-DISCRETIONARY and CATEGORICAL VARIABLES
g) DEA ALLOCATION MODELS – Cost, Revenue and Profit Models for measuring cost efficiency, revenue efficiency and profit efficiency respectively
h) MALMQUIST INDEX for measuring total factor productivity growth (TFPG) and its drivers such as technical efficiency, scale efficiency and technical change

[MODULE 1 (B)] APPLICATION PART [9 sessions]
Here we will be examining how DEA can be used in various other measures of performance of decision making units such as
a) Measuring CREDIT RATING/RISK
b) Measuring AUDIT RISK
c) Measuring BANKRUPTCY
d) Evaluate STOCK SELECTION (where to invest money)
e) Aggregation of individual financial ratios (RATIO ANALYSIS). This is very much useful when different ratios give conflicting signals on the financial health of a company.
f) Measuring profitability and marketability of a stock/company.
g) Measuring CUSTOMER SATISFACTION EFFICIENCY
h) Measuring CONSUMER WELFATE INDEX
i) Measuring HUMAN DEVELOPMENT INDEX
j) Measuring MACROECONOMIC POLICY PERFOTMANCE and SOCIO-ECONOMIC PERFORMANCE
k) Measuring ECOLOGICAL (ENVIRONMENTAL) PERFORMANCE
l) Decomposing COST/PROFIT CHANGE of a DMU into various factors that drive such change. These drivers are efficiency, technology, resource-mix, output-mix, scale and price.
m) Decomposing CAPACITY UTILIZATION of a DMU into various meaningful components that are of practical use to manager who takes decision to improve profits. These components are efficiency, economic capacity utilization and optimal capacity idleness.

MODULE 2 looks at the broader organizational context and the issues arising in implementing the technical methods covered in MODULE 1_B. Some real life case studies in the area of Finance and Accounting, Risk Management, Marketing, Operations Management, Strategy and Applied Economics will be discussed. [5 sessions]

EVALUATION METHOD
Quizzes : 10%
End-term examination : 30%
Project Report (Group) : 40%
Project Presentation (Group) : 20%
Total : 100%
Note: I will be forming various groups, and each group will be given, depending upon their interest, two case studies to prepare a project report. The goal of the report is to briefly summarize the major points of the case study. The guiding questions to be followed for preparing the report are: “What is unique about this case study”, “What are the strengths and weaknesses of the approach followed?”, “What was the basic application model developed in terms of inputs, outputs, etc.”, “What are the learning from the study”, and at the end of the report, mention two innovative application areas where DEA can be used (here one has to specify a goal and then to achieve this goal, has to indicate what could be the possible inputs and outputs). Finally, each group has to present the report in the class.

REFERENCE BOOKS
Cooper, W. W., Seiford, L. M. and Tone, K. (2000), Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Boston: Kluwer Academic Publisher.

Gregoriou, G. N. and Zhu, J. (2005), Evaluating Hedge Fund and CTA Performance: Data Envelopment Analysis Approach, New Jersey: John Wiley & Sons.

Sherman, D. H. and Zhu, J. (2006), Service Productivity Management: Improving Service Performance Using Data Envelopment Analysis (DEA), New York: Springer.

Fox, K. J. (2002), Efficiency in the Public Sector, Boston: Kluwer Academic Publishers.

Created By: Debasis Mohanty on 11/21/2011 at 12:02 PM
Category: PGDM-II Doctype: Document

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