How To Evaluate The Performance Of The Process Industry Supply Chain

Transcription

1 Performance Evaluation of the Process Industry Supply r Chain: Case of the Petroleum Industry in India :.2A By Siddharth Varma Submitted in fulfillment of requirements of the degree of DOCTOR OF PHILOSOPHY to the MECHANICAL ENGINEERING DEPARTMENT INDIAN INSTITUTE OF TECHNOLOGY DELHI April, 2008

2 ..,L1-0 Ca Acc. No TH 665.6/7 Cs-- /-10) 71,.T

3 Dedicated To My teachers, for their guidance My parents, for their sacrifices My family, for their support

4 CERTIFICATE The thesis titled "Performance Evaluation of the Process Industry Supply Chain: Case of the Process Industry in India", being submitted by Siddharth Varma to the Indian Institute of Technology, Delhi, for the award of the degree of Doctor of Philosophy is a record of bonafide research work carried out by him. He has worked under our guidance and supervision, and fulfilled the requirements for the submission of this thesis, which has attained the standard required or a Ph. D degree of this institute. The results presented in this thesis have not been submitted in part or full to any other university or institute for the award of any degree or diploma. Professor S. G. Deshmukh Department of Mechanical Engineering Indian Institute of Technology, Delhi New Delhi Professor Subhash Wadhwa Department of Mechanical Engineering Indian Institute of Technology, Delhi New Delhi

5 Acknowledgement A doctoral thesis is often the outcome of the contributions of a number of individuals and organizations. This thesis is no different. At the very outset, I would like to thank my two guides: Prof Subhash Wadhwa and Prof S. G. Deshmukh whose unstinted guidance was crucial to the completion of this research study. But for their support and knowledgeable suggestions, this thesis would have never seen the light of the day. I am also indebted to two organizations with whom I have worked, for allowing me to pursue my doctoral research while being employed full time with them: Institute of Management Technology (IMT), Ghaziabad and University of Petroleum & Energy Studies (UPES), Dehradun. The registration for this research study was done while I was an Associate Professor at IMT while the submission was done while I was a Professor at UPES. I would also like to thank all the respondents who spared time from their busy schedules to fill in the questionnaire on which part of this study is based. My special thanks to Mr. Umesh Gautam and Mr. Arun Jyoti for facilitating appointments with the respondents, and to Mr. L R Jain for the useful discussions which helped in development of the simulation model. Thanks are also due to fellow doctoral research students, especially Mr. Jitendra Madaan and Mr. Bibhushan for helping me in the simulation work. I would like to express my gratitude to my parents who encouraged me in my work at every stage. Last but not least, I thank my wife Sam and my two children, Saksham and Soumya for their support to me at home during the research work. /4 d-riti..4.--ti ---(1-\ 01- (Siddharth Varma) ii

6 Abstract Process industries are the building blocks of any country. Industries like steel, cement, fertilizer and petroleum form the backbone of the economy. The petroleum industry has a special place among the process industries since the whole transportation system as well as many industries depend on it for their fuel requirements. The Indian petroleum industry has traditionally been controlled by the government but is now gradually moving towards a more liberalized regime. The fall of the Administered Price Mechanism in 2002 marked the commencement of this transition. Having been protected by the government, and in the absence of any competition from the private sector, the petroleum industry was not aggressively focusing on performance. However, with liberalization taking place, performance is sure to become more important for this industry which is going to be strongly dependent on the supply chains of these firms. In this context, performance measurement of this supply chain assumes a lot of importance. The current research study is an attempt to find out a way to measure the performance of the petroleum supply chain with special reference to India. The topic has been finalized after an extensive literature review on issues faced in supply chain management. The problem of measuring supply chain performance has been handled systematically at three levels. It commences with a macro-level study of four prominent process industries in India by studying their overall profitability with respect to some input parameters. This has been done by applying Data Envelopment Analysis (DEA). Next, the Balanced Scorecard (BSC) has been used to measure performance of the supply chain at a strategic level. BSC has traditionally been used at individual level or firm level. The current research study elevates the use of BSC from the firm level to the industry level. Another iii

7 shortcoming of the BSC has been that it can not combine dissimilar metrics together. This has also been overcome in this study. The Analytic Hierarchy Process (AHP) has been applied in combination with the BSC to enable quantification of relative importance of the four perspectives as well as the underlying criteria. Opinions of Subject Matter Experts(SMEs) has been taken through a questionnaire. At the third level, i.e., the operational level, performance has been studied by developing a Simulation model and looking at cost variations as a function of different parameters. Based on the analysis, insights have been provided and suggestions given for improving performance. The macro-level study indicated that the petroleum supply chain was the worst performer among the four process industries studied, considering raw material and assets as inputs and net profit as output. The cement industry supply chain emerged the best. However, when power and fuel was taken as an additional input, performance of petroleum industry improved while cement industry still remained the best performer. The strategic level analysis using BSC in conjunction with AHP found that customer perspective was the most important perspective followed by the financial perspective. Among the more important criteria which emerged from the analysis were: purity of product, raw material prices, market share, steady supply of raw material, optimization of enterprise and use of information technology. The simulation study showed that total downstream supply chain cost reduces as flow rate of product in the pipeline increases. The total cost increases as batch size of product increases. The findings, thus, can be useful for decision makers at different levels in the petroleum industry. Key words: supply chain management, petroleum, Balanced Scorecard, Analytic Hierarchy Process, Simulation, Data Envelopment Analysis iv

8 Table of Contents Certificate Acknowledgement Abstract Table of contents List of figures List of tables List of abbreviations ii iii xiii xvi xix Chapter Chapter 1: Introduction 1.1 Background Challenges in the supply chain of the petroleum sector Motivation for research The petroleum industry in India: An overview Importance of supply chain management in petroleum industry Performance of a firm General approach to the supply chain performance problem Scope of the study Organization of the thesis 16 Chapter 2: Literature review 2.1 Introduction Defining supply chain management Logistics vs. supply chain management Conventional operations management vs. supply chain management Various perspectives on supply chain management Major issues in supply chain management Strategy formulation Design of logistics 28

9 :hapter Table of Contents Reverse logistics Outsourcing/ partnerships Greening the supply chain Implementing information systems Performance evaluation Research gaps Absence of macro level study of process industry supply chains Lack of identification of unique characteristics of the petroleum supply chain Lack of suitable framework to determine petroleum supply chain performance Quantification of relative importance of BSC perspectives and underlying criteria Absence of a simulation model to study the downstream petroleum supply chain Lack of systematic study to determine effect of flow parameters on downstream supply chain cost Lack of systematic study to determine effect of demand on downstream supply chain cost Contributions of the chapter 2.6 Summary Chapter 3: Research Methodology -3.1 Introduction 3.2 Research challenges 3.3 Objectives of the research 3.4 Methodology for performance evaluation of the supply chain Justification of the methodology Tools used for studying performance of the petroleum supply chain Data envelopment analysis (DEA) Analytic hierarchy process (AHP) Simulation vi

10 Table of Contents Chapter 3.7 Questionnaire design and administration Need for questionnaire Design of questionnaire Sample size Administration of questionnaire Validation of questionnaire Contributions of the chapter Summary 82 Chapter 4: Macro level study using Data Envelopment Analysis 4.1 Introduction Background to Data Envelopment Analysis (DEA) Input and output oriented models Returns to scale Applications of DEA Steps in the application of DEA Characteristics of the proposed DEA model Decision making units (DMUs) Inputs and outputs Constant returns to scale Input minimization or output maximization Data collection and software for analysis Data analysis and insights Case I (Inputs: raw materials, assets; Output: net profit) Case II (Inputs: raw materials, assets, power and fuel; Output: net profit) Contributions of the chapter Summary 101 vii

11 Table of Contents :.:hapter Chapter 5: Characteristics of the petroleum supply chain in India 5.1 Introduction Applying Porter's Model to petroleum supply chain Entry of new competitors Bargaining power of suppliers Threat of substitutes Bargaining power of buyers Industry competition Differentiating characteristics of the petroleum supply chain The petroleum supply chain in India Relevance of the characteristics to India Non-value added activities in the petroleum supply chain Role of information technology in the petroleum supply chain Contributions of the chapter Summary 135 Chapter 6: Measuring petroleum supply chain performance using Balanced Scorecard 6.1 Introduction Importance of performance evaluation in supply chain management Performance of firm vis-à-vis performance of its supply chain Measurement necessary to improve Strategies to be tested Reasons for variance to be understood Challenge of performance evaluation of supply chains Introduction to Balanced Scorecard (BSC) Advantages and shortcomings of using the BSC Select applications of the BSC 145 viii

12 Table of Contents Chapter 6.7 A framework for applying BSC to the petroleum industry Identification of strategic objectives Mapping the objectives to the BSC perspectives Deriving the criteria and identifying measures Applying AHP to determine weights Measurement of BSC criteria Comparison of supply chains Role of innovation and learning Customer in the petroleum supply chain Quantification in the BSC model Methodology Applications of AHP Steps in using the Analytic Hierarchy Process Defining the problem Structuring the hierarchy Pair wise comparisons and matrix preparation Testing for consistency Data analysis and results Validation of criteria Determining the weights Relation of BSC criteria to supply chain cost Customer perspective Financial perspective Internal business perspective Innovation and learning perspective Implementing the model in real life Usefulness of the proposed AHP model Insights into supply chain management Poor performance of petroleum supply chains w.r.t internal business processes 176 ix

13 Table of Contents Chapter Importance of customer perspective Importance of quality Importance of market share Importance of information technology Importance of cost as a performance criterion Contributions of the chapter Summary 180 Chapter 7: Using simulation to determine downstream supply chain performance 7. 1 Introduction Need for tackling operational issues Introduction to simulation The petroleum supply chain Simulation software and its advantages Characteristics of the simulation model Use of simulation in deterministic situations Model variables Uncontrollable variables Decision variables Response variable Logic of the simulation model Procedure for experiments Assumptions of the model Simulation experiments Variation of cost with flow rate (varying batch sizes) Variation of cost with batch size (varying flow rates) Variation of cost with batch size (varying demand rates) 203

14 Table of Contents Chapter Variation of cost with flow rate (varying demand rates) Variation of cost with batch size (varying storage capacity) Variation of cost with flow rate (varying storage capacity) Variation of cost with demand rate (varying storage capacity) Variation of cost with demand rate (varying flow rates) Variation of cost with demand rate (varying batch sizes) Simulation results Variation of cost with flow rate (varying batch sizes) Variation of cost with batch size (varying flow rates) Variation of cost with batch size (varying demand rates) Variation of cost with flow rate (varying demand rates) Variation of cost with batch size (varying storage capacity) Variation of cost with flow rate (varying storage capacity) Variation of cost with demand rate (varying storage capacity) Variation of cost with demand rate (varying flow rates) Variation of cost with demand rate (varying batch sizes) 7.14 Summary of experiments 7.15 Relation of the simulation model with the BSC model 7.16 Insights for supply chain management 7.17 Model validation and verification 7.18 Contributions of the chapter 7.19 Summary Chapter 8: Summary and conclusions 8.1 Summary of work done Identification of suitable research problem Selection of suitable models for research study Data collection for various models Analysis of data Insights into supply chain management 8.2 Contributions of the present research to literature 8.3 Suggestions for improving supply chain performance xi

15 Table of Contents Chapter 8.4 Plugging the gaps identified and deliverables of the research study Integration of the three models Possible extensions of the study Limitations of the study and scope for future work Concluding comments 245 References 248 Appendices Appendix 1: Questionnaire for AHP 283 Appendix 2: Input data for DEA Model 289 Appendix 3: Data for criteria validation 290 Appendix 4: Input data for AHP (pairwise comparisons) 292 Appendix 5: Results for simulation experiments 296 List of publications 305 Bio-data of the researcher 306 xii