Identifying and Prioritizing Supply Chain
Management Strategic Factors Based on
Integrated BSC-AHP Approach
Sina Zare
Master of Science Thesis
KTH
Industrial Engineering and
Identifying and Prioritizing Supply Chain Management
Strategic Factors Based on BSC
-
AHP Approach
By
Sina Zare
Submitted to the Production Engineering and Management Program in Partial
Fulfillment of the Requirements for the Degree of
Master of Science in Engineering and Management
At the
II
Abstract
Nowadays, with regard to the fast-developing market and growing customers’ expectation, firms strive to identify and implement the most efficient and applicable strategies. Companies are not only trying to survive within such competitive market, but also searching for initiatives to underpin competitive advantages. This research endeavors to identify essential strategic factors and prioritize such criteria in order to propose the most significant steps should be taken to develop a Supply Chain (SC) strategy beyond its tradition.
On the basis of literature review and interviews conducted, numerous factors and methods can be considered in order to develop SC strategy. In this survey, the methods studied comprise Key Performance Indicators (KPIs), Balanced Scorecard (BSC), and Analytical Hierarchy Process (AHP). The most significant KPIs were investigated in order to find the most effective success factors in strategic development. Moreover, Balanced Scorecard (BSC) technique was applied to shape a strategic framework in which every KPI is categorized under each of four different BSC’s perspectives. Analytical Hierarchy Process (AHP), as a Multi-criteria Decision Analysis (MCDA) technique, was employed to evaluate the relative importance of various KPIs by pair-wise comparisons. Several brainstorming sessions and interviews have been conducted along with a questionnaire enabling specialists interviewed to participate in pair-wise comparison process in AHP method. The result of this thesis elaborates how strategic management influences supply chain efficiency. The thesis outcomes introduce state-of-the-art supply chain attributes by which SC can be developed beyond the conventional boundaries. The first purpose of this research is investigating the most important key indicators that affect supply chain efficiency. The second goal focuses on BSC application in categorizing KPIs under four particular strategic approaches. The third objective is evaluating the degree of importance of each KPIs investigated and prioritizing these factors based on how they correspond to the weight each obtained.
III
Sammanfattning
I dagens samhälle med den snabba utvecklingen på olika marknader och växande förväntningar från kunder strävar företag efter att identifiera och implementera de mest effektiva och applicerbara strategierna. Företagen försöker inte bara överleva på den konkurrensutsatta marknaden utan söker också efter initiativ som kan stödja dem och ge konkurrensfördelar. Detta forskningsarbete strävar efter att identifiera viktiga strategiska faktorer och fokusera på sådana kriterier som lyfter fram åtgärder vilka bör prioriteras för att utveckla en Supply Chain (SC) strategi ytterligare.
Från litteraturstudier och genomförda intervjuer framgår att många faktorer och metoder kan användas för att utveckla SC strategier. I denna undersökning har följande metoder studerats; Key Performance Indicators (KPI), Balanced Score Card (BSC) och Analytisk Hierarki Process (AHP). Nyckeltalen med störst inverkan undersöktes för att hitta de mest effektiva framgångsfaktorerna för den strategiska utvecklingen. Dessutom har Balanced Score Card teknik tillämpats för att forma ett strategiskt ramverk där varje KPI är kategoriserad under en av fyra olika BSC perspektiv. Analytical Hierarchy Process (AHP) är en multi kriterium beslutsanalys. Multi-Criteri Decision Analysis (MCDA) teknik används för att bedöma den relativa betydelsen av olika nyckeltal genom parvisa jämförelser. Flera brainstormingsmöten och intervjuer har genomförts kompletterat av ett frågeformulär som gör det möjligt för de specialister som intervjuades att delta i en parvis jämförelseprocess i AHP-metoden.
Resultaten i denna avhandling visar hur strategisk ledning påverkar effektiviteten i försörjnings-kedjan. Avhandlingen presenterar state-of-the-art för försörjningskedjans attribut. Genom dessa kan SC utvecklas utanför de konventionella gränserna. Det första syftet med detta forskningsarbete är att undersöka hur de viktigaste nyckeltalen påverkar effektiviteten i försörjningskedjan. Det andra målet är inriktat på BSC tillämpning för att kategorisera nyckeltalen inom fyra specifika strategier. Det tredje målet är att utvärdera vikten av varje nyckeltal som undersökts och prioritera dessa faktorer efter motsvarande viktning de erhållit.
ACKNOWLEDGEMENTS
Foremost, I would like to convey my appreciation to those whose contribution made this paper possible. I am particularly grateful for the assistance of my supervisor, Dr. Ove Bayard, for his support, encouragement, and guidance in various ways from the very early stages of this research.
In addition, my sincere thanks also go to Dr. Jerzy Mikler for his encouragement, insightful comments and kind supports.
Finally, the support and encouragement of my family and friends has been (as always) invaluable during the process of writing this paper.
Thank you all!
List of Figures
Figure 1 Supply chain decision categories mapped to the SCOR-model Version 9 (source: Supply Chain
Council, 2009) ... 7
Figure 2 Overall Research Process ... 8
Figure 3 Different Data Collection Methods (Durrance, 2005) ... 10
Figure 4 Experimental Design and Evaluation Process ... 20
Figure 5 Balanced Scorecard framework (Kaplan & Norton, 1996) ... 21
Figure 6 Network optimization applying BSC-AHP technique... 27
Figure 7 Different Supply Chain Strategies ... 34
Figure 8 A Hierarchy Structure- Network Optimization Based on AHP-BSC Metric Introducing Alternatives Level ... 36
Figure 9 Pair-Wise Comparison Matrix based on a Numerical Judgment Scaling System ... 37
Figure 10 Pair-Wise Comparison Matrix based on a Verbal Judgment Scaling System ... 38
Figure 11 Pair-Wise Comparison Matrix based on a Graphical Judgment Scaling System ... 38
Figure 12 Final Results derived by Expert Choice Software ... 40
VIII
List of Tables
Table 1 Terminology ... 4
Table 2 Information regarding the interviewees’ profile and their contribution ... 13
Table 3 List of KPIs and the Corresponding BSC Perspectives ... 16
Table 4 Scale of Relative Importance (Saaty, 1980) ... 24
Table 5 Random Index (Saaty, 1977) ... 25
Table 6 Relative importance, normalized weights, and consistency ration for each element in sub-criteria level... 28
Table 7 Weights and consistency ratio at the BSC perspectives (criteria) level ... 29
Table 8 Local and global weights of each performance indicator ... 30
VIII
Glossary
BSC Balanced Scorecard
AHP Analytical Hierarchy Process KPIs Key performance Indicators SCOR Supply Chain Operations Reference
SC Supply Chain
SCM Supply Chain Management
SCS Supply Chain Strategy
Legile An integrated approach combines Lean and Agile concepts
FMCG Fast Moving Consumer Goods
ROI Return on Investment
FMCG Fast Moving Consumer Goods
Table of Contents
Abstract ... II
Sammanfattning ... IV
ACKNOWLEDGEMENTS ... VI
1 Introduction ... 1
1. 1 Background ... 1
1.2 Problem Statement ... 2
1.3 Research Purpose ... 2
1.4 Delimitations ... 3
2 Related Works and Literature Review ... 4
2.1 Definitions ... 4
2.2 Strategic Supply Chain Management ... 5
2.3 Supply Chain Flexibility ... 6
2.4 Supply Chain Operations Reference ... 6
2.5 Balanced Scorecard (BSC) ... 7
3 Research Methodology ... 8
3.1 Research Plan... 8
3.2 Data Collection Process ... 8
3.2.1 Data Collection Methods ... 9
Preliminary Studies ... 10
Focus Group ... 10
3.2 Literature Review Steps ... 11
3.3 Preliminary Studies and Analysis ... 11
3.4 Interview ... 12
3.4.1 Interviewees’ Profile ... 12
3.4.2 Interview Questions ... 14
3.5 Focus Group ... 14
3.6 KPIs Derived from Data Collection Process ... 15
3.7 Validity and reliability ... 17
3.7.1 Validity ... 17
3.7.2 Reliability ... 17
3.8 Limitations ... 18
4 Experimental Design and Evaluations Process ... 19
4.1 Experimental Design and Different Phases of Evaluation Process ... 19
4.1 The Balanced Scorecard (BSC) ... 21
4.2 Analytical Hierarchy Process (AHP) ... 22
4.3 Implementation ... 26
4.3.1 AHP Structure Design ... 26
Strategic Supply Chain Management ... 27
4.3.2 Result of KPIs Prioritizing Process ... 30
5 Application of BSC-AHP in Supply Chain Strategic Management ... 33
5.3 BSC-AHP Modeling via Expert Choice ... 35
5.3.1 Problem Modeling ... 35
5.3.2 Pair-wise Comparison ... 37
5.3.3 Different Judgment Scales ... 37
5.4 Results ... 38
6 Conclusion and Further Research ... 41
6.1 Conclusion and Managerial Interpretation ... 41
6.2 Further Research ... 43
References ... 44
Appendices ... 48
Appendix A-First Likert Scale Questionnaire ... 48
Appendix B-Second Likert Scale Questionnaire ... 49
Appendix D-AHP Pair wise Comparison ... 51
Pair wise Comparison 1 - BSC Perspectives ... 52
1 Introduction
This chapter tries to provide the readers with a generic perspective toward this dissertation. The first subdivision comprises background, and the problem statement which will be followed by the research purpose, and finally the chapter ends up with dissertation’s delimitations and limitations.
1. 1 Background
Nowadays, different organizations are considering success factors which help them to develop their strategic and competitive advantages against their competitors. Since supply chain refers to internal and external organizational processes, it internally addresses the inbound process and interaction among different sections of an organization as well as externally reflecting the organization’s image. Therefore, Supply Chain (SC) plays a critical role in an organization’s strategic development, and brings competitive advantages for an organization.
Consequently, the majority of organizations strive to achieve a comprehensive perception towards effective metrics in SC performance evaluation which enables such enterprises to develop integrated strategy in Supply Chain Management. However, these firms usually are facing numerous obstacles to develop such integrated approaches due to an absence of a balanced performance measurement method and an explicit concept to distinguish metrics in accordance with strategic, operational, and tactical levels (Gunasekaran, Patel, & Tirtiroglu, 2001; Hudson, Lean, & Smart, 2001).
1.2 Problem Statement
Supply Chain Management (SCM) i s comprised of different consecutive activities such as procurement, production and manufacturing, logistics, and distribution of products to retailers or middle/end customers (Farahani, Asgari, & Davarzani, 2009). Since years ago, enterprises are focusing on SCM and its strategic advantages (Stadler 2008).
Performance measures are categorized into two divisions consisting of quantitative and qualitative measures through which responsiveness, performance, flexibility, cost, availability and other criteria in SC design are discussed (Beamon, 1998). When a system performance is analyzed, qualitative evaluations such as “good”, “best”, “sufficient”, “perfect” are ambiguous and cannot be explicitly utilized in a tangible way. Therefore, qualitative performance measures are less preferred than quantitative methods (Beamon, 1999). On the other hand, numerous papers address the SC concept, but very little speak about strategic means that can help a firm to boost its SC performance aligned with overall strategy. Therefore, any attempts to enhance measurement techniques in SC performance play a crucial role in developing SC integration (Gunasekaran et al. 2001). They also increase interaction and cooperation among different section of SC (Chan et al. 2003).
Besides improving SC performance and strategic advantages, SC performance measurement can be implemented to achieve other competitive advantages and improvements such as aiming at market share development, cost reduction, and service quality improvement (Lambert and Pohlen 2001).
1.3 Research Purpose
In this research t h e author strives to elaborate an important contribution that SC has in an organization’s success. Secondly, integrated BSC-AHP approach is introduced as a strategic evaluation model to appraise the most important KPIs in order to systematically develop SCM performance. A case study is conducted to demonstrate utilization of integrated BSC-AHP model in real world experience.
1.4 Delimitations
This study is conducted with a broad range of limitations, thus the research process is considerably more significant than only relying on the mere outcomes. The judgment process is carried out with the help of many experts and managers from both industries and academia.
In pair-wise evaluation and KPIs ranking process, the qualitative measures cause a very minor inconsistency that is modified with a slight change in comparison matrix elements within the allowance span.
2 Related Works and Literature Review
This chapter includes the studied scientific literatures and describes corresponding endeavors that have been conducted to date. The first subsection covers the most essential terminology used within this field of research. This subsection will be followed by indicating respective industries in which the studied results would be effectively applied. The third subdivision emphasizes the three different functions of the supply chain. Finally, this chapter ends with an integrated framework of BSC-AHP which features both parties’ attributes.
2.1 Definitions
In order to convey an explicit concept of overall thesis work for the readers, it is essential to provide a sound definition of the most used terminologies related to the research subject. The key concepts used in the present research are indicated below. (Table 1)
Table 1 Terminology
Concept Definition
Strategic Management Refers to a comprehensive managerial concept covers a vast field includes economics, sociology, marketing and management. (Nag, Hambrick, & Chen, 2007)
Strategic supply Chain
Management Stands for a type of supply chain management which takes strategic decisions throughout the chain which are aligned with the firm strategy. Key performance
Indicators
Represents the most significant factors influencing a corporation’s performance level.
Analytical Hierarchy
Process A method for organizing and prioritizing complicated decision factors through mathematical and psychological techniques.
Balanced Scorecard “The balanced scorecard is a strategic planning and management system that is used extensively in business and industry, government, and nonprofit organizations worldwide to align business activities to the vision and strategy of the organization, improve internal and external communications, and monitor organization performance against strategic goals.” (Retrieved February 4, 2013 from www.balancedscorecard.org)
BSC-AHP An integrated method which takes advantage of the strategic approach of BSC to develop KPIs based on a standard platform, and AHP as a tangible and analytical means for prioritizing critical strategic factors.
Third Party logistics (3PL) A firm that provides its client with multiple value-added solutions in
2.2 Strategic Supply Chain Management
Supply Chain Management (SCM) encompasses numerous strategic decisions taken towards satisfying customers’ needs along with meeting shareholders’ expectations considering conventional tradeoff between cost and profit. Mallen’s (1963) organizational extension theory inspired a novel concept in firms’ management which is called SCM.
Mallen’s philosophy with a consideration o f marketing concepts was subsequently extended to comprise different levels of distribution channels which closely resembles Porter’s Value System (Porter, 2008; Green Jr, McGaughey, & Casey, 2006). Many scholars believe that supply chain enhances customer satisfaction and provide clients with a better service aiming for being aligned with marketing strategy (Lummus and Vokurka, 1999; Wisner, 2003). Morash and Clinton (1997) explain supply chain as: “the organizational efforts by three or more firms to manage and integrate material and related information flows in order to get closer to customers.”
There is a consensus among different scholars emphasizing the fact that a well-developed strategy for supply chain, which offers it as a competitive advantage, is indebted to management’s competence to identify and utilize supply chain flexibility in accordance with an ever changing environment, and in order to effectively allocate resources towards customers’ satisfaction (Stonebraker and Afifi, 2004). In other word, strategic supply chain management enables firms to properly respond to environmental changes and react with respect to external demand (Thompson, 1967).
2.3 Supply Chain Flexibility
With regard to SC responsiveness as a very crucial factor enables a firm to effectively respond to the external demand in ever-changing environment, SC flexibility draws attention among strategic managers. Therefore, SC flexibility enables companies to effectively deal with environmental uncertainty and increase business performance. As a respond to increasing diversity and uncertainty within both external and internal environment, SC flexibility can be developed to improve a firm’s operational strategy (Jayant & Ghagra, 2013).
Although all the SC members, at any level, contribute to improve SC flexibility and enhance SC adaptability to effectively respond to environmental changes, Calantone & Dröge (1999) believes “excellent performers on supply chain flexibility are rewarded at the bottomline.” On the other hand, the authors also emphasize financial and market performance indebted to performance in “volume”, “launch”, and “target market flexibility” as other criteria in comprehensive definition of SCM.
Thus far, numerous studies concern intra-firm flexibility and studied interior changes within an enterprise enhance flexibility in SC, while Duclos, Vokurka, & Lummus (2003) believe SC flexibility is not restricted within a firm’s environment and cross-functional nature of SC flexibility should be developed beyond a firm’s boundaries and improve it across the firm engaged throughout the SC.
In recent years, competitive environment increases complexity of process within SC along with uncertainty degree in strategic level. Today’s uncertain environment obliges firms to get prepared for encountering any eventuality (Singh & Acharya, 2013). Therefore, a prosperous SC strategy should encompass a broader SC flexibility framework which covers more unpredicted scenarios happened in both internal and external environment.
2.4 Supply Chain Operations Reference
Supply Chain Operations Reference (SCOR) model has been developed in 1996 by the Supply Chain Council (SCC). The aim of this model is analyzing for dimensions: flexibility/ responsiveness, business performance reliability, supply chain cost and turnover of invested capital. This model known as a means of strategic planning enables managers to decrease the complexity of SCM (Huan, Sheoran, & Wang, 2004).
level in order to enables a company to develop its strategic planning. The authors also state calculation models of SCOR define indicators corresponding to each process.
Figure 1 Supply chain decision categories mapped to the SCOR-model Version 9 (source: Supply Chain Council, 2009)
2.5 Balanced Scorecard (BSC)
One of the most applicable strategic methods to evaluate an organization performance aligned with generic vision of that organization through both financial and non-financial metrics is known as Balanced Scorecard which is developed by (Kaplan and Norton, 1992). Although this method initially was developed to evaluate and assess an organization’s performance
,
after being developed in terms of pragmatic application, BSC has been considered as a strategic framework aligned with the organization’s vision (Kaplan & Norton, 1996)Figure 2 Overall Research Process
3 Research Methodology
This chapter provides readers with a theoretical analysis of the methodologies and principles applied to extract analytical raw data. This section, as well, comprises a description of research procedures, data collection methods, and is concluded with the study’s limitation arose during the empirical process.
3.1 Research Plan
Nearly, every academic research is supposed to encompass a research plan which concisely describe project progress trend, simultaneously, provide readers with theoretical patter, quantitative, and qualitative methods of research project.
The figure below explicitly illustrates a breakdown structure of the process conducted align with research objectives.
Initial Research Idea Related work & Literature Review Data Collection Experimental Design & Evaluation Data
Analysis Discussion Conclusion
Presentation & report Submission
3.2 Data Collection Process
Data collection is a crucial process in any type of research. Any failure in this process can end up with invalid results. There are numbers of reasons resulting in unreliable data which should be taken into account during data collection process. Depending on the method conducted, the aiming results might be inclined towards the wrong results. Therefore, the biased data ought to be omitted prior to embark on the analysis process.
way of conducting a survey. In this project, Data collected provides executives with raw data that should be processed in order to obtain an explicit perspective towards current organizational conditions, whilst it could address a trend of organizational progress towards the future situation.
Since there are numbers of different ways and methods in data collection process, this research project strives to take advantage of relative and effective methods so that all gathered data address directly the issues studied. However, no one can assert that all data collection process used should be regarded as a fully qualified method that is failure free. With regard to the context of an academic research, data collection is a quantifiable method that is applied to measure studied factors. There is no rigid rule to highlight the stepby -step process of data collection. Therefore, a number of questions w e r e raised to address the steps that should be taken towards an applicable and reliable data collection process: 1. What sort of data should be collected?
2. When/where data collection process should be conducted? 3. What is the number of sample size?
4. What kind of operational function can be implied through data gathered?
Finally, the above-mentioned questions provide experts with a guideline in order to propose a practical/reliable data collection process which is developed aligned with the project approach. Resulted data, from execution of data collection process, might need to be standardized through some kind of analytical processes. For instance, in order to have a standardized data set we can apply data sorting process, data ranking, eliminating inconsistent data, trend evaluation, etc.
3.2.1 Data Collection Methods
In this project different types of data collection methods have been employed, and the captured results are modified in accordance to the scope of research. First of all, the author strives to acquire a clear perspective of t h e main concept based u p o n which the thesis work is developed. Therefore, the most conventional issues, as well as state of the art concepts, regarding this particular subject are studied at the stage of defining thesis work structure.
• Strength: 1. Convenient form of responding the questions for participants. 2. Personal contact might help interviewer to modify questions as the interview progresses. 3. Very effective way to capture real attitude, idea, or opinion of interviewees.
•Weakness: 1. Every interview session needs its own particular arrangement which differ one from another. 2. Takes employees' time and needs some special equipment to document responses.
• Strength: 1. Easy for individual participant to arrange their time and place to respond to the survey questions. 2. Can be conducted through computer-based methods (internet, email, mobile applications, etc.), or from filling out a paper version. 3. Includes both open-ended and close-ended questions. •Weakness: 1. The participants’ responses are limited to the provided questions. 2. High probability of misunderstanding the questions or wrong implication from the answers. 3. Participants' reluctance in reading questions or writing answers. 4. Survey is not considered as a preliminary means of data collection.
•Strength: 1. It doesn't require writing or reading literacy. 2. The responses are more reliable since they are extracted from a group consensus. 3. It can be used to consider the criteria studied in more detail. •Weakness: 1. Requires a preliminary arrangement to gather participants in a group. 2. Needs facilities,
equipment, as well as a task instruction for each of the individual participant. 3. It takes employees' time and needs a rigid schedule to form a focus group.
Figure 3 Different Data Collection Methods (Durrance, 2005)
Each of the mentioned methods is evaluated and performed with a deep consideration towards its particular strength and weakness.
Preliminary Studies
•Strength: 1. No time and place restriction to conduct the study. 2. Can be done through both digital (online) or conventional documents and sources. 3. Covers a generic concept of topic studied.
•Weakness: 1. Since it is one of the most initial steps in data collection, it might not emphasize the exact issue that is being studied.2. This methods waists time due to the consideration of irrelevant information to the main scope of research.
Interviews
Survey
3.2 Literature Review Steps
Fundamental understanding about the following concepts: Strategic Management
Supply Chain and Logistics Management
Balanced Scorecard as a Strategic Decision Maker tool
Analytical Hierarchy Process as a method for classifying and prioritizing alternatives
Key Performance Indicator as a tool for identifying critical factors that aim to improve conventional processes
Gaining a generic interpretation towards the studied industries.
Two different industries have been studied in this research in order to facilitate the analysis process and gain more reliable results. The studied industries include Oil/Gas, and Fast Moving Consuming Goods (FMCG). These industries are in some manner linked to each other, but sometimes their expectations from logistics process differ.
Earning a generic understanding of three main supply chain functions. Strategic level
Tactical Level Operational Level
Studying about the functional benefits yielded from BSC-AHP integration.
3.3 Preliminary Studies and Analysis
For the first step, indicating the most substantial Key Performance Indicators (KPIs) seemed to be a challenging process, especially when we are merging different concepts to come up with a logical consensus. In this regard, an elaborative interview was conducted with participants selected from a group of proficient SC managers who have years of experience within particular businesses studied. In addition, the suggested KPIs were defined and proposed in accordance with Balanced Scorecard (BSC) perspectives. In some cases, an expert recommended very significant KPIs which could not be categorized under individual BSC perspectives. Therefore, neglecting such KPIs was regarded as the best decision to prevent excessive complexity in the Analytical Hierarchy Process (AHP) model. The most crucial KPIs are identified and categorized through interviews carried out in individual BSC perspective with regard to the role that each of such KPIs plays in strategic development of the corporation.
3.4 Interview
At any stage of a survey, interviews are considered as one of the most applicable methods through which an observer can directly be addressed to the main context studied. Moreover, any observation in an organization needs an appropriate interaction between observer and different sections/key people of that organization, and such interaction could be shaped during the interview process.
In order to develop a comprehensive and adaptive BSC model, numbers of interviews have been carried out in collaboration with SC managers in different levels. All the studied KPIs are extracted from interviews carried out, and later on pair- wise comparison has been performed by those managers as well.
3.4.1 Interviewees’ Profile
In the interview process, the author strives to interview several SC experts and managers who are making crucial decisions aligned with organization strategy. Different sessions of interviews enable the author to develop and modify BSC model as well as the methodology applied in this survey.
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Table 2 Information regarding the interviewees’ profile and their contribution
Number of
Participants Questionnaire Ref. # Participants’ Job Title Interview Objective
3 Financial (1001) SC Cost Analyzer Evaluating Financial Perspective, Revenue Growth, etc.
3 Financial (1001) Operations
Management Productivity Improvement, Cost Reduction, Lean SC, etc.
1 Financial (1001) Asset Manager Asset Utilization and Investment Strategy, etc.
3 Customer (1002) CRM Experts Customers’ Satisfaction, Retention, and Acquisition Metrics, etc.
2 Customer (1002) Marketing Managers Market Share Analysis, Market Expansion Strategy, Service, Availability, etc.
3 Customer (1002) Brand Manager Brand Reputation, Partnership, Service, Availability, Price, etc.
2 Internal Business
(1003) Change and Innovation Management Launch New Products/Services, Opportunity Indicators, R&D Portfolio, Design New Product/Service and Product/Service Development, etc.
3* Internal Business (1003) Operations
Management Procurement, Supply, Production process, Distribution Networks, Risk Management, etc.
2 Internal Business (1003) Customer relationship Manager
Target Market, Customer Acquisition, Retention, and Growth, After Sale Service, etc.
2 Internal Business (1003) HR Manger Environment Adaptability, Safety and Health, Employees’ Satisfaction, etc.
2* Learning and Growth
(1004) HR Manger Employees’ Capabilities; Satisfaction, Retention, Productivity, Workshop, Learning Team Work and
Interpersonal Skills, etc.
2 Learning and Growth
(1004) CEO and VP Organizational Objectives, Culture, Leadership, Alignment, Motivation, Empowerment, etc.
4 Learning and Growth (1004)
* Asterisks draw your attention to the fact that the experts responding to interview questions are the same people who participated in the preceding interview sessions corresponding to the
participants’ job title.
IT Administrator Information System Capabilities; Employees’ Computer Skills, Digital Internal Communication, Embedded IT System throughout SC Network from Suppliers to end customers and Vice Versa, Reverse Supply Chain Capabilities, Digital Customer
3.4.2 Interview Questions
Interview questions are modified based on the interviewee’s field of expertise, and each participant is assigned to respond to the corresponding perspective of BSC which is roughly related to the department where s/he is assigned. For instance, CRM experts are invited to answer questionnaire 1002, which discusses specific KPIs corresponding to customer perspectives of BSC, such as customer satisfaction, retention, acquisition, etc.
Demographic and general questions at the beginning of the interview template are identically defined for every participant regardless o f his/her field of expertise, while questions regarding technical aspects of the research involve participants’ attitudes towards each specific metric questioned.
Accordingly, in this survey four different interview structures are designed, and each expert is provided with the respective questions. In order to make a robust interview, all the interviewees are explicitly briefed about the main objective of the interview, core concepts of BSC and AHP methods, and the competitive advantages of using the integrated model of BSC- AHP. This enables both interviewer and interviewee to be frankly streamlined towards an efficient discussion instead of merely answering pre-designed questions.
3.5 Focus Group
Firstly, a focus group enables researchers to be in contact with participants who are experts in that particular subject and can directly address the main issues. This makes data collection a less time consuming process that is easier than carrying out an individual interview. Secondly, a focus group meeting provides the author with a unique opportunity to investigate and explicitly convey the participants’ attitudes towards the matter under discussion (Edmunds, 1999).
Thirdly, interactive discussion makes participants more enthusiastic to share their logical comments, rational judgment, and critical thought with other participants under the researcher’s observation.
3.6 KPIs Derived from Data Collection Process
As it is mentioned in the preceding chapters of this report, by conducting a literature review, a technical interview, and a focus group meeting with different experts within such particular businesses, t h e author aims to briefly acquire and categorize the most efficient and applicable KPIs affecting supply chain strategic objectives.
Financial Perspective Internal Business Process Perspective Rank 1 KPI Revenue Encompassed Revenue Growth and mix,
Rank 1
KPI Operations
Encompassed On-time delivery, Lead time Growth Productivity improvement,
Expand revenue opportunity, etc.
Optimization deduction, sustainability, process improvement,
2 Assets Utilization
Investment strategy, Facilities cost management, Procurement strategy, regular stock takes of capital assets, etc.
2 Customer Orientation
Delivery performance, packaging initiatives, product quality, reaction in time, complaints handling, etc.
3 Cost
Reduction
Improve cost structure, Cost per operation hour,
Information carrying cost, etc.
3 Innovation Process
Product/service
development, short product time to market, innovative solutions for process smoothness, etc.
Customer Perspective Innovation (Learning & Growth) Perspective
Rank KPI Encompassed Rank KPI Encompassed
1 Customer satisfaction
Customer rating, CRM initiatives, Satisfied customer rate, Number of customer complaints, customer retention rate, etc.
1 IT Capabilities Using internal
management software (e.g. SAP), intranet networking platform, electronic ordering, warehousing, tracking system, etc. 2 Functionality Customer per employee,
facilitating return process, customer query time, Facile order making process, etc.
2 Employee Capabilities
Communication skills, Interpersonal skills, training and development, thinking and innovation, Problem solving/analytical skills, etc.
3 Availability Market share, Online selling system, Online CRM system, number of shopping store (selling and returning), etc.
3 Organizational Culture
Team work culture, customer oriented culture, international and
3.7 Validity and reliability
3.7.1 Validity
As an observer, one should be assured whether the observation method and data collection process conducted are genuinely measuring what s/he exactly needs to measure. The results from observation and other data collection methods have to be valid in order to come up with robust conclusions after passing through all of the project steps. As Segers (1983) asserts:
“The notion of validity implies that the research data have such a character
that one can move legitimately from the level of the empirical variables to the level of theoretical concepts.”
In order to enhance the validity degree of data collected, the author proposed different alternatives to cope with this crucial requirement. Considering the fact that reaching absolute validity is impossible, the following validation studies have been applied to maximize the validity degree of research.
1. Expert Validity:
Dealing with complicated issues in scientific observations obliges an observer to take advantage of the professionals’ input towards the concept studied. In this research project, the author reached an interdisciplinary consensus through carrying out interactive interviews and focus group meetings with collaboration of academic and industrial experts. 2. Content Validity:
We asked expert interviewers to design and develop the questionnaires based on the performance domain. This helps us to have more content related measures which enhance our study’s content validity.
3.7.2 Reliability
Reliability refers to the degree of accuracy of data collected which is claimed by the researcher. In human science, reliability means an observation without systematic bias. The reliability of an observation method (e.g. questionnaire) can be interpreted as obtaining the same results through repeated observations at close intervals.
3.8 Limitations
Two of the most significant limitations in the data collection process through interviews are the participants’ attitudes and the researcher’s intentions. While the majority of participants were selected from a group of experts from the companies being observed, this limitation made the observation process more complicated. In order to prevent any kind of biased judgment, the observer decided to keep questionnaires anonymous and addressed the issues to the strategic point of view, instead of categorizing them in correlation with different departments that participants came from.
4 Experimental Design and Evaluations Process
In this chapter, firstly, the readers are provided with a sound and comprehensive definition of BSC, AHP, and t h e integrated BSC-AHP model. Secondly, t h e BSC-AHP structure is designed, and a paire-wise comparison of KPIs selected in the previous chapter will be conducted. Finally, KPIs local and global weights are calculated, and consequently, all the KPIs studied are ranked through AHP method. This model is used as a fundamental model that is going to be applied for an alternative prioritization process in the next chapter.
4.1 Experimental Design and Different Phases of Evaluation Process
This section elaborates different phases of the research, and tries to provide readers with a sound definition of concepts used and the procedures that resulted in prioritizing KPIs studied.
In the first phase, the initial BSC-AHP model is structured based on the interviews and group meetings conducted, based on preliminary studies and literature reviews.
The second phase emphasizes the validity test of the initial BSC-AHP model with the cooperation of industry experts and managers. A finalized format of t h e BSC-AHP model is developed throughout this phase, and the final model is proposed.
4.1 The Balanced Scorecard (BSC)
In this research BSC is employed to tangibly address strategic indicators which are aligned with the overall organization vision. At the beginning of this process, an explicit definition of an organization’s mission is required in order to understand core values of an organization and its overall vision. The importance of an organization’s vision should not be neglected since Kaplan and Norton (2001, p. 19) believe that the vision “creates a clear picture of the company’s overall goal” and “the strategy identifies the path intended to reach that destination.”
Figure 5 Balanced Scorecard framework (Kaplan & Norton, 1996)
As it is illustrated in Figure 5, the strategic objectives framework presented by BSC is categorized into four perspectives:
either developed by reducing an organization’s expenses, or efficiently utilizing its assets
(Kaplan & Norton, 2001).
2. Customer Perspective: Many strategic factors positively affect Customers’ satisfaction and meet customers’ expectations. Kaplan & Norton ( 2001, p. 19) believe customers’ perspectives play a crucial role to link customers with the internal process in order to improve results.
3. Internal Business Perspective: This perspective enables an organization to adopt effective processes internally to attain differentiated value proposition and enhance productivity, which should be aligned with financial perspective (Kaplan & Norton, 2001). 4. Learning and Growth Perspective: A strategy cannot be developed without considering innovative solutions and learning new concepts. Information technology competencies along with human resource competencies and organizational culture are employed to develop the strategy. This perspective helps an organization to “align its human resources and information technology with the strategic requirements from its critical internal business processes, differentiated value proposition, and customer relationships” (Kaplan & Norton, 2001, p. 20).
Though numerous companies are taking advantage of beneficial concepts that BSC provides for their strategy and business, there is some criticism related to the concepts developed by BSC method which tends to focus on more general affairs. Moreover, due to such attributes managers are faced with difficulties to adapt this concept in their organization culture (Butler, Letza, & Neale, 1997). In addition, t h e BSC quantitative based measurement system cannot explicitly depict various aspects of an organization strategy (Vaivio, 1999).
4.2 Analytical Hierarchy Process (AHP)
Among numerous advantages achieved through AHP implementation, Abdul-Hamid, Kochhar, & Khan (1999) listed some of such advantages as follows:
The decision-making process resulted in accurate findings due to illustrating criteria studied into hierarchical structure.
Consistency of potential decisions can be mathematically evaluated.
The problem can be explicitly defined through dividing into sub-categories.
Comparison analysis can be conducted by a team consisting of experts who are familiar with the problem and potential solutions. The team members reach a consensus on the solutions available.
Prior to making a final decision, sensitivity analysis can be conducted by computers through the results achieved.
This method is mostly applied where the defined problem can be structured in a hierarchical way and divided into different sub-criteria (Saaty & Vargas, 2006). AHP conducts a pair-wise comparison of the importance of each alternative in terms of sub- criteria in BSC structure. Pair-wise comparison requires a scaling system to indicate the importance of one parameter over another to address the prioritization assessment. Table 3 illustrates a scale of relative importance in BSC technique.
The AHP method is constructed on three main principles: 1. Making a structure of the problem studied.
2. Conducting a comparison based judgment of the sub-criteria and alternatives. 3. Synthesizing the priorities.
3
Table 4 Scale of Relative Importance (Saaty, 1980)
Intensity of relative
importance Definition Explanation
1 Equal importance
Two activities contribute equally to the objective
Moderate importance of one over
another Experience and judgment slightly favor one
activity over another
5 Essential or strong importance Experience and judgment strongly favor one
activity over another
7 Demonstrated importance An activity is strongly favored and its
dominance is demonstrated in practice
Extreme importance
9 The evidence favoring one activity over
another is of the highest possible order of affirmation
2,4,6,8 Intermediate values between the two When compromise is needed
adjacent judgment
Reciprocals of above non-zero numbers
If an activity has one of the above numbers compared with a second activity, then the second activity has the reciprocal value when compared to the first activity.
Assuming that C = {Cj | j = 1, 2, . . . , n} presenting the set of criteria studied. The pair-wise
comparison results on n criteria is concluded in an (n x n) square and reciprocal matrix A. In this matrix every aij (i, j = 1, 2, 3, ..., n) element refers to the weight allocated to that
particular criterion. (Equation 1)
A
The relative weight of each criterion is calculated through normalizing the respective matrix. Equation (2) formulating an eigenvector problem in which relative weights are calculated by eigenvector (W) with respect to the maximal eigenvalue (λmax) as shown below:
Aw = λmax .w (2)
The pair-wise comparison is completely consistent if the matrix A does have rank 1 and eigenvalue equals to n. In order to acquire all element weight, all the rows and columns of matrix A should be normalized (Albayrak & Erensal, 2004).
Definitely, the reliability of results obtained from AHP technique directly depends upon the consistency ratio of the pair-wise comparison. In case a slight inconsistency occurred, with regard to the perturbation theory (Saaty, 2003), the weight allocated to the set o f elements may slightly change. Saaty (1997), according to the eigenvalue method, suggested consistency index (CI):
(3)
λmax
=
maximal eigenvalueThe consistency ratio is defined as the proportional relation of CI and RI formulated below:
(4)
RI: the random index
The maximum number for CR is 0.1 which means that if the overall consistency ratio exceeds this limit, the evaluation process has to be modified or repeated so that the CR represents a value equal to 0.1 or lower.
Table 5 Random Index (Saaty, 1977)
n 1 2 3 4 5 6 7 8 9 10
preceding criteria so that we obtain global priority. Global priority for each alternative solution can be calculated through the equation below:
G
i=
Ʃ
jw
j. L
ij (5)Gi : Global priority corresponding to the alternative solution i Lij : Local priority
wj : Weigh of criterion j
4.3 Implementation
4.3.1 AHP Structure Design
The selected KPIs from chapter 3 should be categorized in AHP hierarchical structure as appears in Figure 6. After reaching a consensus regarding the most important KPIs, this is the second step in BSC-AHP method in order to explicitly organize KPIs under their corresponding BSC perspectives. T h e BSC-AHP structure consists of four distinguished levels from Level1 - Overall Objective at the top to Level 4 - Decision Alternatives at the lowest level. The complete name of each KPI illustrated in t h e BSC_AHP structure is abbreviated in order to prevent any messiness and complication.
Figure 6 Network optimization applying BSC-AHP technique
Level I:
Overall Objective
Strategic Supply Chain
Management
Level II: Criteria Level III: Sub-Criteria Financial Perspective F1 F2 F3 Customer satisfaction C1 C2 C3 Internal Business Perspective P1 P2 P3Learning & Growth Perspective
I1 I2 I3
Level IV: Decision Alternatives
Alternative 1 Alternative 2 Alternative 3
-F1: Assets Utilization. F2: Revenue Growth. F3: Cost Reduction. C1: Customer Satisfaction. C2: Availability. C3: Functionality.
P1: Operations Optimization. P2: Innovation process. P3: Customer Orientation.
I1: Employee Capabilities. I2: Organizational Culture. I3: Information Technology (IT) Capabilities.
In step four, the local normalized weights are calculated for each KPI. The resulting matrix of performance indicators and normalized weight of each KPI are illustrated in Table 6. As it is mentioned in the preceding chapter, approved value for consistency ratio (CR) for each matrix should not exceed limitation of .01. Therefore, all the matrices shown below are approved and validated in terms of consistency ratio.
Table 6 Relative importance, normalized weights, and consistency ration for each element in sub-criteria level
Financial F1 F2 F3 W Process P1 P2 P3 W F1 1 1/2 4 0.333 P1 1 4 2 0.558 F2 2 1 5 0.570 P2 1/4 1 1/3 0.122 F3 1/4 1/5 1 0.097 P3 1/2 3 1 0.320 CR 0.02 CR 0.02 Customer C1 C2 C3 W Innovation I1 I2 I3 W C1 1 5 3 0.637 I1 1 2 1/2 0.297 C2 1/5 1 1/3 0.105 I2 1/2 1 1/3 0.163 C3 CR 1/3 0.04 3 1 0.258 I3 CR 2 0.01 3 1 0.540
organization’s strategies. For the internal business perspective, indicator P1 (Operations Optimization) ranks as approximately 4.57 times more important than indicator P2 (Innovation process). With regard to the discussion held with operations managers, all three acknowledge that currently the main aim of their department is focusing on the current operations and their continuous improvement instead of putting a lot of effort into defining innovative and novel processes. Finally, for the last perspective (learning & growth perspective) indicator I3 (Information Technology (IT) Capabilities) ranks almost 3 times as important as indicator I2 (Organizational Culture). This confirms the IT experts’ assertion of requiring urgent development in IT capabilities. In other words, due to worldwide financial crisis, the organization was mostly investing on human capital during the last 8 years; therefore, any improvement in the organization’s IT capabilities is highly recommended.
In step 5, all experts requested to indicate the relative weights of each BSC perspective versus each of the others applying a 9-point scale of importance method (Saaty, 1980). Step 6 addresses the process that has to be conducted in order to calculate each BSC perspective normalized weight as it is elaborated in step 4. In step 7, the consistency ratio is being considered to find out whether the pair-wise comparison needs to be repeated in order to reduce inconsistencies or not. Table 7 demonstrates pair-wise comparison with the relative weights that have been calculated for each BSC perspective.
Table 7 Weights and consistency ratio at the BSC perspectives (criteria) level
Perspective Finance Customer Process Innovation W
Finance 1 2 3 5 0.449
Customer 1/2 1 4 6 0.356
Process 1/3 1/4 1 3 0.134
Innovation 1/5 1/6 1/3 1 0.061
The last step in this process is calculating the global weight of each indicator which is contributing to the final objective. The Global weight of each indicator is the result of the multiplication of performance indicator local weight by the local weight of corresponding BSC perspective. All the performance indicators’ local and global weights are shown in Table 8. For instance, the global weight of indicator F1 is calculated below:
Global weight of F1 = weight of finance perspective X local weight of indicator F1 Global weight of indicator F1 = 0.449 X 0.333 = 0.15
Table 8 Local and global weights of each performance indicator
Perspective Indicator Weight Perspective Indicator Weight Finance Local Global Process Local Global
Weight F1 0.333 0.15 Weight P1 0.558 0.075
0.449 F2 0.570 0.256 0.134 P2 0.122 0.016
F3 0.097 0.044 P3 0.320 0.043
Perspective Indicator Weight Perspective Indicator Weight
Customer Local Global Innovation Local Global
Weight C1 0.637 0.227 Weight I1 0.297 0.018
0.356 C2 0.105 0.037 0.061 I2 0.163 0.048
C3 0.258 0.092 I3 0.540 0.033
4.3.2 Result of KPIs Prioritizing Process
5 Application of BSC-AHP in Supply Chain Strategic Management
In this chapter a real case is defined and modeled via Expert Choice Software. Decision making processes are based on the BSC perspectives’ weight derived in the previous chapter, while the relative importance of each indicator is evaluated in a pair-wise comparison process with regard to the four objectives (Supply Chain Strategies). Finally, all four strategies are prioritized with respect to the degree of importance that each strategy possesses. A graphical sensitivity analysis is also carried out to evaluate decision robustness.
5.1 Companies Introduction
In order to implement a real case study, the empirical phase of this thesis work has been conducted with the help of a group of managers and industry experts from a joint-stock and distribution company. Due to the company’s internal regulation, the name of t h e studied company and the source of data gathered are considered as confidential information, and can only be revealed and provided for supervisors both in the company and university.
The Company (named as DC Co. from now on) is a distribution company founded in 1960s, governing by a multi-cultural group of managers in 24 local subsidiaries and 5 global branches. This company is regarded as a leading distributor in the local market with an estimated 700,000 tons of distribution volume in 2012. Approximately, 2,600 employees are working at different branches delivering more than 600 SKU to about 1.3 million customers. Dc Co. is mostly focusing on FMCG and cosmetics market segment, and is providing more than 50 international brands with extensive services including marketing, warehousing, distribution, reverse SC, CRM, service development and utilization, etc.
5.2 Conventional Supply Chain Strategies
Nowadays, an organization requires a very comprehensive road map addressing all the operations towards its overall mission. In the existing competitive market, managerial solutions seem not to be enough in coping with the complexity of competition. Therefore, strategic solutions are applied to define novel and applicable success factors.
not only survive in the present market, but also should apply competitive advantages to prevail over its rivals.
In this research four conventional Supply chain strategies (SCS) are considered as the objectives of BSC-AHP model. Figure 7 explicitly illustrates all the SCSs and the corresponding attributes related to each of these concepts.
Figure 7 Different Supply Chain Strategies
5.3 BSC-AHP Modeling via Expert Choice
Similarly, different Multi Criteria Decision Making (MCDM) Methods such as MacBeth, SMART, UTA, ELECTRE, etc (Figueira, Greco, & Ehrgott, 2005), are dependent upon four main steps below:
1. Problem Modeling: Make an explicit definition of different aspects of a problem. 2. Calculating Indicators’ Weight: Weighting the degree of importance of each
indicator.
3. Concluding overall weight of each indicator and prioritizing the solutions
4. Sensitivity Analysis: If the value allocated to each indicator is slightly modified, the overall result should not be changed. In this case we can consider the result derived as a robust decision.
Developing a BSC-AHP model via Expert Choice makes a decision making process very tangible, reliable, and less complicated. All the above-mentioned steps are carried out by Expert Choice software V.11, and the graphical figures correspond to each evaluation process adopted from this software.
5.3.1 Problem Modeling
The problem modeling in BSC-AHP is preferred to be done in a group discussion; all upcoming steps are proceeded in this manner. The observer strives to reach a consensus towards an objective which needs very tight collaboration between all decision makers in the group. In this section, a AHP structure is shaped based on the preliminary BSC-AHP structure in chapter four, while the alternatives (Supply Chain Strategies) appeared at the lowest level of this structure (Figure 8).
Figure 8 A Hierarchy Structure- Network Optimization Based on AHP-BSC Metric Introducing Alternatives Level
Strategic Supply Chain Management
Financial Perspective Customer satisfaction Internal Business Perspective Learning & Growth Perspective
Assets Utilization Customer
Perspective Revenue Growth Cost Reduction
Customer
Satisfaction Availability Functionality Optimization Operation Innovation Process Orientation Customer Capabilities Employee Organizational Culture IT Capabilities
Lean
Agile
Postponement
Speculation
5.3.2 Pair-wise Comparison
For each node of hierarchy (criteria), pair-wise comparison of KPIs related to that particular criterion shapes a matrix that will be used in weight aggregation. In Figure 9, a sample of a pair-wise comparison matrix in Expert Choice is illustrated.
Figure 9 Pair-Wise Comparison Matrix based on a Numerical Judgment Scaling System
Psychologically, it is easier and more reliable for decision makers to weigh the importance of two individual factors instead of being confused by simultaneously judging about a multi- criteria problem. In addition, consistency analysis and cross checking of different pair-wise comparisons are more accurate. In AHP, an indicator is weighted in comparison with another indicator by a ratio scale which does not require any unit or index. The judgment is conducted based on the quotient of two indicators A and B which derives a/b. For instance, in figure 9, the main perspective of BSC is illustrated and a pair-wise comparison has been carried out. The relative importance of Financial Perspective to Customer Perspective is twice as that of Customer Perspective. Respectively, it is three times as much as Internal Process, and five times as much as Learning & Growth are.
5.3.3 Different Judgment Scales
Figure 10 Pair-Wise Comparison Matrix based on a Verbal Judgment Scaling System
Figure 11 Pair-Wise Comparison Matrix based on a Graphical Judgment Scaling System
5.4 Results
Expert Choice provides researchers with an outstanding feature that visualized different steps in AHP evaluation. With regard to the case study conducted, different aspects of the analysis process are concluded in the main page of Expert Choice which demonstrated the factors that yielded the final result.
The final ranking of alternatives is shown in figure 12 along with the corresponding weight of each alternative. The ranking process is developed based on the pair-wise comparison that has been carried out for each sub-criterion (indicator) in terms of BSC perspectives.
weight of 0.118. By a simple trade-off, one can interpret that acceptance of agile strategy with respect to the criteria mentioned almost three times more than the acceptance of the postponement strategy.
On the other hand, lean strategy (weighted 0.299) is ranked as the second alternative which obviously prevails over speculation strategy (weighted 0.225).
To sum up, it is obviously interpreted that agile is the best strategy that DC Co. would implement to improve its SC.
Figure 12 Final Results derived by Expert Choice Software
6 Conclusion and Further Research
In this chapter, t h e author provides t h e reader with a concise discussion documenting the outcomes derived, and explicitly conveys managerial interpretation of those results. In addition, this chapter proposed the further possibilities and research opportunities which expand different aspects of the methods studied.
6.1 Conclusion and Managerial Interpretation
In this research an integrated model of BSC-AHP is proposed in order to facilitate the prioritization process of KPIs based on BSC concept. This model enables the strategist and managers to determine which supply chain strategy better suits their organizational objectives and better aligns with customers’ expectations. In this research, the author strives to simply define different AHP approaches that result in a final prioritization of supply chain strategies studied.
An actual case study conducted in supply chain business in order to prove how the BSC-AHP model can contribute to strategic management at the top level. This model can be expanded to other fields such as marketing management, operations management, etc. While there are many indicators that can affect efficiency of a supply chain, the author proposed intangible indicators and strategic factors to demonstrate how quantitative criteria can be evaluated via a mathematical process. Dealing with intangible success factors apparently makes the evaluation more ambiguous; however, via the proposed method, transparency of decision making is improved.
The BSC-AHP method can be considered as a strategic road map that helps managers to modify strategic approaches aligned with organizational features. For instance, organizational culture is one of the most critical features of an organization that influences internal values and shapes its external image, but rarely do managers put weight on this substantial indicator. General belief confirms that intangible success factors should be weighted as a minor issue to be considered, while the impact factor of such indicators definitely shape a critical competitive advantage.
