Development of a supply chain performance measurement system

Guideline for the electronics manufacturing industry


Master's Thesis, 2014
62 Pages, Grade: 1,3

Excerpt

Table of contents

1 Introduction
1.1 Intention of the master thesis
1.2 Structure of the master thesis

2 Evaluation of supply chain performance measurement systems
2.1 Definition of Supply Chain Management
2.2 Description of existing supply chain performance measurement systems
2.2.1 General requirements of SC performance measurement
2.2.2 Tableau de Bord
2.2.3 Skandia Navigator
2.2.4 Performance Pyramid
2.2.5 Quantum Performance Measurement
2.2.6 Balanced Scorecard
2.3 Suitability evaluation of supply chain performance measurement systems
2.4 Supply Chain performance measurement with the balanced scorecard
2.4.1 Financial perspective
2.4.2 Customer perspective
2.4.3 Process perspective
2.4.4 Learning & growth perspective
2.4.5 Cooperation perspective
2.5 Practical advantages of supply chain performance measurement

3 Hypothesis

4 Development of a supply chain balanced scorecard for an electronics manufacturing company
4.1 Industry-based supply chain characteristics
4.2 Methodology
4.3 Definition of a supply chain strategy
4.4 Decision on utilized performance indicators within the balanced scorecard
4.5 Implementation of the supply chain balanced scorecard
4.6 Verification of the performance measurement system’s suitability

5 Summary and conclusion

6 References

Table of figures

Figure 2-1: Visualization of a supply chain network .

Figure 2-2: Connecting order-to- payment processes .

Figure 2-3: Performance attributes in the SCOR-model .

Figure 2-4: Measurement of performance indicators in Singapore companies .

Figure 2-5: Structure of the Tableau de Bord .

Figure 2-6: Structure of the Skandia Navigator .

Figure 2-7: Structure of the Performance Pyramid .

Figure 2-8: Structure of the Quantum Performance evaluation model .

Figure 2-9: Structure of the Balanced Scorecard .

Figure 2-10: Evaluation of performance measurement systems .

Figure 2-11: Comparison of traditional BSC with Supply Chain BSC .

Figure 2-12: Standardized performance indicators in the SCOR model .

Figure 2-13: Supply chain strategy map with cooperation perspective .

Figure 2-14: Financial perspective of Supply Chain BSC .

Figure 2-15: Customer perspective of a supply chain balanced scorecard .

Figure 2-16: Process perspective of a supply chain balanced scorecard .

Figure 2-17: Learning & growth perspective of SC balanced scorecard .

Figure 2-18: Cooperation perspective of supply chain balanced scorecard .

Figure 2-19: Current and future scope of SC performance measurement .

Figure 4-1: Industry-based supply chain characteristics .

Figure 4-2: Implementation process of a performance measurement system .

Figure 4-3: Porter’s five forces

Figure 4-4: SWOT-Analysis of the electronics manufacturing company .

Figure 4-5: Weighting of strategic supply chain directions .

Figure 4-6: Classification of the existing supply chain .

Figure 4-7: Evaluation results of financial performance indicators .

Figure 4-8: Evaluation results of customer-related performance indicators .

Figure 4-9: Evaluation results of process-related performance indicators .

Figure 4-10: Evaluation results of cooperation-related performance indicators .

Figure 4-11: Evaluation results of learning & growth performance indicators .

Figure 4-12: Supply chain balanced scorecard of the electronics manufacturer .

Figure 4-13: Supply chain balanced scorecard of the operational purchasing .

Figure 4-14: Development of a supply chain strategy map .

Figure 4-15: Correlation of forecast accuracy and OEE .

Figure 4-16: Correlation of OEE and deliverability .

Figure 4-17: Correlation of deliverability and inventory days .

Figure 4-18: Correlation of deliverability and production turnover .

Figure 4-19: Cause-and-effect relations within the developed supply chain BSC .

1 Introduction

1.1 Intention of the master thesis

The goal of this master thesis is to provide an analysis of existing supply chain performance measurement systems as well as an evaluation of their suitability for the electronics manufacturing industry. Furthermore, the hypothesis that the implementation of a supply chain performance measurement system in cooperation with supply chain partners will lead to sustainable competitive advantages within the supply chain is going to be proven.

As competitiveness in future industry will be increasingly “supply chain vs. supply chain”, rather than “firm vs. firm”, holistic performance measurement systems become more and more relevant to global operating companies (Hult, 2008, p.538). Although the efficient management of global supply chain networks already has the potential to create competitive advantages, most industrial companies still focus on production efficiency and selective optimization that disable fast adaption to changing customer requirements. In increasingly saturated markets a technology-driven competitive advantage is often quickly compensated by low-cost countries. In contrast high service quality established by efficient logistics processes can hardly be adopted in short time (Richert, 2006, p.44). Especially in the areas of fast moving consumer goods and the electronics industry, companies need to be able to quickly react on changing consumer demands in order to fulfill the customer’s requirements in a flexible way.

Cooperative management between supply chain partners creates higher transparency and market-orientation, that allows the entire supply chain network to operate in a more flexible and efficient way. In consequence the supply chain’s competitiveness will increase due to higher service value for the customer. But, as most industries still struggle with the development of flexible supply chain structures, suitable management tools are obviously not available or applied yet. Therefore, this master thesis provides in a first step an evaluation of existing supply chain performance measurement systems regarding their suitability for current business environments. In a second step the development process towards a practical implementation of the most suitable performance measurement system in an electronics manufacturing company is described. Based on a defined supply chain strategy a standardized approach leads to the development of a holistic supply chain management system providing the preconditions for creating a competitive advantages within the electronics industry.

1.2 Structure of the master thesis

The master thesis is structured in three main parts, starting with a detailed description and evaluation of existing supply chain performance measurement systems. After a short paragraph containing general definitions of supply chain management and a quick overview of the most common terms and supply chain instruments, the focus of this part lies on the evaluation of existing supply chain performance measurement systems. The evaluation compares the functionality of the described systems with the particular requirements of a supply chain-related performance measurement instrument. This is completed by several surveys describing the practical advantages and disadvantages of supply chain performance measurement.

Based on this evaluation the following hypothesis is formulated:

“ Suitable supply chain performance measurement systems offer companies with a high dependency on supply chain partners the opportunity to realize a sustainable competitive advantage. Supply chain performance measurement systems provide a holistic approach to focus on the key drivers of Supply Chain performance and therefore on the business success. Based on a common supply chain strategy that is in accordance with the individual business strategies of the supply chain partners, an implemented cross-company performance measurement system will support the entire supply chain network to increase their competitiveness. By transforming the common supply chain strategy into strategic targets of the supply chain partners, suitable management systems offer a holistic approach to measure and control the performance of the value chain. The continuous improvement of identified potentials as well as the reduction of complexity allows the design of a more flexible and cost-efficient supply chain network.”

In the third part this hypothesis is going to be proven by an empirical analysis of an existing supply chain network of an electronics manufacturing company. Based on this analysis a supply chain performance measurement system will be developed. Therefore, the company’s supply chain strategy is going to be defined as well as the most relevant performance indicators to measure and control the supply chain activities. Furthermore, the suitability of the developed measurement system will be verified by comparing the system’s implications with the company’s supply chain performance of the past year.

The master thesis closes with a suggestion of further development and implementation steps to establish this performance measurement system along the supply chain organization.

2 Evaluation of supply chain performance measurement systems

2.1 Definition of Supply Chain Management

Since middle of the 90s the term “Supply Chain Management (SCM)” is used in the German business environment, first as a synonym for value chain or logistics activities, although supply chain management includes production activities as well as information and financial flows (Eisenbarth, 2003, p.19). As most companies cooperate with several supply chain partners in order to manufacture products or services, the chain itself can be seen as a network of organizations as shown in the figure below (Busch, 2002, p.4).

illustration not visible in this excerpt

Figure 2 - 1: Visualization of a supply chain network (Albert, 2009, p.28).

In general supply chain management describes the integration of key business processes from end user through original suppliers that provides products, services and information that add value for customers and stakeholders (Lambert, 2008, p.354). The principal functionality of supply chain management can be described by the Order-to-Payment S according to KLAUS. Starting point of the supply chain process is the customer order initiating the material and production planning. After purchasing the required raw materials from the supplier the order fulfillment is ongoing until the final product gets delivered to the customer. Finally the customer payment for the delivered product initiates the financial flow from the OEM down to the raw material supplier in the supply chain network. The linkage of several Order-to-Payment processes visualizes the holistic supply chain network (Eisenbarth, 2003, p.21).

illustration not visible in this excerpt

Figure 2 - 2: Connecting order-to- payment processes (Albert, 2009, p.46).

Main target of SCM is the design of an efficient and flexible value chain across company borders in order to supply customers with the required products and services. This target should be obtained by higher market-orientation, demand-oriented production and reduction of inventory along the supply chain (Albert, 2009, p.12). Therefore, some prerequisites are the creation of transparency among the supply chain partners, the reduction of information deficits, the improvement of material flows, as well as the reduction of complexity within the single companies (Sommer, 2007, p.41). Strategies for reducing complexity are for example postponement, mass customization or the implementation of information and communication technologies (Wildemann, 2001, p.5). Within the supply chain network each supply chain partner has to avoid opportunistic behavior in order to realize a holistic optimum of the supply chain that creates the highest customer value.

Besides the above mentioned improvement potentials through SCM, the operational implementation of this management concept faces serious obstacles in business environments. These obstacles are usually irrespective of company size or industry and can be summarized according to SOMMER to the following four points (Sommer, 2007, p.45):

1. Cooperation: The lack of trust and openness, cross-company trade-offs, as well as the fear of increasing dependencies can be reasons for opportunistic behavior. Furthermore the expectation of competitive disadvantages or the absence of risk-sharing models may also lead to a reduced willingness for cooperation.
2. System-specific obstacles: Missing acceptance for cooperation within the supply chain, resistance against change processes, high complexity within the value chain, incompatibility with existing organizational structures or high effort for SCM implementation are the most common reasons.
3. Incompatible information systems: Insufficient data availability and quality, dissimilar data formats, different IT-levels of supply chain partners, high effort for data aggregation, unavailable data interfaces or the fear of data abuse are potential IT-specific obstacles.
4. Miscellaneous reasons: Geographical distance or high competition with other supply chain networks.

A strategic implementation of SCM in business environments can be realized with different management concepts, such as efficient consumer response (ECR) or collaborative planning, forecasting and replenishment (CPFR). A further description of these concepts will not be provided in this master thesis but can be found amongst others from BUSCH, EISENBARTH or SEIFERT (Busch, 2002, p.45; Eisenbarth, 2003, p.29; Seifert, 2006, p.16). Neither the most common operational supply chain instruments for controlling and coordinating material flows like pull systems, Just-in-Time or Kanban are going to be described in detail. An overview about these topics can be withdrawn from WILDEMANN, GEIGER or DICKMANN (Wildemann, 2001, p.165; Geiger, 2002, p.21; Dickmann, 2008, p.351).

In contrast, the following part of this master thesis will focus on the description and evaluation of existing performance measurement systems for supply chains. As already mentioned above a large variety of obstacles for SCM implementation exist among the supply chain partners. Nevertheless the previously mentioned advantages and improvement potentials regarding increased competitiveness should convince companies to put more effort in establishing efficient SCM structures within their value chains. This approach can only be realized by a common supply chain strategy that is supported by a common performance measurement system. This is able to provide value chain based information to the management in order to optimize supply chain-wide processes the customer is willing to pay for. Rather than optimizing functional-based processes, SC performance measurement is able to integrate relevant information along the whole value chain, and overcomes existing interfaces between departments. Therefore, all business processes or functions need a high level of upstream and downstream coordination and visibility (Richert, 2006, p.43). The following paragraph will therefore analyze the existing supply chain performance measurement systems as well as their state of application in current business environments.

2.2 Description of existing supply chain performance measurement systems

In the following paragraph the most common performance measurement systems for business process management will be described. These are the Tableau de Bord, the Skandia Navigator, the Performance Pyramid, the Quantum Performance Measurement and the Balanced Scorecard. Before describing these tools, the general requirements a performance measurement system for supply chains has to fulfill need to be taken into consideration.

2.2.1 General requirements of SC performance measurement

In literature several approaches regarding requirements for SC performance measurement exist. RICHERT summarizes these requirements as follows (Richert, 2006, p.40):

- Implementation of a standard communication basis
- Creation of a holistic inventory and capacity management
- Establishment of a cross-company process organization
- Providing performance-related information of all Supply Chain partners
- Existing SC strategy and activity-based costing
- Consistent data basis
- Defined responsibilities within the organization
- Definition of strategic performance indicators
- Based upon strategic indicators, definition of operational indicators
- Linkage between defined strategic and operational indicators

As a helpful tool for defining these requirements, RICHERT mentions the SCOR-model (Supply Chain Operations Reference) which was created by the Supply Chain Council. The SCOR-model describes logistics business processes and provides performance measurement tools as well as best practices. The described logistics processes are demand management, order fulfillment, manufacturing flow management, supplier relationship management and returns management (Brewer, 2000, p.7). It offers a detailed overview of performance attributes that can be implemented in a supply chain performance measurement system as well as particular indicators for each of the previously mentioned logistics processes. The following figure shows the translation of these logistics processes into performance metrics.

illustration not visible in this excerpt

Figure 2 - 3 : Performance attributes in the SCOR-model (SC Council, 2002, p.7).

A quite similar approach is described by GIESE where the main requirements towards a performance measurement system for supply chains are (Giese, 2012, p.68):

- Combination of lag and lead indicators
- Combination of internal and external view (employees and customers/suppliers)
- Short- and long-term improvement potentials should be pointed out
- Combination of financial and non-financial indicators
- Combination of qualitative and quantitative measures
- Strong linkage to company’s strategy
- Continuous improvement process should be supported
- Reflection of different SC levels (holistic-, company- and department-based view)
- Root-cause-relations between different SC levels should be pointed out
- High process orientation and reduction of interfaces
- Low change effort in case of supply chain modification

One of the most important requirements that should be pointed out is the linkage between the performance measurement system and the company’s strategy. Within the performance measurement system this can be realized by sophisticated performance indicators that reflect the strategic goals of the company. In real business environments this linkage is often missing. A current survey of GIESE among German managers from 2011 shows that 64% of consulted managers stated that currently existing measurement systems are not related to the company’s strategy and only reflect the financial performance of the company (Giese, 2012, p.43). These results can be confirmed by a second survey of CHIA among logistics service providers, manufacturers, retailers and international procurement offices located in Singapore. In total 113 consulted managers were asked to denote the importance of 15 different performance indicators for their business environment. The given answers were on-time delivery (first), customer satisfaction (second) and cost reduction (third). In contrast, the most measured performance indicators in these companies are gross revenue, profit before tax and cost reduction, as shown in the following figure. (Chia, 2010, p.607).

illustration not visible in this excerpt

Figure 2 - 4 : Measurement of performance indicators in Singapore companies (Chia, 2010, p.614).

Again, this result clearly shows a discrepancy of real business performance and evaluated indicators. Furthermore the analysis confirms that significant improvements in non-financial indicators are necessary for a moderate improvement in financial indicators. Companies looking for a better financial performance should therefore track and work on the improvement of non-financial indicators. From a supply chain perspective, the non-tangible logistics performance indicators such as on-time delivery, customer satisfaction, and cost reduction are perceived to be most important, but aren’t the most measured of the indicators (Chia, 2010, p.627). Both surveys emphasize the need for a more balanced approach regarding the evaluation of a company’s performance. The combination of financial and non-financial performance indicators offers a more holistic view of the business environment and supply chain processes. In the following paragraph the above mentioned performance measurement systems will be described and evaluated regarding their suitability for supply chain performance measurement.

2.2.2 Tableau de Bord

The Tableau de Bord represents a very flexible performance measurement tool, as no standardized concept exists. Main target of this tool is the visualization of the current performance of different company divisions, as well as the regular review of processed tasks based on the measurement results. Furthermore the Tableau de Bord offers the evaluation of future potentials as well as a benchmarking with the performance of internal and external competitors (Grüning, 2002, p.51). The basic structure of a Tableau de Bord is shown in the figure below.

illustration not visible in this excerpt

Figure 2 - 5 : Structure of the Tableau de Bord (Epstein/Manzoni, 1997, p.30).

Based on the company’s vision, strategic targets are defined for each company division. Critical success factors are assigned to each strategic goal as well as particular performance indicators that reflect the overall targets. Mostly these performance indicators are non-financial indicators. From the divisional level the targets are once again broken down to the functional level. So, each department defines his individual Tableau de Bord that needs to be in accordance with the strategic targets of the superior company level (Giese, 2012, p.50). This allows the top management to verify which division or functional department most contributes to the company’s performance. Furthermore each department needs to consider interdependencies with other departments when defining their individual Tableau de Bord in order to avoid inefficiencies. This forces the department leaders to deal with trade-offs and to find an agreement among each other concerning the individual targets that need to be consistent with the company’s strategy. Another advantage of the Tableau de Bord is the establishment of a standardized reporting system within the organization, especially for regular performance evaluation and reporting. This provides aggregated information to the top management what allows them to take decisions based on verified data (Epstein/Manzoni, 1997, p.192).

2.2.3 Skandia Navigator

The Skandia Navigator represents one of the first performance measurement instruments that considers non-accountable values like the know-how of employees, the organizational knowledge of the company as well as the company’s brands and the customer base (Giese, 2012, p.52). The development of this performance measurement tool was initiated by Skandia after recognizing that the market value of a company can’t be expressed in total by financial indicators. Often the market value exceeds the book value of a company, especially if the intellectual capital represents one of the core competencies. In research and development or in the service industry this is very likely to happen. Although the intellectual capital of a company may lead to competitive advantages this value is often neglected. Therefore, main target of the Skandia Navigator is a balanced description and visualization of financial and intellectual capital. The structure of the performance measurement tool is based on five different perspectives as shown in the following figure.

illustration not visible in this excerpt

Figure 2 - 6 : Structure of the Skandia Navigator (Edvinsson/Malone, 1997, p.68).

The financial perspective evaluates the book value of the company that is calculated by past-oriented financial indicators. The customer, employee, process and innovation perspective show the intellectual capital of the company, in which the present situation is represented by existing customers and processes and the future situation by potential innovations and developments. In the center of the Skandia Navigator the employee perspective is situated which is connected to each of the surrounding perspectives. Each perspective provides a selection of performance indicators to measure the financial and intellectual capital of the company. To mention some examples, the financial performance can be evaluated by the return on investment, revenue growth per year or turnover per employee. The customer perspective offers indicators like the average turnover per customer or the average duration of a customer relationship. Within the process perspective the value of integrated information systems and technologies is considered. Examples for performance indicators are the delivery performance rate or the order fulfillment time. The innovation and development perspective shows the company’s efforts to prepare for future challenges like changing customer requirements or product innovations. Therefore, the Skandia Navigator offers performance indicators like investments per customer or investments for the development of new markets. Finally, the employee perspective contains the competencies and abilities of the staff to run the business and to guarantee the competitiveness of the company in the future. Mentionable performance indicators in this perspective are the labor turnover rate or the amount of improvement ideas per employee per year (Giese, 2012, p.54).

2.2.4 Performance Pyramid

This performance measurement tool was developed in the 1990s by LYNCH and CROSS (Lynch/Cross, 1995, p.65). It breaks down the strategic goals of the company, which are based on the vision statement, into three different performance levels. On each of these performance levels individual performance indicators are defined which need to be linked to the strategic targets of the company. So, strategic targets are defined top down whereas the performance indicators are determined bottom up. The structure of the Performance Pyramid is organized in a way that the interests of customers and shareholders are considered most. For the different business units financial and market targets are defined. This level is supported by the core processes of the company that are measured by individual performance indicators like customer satisfaction, flexibility or productivity. The base of the Performance Pyramid is represented by different departments like quality, logistics, production and support (Schomann, 2001, p.146). Furthermore the performance measurement tool can be divided into an external scope, representing the customer interests like deliverability, quality or customer satisfaction, and an internal scope, representing the interests of the shareholders like financial performance, productivity or lead time. The company’s vision and the flexibility touch the interests of both stakeholders (Schreyer, 2007, p.47). The following figure shows the structure of the Performance Pyramid at a glance.

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Figure 2 - 7 : Structure of the Performance Pyramid (Lynch/Cross, 1995, p.65).

The structure of the Performance Pyramid also visualizes root-cause-effects between the different performance indicators. The improvement of product quality or high deliverability of customer orders has a direct impact on the customer satisfaction and the flexibility. Satisfied customers enable the company in further step to enlarge its market share and value. Similar to the external scope, root-cause-effects exist in the internal scope. Short lead times and a low amount of non-value adding activities lead to a higher productivity and flexibility. Lower production costs per unit result in higher financial benefits (Lynch/Cross, 1995, p.81f.).

2.2.5 Quantum Performance Measurement

This performance measurement tool was developed by the consulting company Arthur Andersen in order to optimize the performance and service level of companies. The so called “Quantum Performance” can be described as a rate of target achievement (Hronec, 1993, p.20f.). In this concept individual performance indicators are used in order to measure processes and their outputs. The choice of the indicators is based on the company’s strategy and supported by the Quantum Performance evaluation model as depicted below.

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Figure 2 - 8 : Structure of the Quantum Performance evaluation model (Hronec, 1993, p.25).

This evaluation model is structured in four different elements drivers, activators, processes and continuous improvement. The drivers are represented by the leadership and the employees of the company, as well as by external best practices. Their ideas and requirements need to be combined with the company’s strategy and afterwards transported into the organization. This step can be realized by the activators communication, incentives, training and benchmarking. This development process is a prerequisite for the development of new performance indicators and strategic targets. Subsequently, critical processes are identified, measured and categorized in different core activities. This leads to the definition and implementation of performance indicators that measure the output of the previously identified core activities. The last element represented by the continuous improvement focuses on the optimization of the strategy, the targets and the process performance indicators and supports the company to reach the Quantum Performance (Schomann, 2001, p.141).

2.2.6 Balanced Scorecard

The balanced scorecard is a strategic management system that facilitates the implementation of strategy, using measures to ensure that corporate vision and strategy are implemented and achieved. The balanced scorecard was initially conceptualized by KAPLAN and NORTON as a performance measurement system where traditional financial measures were supplemented with non-financial measures pertaining to the customers, internal business processes, and the organization’s learning and growth activities (Chia, 2010, p.606). The general structure of this performance measurement tool is to some extent similar to the Skandia Navigator, as it contains the same perspectives. KAPLAN and NORTON only combined the innovation & development perspective with the employee perspective of the Skandia Navigator into the innovation & learning perspective. Within the different perspectives individual targets and performance indicators need to be formulated by the company using the scorecard for the evaluation of business performance.

According to the previously described performance measurement systems, also the balanced scorecard approach is based on the company’s vision and strategy before defining the particular performance indicators. The intent of the scorecard is to provide a formalized mechanism for influencing managers to achieve a balance between nonfinancial and financial results across short-term and long-term time horizons (Brewer, 2000, p.76). Once the company’s targets and performance measures are defined, the necessary requirements and actions to achieve these targets are described. The balanced scorecard framework suggests that balance is obtained by adopting performance measures from the four different areas mentioned above. This framework balances the inclination to overemphasize financial performance by long-term oriented performance measures (Brewer, 2000, p.83).

The financial perspective proves whether the realized actions result in a higher financial success. Examples for performance measures in this perspective are the return on investment, sales growth or earnings before interest and taxes. Furthermore the financial perspective represents the targets for the other perspectives of the balanced scorecard, what is quite similar to the described root-cause-effects in the Performance Pyramid.

[...]

Excerpt out of 62 pages

Details

Title
Development of a supply chain performance measurement system
Subtitle
Guideline for the electronics manufacturing industry
College
University of Applied Sciences Kempten
Grade
1,3
Author
Year
2014
Pages
62
Catalog Number
V282843
ISBN (eBook)
9783656820291
ISBN (Book)
9783656828655
File size
3540 KB
Language
English
Series
Aus der Reihe: e-fellows.net stipendiaten-wissen
Tags
Supply Chain Management, Performance measurement, Balanced Scorecard, Electronics
Quote paper
Dipl.-Wirtsch.-Ing. Christian Biewald (Author), 2014, Development of a supply chain performance measurement system, Munich, GRIN Verlag, https://www.grin.com/document/282843

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