Which drivers need to be considered related to the decision making?

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European Distribution Network

Which drivers need to be considered related to the decision making?

─

_{An introduction of generic model for MEBV}

By

Limin Zhao

(s1745042)

University of Groningen

Faculty of Management and Organization

Master Thesis

For

Master of Science Business Administration (MSc BA)

Specialized in Operations and Supply Chains

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Author Limin Zhao

Student number 1745042

Email zlm8241@hotmail.com

University University of Groningen (Rijksuniversiteit Groningen, RUG)

Faculty Economics and Business

Program Master of Science Business Administration

(MSc BA)

Specialization Operations and Supply Chains

First Supervisor Dr. ir. S. Brinkman

Second Supervisor Dr. Gera Welker

Company MEDRAD Europe B.V.

Location Maastricht, The Netherlands

Company Supervisor Marc Nelissen

Date August 30, 2009

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Acknowledgement

This project is the final journey of MSc BA specialized in Operations and Supply Chains. I am very glad to spend this half a year internship in MEBV as the final part of this journey. Hereby I would like to thank my company coach Marc Nelissen who offered this case study and coached me with his highly professional logistics experience and knowledge. Appreciations also go to all my colleagues from MEBV and 3PL who have provided me with the information in one way or another, in particular to Tom Robson.

I would like to dedicate my gratitude to my first supervisor Dr. ir. S. Brinkman. His guidance has greatly enhanced my capability to perform the project in the real business environment. In addition, this final version is significantly enhanced by his in-depth comments and suggestions. I own special thanks to my second supervisor Dr. Gera Welker, who is willing to cope with my tight final session date.

I am indebted to my cousin Jiwei Guo, who has tireless helped me to view and review this manuscript in order to avoid the spelling and grammar mistakes. Many thanks to his amazing effort and patience.

Finally and most importantly, I would like to thank my parents: Wanhua Guo, Jinglong Zhao, and uncle Dawei Guo for their unweaving support and encouragement in my 5 years of studies abroad.

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Executive Summary

The research has been conducted in MEBV, which is the European headquarters for Medrad. The company is the global market leader of the diagnostic imaging and therapeutic medical devices and service. Their physical product groups can be generally categorized as 2 models: 1) Medical Equipment (ME) with high value but low volume; 2) and Syringes and Disposables (S&D) with low value but high volume. Due to the historical reason and the increasing pressure of cost rationalization in the healthy industry, the management board has been confronted with a dilemma regarding the distribution network of S&D in terms of the total value delivered to the customers. Therefore, the objective of this research was to identify the drivers which would influence the logistics performance in the near future related to the decision making of centralized or decentralized distribution network, and private or public warehouse.

Hence, my research question was raised below.

Which drivers including those influenced or least influenced by the Logistics department of MEBV can cause the effect on the supply chain performance in centralized or decentralized distribution structure for S&D in the direct sales market of MEBV?

And the next question was

Which logistics performances are relevant to the decision making of private or public warehouse for S&D in the direct sales market of MEBV?

1. Centralized or decentralized distribution structure for S&D in the direct sales market of MEBV

The first question was further narrowed down to the 4 sub-questions. They were a) logistics performances; b) variables influenced by the Logistics department; c) variables least influenced by the Logistics department; d) and their impact on the logistics performances. The ideal supply chain model was initially expressed in a simple formula as follows.

Supply chain performance objectives = f (Independent variables, Designed variables)

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There were a total of 17 discovered variables including discovered and independent, out of which 6 were hardly manipulated by the Logistics department owning to the complexity, they are:

1) Customer demand variety (independent variable) 2) Packaging (independent variable)

3) Annual flow through the warehouse (independent variable)

4) Product demand volatility and Product volume (independent variable) 5) Geographical distribution of demand (independent variable)

6) The frequencies for customer delivery (independent variable)

Although the remaining 11 variables were likely under control, the last three were more related to the inventory management strategies, and it is seen as a step further after network configuration. Hence, the impact of there three vareiables on the performance objectives was not considered in this paper.

1) Transportation models in terms of the service agreement (independent variable) 2) Types of order (independent variable)

3) Larger shipments for the quantity discount (independent variable)

4) Distance between the proximity warehousing facility and customers (independent variable)

5) Service level requirement regarding the lead time (independent variable) 6) Distance between two warehousing facilities (independent variable) 7) Shipping from local warehousing facility (designed variable) 8) Shipping central warehousing facility (designed variable) 9) The availability of the products (independent variable) 10) Replenishment cycle and cycle stock (independent variable) 11) Accessing and handling spaces (independent variable)

For the assumed positive or/and negative relation which indicates the direction to defined supply chain performance objectives, the principles are

The leading factors ─ quality and dependability, the relation is positive when these factors are improved or vice verse.

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Eventually, 8 variables were assigned the numerical value for the analysis of their impact on the targeted performance objectives in two of selected countries, which are UK and Italy. During this empirical study, unfortunately, two of the performances: package in good condition and on-time order completion were hardly measured by manipulating the related variables in view of the shortage of historical data. As a result, the total value could only consist of system wide cost and lead time. In addition, a new independent variable was introduced in the empirical study, called the length of period, which consists of the length of review period and the length of replenish lead time. The impact on the cost performance is negative. Like the other three independent variables, it is recommended to be grouped into the topic of inventory management strategies. The results based on the two case studies showed that the larger shipments and types of order have no or less significant impact on the cost performance in the scenario of decentralized and centralized distribution network respectively, when referring to 2 days standard lead time. In contrast, the remaining 6 variables all play a critical role in their relevant performances and the positive or/and negative relations are in line with the principle.

Furthermore, the total value delivered by different distribution structures for UK and Italy are illustrated in the following.

UK current distribution network

100% or 100%

System wide cost €292,861.87 2 days delivery lead time customers cartons

Totalvalue =

× UK proposed distribution network

99.77% or 99.98%

System wide cost €281,596.64 2 days delivery lead time

customers cartons

Totalvalue =

×

It was hard to differentiate the total value by only viewing the quantitative data. Therefore the qualitative data were collected, such as the coordination and management time, or the potential misunderstandings and misinterpretation between each operation. In view of those hidden factors, the balance was inclined to the centralized distribution system.

IT current distribution network

100% or 100%

System wide cost €340,873.26 2 days delivery lead time customers cartons

Totalvalue =

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It was not difficult to make choice on the case of Italy because the current distribution network can completely fulfill the market requirements in a slightly more cost efficient way.

On the other hand, there were some limitations in the approach.

1) The analysis did not take the future demand pattern into account.

2) Delphi method as one of the judgment methods was not used in the paper.

3) Since the quality and dependability performances could not be quantified in this paper, the “total value” shown in the conclusion part could merely represent the overall value created by the supply chain network

One of the expectations is to overcome these limitations in the future research. More specifically, there are some suggestions for each country.

In UK, the change of customer’s expectation is a big challenge when closing the local warehousing facility because the delivery lead time will be increased by 1 day. Secondly, the space to strive for long term delivery contract is apparent by taking advantage of the multi-use policy. As for Italy, it is wise to consider managing the inventory in the next stage.

2. Private or public warehouse for S&D in the direct sales market of MEBV

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List of Figures

Figure 1.1 A simplified Medrad organization chart... 14

Figure 1.2 A simplified MEBV organization chart... 15

Figure 1.3 A brief example picture of ME and S&D... 16

Figure 1.4 Units; Revenue and Gross Margin of ME and S&D between 2004 and 2008 ... 17

Figure 2.1 A simplified European distribution network of Syringes and Disposables (S&D)... 23

Figure 3.1 Research Plan (Chapter 3) ... 26

Figure 4.1 Trade-off between efficiency and effectiveness ... 31

Figure 4.2 Value Metrics (Johansson et al. 1993, p4)... 32

Figure 4.3 Operations strategy matrix analysis for MEBV... 34

Figure 4.4 Push-pull and leagility among supply chain structure... 35

Figure 4.5 The Traditional Bain/Mason Industrial Organization Paradigm (Porter 1981) ... 35

Figure 4.6 Reformed Equations ... 36

Figure 4.7 The central or local warehousing facilities... 42

Figure 4.8 Conceptual model ... 43

Figure 5.1 Current UK distribution prototype ... 46

Figure 5.2 Order fulfillment process... 47

Figure 5.3 Relationships of operation terminologies ... 48

Figure 5.4 Cumulative frequencies for customer delivery... 53

Figure 5.5 Current distribution network... 53

Figure 5.6 Proposed distribution network... 58

Figure 5.7 Current Italian distribution prototype ... 63

Figure 5.8 IT frequencies for customer delivery... 67

Figure 5.9 Current distribution network... 67

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List of Tables

Table 4.1 Definition of Decision areas (Slack and Lewis 2008, p21-22). ... 30

Table 4.2 Considerations of Centralized and decentralized warehousing facility... 41

Table 4.3 Advantages and disadvantages of the use of 3PL ... 44

Table 5.1 UK market performance in 2008 ... 47

Table 5.2 Average shipment size ... 49

Table 5.3 Number of cartons per shipment in 2008... 50

Table 5.4 S&D in UK ... 50

Table 5.5 Types of order ... 51

Table 5.6 Average consumption per customer in UK... 52

Table 5.7 Average # shipments per customer ... 52

Table 5.8 Lead time by Movianto ... 54

Table 5.9 The explanation of the formula (referring to Simchi-Levi et al. 2008, P42) . 54 Table 5.10 Outbound transportation cost in ₤... 57

Table 5.11 Exchange rate... 57

Table 5.12 summaries of performance outcomes in UK current distribution network.. 58

Table 5.13 Lead time by DHL Economy and Express... 59

Table 5.14 Outbound logistics cost... 60

Table 5.15 Outbound transportation cost ... 61

Table 5.16 Summaries of performance objectives in proposed distribution network ... 62

Table 5.17 Italian mark performance in 2008... 63

Table 5.18 Average shipment size ... 64

Table 5.19 Number of cartons per shipment in customers... 65

Table 5.20 Average Revenue and contribution margin per syringe and disposable... 65

Table 5.21 Types of order ... 66

Table 5.22 Average consumption per customer... 66

Table 5.23 Average # shipments per customer ... 66

Table 5.24 Lead time by GLS ... 68

Table 5.25 the modified parameters... 68

Table 5.27 Summaries of performance objectives in current distribution network... 70

Table 5.28 Lead time by DHL Economy and DHL Express ... 71

Table 5.29 Outbound logistics cost... 73

Table 5.30 DHL Economy delivery and Normal transportation carrier delivery ... 74

Table 5.32 Summaries of performance objectives in proposed distribution network ... 75

Table 5.33 Sensitivity analysis of transportation model in local warehousing facility (UK) ... 77

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Chapter 1 Introduction

Chapter one is devoted to the organization background, structure and the product groups, portraying the environment in which MEBV is navigating.

1.1 Medrad

Medrad was founded in 1964, near Pittsburgh, Pennsylvania, U.S.A. After more than 40 years’ development, it has grown to become a worldwide leading provider of medical devices and services that enable and enhance imaging procedures of the human body. At a global level, its revenue reached Euro 395.4 million in 2008 with an average annual growth rate of 10-15%. Carrying on with the spirit of the slogan “Performance. For life.”, Medrad is continuously committed to working on the pioneer medical devices and a variety of services. It is an affiliate of Bayer AG1 since 2006 and acquired Possis Medical2 in last year. Through the acquisition, Medrad expects to have an organic growth containing the existing product portfolios, as opposed to expansion that comes from buying new businesses.

The company’s mission3 is to be a global market leader of innovative, high quality diagnostic imaging and therapeutic medical devices and services that improve healthcare for patients worldwide. The company will accomplish this mission by achieving performance excellence across five corporate goals, which are

Exceed the Financial objectives Grow the Company

Improve Quality and Productivity Improve Customer Satisfaction

Improve Employee Growth and Satisfaction

1

Bayer AG is a global enterprise with core competencies in the fields of health care, nutrition and high-tech materials. (The information is from http://www.medrad.com/newsroom/display-press-release.html?PRid=222 and viewed at 12.40 P.M on 23rd March 2009.)

2

Possis Medical develops manufactures and markets pioneering medical devices for the large and growing cardiovascular and vascular treatment markets. (The information is from

http://www.medrad.com/newsroom/display-press-release.html?PRid=222 and viewed at 12.40 P.M on 23rd March 2009.)

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1.2 Medrad Europe B.V. (MEBV)

Medrad Europe B.V., as a wholly owned subsidiary of Medrad and its legally authorized European headquarters was established in the year of 1989 by Mr. John Tedeschi4. It is located in Maastricht, The Netherlands. With the growth of business, its subsidiaries were open in France, Germany, Italy, UK, Norway, Sweden, and Denmark in succession, among which, MEBV operates directly in the region of Benelux instead of the Netherlands alone. The main business activities in Europe are sales and services. Hence, their products are mostly supplied by Medard in Pittsburgh. In 2008, the total revenue in the direct European markets increased by 11.3% to Euro 82.9 million, which is almost 1/5 of the worldwide turnover.

In order to support the worldwide business activity better, the international mission statement5 is to lead Medrad to achieve substantial and sustainable international growth and represent the Medrad Brand by delivering regional customer solutions.

1.3 Logistics department

It is useful to mention the Logistics department in which the project is conducted. The objective of the Logistics department in MEBV is to focus on quality, cost and delivery performance, and at the same time, provide employees with an environment for them to excel and succeed. This is in line with the strategy of Medrad’s Global Supply Chain Management team (GSCM), which aims to improve customer satisfaction and end-to-end supply chain management. At a European level, it consists of central operation in the Netherlands and local operations in France, UK, Italy, and Norway respectively, and works closely with third-party logistics (3PL) providers. In total, there are 8 employees working in the Logistics department, 3 are located in Maastricht, and the remaining are recruited to serve in the local warehousing facility in the ratio of 1:1 except in France where there are two full time workers because of the higher annual demand. In 2008, the freight including inbound and outbound transportation cost allocated to the Logistics cost center in MEBV was almost 3.5 million euros, which is around 18% of the company’s expenditures.

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instance, they are responsible for every 3PL contract. The local operation is involved in the daily operations such as outbound transportation arrangement.

The other difference is reflected in their types of warehousing: MEBV’s warehouse is contracted6 and the local ones are private7. This difference is caused by the past management. As a result, warehousing activities are provided by 3PL in the former and operated in-house in the latter. On the other hand, as a traditional warehousing strategy, they are both required to carry stock and provide downstream customers with inventory when needed (Simchi-Levi et al. 2008, p231).

1.4 Organization Structure and the Product Groups

Recently, Medrad is organized on a business-based structure (BUS), which consists of Interventional, Radiology, and International/Service in the divisional level with a different structure and 3 centralized support functions which contain Human Resources (HR), Information Technology (IT), Accounting, International Property, Quality system etc. in general. Obviously, Medrad operates with a hybrid structure by using a multidimensional structure and creates self-contained divisions; then selecting the structure (Jones 2010, p193). When the hybrid structure is managed effectively, its selected structure in each division can best meet the needs of the particular environment, strategy, and so on (Jones 2010, p193). On the other hand, it is very expensive to operate. Since each division has a full complement of support functions, there might be an extensive duplication of activities within the organization (Jones 2010, p182). A simplified worldwide organization chart is depicted in Figure 1.1. As shown in the divisional level, the last segment focuses on the services and overseas business. Hence, MEBV is included in this division as a separated operational entity outside of the States. Since it is the European headquarters, MEBV is grouped to the European operations as highlighted in dash Oval in the figure below.

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Contract warehousing is a variation of public warehousing. It is an arrangement between the user and provider of the warehousing service, which in some cases is a 3PL (Grant et al. 2006, p234). It charges customer for both material handling and storage (Chopra and Meindl 2007, p239).

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CEO

Interventional Business

Radiology

Business International_/Services

Sales Marketing Operations Services Sales Marketing Operations (GSCM) Services Europe GDN International Japan Service Australia

CAO Group CDI Group CCO Group

Functional structure

Geographic structure

Figure 1.1 A simplified Medrad organization chart

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MEBV MVA Clinical Support Service Sales HR IT Logistics Finance Central Operations 3PL Local Operations Medrad Global Supply Chain

Market

Supportive functions Core functions

Figure 1.2 A simplified MEBV organization chart

The first two divisions are made up of various product groups. The most respective product lines in Radiology9 are computed tomography (CT), magnetic resonance (MR) and the ones in Interventional10 are MEDRAD/ Possis® and MEDRAD Avanta®. For each product line, Medrad delivers a range of types of the equipments, as shown in the example of CT in Figure 1.3. It can be Stellant® CT or Vistron® CT, etc.

9

Radiology is the study of images of the human body by the use of radiant energy. The original field of radiology involved the use of X-ray or radiological devices in medical imaging, but today radiology also includes high frequency sound, magnetic, and radioactive imaging. View

http://www.superpages.com/supertips/radiology.html at 19.15 on 28th August, 2009.

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There are two branches in this area as explained below.

1. Interventional Radiology involves the use of imaging guidance for the purpose of treating patients. View http://www.cirse.org/index.php?pid=4#history at 19.35 on 28th August, 2009

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Radiology

Equipment •Types

Stellant® CT Spectris Solaris® MR

Interventional

Vistron® CT MEDRAD Avanta® Possis®

S&D •Versions

SPESOL SYR one standing outside of tyvek pkg SDS_CTP_ SPK 125 ML and 200 ML CT SYR XMI Multi – Patient Disposable Syringe

Figure 1.3 A brief example picture of ME and S&D

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0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Units 2004 Units 2006 Units 2008 Rev 2005 Rev 2007 Margin 2004 Margin 2006 Margin 2008

Units; Revenue and Gross Margin in Europe in 2008

ME S&D

Figure 1.4 Units; Revenue and Gross Margin of ME and S&D between 2004 and 2008

1.5 Environment

The position of MEBV at the same time is influenced by the external factors, including the political and legal; economic; culture and social; and competitive environment (Grant et al. 2006, p303) as briefly presented below.

1. Annual study (2008) by Arvato Services with the help of Buck Consultants International gave an insight into the current supply chain set-up of Medtech companies in Europe. There are 13 companies participating in the survey, including Philips; Siemens and so forth. 10 of the participants are originated from U.S.A. 2 are from Europe and 1 is situated in Japan. All of them choose to either locate their European distribution center (EDC)11 in the Netherlands, or Germany, or Belgium. And the majorities of them perform EDC in-house and outsource regional distribution centers (RDC) and national distribution centers (NDC) to 3PL. In contrast, MEBV works the other way around, with EDC outsourced and NDC performed in-house. The concepts of private and public warehousing facility have been given in section 1.3 and their related advantages and disadvantages will be further discussed later in section 4.5. 2. In addition, the current Medrad’s decentralized distribution structure (NDC) is formulated in the way by following the expanded sales scale owing to the belief that the fast delivery can only be guaranteed when there is a local warehouse. In the

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meantime, the merges and developments in freight carriers are constantly pushing out the frontier of delivery capabilities and making the cost more competitive at the same time. As a consequence, it might challenge the original belief of the presence of local warehouse for the fast delivery.

3. In Bayer AG, one of the decisions in its supply chain design is to use the decentralized warehousing facility in compliance with pharmaceutical grade either for one region or country. The general contract is negotiated by Bayer AG and each division performs the business activity in a comparatively independent manner but by following the same supply chain strategy. This is called “Shopping mall concept”, which indicates that all business have their own operations but under one roof. As an affiliate of Bayer AG, this notion applies virtually to MEBV as well.

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Chapter 2 Problem Statement

In this chapter, the purpose of conducting the research is presented. In order to achieve the objectives, the main research questions and sub questions are formulated in the certain scopes.

2.1 Management Problem

It was not expected that MEBV would grow so fast from an office of only 2 persons in 1989 till approximately 180 employees working in Europe now. On average, the company has 10-15% yearly revenue growth since start-up.

Up till the first half year of 2007, the European supply network was managed by Medrad in USA with the execution delegated to several other departments like Customer Support in MEBV. Under such informal management, the S&D followed the expanded sales scale to have local warehouses in France etc. as mentioned in the previous chapter and ME was remained in the central warehouse in Maastricht because of the required technical workforce. In the global environment of the cost rationalization, the pressure is constantly put on GSCM group to ensure that MEBV supports its customers at the right service level but at the same time in most cost efficient way.

In 2006, the distribution system concerning ME has been studied by centre-of-gravity approach12. The model applied for ME was confirmed from that time onwards. Nevertheless, the management board is still confronted with a dilemma referring to the S&D distribution network.

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Even though S&D have much lower value compared to ME, its supply chain structure is certainly worthwhile being studied in the light of the impressive profit margin which is on average 15% higher than that of ME based on the annual sales units from 2004 to 2008.

2.2 Current S&D Sales and Distribution Channels

In general, MEBV serves three kinds of customers as follows. They are configured in Figure 2.1.

1. Original equipment manufacturer (OEM) such as GE, Philips, and Siemens. Usually, OEM signs the contract with hospital to deliver an entire package for the scanning room, for instance. In other word, this is called “one stop shop” service in marketing, by providing many services in one place; shops can offer customers the convenience of obtaining their needs in one stop13. For some of the equipments and accessories which are included in the contract but are not manufactured in their factories, they will be subcontracted to other capable companies, like CT, MR from MEBV.

2. Distributors, who are generally entrusted with the maintenance of Medrad devices and S&D sales when MEBV does not have direct sales offices in some countries like Poland, Russia.

3. And end users who are approached directly by the sales representative in MEBV and its subsidiaries. They are usually hospitals. In total, there are 10 direct sales markets in Europe as listed in the previous section 1.2.

The units of S&D sold by MEBV to the first group of OEM customers are minimized as much as possible. The main reason is that MEBV does not want to create the complexity of the sales channels. As mentioned above, the distributors take care of the after-sales services of Medrad. However, they are usually more interested in the business of selling S&D because of the generous profit margin. Suppose OEMs encroach the distributors’ domain with Medrad’s S&D by taking advantage of their broad coverage of sales channels, strong negation power to the customers, competitive transportation costs, being less greedy on the profit margin and so forth, it will have big negative impact on the distributors’ sales and further influence their motivation to continue other business activities with MEBV. Therefore, this group of customers can be neglected.

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As for the distributors, they typically adopted Ex works (Maastricht), which is one of the 13 INCOTERMS14 2000. This term means that MEBV deliver the goods at the disposal of the buyer at the MEBV’s premises or another named place without any clearance for export and loading on any collecting vehicle15. Therefore, MEBV completes its duties as long as the products are ready to be picked up at the agreed time and quantities in MEBV’s warehouse. In addition, the basic reason to work with distributors is that the sales quantities are still under developed and the local market is immature.

The last category is called direct marketing channel, through which, the company sells directly to consumer (Kotler et al. 2006, p364). As highlighted in Figure 2.1, the current distribution network consists of three following scenarios.

1. For the subsidiaries which have no own warehouses, they follow the procedure as having the direct shipment from MEBV to the end users.

2. In France and Italy, their stock is mainly replenished by Medrad in U.S.A for the reason of total less replenishment cost by direct shipment rather than via the central warehouse in between, with MEBV as a backup in case of the emergency.

3. The most special cases are held in UK and Norway. Although they have their own leased warehouse, their stock was replenished from MEBV due to the issue of having less economic benefit from the current sales quantity.

No matter under which situations, MEBV and its local warehouses act as the order penetration point (OPP). From this point, the downstream is driven by customer orders; upstream processes are driven by forecasts and plans (Schőnsleben 2007, p41). Since S&D is made to stock, the delivery takes place from MEBV or its local warehouse on customer’s request in Europe. Noticeably, pull strategy is applied to European portion of worldwide supply chain for Medrad. OPP and pull strategy will be further explored in section 4.3.

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Supplier (mainly in USA) The rest of subsidiaries End users Distribution Center MEBV (Maastricht)

Syringes and Disposables (S & D) End users End users Distributors Original Equipment Manufacturer MEDRAD UK and Norway MEDRAD France and Italy Direct Market Physical flow Information flow Backup replenish flow

Figure 2.1 A simplified European distribution network of Syringes and Disposables (S&D)

2.3 Research Objective and Research Questions

Based on the management problem, the research objective is set to identify the drivers which influence the logistics performance in the near future related to the decision making of centralized or decentralized distribution network, and private or public warehouse.

Hence, my research question is raised below.

Which drivers including those influenced or least influenced by the Logistics department of MEBV can cause the effect on the supply chain performance in centralized or decentralized distribution structure for S&D in the direct sales market of MEBV?

And the next question is

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2.4 Sub Questions

Sub questions are formulated in order to contribute to the solutions of main research questions. Concerning the first research question, they are:

1. Which logistics performances are important for the supply chain design in the near future?

2. Which drivers influenced by the Logistics department of MEBV are determining these logistics performances?

3. Which drivers least influenced by the Logistics department of MEBV can still determine these logistics performances?

4. How do they affect on these logistics performances?

Regarding the second research question, the sub questions are:

1. Which logistics performances are considered to outweigh the others in decision making of private or public warehouse?

2. How does MEBV cope with the downside of either private warehouse or public warehouse?

2.5 Research Scopes

1. The study is engaged for the supply chain management of MEBV. Therefore, any performance objectives considered are from the European perspective.

2. When considering decentralization, the local warehousing facility coverage is based on the national level instead of the regional level.

3. The research is applicable to and deliverable for the European direct market.

4. Although the research question regarding the private and public warehouse has been put forward, the answers will be given in Chapter 7 due to the research time constrain. This is certainly the start of this subject and is recommended and deserves to be further investigated. Their strategic importance will be addressed in section 4.5.

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Chapter 3 Research Design

In order to answer the research questions, it is useful to have an overall blueprint of the research. It includes the research plan for the structure of investigation; the data gathering and methodology concerning what data to collect and how to collect them, and the configuration of the datasets in order to represent the targeted population (Cooper and Schindler 2003, p138).

3.1 Research Plan

Based on the research objective, the study is set to develop an ideal supply chain model by pursuing required key performance objectives and their generally related drivers (Figure 3.1). It can be represented by the following formula:

Supply chain performance objectives = f (Independent variables, Designed variables)

The designed variables are defined as shipping S&D from central or local warehousing facility. They have been envisioned by MEBV. The Independent variables are seen as the synonyms for the drivers mentioned in the research question and objective. It can be influenced and least influenced by the Logistics department of MEBV.

The ideal model is used as reference for evaluating the performance of the current distribution network. It will be experimented on two of the selected direct markets in order to collect factual information about presumed relationship between two sides of the above formula. Based on the outcomes, a revised supply chain structure might be recommended with the consideration of external environment. These areas will be organized into 8 chapters as follows and illustrated in Figure 3.1.

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conceptual model is conducted in two of the selected direct markets, while Chapter 6 discusses the findings and eventually is able to provide the answers to the research questions. Chapter 7 validates the collected data and the conceptual model by comparing them to the existing accounting data. Furthermore, the 2nd research question and its 2 sub questions are answered through the consideration of changing the actors who perform the warehousing activities. The paper ends with the recommendation to show the potential direction for the future investigation.

Ideal Model (Chapter 4)

1. Required key performance indicators 2. Drivers for the performance indicators

• Review the literature/concept • View of experts

• Observation of MEBV business

External Business Environment (Chapter 1)

1. Current supply chain set-up among Medtech companies

2. Number of changing things taking place: like capability of freight carrier 3. In line with Bayer’s SCM strategy 4. Combination of cost rationalization and

required service level Current situation

(Chapter 1 & 2) 1. Company

2. Product groups (S&D) 3. Current SC evolved

over time

Model and Data validation (Chapter 7)

• The validity of data and model

Experimental Study (Chapter 5)

1. Current distribution network 2. Proposed distribution network Reference for the

evaluation of current approach

Applied to two of the direct markets

Conclusion (Chapter 6) • Statement of findings Limitations and

Recommendations (Chapter 8) • Direction for future investigation Figure 3.1 Research Plan (Chapter 3)

3.2 Data gathering and Methodology

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by following a rather standard questionnaire (Appendix 2) so that the author can focus on exactly the same issue from different angles at each meeting. These diverse perspectives were obtained from multiple respondents in the following departments: Sales; OEM; Global Distributor Network (GDN); Marketing; Customer Supporter, Logistics, and GSCM which are in one way or another related to the supply chain design. The majority of the selected interviewees were either the department’s manager or supervisor in MEBV. Two of them were requested from the Medrad’s 3PL provider concerning the topic of private or public warehouse. They are warehousing manager from CEVA16 and business development manager from DHL. In this way, the reliability and availability of the gathered information are increased. Every single interview was carried out in 1-2 hours either by face-to-face conversation or telephone for the reason of inconvenient location.

In the meantime, the author observed how the operation decision is made on the daily business: such as the choice of freight carrier, and the method of dealing with emergency. Such information is to calibrate some of the parameters used in the model, which not only enables it to reflect the distribution network more accurately, but also recommends potential improvements in the utilization of the existing network (Simchi-Levi et al. 2003, p91). Lastly yet importantly, the non-qualitative data was extracted from SAP with the help of IT manager in order to quantify the relations between variables and performance objectives.

From the start of research, all the collected internal materials, interview transcriptions and the answers, the record of observations, the daily operation information taking place in local warehouse and 3PL provider which were proceeded by email or personal communication and quantitative data from SAP and 3PL provider, were coded within 2 formats: the word document containing the qualitative data, and the Excel spreading sheet for the non-qualitative data. Both types of documents were processed by means of triangulation. Any contradictory or incomplete parts were sorted out. Due to the issue of time constrain, they were usually confirmed with MEBV Logistics Manager. Otherwise, Delphi method is a better structured technique for reaching a consensus with a panel of experts and eliminate the danger of one or a few strong-willed individuals dominating the decision-making process (Simchi-Levi et al. 2003, p57). For example, the discussion of service level requirement regarding the lead time differs from OEM Account and Sales manager. The former thought that 3 to 5 working days are appropriate based on the previous working experience if the sales representative approaches the customer in the

16

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right manner. The latter confined the lead time to 2-working day in 90% of the cases and 10% of the shipments was required within 24 hours. In this respect, if the author could invite a group of salespeople who have a good understanding of market requirements, their opinions could be compiled and summarized and each individual was given the opportunity to change his or her opinion after seeing the summary; this process was repeated until consensus was achieved (Simchi-Levi et al. 2003, p58); the judgment would be more convincing and reliable. Although this judgment method has not been executed in this research, the survey was designed and attached in Appendix 3 for the potential investigation in the near future.

3.3 Sample description

For the purpose of testing idea model mainly built on the theories, the quantitative data was collected in different ways. The most important one is used for the analysis of demand and distribution pattern. Some of the important criteria used to create data set are briefly presented below. A comprehensive template of mining database was attached in Appendix 4.

• Types of Product: all the S&D

• Destination of Shipping: European direct markets • Origin of Shipping: any countries in the Europe • Types of Order: all the orders placed by the end users • Delivery date: taking place in 2008

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Chapter 4 Conceptual Model

A model is defined as a representation of a system, which is constructed to study some aspects of that system or the system as a whole (Cooper and Schindler 2003, p55). By following the simple formula expressed in words in the research plan, the conceptual model is designed for the visualization of the relationship among the variables assumed to be of importance and the required supply chain performance objectives (Welker and Broekhuis 2008). The model will be further deployed to obtain the empirical evidence on those relationships (Cooper and Schindler, 2003, p138). Literatures concerning the performance objectives and two general types of variables are reviewed beforehand in order to state the uniformities, narrow down the range, and predict phenomena (facts) (Cooper and Schindler, 2003, p54).

4.1 Supply chain management

Before dwelling on the logistics performances, the supply chain management (SCM) will be firstly defined in general terms. According to Simchi-Levi et al. (2003, p1), SCM is interpreted as a set of approaches utilized to efficiently integrate all the players so that merchandise is produced and distributed at the right quantities, to the right locations, and at the right time, in order to minimize system wide costs while satisfying service level requirements.

Based on the definition, one of its objectives is to be efficient and effective across the entire system rather than simply to emphasize on one or two activity cost(s). The similar study can be found in Chopra and Meindl (2007, p5). It states that the objective of every supply chain should be to maximize the overall value generated. The value of a supply chain generates is defined as the difference between what the final product is worth to the customer and the cost the supply chain incurs in filling the customer’s request. The bigger the difference, the more values will be generated. In return, the more successful the objective of the supply chain can be achieved.

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As the policy deployed from GSCM, MEBV aims for the external customers’ satisfaction regarding the quality and delivery performance, and internal cost rationalization for the entire European distribution network. Following the principle of the aforementioned SCM definition, the difference between the internal and external dimension is the overall value generated by MEBV SC.

However, it is challenging and far from trivial to design and operate such a chain so that the system wide cost is minimized and the overall service level is maximized (Simchi-Levi et al. 2003, p2) for several reasons: a) SC is a complex network. b) Different facilities in the SC frequently have conflicting objectives. c) The chain is a dynamic system, and d) System varies over time. Centering on a single organization, there are even more decision issues taken into consideration from the perspective of SCM and they span over a large spectrum of a firm’s activities, such as Inventory Control, Production Sourcing, and so forth (Simchi-Levi et al. 2003, P2). Any of them is going to affect supply chain performances. In general, these issues can be classified into 4 decision areas in order to manage the resources of the operation (Slack and Lewis 2008, p21). They are capacity, supply network, including purchasing and logistics, process technology and development and organization. Each decision area has its own focus and their concerned ranges are summarized in Table 4.1. Therefore, it is interesting to find the generic drivers which influence the supply chain performances related to the centralized or decentralized distribution network. Not surprisingly, the defined variables are in the range of capacity and supply network strategy since shipping from centralized or decentralized warehousing facility is related to the number of sites in Europe (Slack and Lewis 2008, p80) and thus might change the configuration of the supply network and the scope of the activities performed in each operations (Slack and Lewis 2008, p130).

Decision Areas Concerns…

1. Capacity strategy how capacity and facilities in general are configured. 2. Supply network strategy,

including purchasing and logistics

how operations relate to its interconnected network of other operations.

3. Process technology strategy

the choice and development of the system, machines and processes which act (in)directly on transformed resources to convert them into finished products and services..

4. development and organization

the set of broad- and long-term decisions governing how the operation is run on a continuing basis.

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4.2 Supply Chain Performance Objectives

As it was proposed in the formula, the first question is “which service level requirements do the customers want”? The keys lie in the market requirements perspective. Slack and Lewis (2008, p13) summarized 5 generic performance objectives which can be applied to any types of operation. They are quality; speed; dependability; flexibility and cost, although their priority will differ in cases and over time. When referring to “value metrics” explained at the beginning, quality; dependability and flexibility will be grouped into the leading dimension and the remaining belong to the lagging indicators. To some extent, it is recognized that these aspects of performance will trade off against each other (Slack and Lewis 2008, p55). Hence, they are distinguished by the order-winning and qualifying factors in general (Slack and Lewis 2008, Hill 1993). The former is seen as the most direct and significant contribution to win the business. The latter is viewed as a particular level to be considered by the customers for the business (Slack and Lewis 2008, p45). Traditionally, performance measurement has been seen as a means of quantifying the efficiency (cost) and effectiveness (customer related performances) of action (Slack and Lewis 2008, Perona et al. 2002). Figure 4.1 shows their relation. For example, A and B lying in concave line reflects the trade-off of their relative performances: priority in effectiveness (A) or efficiency (B). They are presumably influenced by the market strategies.

Effectiveness (Customer related performances) Efficiency (Cost related performances)

A

B

H L L H

Figure 4.1 Trade-off between efficiency and effectiveness

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development (Johansson et al. 1993, p4). The numerator and dominator represent the leading and lagging indicators respectively. The leading factors for the organizational growth are driven by improving the quality and service, and the lagging factors are considered to be the reduction of the cost and cycle time. Additionally, this equation is particularly helpful as it emphasizes the total value by including all the performances and can clearly indicate how each performance measure is influenced in the quantitative manner and thus is reflected in the final outcomes.

Value

Quality

Service

Cost

Lead Time

•Meeting Customer Requirements •Fitness for Use

•Process Integrity •Minimum Variances •Elimination of Waste •Continuous Improvement •Customer Support •Product Service •Product Support

•Flexibility to Meet Customer Demands

•Flexibility to Meet Market Changes

•Design and Engineering Conversion •Quality Assurance •Distribution •Administration •Inventory •Materials •Time to Market - Concept to Delivery - Order Entry to Delivery •Response to Market Forces •Lead Time -Design - Conversion -Engineering - Delivery •Materials •Inventory

x

=

Figure 4.2 Value Metrics (Johansson et al. 1993, p4)

The market requirements and operations resources analysis for MEBV

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themselves, which is dependability. It refers to as on-time order completion for the customers translated from the original meaning of keeping delivery promises (Slack and Lewis 2008, p38). Therefore, the dependability is measured by the number of orders which can be completed on time as its promise to the end users. The importance of cost is differentiated by the markets. It weighs more critically in the single-used country than the multi-used country due to the consumption volumes. Even in the less important case, the saving in the cost will be eventually added to the overall profit and thus improve the overall organization performance because it belongs to the lagging dimension. The cost refers to system wide logistics cost, the elements of which are following the prototype of the centralized or decentralized warehousing facilities illustrated in Figure 4.7. In addition, due to the current different warehousing types, the cost structure differs as elaborated below.

• Inventory cost: holding cost of safety stock • Warehousing cost

Private warehouse / leased warehouse / In-house operation

Public warehouse / Contracted warehouse / 3PL

Storage cost Storage cost Inbound logistics Inbound logistics Outbound logistics cost Outbound logistics cost Building and utilities cost

Labor cost

• Transportation cost: inbound and outbound transportation cost

The flexibility is not included since Medrad has already maximized the magnitude unless the ordering policy with regard to having no boundary for the ordering time and quantities is adapted.

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QUALITY of products The package in good condition * SPEED indicating the market required

lead time

The recognition of the need for an order and the

receipt of goods * DEPENDABILITY with regard to on-time order completion Keeping delivery promises * COST in terms of minimizing system wide logistics cost

System wide Logistics cost***/*

Number of warehousing facilities (Re)configuration * Qualifying factor *** Order-winning factor CAPACITY SUPPLY NETWORK PROCESS TEHCNOL OGY DEVELOPME NT AND ORGANISATI ON

Figure 4.3 Operations strategy matrix analysis for MEBV

(Adjusted based on Slack and Lewis 2008, p28 Figure 1.10)

4.3 Supply Chain Strategy

Different paradigms have been developed one after another to emphasize the importance of supply chain strategy. The traditional ones are often categorized as push or pull strategies which probably stems from the manufacturing revolution of the 1980s (Simchi-Levi et al. 2003, p188). The focus of the former is on cost minimization by better utilizing resources such as in production, transportation and inventory (Simchi-Levi et al. 2003, p189). It is characterized by low demand uncertainty and long lead time. While the latter aims at providing a flexible and responsive supply chain to customer demand (Simchi-Levi et al. 2003, p189). It usually faces high demand uncertainty in a short cycle time. In 1997, Fisher proposes a new framework for the supply chain design based on the nature of the demand for the company’s product. He found that functional products require an efficient process while innovative products are matched with a responsive supply chain (Fisher 1997). Afterwards, Mason-Jones et al. (2000)

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customer order decoupling point (CODP). In addition to the interpretation defined in section 2.2, the decoupling point is often held as a buffer between fluctuating customer orders and/or product variety, and smooth production output (Naylor et al. 1999). By linking to CODP, a new supply chain strategy, called “leagility” is built up based on the careful combination of both lean and agile paradigms. In this new strategy, the lean paradigm is applied to the supply upstream of the OPP in order to eliminate all the waste and the agile paradigm must be applied downstream from the OPP for the responsiveness of market requirements (Naylor et al. 1999). The same principle is suitable for push-pull supply chain strategy which takes advantage of the best of them (Simchi-Levi et al. 2003, p190). These combined supply chain strategies with the primary objectives are illustrated in Figure 4.4.

Push strategy Pull strategy

Lean Agile

Raw materials _{End Customer}

CODP Traditional supply chain strategy Mason-Jones et al. (2000) Cost minimization Market responsiveness Figure 4.4 Push-pull and leagility among supply chain structure

(Adjusted based on Simchi-Levi et al. 2003, p190 Figure 6-8)

Supply Chain Strategy for MEBV

As Porter (1981) found that a firm’s performance in the marketplace depends critically on the characteristics of the industry environment in which it competes. This finding can be formulated as structure-conduct performance framework in Figure 3.1. Referring to the section 1.5, the combination of cost efficiency and required service level is the outlook in the healthcare industry. Additionally, in view of the specialty of this industry which is to save patient’s life as the highest priorities (Nieva and Sorra 2003), an appropriate responsive supply chain is still predominant, but with the objective of controlling cost. This fits the principle of push-pull or leagility paradigm in Figure 4.4

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4.4 Variables

By borrowing the ideas of 5 performance objectives, value matrix and efficiency & effectiveness dimensions, the equation proposed in Chapter 3 can be interpreted in Figure 4.6. The original concepts from value matrix are replaced by the 4 defined performance objectives of MEBV. In the meantime, they can be differentiated based on the efficiency & effectiveness dimension respectively (Figure 4.6). Although the elements for the cost performance elaborated in the section 4.2 can be focused on 2 different objectives ─ cost minimization and Market responsiveness, there is no discussion to position the performance objective of cost in the efficiency dimension because the sum of these elements is regarded as the synonyms for system wide cost.

The simultaneous change of both independent and designed variables will trigger each of the performance objectives and all of them will be eventually reflected in the “Total Value”. Not every performance objective has the same variables according to the findings. This will be further discussed from section 4.4.2 to 4.4.3. Additionally, some of the independent variables do influence the supply chain performance objectives although they cannot be manipulated by the Logistics department alone. These valuable drivers are still programmed but in a separated category, called complexity issue/least influenced. In general, the independent and designed variables are group into 2 layers: short term and middle/long term in terms of the time line. And they are initially outlined in section 4.4.1.

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4.4.1 Outlines of variables Short term

The following variables are independent and can be manipulated by the Logistics department. 1. Transportation models in terms of the service agreement

2. Types of order

3. Larger shipments for the quantity discount

Middle/Long term

The following variables are independent and can be manipulated by the Logistics department 1. Distance between the proximity warehousing facility and customers

2. Service level requirement regarding the lead time 3. Distance between two warehousing facilities 4. The availability of the products

5. Replenishment cycle and cycle stock 6. Accessing and handling spaces

The following variables are independent and are least manipulated by the Logistics department. 1. Product demand volatility and Product volume

2. Geographical distribution of demand

3. The frequencies for customer delivery and shipment sizes 4. Customer demand variety

5. Packaging

6. Annual flow through the warehouse

The following variables are designed.

1. Shipping from local warehousing facility 2. Or shipping from central warehousing facility

4.4.2 Independent variables

Influenced independent variables

Quality ▬ the package in good condition

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Speed ▬ lead time

It is without doubtful that distance has impact on the lead time when end users could receive the products (Chopra and Meindl 2007, Simchi-Levi et al. 2003). The loner the distance between warehousing facility and customers, the average traveling time to the customer will be increased. Moreover, Companies can choose different transportation modes for products, like air, truck and so forth. Each mode has different service levels with respect to the speed, size of shipments (individual parcels to pallets to full trucks to entire ship), cost of shipping and flexibility that lead companies to choose one particular mode over the other (Chopra and Meindl 2007, p54).Transportation choices have a large impact on supply chain effectiveness and efficiency (Chopra and Meindl 2007, p45). Small package carriers such as DHL are the preferred transporters for the time-sensitivity products, but also less efficient given the high costs (Chopra and Meindl 2007, Grant et al. 2006).

Dependability ▬ on-time order completion

In principle, dependability is the difference between the due delivery time and actual delivery time (Slack and Lewis 2008, p39). If due delivery time > actual delivery time, high dependability could be achieved, such as blanket orders with the scheduled delivery time. If due delivery time = actual delivery time, the latter can be the consequence of distance and modes of transportation as specified above. Or it is decided by the availability of the products. The less probability of stock out per order cycle, the higher service level is achieved (Schőnsleben 2007, p554). Higher service level comes at an increased safety stock. In return, the more dependable the products can be shipped on time. In short, blanket orders, distance, transportation mode, and the availability of the products influence the actual delivery time.

Outbound Transportation Cost

The distance between shipping and receiving the goods and transportation modes, each of them affects the level of service that the company could provide to the customers. The customer service level (Grant et al. 2006, p217), especially concerning the lead time is the indispensable objective of the logistics management in Medrad. 2-day lead time is considered to be standard in 90% of the cases, however, comes at a cost.

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Cost varies considerably with volume of shipment (cube), weight of shipment (Grant et al. 2006, p20). To some extent, the transportation costs on a per-item or per-tonne basis will be less for larger shipments (Grant et al. 2006, p216). Secondly, in conjunction with the frequency of delivery, the total transportation cost is higher in smaller shipments with frequent delivery than in the larger shipments but occasional delivery. Nevertheless, the frequencies for customer delivery and shipment sizes are least determined by MEBV.

The traffic function is also interfacing with the packaging when the freight charges are in relation to the volume weight. Hence, products that can be packed more compactly are cheaper to transport (Slack and Lewis 2008, p342). However, different products might simply differ in the types of packaging and they are supplied on the customer’s request, which is hardly influenced by the supplier.

Inbound transportation cost / Inventory cost / Storage cost incurred in the Contracted warehouse / building cost from in-house operation

Since the principle objective of the inbound transportation is different from the outbound transportation, the terminologies of frequencies for customer delivery and shipment sizes are replaced by the replenishment cycle and cycle stock. In addition to the distance between 2 warehousing facilities, choices of transportation modes and the compactness of packaging all have the impacts on the inbound transportation cost. In the meantime, with the increase in cycle stock, however, also comes an increase in carrying costs for the inventory; and storage costs in the situation of contracted warehousing (Chopra and Meindl 2007, Simchi-Levi et al. 2003). Together with holding the safety stock, it further triggers the increase of facility cost because it is proportional to warehouse size (capacity) but in a nonlinear way (Simchi-Levi et al. 2003, p88). Among this cause-and-effect chain, some other factors also plays a role in one way or another, for example, accessing and handling space for the capacity in warehouse (Sunil et al. 2007, Grant et al. 2006)

Labor and utilities cost

It is proportional to the annual flow through the warehouse (Simchi-Levi et al. 2003, p88).

Least influenced independent variables

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products and so forth (Perona et al. 2002). On the one hand, variety of suppliers, products, and distribution channels can increase the competitive advantage for the company, but increase coordination and management costs on the other hand, up to the point of more than counterbalancing that competitiveness (Perona et al. 2002).

Geographical distribution of demand

Customer order size is indicator of demand volume (Olhager 2003). However, if they are geographically distributed associated with small order size every time, it would be hardly to achieve the economy of scale in the transportation management, let alone the customers demand immediate service. Outsourcing allows buyer to transfer demand uncertainty to the freight carriers. One advantage that the carriers have is that they aggregate demand from many buying companies and thus reduce uncertainty through the risk-pooling effect (Simchi-Levi et al. 2003, p281).

Product demand volatility and product demand

This proliferation of products makes it increasingly difficult to predict demand for a specific model (Simchi-Levi et al. 2003, p31). Each of the product demand volatility indicates to what extent it is possible or reasonable to make products to order or to stock (Olhager 2003). Low volatility means that the item can be forecast-driven and high volatility makes forecasting difficult, wherefore such items typically need to be produced to order (Olhager 2003). In the meantime, product volume is related to demand volatility in that the relative volatility is lower for high-volume items (Olhager 2003). However, if the customer’s tolerance time is smaller than the delivery lead time, thus MTS is forced to be adopted as the product delivery policy. Hence, concerning the products with high-demand volatility and low-volume, the risk for obsolete materials in finished product inventories will increase.

The frequencies for customer delivery and shipment sizes

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Customer demand variety

The significance of supply chain diversification is increasingly brought up in the supply chain position upstream generated by a small change or no change in customer demand (Schőnsleben 2007, p106). It is particularly influenced by the number of participants in a supply chain and the diversification of a transaction line (Wikner et al 1991).

4.4.3 Designed variables

Shipping S&D from central or local warehousing facility, when there are alternatives from which to choose from, a rational way to approach the decision is to try to assess the outcomes of each action (Cooper and Schindler 2003, p74). Usually, the action which can generate the best outcome in terms of criteria established for judging alternatives is chosen (Cooper and Schindler 2003, p74). Separating capacity into several small units may be necessary if demand for a business’s products or services is widely distributed. This will be especially true if customers demand high absolute levels or immediate service (Simchi-Levi et al. 2003, p80). However, in the setting of the local warehousing facility, it will yield: a) higher safety stock owing to the no/less use of the risk pooling; Risk pooling suggests that demand variability can be better reduced when they are aggregated across more locations and the behavior of these markets are less positively correlated (Simchi-Levi et al. 2003, p48-51); b) increased overhead as suggested by Economy of Scale (EOS); c) reduced shipping time to the customers because of the closer warehouse location to the customers; d) The total inbound transportation cost is increased when getting the products from the manufacturer compared to the central warehousing facility because of the generally longer distance. In contrast, the transportation cost between customers and local warehouse is very likely reduced for the reasons of overall closer distance. Table 4.2 summarized some of the important considerations regarding these two decisions (Simchi-Levi et al. 2003, Chopra and Meindl 2007, Alain Beerens from Groenewout Consultants & Engineers). Meanwhile, two systems are illustrated respectively in Figure 4.7 Strategy attribution Centralized warehousing facility Decentralized warehousing facility

1. Safety stock lower higher

2. Overhead lower higher

3. Delivery Lead time increased reduced

4. Transportation cost

Which drivers need to be considered related to the decision making?

European Distribution Network