Diagnosing the supply chain of bulk products:

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Diagnosing the supply chain of bulk products:

Increasing cost efficiency of transport at Company X

Master’s Thesis

Author: Mark Leenheer

Student ID: 1460854

Date: June, 2010

Address: Grevingaheerd 44 9737SE Groningen

Email: markleenheer@gmail.com

University: University of Groningen Faculty: Economics and Business

Study: MSc Technology Management

1st Supervisor: dr. X. Zhu

2nd Supervisor: prof. dr. R.H. Teunter

Company: X

Department: Operations Supervisors: M. K.

J. V.

Public Version:

This research contains confidential information. Therefore the original thesis is converted to this public version. The name of the company is replaced by “Company X”.

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Master’s Thesis: Diagnosing the supply chain of bulk products ABSTRACT

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Master’s Thesis: Diagnosing the supply chain of bulk products PREFACE

In the past five months I finished my MSc Technology management by spending a lot of time and effort doing research and writing this thesis. Luckily to me, it was worth every minute and I am proud of the thesis in front of you.

A big support in writing this thesis is the help of my two supervisors of the University of Groningen. Both dr. X Zhu (Stuart) and prof. dr. R.H Teunter (Ruud) contributed with valuable feedback and critical reviews on content and writing.

I am very pleased with the opportunity I got from COMPANY X to do my final project in a business environment. I gained a lot of experience and knowledge that both are of great addition to my education at the university. Therefore I strongly recommend everyone to do their final project in a company and bridge the gap between university and business.

Various people within COMPANY X contributed a lot to my research. I want to thank all of them for sharing their knowledge and their pleasant collaboration. My special thanks go to Marco, who has been great support, inspirer and mentor to me. I want also to thank Jaap, who really helped me through the woods of collecting data in SAP, taught me essential tricks in Excel and for being a helpful sounding board. And last but least I want to thank Eric for being a cheerful and supporting office pal.

Also, I want to thank friends and family for their support. Especially I want to thank Marloes, my girlfriend who supported me with her knowledge and love.

This Master’s thesis marks the end of my MSc Technology Management at the University of Groningen. The period I spend on studying brought many happy memories and made me the person who I am today. I had the opportunity to gain a lot of knowledge and experience accompanied with a solid network of fellow students and precious friendships. I hope that finishing this study is not the end of that, but a beginning of a time with new adventures, continued friendships and chasing personal development.

Enjoy reading.

Mark Leenheer

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Master’s Thesis: Diagnosing the supply chain of bulk products MANAGEMENT SUMMARY

Increased dependency on cost savings motivated this research to diagnose the supply chain of bulk products at COMPANY X. The objective of the research was to develop a model that analyses performance and identifies opportunities for improvement. The method and calculation model developed in this research showed its value to COMPANY X of identifying critical factors that can be improved to increase efficiency. Its application can be repeated at other times or used to other logistical flows.

This research focused on transport costs, which largely contributes to logistical costs (Holter, Grant, Rithcie & Shaw, 2008) and are often forgotten in optimisation (Mason, Lalwani & Boughton, 2007). A higher utilization of transport capacity is needed for minimisation of costs. It was believed that in the current process bulk products were shipped in quantities less than the maximum capacity of transport. Therefore the main question that this research led was: Which factors are critical for improving the of utilisation transport capacity. The answer is a list of factors and their impact to the utilisation of transport capacity.

The model to create such a list starts with process flow mapping to identify all processes that are involved. In this case, the processes are divided into two key processes: ordering and loading. The next step in the model is to identify the sub-problem of these two processes, by qualitative analysis. It is found that the ordering process inefficiently converted maximum loads into different order quantities. The loading process inefficiently converts ordered quantity in delivered quantity. The model continues with a numerical analysis to determine the impact of both sub-problems to the use of capacity. The information needed for this analysis is obtained by creating a data set, based on the identified processes and problems.

In total the transport capacity loss was found to be XXX,XXX tonnes, with a value of € XXX,XXX. The ordering process is responsible for the largest share of this loss, based on: the highest average efficiency loss (-X.X%), the highest standard deviation (X.X%), joint analysis showed that efficiency loss in ordering relates to efficiency loss in loading, the highest capacity loss measured in both weight XXX,XXX tonnes) and money (-€XXX,XXX)and finally, the loading process concerns the transformation of information to information and is easier to adapt than the information to material transformation of loading.

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Master’s Thesis: Diagnosing the supply chain of bulk products

Part of under- ordering

(money based) Critical factors

42% € XXX,XXX The ordering process at front office is inefficient. Checking for maximum loads lacks control and measures.

€ XXX,XXX 16% has no limited silo capacity issues

17%

€ XXX,XXX

The lack of information about volume capacity and

bulk density. 1% has limited silo capacity issues

€ XXX,XXX 7% has not contracted sub-optimal ordered

quantities 16%

€ XXX,XXX

Limited silo capacity as a result of customer order behaviour and delivery performance of COMPANY X.

9% has contracted sub-optimal ordered quantities.

13% € XXX,XXX Tactical mismatch of vehicle volume capacity and bulk density of the product.

4% € XXX,XXX Changes made for any reason by back office employees.

4% € XXX,XXX Causes remain unknown.

3% € XXX,XXX Mistaken for under-ordering by using out-dated information of maximum _loads.

Copy of table 10: Summary of all factors critical to the under-ordering problem.

The main causes of under-ordering are related to the lack of control, measures and information in the ordering process. So, the performance of processes currently depends for a big part on individual employees’ skill and motivation and ad hoc collaboration between departments. Therefore it is recommend to COMPANY X to formalise and automate the ordering process. As defined by (Welker, 2004) formalization is the degree to which decisions, activities and working relationships are controlled and coordinated by formal, explicit rules and procedures. By formalizing and subsequently automating the use of maximum loads as standard order quantities, the ordering process will perform more efficient with less ambiguity.

In addition it is recommended to expand the formalisation to the loading process. Adapting the tolerance interval (i.e. the rules) and automating the release of deliveries are found to be a requirement for the use of formalisation in ordering. Moreover, this recommendation contributes to decreasing the impact of under-loading, based on the basic analysis of loading in this research.

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Master’s Thesis: Diagnosing the supply chain of bulk products TABLE OF CONTENTS Abstract... 1 Preface... 2 Management Summary ... 3 Table of Contents ... 5 List of Figures... 6 List of Tables... 7 Chapter 1: Introduction ... 8 1.1 Company description ... 8 1.2 Research design ...12

Chapter 2: Process Flow Description...18

2.1 Production...18

2.2 Storing ...19

2.3 The customer order flow ...19

2.4 Specification of the maximum load...25

2.5 Exceptional order flow: vendor managed inventory ...26

Chapter 3: Problem Identification ...27

3.1 Identification of sub-problems ...27

3.2 Factors of inefficient ordering ...28

3.3 Factors of inefficient loading ...30

Chaper 4: Numerical Analysis ...32

4.1 Output analysis of the bulk supply chain ...32

4.2 Individual analysis of ordering and loading...33

4.3 Joint analysis of ordering and loading ...36

4.4 Summary of the findings ...38

Chapter 5: Analysis of Under-Ordering...39

5.1 Difference in maximum load...39

5.2 The volume capacity of transport equipment...40

5.3 Changes in the “creating deliveries” process...42

5.4 The model and overview results...43

5.5 Customer analysis for other causes. ...45

Conclusion ...49

Recommendations ...52

Discussion and further research ...56

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Master’s Thesis: Diagnosing the supply chain of bulk products LIST OF FIGURES

Figure 1: Primary Process of COMPANY X ... 9

Figure 2: Pie chart of the delivered quantity per customer division ...11

Figure 3: Scope of the research by elements of the product flows...15

Figure 4: The scope of the research by functional areas of the BSC ...16

Figure 5: Process flow of bulk products from customer order to delivery. ...18

Figure 6: The customer order flow...19

Figure 7: Process flow of the sub-process: “entering sales order” ...19

Figure 8: Process flow of the sub-process: “creating deliveries” ...21

Figure 9: Process flow of the sub-process: “loading” ...22

Figure 10: Basic Input/Output model of the bulk supply chain ...27

Figuur 11: Disaggregated model of the bulk supply chain...27

Figure 12: Frequency plot of the difference between DQ and ML as percentage of ML ...32

Figure 13: Frequency plot of the difference between OQ and ML as percentage of ML...34

Figure 14: Frequency plot of the difference between DQ and OQ as percentage of OQ...35

Figure 15: Scatterplot of differences in ordering versus differences in loading...37

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Master’s Thesis: Diagnosing the supply chain of bulk products LIST OF TABLES

Table 1: Values of ordered quantity, delivered quantity and transport capacity...33

Table 2: The transport capacity loss of the main processes and their components...35

Table 3: Joint analysis of the ordering and loading process...37

Table 4: The effect of using of sub-optimal maximum loads. ...39

Table 5: Analysis of constrained transport-product combinations ...42

Table 6: Continuation of table 5, financial results...42

Table 7: Analysis of afterwards changes ...43

Table 8: Summary of results of the analysis model...45

Table 9: The impact of root causes in the ordering process...48

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Master’s Thesis: Diagnosing the supply chain of bulk products CHAPTER 1: INTRODUCTION

This section deals with the research design of this thesis. First of all COMPANY X, the company where the research is done, is introduced. Secondly the research design is discussed.

1.1 Company description

This section introduces the company. The company introduction consists of a discussion of its general aspects. It is followed by a discussion of the organisational embedment of this research, a description of the primary process and products. The section ends with pointing out the industry characteristics.

General

COMPANY X is a company that produces product X. Product X is a renewable resource that is used in many products that people all over the world use daily. Product X is an important food ingredient and input to the paper and board industry. Product X is wanted in both food and industrial markets because of its chemical properties, such as non-toxicity, poly-functionality and high chemical reactivity. Other factors favouring the uses of product X are its relatively low cost, the fact that it is derived from a renewable resource and that it is biodegradable (Maurer & Kearney, 1998).

*CENSORED*

The business form of COMPANY X is a operative of *CENSORED* farmers. A co-operative is defined as an “autonomous association of persons united voluntarily to meet their common economic, social, and cultural needs and aspirations through a jointly owned and democratically controlled enterprise” (International Co-operative Alliance). Approximately 3300 farmers are owners as well as members of the company. Farmers are committed to supply all of their produce to the company and the company maximises the value of it.

The current strategy to create value is that of low-cost leadership. Besides this strategy, it is the ambition of COMPANY X to earn a global reputation for innovation and sustainability. The mission to realise that consists of:

• seeking to understand customers’ business requirements for product X,

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• managing the complete supply chain, from customer to farmer in order to achieve operational excellence,

• contributing to customers’ development and production processes in partnerships that aim at sharing knowledge and ideas, joint development and joint quality monitoring.

Organisational embedment of the research

COMPANY X Group consists of four divisions: CENSORES. COMPANY X Operations manages and operates the supply chain of product X based products from source to customer. This task is performed by several departments, one of which is Planning, Logistics & Purchasing. Within this department the project called “XXX” is launched to improve various customer, product and transportation combinations, in such a way that costs are minimised. The research will be part of this project and specifically the sub-project “Bulk optimal loading” that deals with the bulk products of COMPANY X.

Primary Process

The primary process of COMPANY X is to change raw material into different end products, also referred to as “customer solutions”. This transformation is depicted in figure 1 and begins with collecting raw material from the co-operative of farmers. Each farmer has a yearly quota that he has to supply and that COMPANY X has to accept. The harvesting and transportation of raw material is only performed in a specific time window which is called “the campaign”. In The Netherlands the campaign starts in August and ends in mid April, in Germany the campaign already ends mid January. The period between successive campaigns is called “the intercampaign”.

Figure 1: Primary Process of COMPANY X. The triangle represents inventory of (raw) material and

each rectangle represents a production location. The area within the dotted line shows the area of concern.

Four production locations, X, X, X and X, process the raw material during the campaign. The main product that results from this process is product T; secondary products are U and V. The production locations differ in which of these secondary products they produce. Before

Production Native Starch

Customers Production

Derivatives Raw Potatoes Native Potato Starch &

Secundary Products

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the products are shipped to the customer, they are packed in small bags (e.g. 25kg), BigBags (>500kg) or in bulk containers or trucks. After packaging there are several diverging flows for Product T and its secondary products:

• they are stored at the production plant,

• they are shipped to and stored at an external storage location, • they are shipped directly to other production locations ,

• they are shipped directly to the customer, • they are collected by customers themselves.

Three production locations, X, X and X (SE), use T as input to produce many different products, together called “derivatives”. These derivatives are produced during both the campaign and the intercampaign. Derivatives have the same storing and shipping possibilities as pointed out with product T. However, there are no bulk products shipped from the X production plant.

Products

COMPANY X defines its products as customer solutions and divides them by customer industry in six divisions. These are: Food, Paper, Industrial Specialties, Cross Division and Feed. Figure 2 displays the volume of bulk flows of each division. Within these divisions 19 products cover XX% of the total delivered quantity (see figure A.1 in the Appendix).

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Master’s Thesis: Diagnosing the supply chain of bulk products Paper Food Proteins Industr. Specialties S & F (Feed) Div ision 1,0_% 1,5_% 5,5_% 22,6% 69,5%

Distribution of Deliverd Quantity By Division

based on deliveries from 01-02-2008 till 31-01-2010

Figure 2: Pie chart of the share in delivered quantity per customer division of COMPANY X. Paper

and Food are the biggest divisions.

Industry Characteristics

First of all, COMPANY X is a co-operative of farmers and it is therefore obligated to accept (“purchase”) a specified amount of material each season. This can be seen as a “push” of raw material. Cooperative organizations have a specific supplier/customer relationship. They must be efficient and competitive in their downstream operation in order to offer the optimal price of raw material to their members (Hovelaque, Duvaleix-Tréguer & Cordier, 2009).

COMPANY X belongs to the process industry, because it adds value to materials by mixing, separating, forming or chemical reactions (Fransoo & Rutten, 1994). This kind of industry has some characteristics such as natural variation in quality, quantity and availability, caused by the agriculture origin of the raw material and its seasonal influences. Moreover, yields are uncertain and the available raw material quantities cannot be known with certainty before harvests. This kind of industry is also characterised by secondary products, long processing times and divergent flows of material (Fransoo & Rutten, 1994; Hovelaque et al., 2009). Material flows are divergent especially in the packing stage of the process (van Donk, 2001).

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Although COMPANY X sells its products globally, those that are shipped in bulk do not leave the European continent. Figure A.2 in the Appendix illustrates the number, magnitude (kg) and location of bulk customers. An aspect that is shown in this figure is that the supplied industries have a few large customers that are responsible for a large part of the entire demand. Production plants in the papermaking industry act as local customers, but can belong to the same multinational company like X or X.

A specific characteristic of the paper making industry that is supplied is its dependence on quality and reliability. The paper making industry has continuous processes that, when interrupted by a shortage or wrong quality of raw material, have to be shut down. Such a production freeze is costly and raw material suppliers can expect large claims to recover these costs. So suppliers like COMPANY X have to be conscious about the possible impact of changes they make, when improving the supply chain to achieve lower costs.

A final characteristic is the agricultural aspect of COMPANY X. The processing of materials originating from agriculture is subsidized and regulated by the European Community. Since 1995/96 the cultivation of material is regulated by production quota and farmers as well as agricultural processing companies receive subsidies from the European Community. However, the European market for agriculture products is being deregulated and as a result of that, the quota and subsidies will end in 2012/13.

1.2 Research design

The next section introduces the research design of this thesis and starts with discussing the research context. Consequently it discusses the research objective, questions, method and ends with the research scope.

Research context

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One of the concerned areas for improvement is that of the logistical costs. Transport is the main element of logistical costs (Holter et al., 2008) and is even called the forgotten process by Mason, Lalwani and Boughton (2007). The transport costs are incurred per delivery regardless of the actual capacity that is used. For products of COMPANY X the average unit price ranges from XX to XX euro per tonnes of product and includes transport costs ranging from XX to XX euro per tonnes of product.

The logistics department of COMPANY X believes that the supply chain for bulk products (BSC) has higher transport costs than necessary. In the past years transport costs per delivery have fallen, so these pure transport tariffs are not the main issue. Management believes that the number of transports used to deliver the total amount of product is too high. To be more specific, they believe that the product quantity that is delivered to each customer differs from the maximum quantity that could have been delivered with the use of the transport equipment. In case of negative difference between these two, it implies that more deliveries are needed to satisfy the total demand than when solely maximum loads are delivered. Since the price per transport is fixed and independent of the quantity that is delivered, the transport costs are not minimal. In case that delivered quantity exceeds its maximum load, laws are violated and the transporter risks being fined. These fines will be charged to COMPANY X and increases transport costs. Conclusively the problem situation that signalled the need for this research can be summarised as follows:

Problem situation: The product quantity that is delivered to customers differs from its maximum quantity, causing transport cost inefficiency.

Keeping transport costs to a minimum is essential to achieve the corporate objective of low-cost leadership. Moreover, subsidies of the European Commission will end at the start of season 2012/13. According the director of COMPANY X Agro in Engwerda (2010), an additional amount of around € 80 per tonnes products is needed to cover the upcoming disappearance of subsidies. To gain this amount, either the unit price has to increase or the costs have to decrease. The low-cost leadership strategy of COMPANY X aims for cost decrease rather than for price increase. As discussed above transport costs are quite a part of the total unit price and optimising them thus helps decreasing the total costs and prepares COMPANY X for 2012/13. The increasing importance of high cost efficiency in the bulk supply chain is therefore the motivation for this research.

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The problem(s) causing the sub-optimal output is/are unknown, since there is no method to analyse the performance and to indicate improvement opportunities of the BSC. The main objective of this research is:

The development of a model that analyses performance and identifies opportunities for optimisation of transport cost in COMPANY X’s bulk supply chain.

Besides identifying problems and root causes of the problem situation, they also have to be assessed on their importance.

Research questions

The main research question is defined as: Which factors are critical for improving the utilization of transport capacity. To answer this question, six subordinate research questions are addressed. These questions are formulated as follows:

• What are key processes within the BSC? (RQ1) • What is the current performance of the BSC? (RQ2)

• Which sub-problems in the performance of the BSC can be identified? (RQ3) • What is the impact of the different sub problems? (RQ4)

• What are the critical root causes? (RQ5)

• How can COMPANY X optimise performance of the BSC? (RQ6)

Research methodology

The general type of this research is a diagnostic research. According to De Leeuw (2002b), the purpose of such a research is to transform a fuzzy problem situation in a well defined management problem and develop recommendations for a design of improvement. This research will not include the realisation phase of problem solving. The diagnostic research is performed by doing an explorative, theory building case study.

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understood. The third strength is the principal reason for the use of case study research, since the problem situation at COMPANY X is not yet understood and the objective is to find the critical factors.

Case study is used for different types of research purposes such as: exploration, theory building, theory testing and theory extension/ refinement (Voss, Tsikriktsis & Frohlich, 2002). This research uses case study for both exploratory and theory building purposes.

In depth field studies combined with process flow mapping, will be used to explore the situation (RQ1). After identifying the key processes, a case study will be used to create a data set that enables assessment of the BSC performance (RQ2). Process flow mapping and in depth field study will identify problems relating to the sub-optimal deliveries (RQ3). Data analysis assesses the impact of the problems and thereby indicating which processes or causes are critical to improvement and worth pursuing further (RQ4). The data analysis also identifies the relationship between problems, why these exist and what their root causes are (RQ5). Combining the answers of these five research questions will enable the development of a theory on how the BSC performance is constructed and which factors should be improved. Thereby the main question is answered. Recommendations will succeed the conclusion of this construct and discuss how the performance can be increased (RQ6).

Research Scope

The scope of this research is set on two axes: specific element of the product flows (figure 3) and the functional areas of the SC (figure 4). The elements of product flows are discussed firsts and are followed by the discussion of the functional areas.

Figure 3: Scope of the research by elements of the product flows. The dotted areas are out of scope.

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wrong quality. The ex-works shipment is a delivery of which the transport is arranged by the customer himself. Only the “direct to customer” shipments will be researched, because they represent the largest volume and have the highest transport cost per tonnes.

The divisions of Feed and Proteins will be left out the scope of this research, due to their relatively small part of delivered quantities (see figure 2) and their complicating characteristics. Also the Industrial Specialties division has a low share in the total delivered quantity, but some products are similar to those of the other divisions. For this reason it is within the scope of the research.

There are several modes of transport used to ship bulk products to the customer. The most common mode is the use of road and intermodal transport. Road transport consists of the use of silo trucks. Intermodal transport consists of the combination of road, rail and water vehicles and requires the use of silo containers (a.k.a. combined transport). Within Europe pure sea transport is not used, neither is “less than truckload” transport (e.g. the transport company combines “less than truckloads” from different suppliers in one full truck load). Pure rail transport is used for just one customer and is a small part of the total bulk product flow. Therefore the scope is set just to road and intermodal transport.

Figure 4: The scope of the research by functional areas of the BSC.

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specific transport capacity in advance. The research is held within the set of these functional areas.

Report lay-out

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CHAPTER 2: PROCESS FLOW DESCRIPTION

This chapter deals with the processes of the Bulk products of COMPANY X to answer research question 1. The process flow is depicted in figure 5 and each of its elements is discussed in this chapter. There are also processes discussed, like production and storing, that are not directly within the area of concern, but need some attention to obtain a more complete understanding of the process. The chapter will start with these two processed and then continue with the process flow of customer orders. Next the process of specifying the maximum load will be discussed. The chapter ends with the discussion of an exceptional process flow: the vendor managed inventory orders.

Transporting Loading Specifying the Maximum load (ML) Customer need Purchasing transport Setting routes Entering sales order (SO) Transport Equipment Creating deliveries Storing Production Product Information flow Material flow Entirely outsourced Partially outsourced scope

Figure 5: Process flow of bulk products from customer order to delivery (i.e. the bulk supply chain).

The channel constituted by the two dotted horizontal line shows how the processes relate to the scope of this research. A larger version of this figure is shown in figure A.3 of the Appendix.

2.1 Production

COMPANY X applies a make-to-stock strategy for the majority of its products. Production is planned two weeks ahead. Most products are produced once a week. Make-to-order is impossible since the production sequence of products is rigid. Frequent switches between products also result in an increase of product defects and quality issues. At other production locations than Ter Apelkanaal, it is possible to supplement the make-to-stock strategy with some make-to-order aspects.

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Master’s Thesis: Diagnosing the supply chain of bulk products 2.2 Storing

Stock of the bulk products is located in the northern part of The Netherlands and at several foreign locations. Stock is internally and externally held in: silos, BigBags and paper bags. Internal stock points are both managed and operated by COMPANY X, while at external stock points only the operation is outsourced.

The use of silos to stock products is most common for bulk products. The availability of storage silos is limited and the acquisition or deployment of new silos is expensive. Therefore not all products can be stocked in silos and are consequently stocked in BigBags. Besides these products, BigBag storing is used for bulk products that are not frequently produced or have a low sales volume. Also the production of some products serves the purpose of process equipment cleaning more than meeting the products’ weekly customer demand. The quantity of a “cleaning product” that exceeds its weekly customer demand is stored in BigBags. It should be noted that products are also stored in BigBags to serve the customers who only can receive BigBags, but these customers do not belong to the scope of this research (i.e. they are not part of the BSC). Storing product in paper bags is normally part of the packaged goods flow and not of the bulk flow. However, in case of urgent product deficits these paper bags can also be used for bulk deliveries.

2.3 The customer order flow

The customer order flow is the main process flow consisting of the following processes: entering sales order, creating deliveries, loading and transporting. Figure 6 illustrates this flow. This section discusses each component of the main process flow individually.

Figure 6: The customer order flow.

Entering sales order

The customer order flow starts with the process of entering a sales order. This process is executed by the front office in interaction with the customer. The entering sales order process consists of several sub-processes that are discussed next. Figure 7 gives a graphical overview of the entering sales order process.

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Receiving customer orders. A customer order is received by fax, telephone or email. The frequency of ordering differs per customer. There is also a category of customers who are involved with a vendor managed inventory concept. Orders from these customers are similar to replenishment orders and are automatically released in the SAP system. When the customer order is received by the front office the process continues with several checking stages.

Checking for feasibility. This process first checks if the order quantity falls within the demand forecast of a product and if it is possible to deliver it within the requested lead time. In case of a mismatch, the customer requirements are changed in negotiation with the customer or an internal solution is sought in negotiation with the back office (i.e. sales planning or order management).

Checking for maximum loads. The next step is checking the order quantity for optimal loading. The goal of that procedure is to determine whether the requested quantity per delivery is in accordance with the maximum load of the transport equipment. To check the applicable maximum load for a specific destination the following information is needed: the country, the area zip code of the point of departure and destination and the transport equipment on which the sales order is based (e.g. Silo truck non-food from Germany zip code 29 to Belgium zip code 93). The place of departure is equal to the loading location appointed by default in SAP. With this information the maximum load can be found in a shared document, also known as “freight rate document” that is maintained by Transport Management.

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Checking master data. The next step in the process is to check whether differences exist with the master data .The master data is the core data that SAP needs. In case of a new customer or changes of existing customers, the master data is adapted. Maintaining this data is the responsibility of the front office. The front office verifies that the route and transport equipment fits the destination and capabilities of the customer for each order.

Entering the order. When all checks are completed the order is confirmed to the customer and entered into SAP. Sometimes the sales order quantity consists of multiple deliveries. In such a case, the gross amount is entered into SAP together with a “package proposal” that specifies the number of deliveries (i.e. “packages”).

Creating deliveries

The next step in the customer order flow is turning the sales entry into planned deliveries. The back office (i.e. order management) receives the entered sales orders in SAP, where they are sorted on Earliest Due Date (i.e. Planned Good Issued Date). In order to create a delivery, a sales order needs a check of its feasibility with the loading location, loading date and product availability. The creating deliveries process is depicted in figure 8.

Figure 8: Process flow of the sub-process: “creating deliveries”.

Checking product availability. The requested order quantity of the sales order is checked for availability at he loading location and date. The back office has the possibility to change location and date in cases of mismatches. This occurs in correspondence with other departments of COMPANY X. Interaction with the customer has to pass via the front office.

Checking of loading location / type. The loading location is dependent on the type of loading operation, which can be grouped into three categories: loading direct from production, from silo and from BigBags. The first type of loading especially occurs with products that are shipped to Scandinavia, since they are decoupled from customer order. The second type is the most common type of loading. Loading from BigBags is needed for three reasons:

• there is no stock left in silos and there is no production run within the requested lead time,

• the product is only available (i.e. stocked) in BigBags,

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The SAP system generates a default loading location that can be changed afterwards, if needed. A customer sometimes requests a product from a specific plant, what limits the choice of possible loading locations. The sales order data is checked for its alignment with the production plan when directly loaded from production, or with the silo plan when loaded from silo or availability of BigBags at the loading location when loading from BigBags.

When the product is loaded out of BigBags an internal transport order has to be created. This internal transport order instructs the movement of BigBags from the stock point to the loading location. It is also possible that an order originally planned for loading from silo or directly from plant has to be changed into loading from BigBags. In such a case the transport company has to be updated about these changes and an internal transport order has to be created for the BigBags.

Checking and adjusting loading date. Until the loading date has passed, it remains possible that an order is postponed or expedited. Such changes will then be adapted in SAP and external parties (e.g. external loading location, transport company) have to be informed.

Entering the deliveries. The loading location is confirmed if product is available at the loading location and loading date. If everything is correct, the sales order is used to create a number of deliveries (i.e. “packages”) that is needed to deliver the sales order quantity. Each delivery then obtains an ordered quantity that is based on the quantity of the total sales order divided by the number of deliveries. If the sales order quantity has been based on optimal loads, the ordered quantity of the delivery should be equal to the maximum load. When this is not the case deliveries are created with a sub-optimal efficiency. To prevent this from happening, the back office contacts the front office to inform whether it is possible to increase or decrease the demand. The front office informs with the customer the possibilities and supplies the back office with feedback.

Loading

The loading process combines the order information, product and transport equipment flow into a customer delivery. This process also consists of several characteristics and procedures. These are shown in figure 9 and individually discussed next.

Figure 9: Process flow of the sub-process: “loading”.

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Loading instructions. The loading of product to the transport equipment will take place on the loading date and location as is planned in SAP. The loading location either gets its information about the ordered quantity directly from SAP or from a paper copy that is printed automatically when a delivery is created.

Aligning transport and product flow. According to the loading schedule the transport equipment arrives at the planned loading time with the planned transport equipment. In production as well as transport there is uncertainty that can result in a misalignment of transport and product. There is communication between the operators at the loading location and the transport company, so they can adjust the time of arrival. This is especially important when the product is loaded directly from the production plant. First, since having the transport equipment lined up without any product to load it with, will result in waiting costs being charged to COMPANY X by the transport company. Secondly, since having the product available without any transport equipment to load it to, will result in a costly production stop.

Actual Loading. When the transport equipment has arrived it is placed underneath the silo or it is hooked to the unloading equipment of the production plant. The loading operator starts the loading process and instructs the driver to move the transport equipment to align with the right manhole. Some loading locations have equipment that automatically stops if the distance between load and equipment becomes too close. Other loading locations are manually operated by pushing and releasing a button.

A special case in the actual loading process is that of using stock from BigBags instead of silos. The loading from BigBags is different, mainly because it involves other material flows and the process has specific characteristics. For example when transport equipment has to be loaded with product from BigBags, these bags have to be transported to the loading location and unloaded into the transport equipment. This operation roughly takes up to twice as long as the normal loading process.

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the customers’ site, the figures in the system are updated if needed. The weighing process differs per loading location. There are three types of weighing procedures.

The first procedure consists of using an isolated weighing facility at the entry of the production site that is managed by the lodge-keeper. When the loaded quantity differs from the ordered quantity, the lodge-keeper can decide to hold the truck and contact the back office for further instructions. They decide to let the truck pass, to load extra product or to subtract product from the transport equipment. This last option is an expensive one in terms of time and money.

The second procedure uses a weighing facility is located straight under the loading facility. This enables the loading operator to monitor the progress of the loading real-time. Only the total weight is shown and the operator has to subtract the empty weight himself to calculate the ordered quantity.

In the third procedure the silo is weighed instead of the transport equipment. The silo is placed on pressure sensors that calculate the weight of the silo content. The operator deducts the ordered quantity from the initial weight and uses this figure as the signal to stop loading. This kind of weighing needs the production feed to stop. Stopping the production process is costly and wastes scarce production capacity. Therefore this is not used often, so the weighing ultimately occurs at an isolated weighing facility

In all three procedures there is a common characteristic, which is the relevance of experience of the loading operators. Loading operators can for example approach the ordered quantity by using just a selection of manholes of the transport equipment. This selection differs per type of transport equipment and product. Moreover, at some locations there is a small buffer (500-800kg) between the silo and the loading equipment that operators can use to adjust the load.

Transporting

After the product is loaded on the transport equipment and weighed, it will be transported to the customer. The quantity that is loaded to the transport equipment is assumed to be the same to the quantity that is delivered. As said before, transport is done by road or intermodal transports. Both intermodal and road deliveries are also divided in food and non-food equipment, as well as in pressurized and non-pressurized equipment.

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transporting, transferring between types of transport, short storing loaded containers and cleaning the equipment. This price is fixed and therefore not influenced by the actual transported quantity. Additional costs like fines caused by violation of vehicle weight limits and waiting hours are charged separately.

2.4 Specification of the maximum load

One part of the customer order flow is to match ordered quantities with maximum loads, as is discussed in the “checking for optimal load” process. The Maximum Load (referred to by the company as the “payload”) is the maximum load that transport equipment is allowed to carry. It is determined by national weight limits on a specific route and by the weight of the transport equipment. Each European country has its own weight limit that differs between road transport and intermodal transport. The lowest weight limit on the route from loading location to the customer destination, determines the first part of the maximum load.

The route is based on the loading location and destination combined with the type of transport equipment. Setting the transportation route is normally the responsibility of transport management, but the transport company can also impose the route and maximum load

The European weight limits apply for the combined weight of transport equipment and its load. Therefore the maximum load is equal to the lowest weight limit reduced by the empty weight of the transport equipment. The empty weight varies per type of transport equipment, as well as by the transport company supplying the transport equipment. This weight is specified in the tender of the transport company. Transport Management contracts transport companies for each destination. By doing so, they specify the equipment that will be used, its empty weights and its volume capacity.

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Master’s Thesis: Diagnosing the supply chain of bulk products 2.5 Exceptional order flow: vendor managed inventory

The description of the bulk order process is the standard for the majority of the customers. There is one exception that needs an additional explanation, which is the product flow to Scandinavia.

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CHAPTER 3: PROBLEM IDENTIFICATION

In the preceding section the process order flow was discussed. This chapter continues the diagnosis with an identification of sub-problems. Afterwards, this section discusses the factors of the individual sub-problems.

3.1 Identification of sub-problems

The bulk supply chain can be modelled at the highest level of aggregation as a black box that converts input to output. The input is the maximum load that is supplied by transport management. The output of the system is the quantity of product that ultimately is delivered to the customer. The objective of the bulk supply chain is to deliver maximum loads, thereby optimising efficiency. This basic input/output model is shown in figure 10.

Figure 10: Basic Input/Output model of the bulk supply chain.

In section 1.2 it is said that the management believes that for many shipments, there is a difference between what is delivered (i.e. Delivered Quantity, DQ) and what could have been delivered maximum (i.e. Maximum Load, ML). According to them, there is a problem within the bulk supply chain that needs attention in order to increase cost efficiency.

With the help of the process flow analysis of chapter 2, the basic bulk supply chain model is disaggregated. It is divided in two main processes: ordering process (i.e. entering sales order and creating deliveries) and the loading process.

Figure 11: Disaggregated model of the bulk supply chain.

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Sub-problem 1: The ordering process inefficiently converts the maximum load into a different ordered quantity.

The loading process is the transformation of OQ into DQ. Several aspects contribute to this transformation, for example the loading and weighing equipment used at the loading location and the type of loading. If this process is out of control then the DQ may differ from the OQ. The second sub problem can be formulated as follows.

Sub-problem 2: The loading process inefficiently converts the ordered quantity into delivered quantity.

3.2 Factors of inefficient ordering

The following factors of inefficient ordering are found during the initial qualitative research. In the subsequent chapters more causes are found and will be discussed there.

Changes in the “creating deliveries” process

One factor of the ordering process is that of creating deliveries. In this process it is possible that order quantities that are recorded the in the system are changed. These changes increase or decrease the difference between OQ and ML and are caused by BigBag loading, volume capacity problems or other reasons. BigBag loading causes a problem when the preference to load from silos is shifted to load from BigBags. This shift is made to prevent BigBag stocks from becoming obsolete. To load from BigBags a number of bags have to be ordered and transported to the loading location. This number depends on the ordered quantity and the weight of the BigBags and is rounded down, because BigBags are not being partially emptied and over-ordering is being avoided. It is also possible that the customer or the front office requests a change in the ordered quantity for a variety of reasons. The numerical analysis of chapter 4 will point out that these changes are not the major factor of the ordering problem, so the root causes of this factor are not traced any further in this research.

The Volume capacity of transport equipment

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and per transport company. The bulk density multiplied by the volume capacity of the transport equipment results in a maximum weight. The maximum weight of such transport-product combination can form a tactical and an operational problem. Both are now discussed separately.

Volume capacity is smaller than maximum load (tactical)

The volume capacity will become a problem if it is combined with a low density product in such a way that it results in a maximum weight that is less than the maximum load. In such a case the OQ is limited to the volume capacity (VC) times the bulk density (BD). That means that the transport capacity loss is the difference between ML and VC*BD. It is caused on one hand by the purchase of transport equipment that is focused only on maximum loads and not also on maximum volume capacity. On the other hand there is the constraining lower tolerance limit of bulk density that is specified by Product Management. This problem of limited volume capacity and low bulk density is defined as the tactical problem. The problem involves the specification processes of both product management and transport management.

“Perceived weight capacity” is smaller than actual weight capacity (operational)

There is also a problem involving the volume capacity at the operational level of the bulk supply chain. As discussed in section 2.3 the front office checks if the ordered quantity meets the maximum load and if not, increases it. In some cases it is not possible to increase it to the maximum load because of a constraining volume capacity. The best thing they can do is to increase the ordered quantity to the maximum weight of the transport-product combination. The problem is that there is no record of volume capacity and bulk density in SAP or even in a shared document like there is for the maximum load. Therefore the check is based on experience, or a “perceived weight capacity”. The employees know that there is a constraint of volume and use a value that differs from the actual. In case they use a lower value to set match OQ with, transport capacity is lost and in case they use a higher value, difficulties may arise at the loading process.

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Master’s Thesis: Diagnosing the supply chain of bulk products 3.3 Factors of inefficient loading

This section deals with the factors of the inefficient loading process that are found during the research.

Product shortage at silo

One problem is the existence of a difference between actual and theoretical stock level. When the stock level equals almost a truckload but there is actually less product than theoretically expected, this causes a delivery deviating from its order quantity, hence the maximum load. The theoretical stock levels are managed in SAP and although the silos have a mounted level indicator, there is no official procedure to compare these two figures. When the theoretical stock level of silos is not corrected for product loss and deviations in the weighing equipment, an unexpected shortage can occur. Particularly when a silo is not replenished any longer since it is to be used for another product or it is to be repelled. Product switches and silo repulsion are prevailing at externally operated silos because they are more flexible and expensive than internal silos. So this problem is especially linked to loading at external silos.

Outdated instructions

Loading schedules are automatically printed for every delivery at the loading location.. Until the loading begins it is possible for the ordered quantity to be changed. However, such changes are not printed, but loading locations are informed by telephone or by email. Since there is no pre-set procedure or system to deal with these changes it happens that the updated information is lost and that the old instruction is used.

Input differences of transport equipment

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Besides the difference between transport equipment types, there is also variation within a transport equipment type, namely the volume capacity. For instance a 30ft silo container can have a volume capacity of 51, 55 or 57 m3. The specification of the transport equipment is recorded by Transport Management, but not published. Different volume capacities result in different heights of the container; according to the loading operators this influences the automatic switch-off point of the loading equipment. There are ad-hoc solutions like a supplementary ring to increase the distance between the loading equipment and the transport equipment. But there is no official procedure for its use.

Effect of Environmental conditions

The loading operation is subjected to environmental and product conditions. Products can vary in their bulk density (up to 350 kg/m3 less than the standard of 700kg/m3) and in moisture content. Both affect the flowing capability of the product and are caused by differences in the production process. Differences in temperature between the inside and outside of loading equipment have also effect on the flow. When produce arrives directly from the production process, it is still warm and moist and has a higher temperature difference with the outside than when the product has been stored for a while inside the silo. These differences are not accounted for in the loading procedure and can therefore lead to a deviation between delivered quantity and the maximum load.

Loading from BigBags

Also in the loading process there is a problem with BigBag loading exists. Since most of the BigBags have a weight ranging between 500 and 1,000kg, there is not as much pressure as that of a silo filled with 100 tonnes when releasing the product to the transport equipment. The lack of pressure results in a product flow that is less powerful and causes piling under each manhole; leaving space in the corners and in between the piles. In earlier days, truck drivers executed a stop-and-go manoeuvre to smooth the surface of the load but due to regulations this is not allowed anymore. To serve the same purpose of equally distributing the product, there exist so called spreaders but not all the loading locations have such equipment.

Loading capability

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Master’s Thesis: Diagnosing the supply chain of bulk products CHAPTER 4: NUMERICAL ANALYSIS

This chapter starts with a numerical analysis of the basic bulk supply chain model to establish an understanding of situation. Consequently, the two sub-problems are assessed on their impact on the performance of the bulk supply chain. Subsequently a joint analysis shows the relation between the two problems. After the analysis, one of the two sub-problems is chosen to continue the research with.

4.1 Output analysis of the bulk supply chain

In order to analyze the processes a dataset is created. The set consists of 14328 single item deliveries over the period of 01-02-2008 till 30-01-2010. A single item delivery is defined as a delivery made by one unit of transport equipment. Although, it is possible that a customer orders a number of deliveries at the same time, the processing occurs independently of each other. Furthermore the reader should be aware that figures shown in this report are based on data over the whole two year period. Statistical analyses are performed with MiniTab15.

To quantify the problem situation, the basic model of the BSC process is used for initial analysis. To measure the performance of this process, the difference between output (DQ) and input (ML) is plotted in a histogram (figure 12). The difference is calculated as a relative percentage, because maximum loads vary between 24 and 32 tonnes and using absolute values distorts the impact. For example a loss 1/24 is bigger than 1/32.

Figure 12: Frequency plot of the difference between DQ and ML as percentage of ML. The figure is

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Figure 12 shows that approximately 19% of all deliveries are near their maximum load (i.e. DQ = -0.5% ≤ ML ≤ 0.5%). Furthermore the distribution is skewed little left with a sharper than normal peak, indicating more negative deviations than positive ones. This is supported by the mean value of -2.7% (i.e. -764kg). Noteworthy are the positive differences, which in theory are violations of European weight limits. A final observation of this figure is the large variance shown by a standard deviation of 6.8% (i.e. 1,900kg).

Table 1 shows the total capacity that is planned, used and purchased (available). The planned capacity is not planned by transport management, but is planned by means of accepting sub-optimal ordered quantities. The performance in the loading process determines if this planned capacity is increased or decreased. It is found that in this case there is a decrease that shows a waste 10,946 tonnes of capacity. The value of planned and used capacity is based on their contribution to transport costs and is in total € XXX,XXX less than total spend on transport.

From this analysis it is concluded that the perception of the management on performance of the bulk supply chain corresponds with reality. That implies that it is not a problem of perception (de Leeuw, 2002b). To find out which factors need to change in the reality, the next step is to analyse the two sub-problems identified in chapter 3.

Type of Capacity x1000 kg Value of capacity (€)

Total Ordered Quantity (OQ) Planned capacity 372,634 € XXX,XXX

Total Delivered Quantity (DQ) Used capacity 372,486 € XXX,XXX

Total Transport Capacity (ML) Available capacity 383,432 € XXX,XXX

Table 1: The sums of ordered quantity, delivered quantity and transport capacity of the total data set.

Transport capacity is the sum of all maximum loads. The difference between available capacity and used capacity is 10,946 tonnes with a difference in contribution to transport costs of € XXX,XXX. Capacity planned to use by accepting sub-optimal order quantities has the highest share. The value of available capacity is the total expenditure and the other two values are the contribution to it.

4.2 Individual analysis of ordering and loading

The ordering process concerns the transformation of ML in OQ (OQ-ML). In order to examine the performance of this operation the difference between ML and OQ for each delivery is plotted in a histogram (figure 13). The histogram shows that 55% of the deliveries have an OQ equal to ML. The other 45% is responsible for an average difference between OQ and ML of -2.7% (-754kg) with a standard deviation of 6.2% (1,760kg). Negative differences occur more often than positive differences and result in a negative mean.

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DQ. Except for DQ-OQ= -7%, it look likes there are no uneven differences. Moreover, it is expected to see a bell shaped graph based on the high number of observations. This abnormal pattern is caused by two factors. First, there is not a continuous range of values of ML, but an array of eleven possible values of which two are more frequent applied than the other nine. Second, the values of OQ tend to be set in steps of 500kg most of the time and not continuously.

Figure 13: Frequency plot of the difference between OQ and ML as percentage of ML. The figure

shows 96% of all deliveries.

Table 2 sums the values of the inefficient ordering in kilograms. It indicates that in total the ordering process is observed by an efficiency loss of -10,798 tonnes. The transport costs vary per route, by expressing the capacity loss in Euros the financial impact is calculated per delivery and summed in the third column of table 2. This is done by multiplying the relative difference of each delivery by its transport costs. Inefficient ordering has caused a capacity loss of -€ XXX,XXX.

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Figure 14: Frequency plot of the difference between DQ and OQ as percentage of OQ. The figure

shows 99% of all deliveries.

It has to be noted that over-ordering is not a positive defect that can make up for a negative defect. Over-ordering increases the risk on road fines and moreover it causes problems in the loading process, as will be shown in the joint analysis of the two processes. However, the under-ordering is a bigger problem than over-ordering.

Ordering Loading

Analysis of the individual processes

and their components. _x1000kg _Euros _x1000kg _Euros

Under- -11,423 -€ XXX,XXX -3,822 -€ XXX,XXX

Over- 625 € XXX,XXX 3,674 € XXX,XXX

Sum of both problems -10,798 -€ XXX,XXX -148 -€ XXX,XXX

Table 2: The transport capacity loss of the main processes and their components. The values are

measured in kilo tonnes and Euros. The sum of both components show the loss as it is observed in reality. It is shown that ordering is mainly caused by one component and that loading has two large components.

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are within six-sigma. According to the management this limit is too high. Moreover, if deliveries are ordered at their maximum load, this kind of performance will lead to violation of the 5% tolerance limit of vehicle weights of traffic regulations (i.e. in Holland, Germany and France). In addition it will cause customer complaints. The sum of the loading problem is 148 tonne and its financial impact as observed in reality is -€ XX,XXX. Table 2 shows that loading problem has two components with both large impacts. Under-loading causes a direct loss of transport costs of -€ XXX,XXX and over-loading a gain of € XXX,XXX. The contribution to transport costs is based on the maximum load, delivering more than the maximum load therefore increases cost performance. Despite the positive influence on transport cost efficiency of over-loading, it is also a problem that leads to traffic penalties and under-ordering. The latter is discussed in chapter 5.

4.3 Joint analysis of ordering and loading

In 55% of the deliveries the ordered quantity was set equal to the maximum load, so this group of deliveries has differences only caused by the loading problem. In the 45% that this is not the case, the difference in the final output is caused by both the ordering and loading problem. In some cases, as shown in figure 15, the difference in the loading process is not a problem, but a partial solution to the problems caused in the ordering process. This is shown by the green zone in the figure. The red dots and diamonds are the differences that are the actual problem of loading, measured as DQ-OQ for the diamonds and DQ-ML for the dots.

In region A there is an under-loading problem with two components. One is represented by diamonds and is under-loading on top of under-ordering. The second is represented by dots and shows the deliveries where the difference of under-loading exceeds the difference of over-ordering. In region B this is the case with over-loading. On top of over-ordering there is over-loading (diamonds) and on the other hand when over-loading exceeds the under-ordering (dots). Regions C and D consist of deliveries that have differences in the loading process to partially cope with the difference originated in the ordering process. In region C this is over-loading to compensate under-ordering and in region D this is under-loading to compensate over-ordering. In addition table 3 shows descriptive statistics of each region.

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Figure 15: The differences in the ordering process are plotted versus the differences in the loading

process. The green diamonds represent the differences in the loading process that are a partial solution to the differences originated in the ordering process. The red dots and diamonds are the differences that are the actual problem of loading. Dots are measured as DQ-ML and diamonds as DQ-OQ. This figure is zoomed in to 95.5% of all data.

Difference in loading

per region Number Mean Std dev.

Sum (x1000kg) Sum(€) A 6,142 -3,456 -€ XXX,XXX B 4,652 -0.34% 3.24% 2,353 € XXX,XXX C 2,819 1,321 € XXX,XXX D 284 1.02% 2.25% -366 -€ XXX,XXX Total* 13,897 -148 -€ XXX,XXX

Table 3: Joint analysis of the ordering and loading process. The table lists the number, sum in

kilograms and sum in Euros of each region of figure 15. The standard deviation and mean are shown for the subsets A-B and C-D. 431 deliveries are located on the x-axis (DQ=OQ) and are not included.

With these actual values of the loading problem it is possible to conclude which problem has the biggest impact. When the figures are compared based on kilograms, it is shown that under-ordering has a loss of 11,423 tonnes versus a loss of under-loading of 3,456 tonnes. Considering transport costs, under-ordering is also approximately three times more costly than under-loading. The ratio in money is smaller than in kilograms, which suggest that under-loading occurs more often to deliveries with high transport cost per tonne.

A C

B