Process optimizations

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Process optimizations

A research regarding process optimizations within the European

Continental Distribution Center of a logistics service provider in

Frankfurt, Germany

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Process optimizations

A research regarding process optimizations within the European

Continental Distribution Center of a logistics service provider in

Frankfurt, Germany

Author Gerard Hazenberg Organization X Frankfurt Germany Supervisor - University University of Groningen The Netherlands

Faculty of Management & Organization

Master of Science degree program Business Administration Specialization Operations and Supply Chain Management Supervisors

Dr. B. Yang Dr. M.J. Land Date

April, 2006

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Preface

This thesis reports on the research I conducted at the European Continental Distribution Center of a logistics service provider in Frankfurt, Germany. The research represents the last stage of my Business Administration study at the University of Groningen, The Netherlands.

Due to the confidentiality of the information presented in this thesis, most of the actors and companies have been made anonymous. Also, some figures and data overviews were removed.

The people whom I worked with at the company made sure that the past months have not only been an educative time, but also a pleasant time. Without their support and co-operation this thesis could not have been written. Therefore I want to thank them for the opportunity that they offered me to conduct my research within their organization. Furthermore, I would like to thank my company supervisors for the provided information, support and feedback.

Finally, I would like to thank my supervisors at the University of Groningen, Mr. Dr. B. Yang and Mr. Dr. M.J. Land, for their insights, support and directions.

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Management summary

This report describes the research assignment performed within the European Continental Distribution Center of a logistics service provider in Frankfurt, Germany. The purpose of this research is to provide an evaluation of the warehousing processes in order to generate improvement proposals to the management, more specifically in increasing efficiency and/ or to lower costs. This was translated into the following main research question:

How do the warehousing processes currently look like and how can they be improved to increase efficiency and/ or to lower costs?

Based on an extensive research, which covered a general analysis of warehouse operations as well as detailed time studies, the following inefficiencies have been identified:

• Decline of cycle time performance of regular orders

• Limited planning capabilities due to lack of forecasts

• Difference in workload over time between inbound and outbound departments

• Limited information about warehouse utilization

• Training of employees limited to departmental boundaries

• Long travelling times for putaway of items

• Long travelling times for order picking

• Packing and checking process is a bottleneck

• Labour intensive, mistakes-sensitive data entry in Access database resulting in delays of inbound information flow

• Waiting at label printing equipment for other employees at mezzanine • Excessive staging in inbound area

• No measuring of productivity

• Unnecessary continuous lightening of area 4

To resolve the above inefficiencies, this research proposed primary improvement strategies as follows:

1. Improving cycle times for regular orders by means of an improvement of the order picking and putaway processes

2. Reducing travelling times for order picking by an improved routing policy and an improvement of the sorting process of incoming orders at the order control department

3. Bottleneck management for packing and checking, realized by increasing the volume flexibility as well as the temporal flexibility of the working station

4. Improving planning capabilities by the implementation of a (collaborate) forecasting method

5. Managing differences in workload between departments by cross training

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5 7. Reducing travelling times for putaway of items by improving the routing policy

and the organization of items on the materials handling equipment

8. Improving inbound operations by the application of scanning for the tracking of incoming items (and resolving the excessive staging of items)

9. Resolving waiting at the mezzanine by increasing the capacity of the printing station

10. Implementation of a system for productivity measurement

11. Saving on electricity costs by the installation of lightening sensors

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Chapter 1: Company profile

In this chapter, background information about the company is provided to introduce the reader into the organisation of X in Frankfurt. The first section describes Y (the entire organisation). The second section is concerned with X (the division of Y, which is concerned with industrial logistics), while the third section focuses on the ECDC of X in Frankfurt, where this research has been carried out. The last two sections present a general description of the core operations which take place in Frankfurt. A more detailed analysis of these operations will be presented in Chapter 3.

Before introducing the company, a clarification needs to be made regarding the terms ‘warehouse’ and ‘distribution centre’ (DC). Both terms are used in the literature and in this report for the same object. But, the terms are not identical. Stock and Lambert (2001: 390 – 391) make a distinction between the two terms, which is shown in the following table.

Warehouse Distribution centre

Inventory All types of products Minimum inventories,

predominantly high-demand items

Activities Mostly non-value adding High percentage of

value-adding

Data collection Batches Real-time

Costs focus Minimizing operating

costs

Maximizing profit impact of meeting customer delivery requirements

Table 1.1: distinction between used terms (Stock and Lambert; 2001: 390 - 391)

According to Stock and Lambert, both terms are used for practical reasons for the same concept, where ‘warehouse’ is used as the more generic term of the two. This is confirmed in publications of other authors. Therefore, in this report both terms are used for describing the empirical situation.

1.1 Y

Y is one of the world’s leading logistics providers of integrated logistics services and employs more than 30.000 people. The company has around 1.000 offices worldwide and has achieved a turnover of several billion Euros in 2004. Table 1.2 presents further key figures about Y.

Activity

Turnover

(million Euros) Employees Locations

Land operations 3.867 22.100 700*

Air & sea freight operations 3.129 10.500 800*

Logistics 1.046 6.400 400*

Total 8.042 39.000 1.100

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9 Formally founded in the 19th century, Y was taken over in 1991 by U, another leading

logistics provider. In 2002, U was taken over by Z. Figure 1.1 shows the position of Y within the organizational structure of Z.

Figure 1.1: organizational chart Z AG (annual report Z; 2004: 31)

After the takeover, Z has integrated Y and two other companies into the business division Transport and Logistics. The three actors represent three business areas: • Integrated logistics services

• Railroad transport

• Freight logistics and intermodal transports •

Y provides the following services:

• Land operations (national/ international transportation networks, information and communication technology, etc)

• Air freight (air transports, intermodal transports, etc)

• Sea freight (ocean shipping)

• Logistics (industrial logistics, aero parts delivery, spare parts distribution, etc) • Global projects (global JIT-deliveries, intercontinental transports, etc)

• Fairs and exhibitions

• Global sports events (Olympic Games, World Championship Football, etc)

• Removals (security, insurance, custom clearance, etc)

• Key account & tender management (customer management)

• Environmental services (environmental performance and logistics

development)

1.2 X

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10 Newsletter; 2005: 2). The organization is a joint venture of Y and V, in which Y

represents 51 percent. X offers industry-orientated customer-specific logistics systems. These systems cover the following industries:

• Electrical engineering

• Mechanical and plant engineering

• Aerospace industry

• Semi-conductor industry

• Electronics industry

• Media- and advertising industry

The following services are being provided:

• Service logistics (regional supply to service technicians, reverse logistics, central organisation of a worldwide spare parts supply system, etc)

• In-house logistics and warehousing (central and regional warehouses,

consolidation and reconsolidation of goods, etc)

• Order logistics (order management, temporary management and personnel leasing)

• Media logistics (distribution of merchandising and media products, digital archiving, etc)

X maintains a network of central warehouses and depots in Germany and other parts of Europe, from which the worldwide distribution and regional deliveries can be controlled. X is currently expanding its activities throughout Europe further towards its presence on a global level. Figure 1.2 provides an overview of the current locations in Germany and the planned locations for the rest of Europe for 2006.

Figure 1.2: current and planned locations of X (July 2005) (X Presentation; 2005: 30)

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1.3 X Frankfurt (ECDC)

X in Frankfurt is a logistics centre of X, which performs service logistics for W. The services which they provide are:

• Worldwide spare parts supply

• Quality inspections of incoming and outgoing goods

• Handling of sensitive parts

• Handling of returned goods

• Short-term materials planning

• Maintaining key performance indicators for daily control of all functions The customer of X, W, is one of the world’s largest suppliers of products and services to the global semi-conductor industry. The machines of W play a major part in the chip manufacturing process. W employs over 10.000 people in over approximately 70 locations throughout China, Europe, Israel, India, Malaysia, Singapore, Japan, Korea, Taiwan and the United States. Their main customers are Intel, AMD and Motorola. W receives and distributes their products and components through three main (continental) distribution centres, which are located in Taipei (Asia), Louisville (North-America) and Frankfurt (Europe). Next to these main distribution centres, several local depots and warehouses are maintained by W. X in Frankfurt is the European Continental Distribution Centre (ECDC). The Holland International Distribution Council defines an ECDC as following: ‘an ECDC is a European warehouse, or part of a European warehouse, where the point of origin of more than 50 percent of the inbound goods flows (by weight or units) is a production location in a different country and where the goods are distributed to customers in at least five different European countries.’ (Koster and Warffemius; 2005: 762). The other two continental distribution centres are run by UPS (United Parcel Service).

The ECDC receives components of suppliers, the distribution centres and the W-factories. The ECDC also receives defective products, which are returned by customer engineers or from the local depots. The ECDC receives, stores, picks, packs, checks and ships components and distributes them to chip manufacturers worldwide. From the ECDC, the products are shipped directly to customers or to local depots. Figure 1.3 depicts the operations network of the ECDC with its tier suppliers and first-tier customers.

Figure 1.3: supply chain of ECDC

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12 The ECDC employs 24 people during two shifts. During the dayshift, 24 people are

working, while during the night shift three employees are available. Furthermore, to respond to workload peaks, the ECDC employs five to six employees from temping agencies. The normal business hours of the ECDC are from Monday 07:00 am to Saturday 07:00 am with 24 hours on site manning. Core business hours are from 08:00 am to 05:00 pm.

1.3.1 Service Centre

The ECDC consists of two main areas: the service centre and the warehouse area. The service centre, which is run by Y, handles import and export issues, after hours service (AHS) and purchase order management (POM). AHS refers to the timeframe in which W can not directly support its European customers. This is during working days from 16 pm until 9 am and during the weekend. During these times, the service centre is responsible for fast solutions in case production breakdowns at the customer plant occur. In these cases, engineers and/ or technicians of the customers of W call the service centre to order spare parts. The service centre employee then takes the order, logs into the SAP Inventory Management System and localizes the requested spare part in the ECDC, another CDC (Continental Distribution Centre) or a regional warehouse of W. The order is then processed in SAP and the fastest transport to the customer is organized.

There are two different types of orders: regular orders and down orders. The regular order has a maximum throughput time of 24 hours. This means that the specific part(s) should be picked, packed and ready to be shipped within this time frame. The down-order is an emergency order, which should be handled within one hour. This requirement also applies to parts which are located in the Asian CDC or the North-American CDC. These parts will be transported to the ECDC and, after cross-docking in the ECDC-warehouse, shipped to the customer.

The service centre tries to decrease the need for down-orders by POM. POM refers to the material requirement planning (MRP) that is made by the service centre employees. The employees make an analysis of the inventory records and take proactive actions in case availability problems are likely to occur.

1.3.2 Warehousing operations

Within the ECDC warehouse area, X performs several operational functions for W. These will now shortly be discussed. More details about the processes will be provided in Chapter 3.

Receiving

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13 Internal transport

Internal transport is mainly performed by means of trolleys. The trolleys are used for the putaway of items as well as for the order picking process. Two reach trucks are used for high-volume products (pallets, crates and packing materials).

Unpacking/ repacking

The items are unpacked, after the receiving has taken place. Items are usually received in bulk quantities and are then unpacked and divided into standard quantities for storage in the ECDC.

Quality assurance

A relatively small quantity of products goes through quality assurance before they are stored in the distribution centre. These are: excess products, firewall products and parts which are suspected to be damaged. Excess products are products, which are send back to the ECDC by local depots and warehouses of W, because of quality problems or obsolescence. These products are then send back to the ECDC. Firewall products are articles from suppliers, which in the past have frequently send those products with quality problems. The quality assurance department checks these products and decides whether they should be send back to the manufacturer, should be repaired or will be returned to inventory as ready for use.

Cross-docking

Certain items can be transferred directly from the inbound receiving dock to the shipping dock, thereby bypassing the storage, picking and packing activities. However, the management of the ECDC can not decide on which products should be cross-docked (see: “inventory planning and control”).

Storage

After receiving and (if required) quality assurance, products are transported to their storage positions. Storage can be identified as the core process in the DC and it identifies the location where the goods are deposited and held until they are demanded for usage. Products are stored in conventional pallet racks, bin shelving systems and drawers, depending on their size, quantity and velocity. Velocity refers to the ABC-classification supported by SAP usage analysis, which is made to determine the velocity of each product, which has consequences for the storage strategy (fast running items are stored at the front of the storage locations). More information on this topic is provided in Chapter 3.

Order picking

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14 internal transport, due to changes in the ABC-classifications (demand based

categorization) of inventory items. Packing and checking

After the products have been picked for single orders, the orders are packed and checked. Checking includes the checking of part numbers, quantities and the checking for potential damages and broken quality seals. Afterwards, the orders are packed in cartons and are transferred to the staging area.

Shipping

Products are shipped via the own fleet of Y as well as via outside carriers. The customer of X, W, maintains worldwide transportation-contracts with DHL, UPS, TNT and FedEx. In this way, W is able to realise lowest shipping costs possible for their shipments. X uses a transportation-matrix for choosing the optimal carrier for a certain shipment. The matrix balances the weight of the shipment against the carrier offering the lowest costs for a specific transport.

Handling of hazardous materials and electro static devices

The ECDC also receives and distributes hazardous materials and electro static devices (ESD). These items require special handling. Hazardous materials should be held in inventory in a specially designated hazardous materials area. This area is located in a small section of the warehouse, which is labelled and protected against unauthorized access. Electro static devices are devices, which are sensitive to static energy, which can be transferred to the devices during physical contact. These items should therefore be handled in an ESD protected area, which includes special equipment for handling these parts. Both hazardous materials and electro static devices can be recognized by special labels on the packages of the products.

Inventory planning and control

Inventory planning and control is not outsourced by W to the ECDC. This activity is performed, as part of the distribution planning, by W-employees in their office in München (Germany). This implies that the management of the ECDC has no direct influence on the levels of items kept in stock and that inventory replenishment is initiated and controlled by W. The W-employees in München also decide on which products are to be handled by cross-docking.

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1.3.3 Main process steps

To be able to understand the research findings, it is necessary to provide some background information on the main process steps of order fulfilment within the ECDC. The process is shown in figure 1.4.

Figure 1.4: main process steps in the ECDC

DN represents the generation of a delivery note. The delivery note corresponds to the customer order form and initiates the process of making items ready for shipment. Delivery notes are translated by a so-called batch run into Transfer Orders (TO), which are printed at the order control desk in the ECDC. The items are then consolidated, checked, packed and tracked into the SAP warehouse management system for outbound storage. The registration in SAP formally finalizes the order fulfilment process and is called Post Good Issue (PGI). W has determined the following cycle times for these basic steps for each order type:

Regulars: Downs:

DN to TO: 4 hours DN to TO: /

TO to PGI: 20 hours TO to PGI: 1 hour

DN to PGI: 24 hours DN to PGI: 1 hour

No cycle times have been determined for the process of DN to TO for down orders, because the batch run is not being applied to these orders, due to their higher priority. The batch run for regulars can vary between a virtual minimum of some seconds to a maximum of four hours. This is because each batch run takes four hours, thus in total six batch runs a day are available. The length of the batch run for a certain order therefore depends on the moment the DN is generated, relative to the progress of the specific batch run. The receiving time of an order also influences the process of TO to PGI. In case the batch run lasts four hours, then 20 hours are left for the warehouse processes. The length of the batch run itself has been determined by IT professionals, based on the capacity of the computer network. A shorter batch run would result in an over utilization and slowdown of the computer network. The processes of DN to TO and thus DN to PGI are actually not relevant for the management of the ECDC, because the management is not able to influence the cycle times of these process. The cycles times of TO to PGI cover the warehouse operations and are thus an important element of the performance measurement of the ECDC. More information about this measurement is provided in subsections 1.3.7 and 3.1.3.

1.3.4 Warehouse layout

The layout of the warehouse can be seen in figure 1.5.

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Figure 1.5: warehouse layout

The warehouse consists of four areas. Area 1 measures 1820 m² and includes a mezzanine. This is the largest area and is used for the storage of small parts, the performance of order control, packing and checking of items, outbound storage and cross docking. The cantina is also located in this area. Area 2 measures 663 m² and is mainly used for the receipt and quality control of items. Besides that, a small amount of pallets and items waiting for review are stored in this area. Area 3 also measures 663 m². This area is used for the storage of pallets and wooden crates. The fourth area measures 672 m² and is mainly used for the storage of high-volume, super slow moving materials (SSMM). Hazardous materials are also stored in area 4. The majority of the incoming lines, 93 percent, are stored in area 1. This indicates that the large majority of products are small parts. Each area is further subdivided into different zones. The loading docks of areas 3 and 4 are not being used. Items normally enter the ECDC through the loading docks in area 3 and leave the ECDC through the loading docks in area 1. Cross docking items are received and send through the docks in are 1.

1.3.5 Storage types

A variety of storage types are used in the ECDC, ranging from conventional selective pallet racks, to bin shelves, modular storage drawers and cartons. An overview of the available storage types is shown in appendix 1. The majority of the items are characterized by a small volume. Therefore, most of the items are stored in bins.

1.3.6 Operating costs

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Figure 1.6: operating costs structure ECDC Figure 1.7: typical operating costs structure of third party logistics provider (Klaus; 2005: sheet 6)

When comparing the costs structure to the typical costs structure of a third party logistics provider in figure 1.7 (Klaus; 2005: sheet 6), it can be noticed that the two are quite similar. However, it is noticeable that the labour costs of the ECDC are significantly lower (- 19 %).

1.3.7 Performance measurement

The performance of the ECDC is measured on a daily basis by the management. The performance is measured by means of a scorecard, which has been constructed by W. The scorecard consists of approximately 130 key performance indicators (KPI’s), classified under: receiving, inventory control, inventory accuracy, down order cycle time, regular order cycle time, pick & ship and quality. The performance on these KPI’s is discussed with the customer of the ECDC, W, on a weekly basis. W has also initiated an incentive program for the personnel of the ECDC, which aims at stimulating the motivation of the employees by providing them with a financial incentive for good performance. The performances on the most important criteria of the scorecard are the main input for this incentive program.

50%

30% 20%

Labour costs Rental costs Write offs and other costs

69% 20%

11% Labour costs

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Chapter 2: Research design

The research design provides information about the problem definition, the theoretical framework, the information sources, the methods for measurement and analysis and the reporting procedure (De Leeuw; 2003: 89). The aim of the first section is to inform about the reasons for the research. In the second section, the research will be typified, which enables an optimized balance between the research and the management of the research. In Section 3, the problem definition will be discussed. In Section 4, the theoretical framework will be presented. In Sections 5, 6 and 7 the information sources, measurement methods and the reporting procedure will be discussed. Finally, in the last section attention will be given to the planning of the research project.

2.1 Research motive

The motive for this research is the need of the management of X for a review of their warehousing operations, with the goal to find out whether certain operations can be optimized to increase efficiency and/ or to lower costs. In general, companies will always search for ways to increase efficiency and/ or to lower costs. But, in this particular case, the customer of X requires the company to take measures for continuous improvement. Moreover, X has taken over the distribution centre from another logistics service provider in 2003. Since then, certain processes have been optimized, but others still leave room for improvements (according to the management of X). The management of X suggests two operations in particular that offer improvement potential: the picking process and the receiving process. In a similar location of X, management has changed the order picking process. This has stimulated the management of X in Frankfurt to look for process improvements regarding the picking process.

The outbound process has previously been optimized. However, according to the management of X, an extensive research on the inbound operations has not taken place yet.

2.2 Typifying the research

In this section, information will be provided about the characteristics of the research. The aim of this section is to make an optimum balance between the research and the expectations of the management about the research.

2.2.1 Scientific research versus empirical research

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reality. The research should provide specific conclusions and recommendations about what should be done (or should not be done). Recommendations always contain a normative and an empirical component: to be able to reach A, B should be performed. (De Leeuw, 2003: 48). In contrast to the empirical research, the scientific research provides new theories/ insights for the general database of scientific knowledge (De Leeuw, 2003: 71).

2.2.2 Process definition and product

The process definition provides a rough overview of the different activities of the research. This is illustrated in figure 2.1.

Figure 2.1: process definition of the research

In contrast to scientific research, the empirical research follows the regulating cycle: the focus is on the application of scientific knowledge, not on the gathering of new scientific knowledge. The empirical research starts with the observation of a specific problem in the reality and ends with the search for and the implementation of solutions from the database of scientific knowledge (De Leeuw, 2003: 72 – 73). The research can also be classified according to the product of the research (De Leeuw, 2003: 76). This research can be characterized as a problem solving research: the research is conducted for a specific customer and covers the customers’ entire problem.

2.3 The problem definition

The problem definition consists of three components: the research objective, the main research question and the demarcations of the research. The research objective defines for whom the research is being performed, what the result of the research will be and why this is relevant. The research objective is translated into the main research question, which is the basis for formulating sub-questions. The demarcations define the limitations of the research (De Leeuw; 2003: 85).

Researcher Scientific knowledge

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2.3.1 Research objective

The objective of this research is to provide an evaluation of the warehousing processes in order to generate improvement proposals to the management of X, whereas the goal is to increase efficiency and/ or to lower costs.

2.3.2 Main research question

How do the warehousing processes currently look like and how can they be improved to increase efficiency and/ or to lower costs?

2.3.3 Demarcations

The following demarcations apply to the research:

• The research has a time limit of five months, more specifically: the research starts on the 10th of October 2005 and ends on the 9th of March 2006.

• The research does not intend to cover all warehousing operations, but focuses mainly on the picking process and the inbound operations. However, those operations, which clearly have a negative impact on the general performance of the ECDC, will also be invested. Operations, which don’t take place within the warehouse part of the ECDC, are out of the scope of this research.

• Inventory planning and control are outside the scope of this research. W performs this activity, as part of their distribution planning.

• Due to the sensitive nature of the information and the confidentiality closure of X and W, the report is only published to the management of X and to the first and the second supervisor at the University of Groningen.

2.4 Theoretical framework

In this section, the theoretical concept will be discussed. Based on the theoretical concept, the main research question will be translated into sub-questions.

2.4.1 Theoretical concepts

A structured method to improve operations processes is provided by Riezebos (2003), who presents a diagnostic tool, “The Groningen Manufacturing Scan”, for processes from an operations management point of view. The scan consist of four stages, based on the theories of (Wijngaard; 2000), for a diagnostic process scan.

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21 In the next stage, processes that contribute to the performance gap are detected. A

global description of the transformation process and the control of the process are generated. Also, a characterization of the sub processes and its supporting functions in terms of complexity and contribution to the performance gaps is made. The aim of this stage is to select a small part of the sub processes that contribute for the largest part to the performance gaps.

In stage 3, a detailed process analysis for each performance dimension is constructed. The analysis includes a description of the selected sub processes in terms of actors, activities, dependencies, resources and contribution to that performance dimension. This part of the analysis will provide an insight in the discovered causes for each performance gap. Moreover, redundancies or incompatibilities within the processes and their control will be detected. Before improvement proposals can be generated, the detected causes for each performance objective need to be checked on consistency and coherence. Afterwards, a decision should be made about the type of process improvement.

The last stage of the scan aims at detecting extra-operational causes for the detected performance gaps. This enables a better foundation for the decision on the type of process improvement. Extra-operational causes have been defined by Riezebos (2003) as possible causes for the detected performance gaps, outside the operational processes. If these are detected, a more radical type of process improvement or a change in these extra-operational causes is needed.

2.4.2 Sub questions

In order to answer the main research question, sub questions have been formulated, based on the theoretical concepts in the previous section.

1. What is the meaning of the performance objectives for the studied situation? 2. What is the relative importance of performance objectives for the operations in

the ECDC?

3. How is the current performance for each performance objective? 4. Is there a gap between the objectives and the current performance?

5. Which different (sub) processes within the warehouse area of the distribution centre can be identified?

6. Which of these processes contribute for the largest part to the main performance gaps?

7. Which inefficiencies or redundancies can be found within these processes? 8. Which extra-operational causes contribute to the performance gaps?

9. Which improvement tools can be identified for each of these inefficiencies or redundancies?

10. How does the consistency and cohesiveness between the improvement

possibilities look like?

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2.5 Information sources

The following information sources are used during the project: documents, media, databases and the reality (the field).

Documents

For the desktop part of the investigation, several sources, ranging from text-books of Business Administration and logistical magazines to reports, are used. A detailed list of the documents is provided in the bibliography.

Databases

The use of databases consists of the internet, in particular the websites of “the Web of Science”, “Business Source Premier”, “Operations Management Society”, “Emerald” and Y.

Reality

Field research is an important part of the investigation. The field is in this case mainly being identified as a physical reality, in which there will be a particular focus on the warehouse part of the ECDC. Another part of the field research is the investigation of the social reality. This aspect is aimed at interviewing employees of X.

2.6 Methods for measurement and analysis

After the sub questions for answering the main research question have been defined, methods for measurement and analysis need to be determined. A distinction can be made between measurement with and without a stimulus, whereas measurement without a stimulus is defined as registration. The advantages of this way of collecting data are the efficiency and the small deviation (De Leeuw, 2003: 107). The registration methods, which will be used, are defined below.

• Observation: observations of warehouse processes

• Analysis of reports: analysis of a wide range of company documents

• Analysis of numerical data: analysis of data from the warehouse management

system and the data of the scorecards

A method with a stimulus, which will be used is interviewing. This refers to the interviewing of warehouse employees as well as the management of the ECDC.

2.7 Reporting procedure

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Phase Time

consumption Project steps

Preliminary research Stipulation of research goal

Phase I Preparation

Phase II Research

Main research

Recommendations & report Phase III Report 3 Weeks 9 Weeks 9 Weeks Collecting data Analyzing data Research objective Main research question

Demarcations

Defining criteria Analyzing & describing current situation

Performing literature study Defining gap

Developing recommendations Writing & presenting report

1 2

3

4

2.8 Project planning

Figure 2.2 provides an overview of the project planning in weeks.

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Chapter 3: Process analysis

In this chapter, the Groningen Manufacturing Scan will be applied to the studied situation. The chapter consists of four sections, in which the four stages of the process analysis will be discussed. In Section 3.1, the performance objectives will be specified for the empirical situation and the existence of a performance gap will be determined. Section 3.2 aims at identifying the relevant (sub) processes that contribute to the identified performance gaps. In Section 3.3, a within-process gap analysis per performance dimension will be made. Section 3.4 discusses the analysis of potential extra-operational causes for the performance gaps.

3.1 Objectives and performance

As mentioned in Sub-section 2.4.1, Slack (2004) distinguishes five performance objectives: quality, speed, dependability, costs and flexibility. Riezebos (2003) follows Wijngaard (2000) by stating that the meanings of these objectives vary per situation.

3.1.1 Determining context specific meaning of performance objectives

In this section, sub question 1 regarding the meaning of the performance objectives for the empirical situation will be answered. The meaning of the performance dimensions can be stated more exactly, based on an analysis of the characteristics of the industry and the specific situation. This analysis has been made, by analyzing the scorecard of the ECDC, analyzing the specific characteristics of W and comparing these analyses to the classification of performance objectives by Slack (2004: 43 - 57). According to Riezebos (2003: 3), this part of the process analysis should result in a description of the measures per indicator. Schönsleben (2000: 94) introduces a matrix, by which this description can be made. Based on the analyses mentioned above, an interpretation of the matrix for the studied situation has been made. The result is shown in table 3.1.

Indicator Quality Speed Dependability Costs Flexibility

Context specific definition Consistently handling items to specifications as set by W Handling items within the customer-specified time frame

On-time staging in outbound area Money, spent on staff, facilities, technology, equipment and material Ability to change the operation to react on changes Reason(s) for measuring - Customer satisfaction - ISO-certification Customer satisfaction Customer satisfaction Offering lowest price Ability to respond to changes Facts to measure (KPI’s) - Part location accuracy - SSMM Part location accuracy - Gross $ accuracy (month-to-date) - Net $ accuracy (month-to-date) - Pick effectiveness - First pass pick effectiveness - Receiving carry over - Receiving backlog > 24 hrs - Putaway backlog - MRB Agings > 10 days - QA Inspection > 48 hrs - Incomplete stock transfers > 24 hrs - Per-order labour costs (handling costs) - Labour hours to achieve output - Valid locations - Occupied locations - Warehouse location utilization

(mix and volume flexibility)

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Indicator Quality Speed Dependability Costs Flexibility

Facts to mea-sure (KPI’s) - Non-confor-mances overall PPM - Non-confor-mances customer PPM - Posting change incomplete > 24 hrs - Dispositioned scrap area > 24 hrs - Receipts not stocked > 24 hrs - Dock quality area > 24 hrs - Quality staging > 48 hrs - Shipping area > 24 hrs - Differences storage type > 10 days - Cycle count differences > 5 days - Pass through agings (all plants) - Average cycle DN-TO - Average cycle TO-PGI - Average cycle DN-PGI - Max cycle DN-PGI - Failures, DN’s (TO-PGI > 1 hr) - Failures, lines (TO-PGI > 1 hr) - % Lines success rate - % Downs DN success rate (TO-PGI)

- % DN Success rate sans excluded failures - Average cycle DN-TO - Average cycle TO-PGI (24 hrs) - Average cycle DN-PGI (24 hrs) - Max cycle DN-PGI - Failures, DN’s (TO-PGI > 24 hrs) - Failures, lines - % Lines success rate - % Reg DN-PGI success rate - % DN Success rate sans excluded failures - Number of different available pick up times - Number of labour shifts (delivery flexibility) - Breadth of qualifications

Table 3.1 (part 2): description of measures per indicator (Schönsleben; 2000: 94)

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3.1.2 Determining objectives

According to Riezebos (2003: 4), the next step of the first phase is to determine objectives per performance dimension. These can be read from the fourth row in table 3.1. The definition of each KPI can be found in appendix 2. The objectives have been determined by studying the KPI’s from the scorecard of the ECDC, comparing them to the classification of performance objectives by Slack (2004: 43 – 57) and filtering them into relevant performance dimensions. Surprisingly, no KPI’s for costs could be detected. The generated KPI’s have been determined based on the article of Ramaswami (2005: 55). According to Ramaswami, these are the most useful costs measures for DC’s and warehouses. Also, Ramaswami has found that these KPI’s are most frequently used in practice.

Special attention should be provided to the dependability dimension. Slack (2004: 43 – 57) defines dependability as doing things in time for customers to receive their goods or services exactly when they are needed, or at least when they were promised. However, the ECDC is not responsible for the arrival of the shipment, due to the fact that the ECDC out sources transportation to other third party logistics providers. This disables the possibility for measuring dependability. Another definition of dependability is provided by Slack (2004: 43 – 57) by applying dependability to the inside of the operation. Dependability is then judged by internal customers (the employees), who will judge each other’s performance partly by how reliable the other processes are in delivering material or information on time. The ECDC should handle the products within the agreed upon lead times for regular and down orders. This applies to the process between receiving and staging before shipping. W has defined cycle times for the internal processes. These are covered, however by the indicators for speed. Therefore, indicators for the dependability dimension could not be established.

3.1.3 Determining weight of objectives

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Figure 3.1: nine-point scale of importance (order qualifying and order winning criteria analysis) (Slack; 2004: 648)

By means of the nine-point scale of importance, an interpretation of the meaning of the performance dimensions has been performed by the management of the ECDC. This has resulted in the following categorization:

• Quality: order winner, strong

• Speed: order winner, medium

• Dependability: qualifier, strong

• Costs: qualifier, strong

• Flexibility: qualifier, medium

According to the management, quality is the most important performance dimension, because quality problems are likely to lead to longer idle times and thus higher costs at the production facility of the customers of W. Speed is only slightly less important. W requires the ECDC to handle standard products within 24 hours, whereas down orders should be made ready for shipment within one hour. These two performance dimensions are also the most important criteria within the incentive program between W and the ECDC and the scorecard of the ECDC. This is another indication for the relative weight of these dimensions.

The statements of the management about the weight of the dimensions have been compared to the publications of McGinnis et al (1995) and Kapur et al (2003). In the first publication, decisions regarding the selection of third party logistics services are discussed. The latter provides information about the new competitive environment of the high tech industry. McGinnis et al (1995: 100) conclude that third party selection issues affected by strategy and environment focus on performance, rather than costs. Apparently, costs are of little importance if performance criteria are not met. Performance and quality requirements are constraints to be satisfied before rates become a significant issue in logistics service provider selection. Rates can be the deciding factor, only when service quality is deemed equal (McGinnis et al; 1995: 99). This confirms the interpretation of the management of the ECDC, in which costs are identified as a strong qualifier, but not an order winner. McGinnis et al also point out that reasons more likely to appeal to potential accounts are in the area of logistics system performance. Other issues will be relevant only if performance objectives can be met or improved on. This emphasizes the importance of the objectives quality and speed. Order winner Qualifier Less important

Strong 1 Provides a crucial advantage

Medium 2 Provides an important advantage

Weak 3 Provides a useful advantage

Strong 4 Needs to be up to good industry standard

Medium 5 Needs to be up to median industry standard

Weak 6 Needs to be within close range of the rest of the industry

Strong 7 Not usually of importance but could become more so

Medium 8 Very rarely considered by customers

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28 Kapur et al (2003: 35 - 36) state that the high tech sector is currently characterized by

a shift from vertical to horizontal business models, i.e. a change from suppliers delivering a complete package consisting of application software, operating systems, hardware, assemblies, semiconductors and semiconductor equipment to suppliers offering only one of these components. According to Kapur et al (2003: 36), every specialized supplier is now being exposed to a price-performance dynamic. This results in an ever-increasing demand for greater performance. This confirms the importance of the performance dimension quality. It is also argued that service and customer relationships are now becoming vital to sustaining success. Product availability is becoming an element of differentiation (Kapur et al; 2003: 38). This is in line with the identified importance of the speed dimension.

3.1.4 Detecting performance gaps

Finally, to be able to answer the formulated sub questions 3 (“how is the current performance of each performance objective?”) and 4 (“is there a gap between the objectives and the current performance?”) in Section 2.4.2; it should be determined whether there is a significant gap between the objectives and the actual performance. Riezebos (2003: 4) states that, if historic data is available, one can relatively eaXy apply a quantitative analysis. This analysis has been applied to the scorecards of the ECDC. For this, all scorecards of the fiscal year 2005 of W have been gathered. It has been decided to use this period, because the data of this period is very recent: the period ends on the 30th of October 2005. Also, the period has been formally closed, which means that all needed data is available. The data of all relevant KPI’s from table 3.1 have been measured for each week ending. The results can be found in appendix 3. The most important findings per performance dimension will now be discussed.

3.1.4.1 Quality

Figure 3.2 shows the performance on the dimension of quality, measured in parts per million failures (PPM).

Figure 3.2: quality measured in part per million (PPM)

The measurement in PPM is in line with the concept of Six-Sigma, discussed by Evans and Lindsay (2002: 595 – 603). According to this concept, a defect is any

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29 mistake or error that is passed on to the customer. Usually, quality output is measured

by defects per unit (DPU):

DPU = number of defects discovered/ number of units produced1

In the definition of Six-Sigma, output quality is measured by defects per million opportunities (DPMO):

DPMO = DPU x 1.000.000/ opportunities for error

As can be noticed from figure 3.2, the amount of failures can be described by a downward trend. The performance, measured by parts per million, stays well within the boundary as set by W. Exceptions can be noticed in weeks four and 17. The latest measurement (Q4) resulted in a value of 512 PPM. Interpreted by the Six-Sigma approach, this implies a quality level of 4.5, which is the fourth quality stage towards Six-Sigma. The lowest value (Q3) is 155, which is almost 5.5-Sigma. The trend line is moving towards 400 PPM, which is almost 5-Sigma (Evans, Lindsay; 2002: 598) and represents a good performance.

3.1.4.2 Speed

From appendix 3, several conclusions about the performance on the dimension of speed can be made. Firstly, the MRB agings (the total sum of the dollars in the Material Review Board, greater than ten business days) showed a poor performance, but can now be described by a declining trend and thus a better performance. The KPI cycle count showed a poor performance during the first two quarters of the fiscal year 2005. However, an improvement has been made during the last two quarters. Also, pass through agings (the total sum of the dollars in all storage locations for a business day) shows a poor performance during the third quarter, but improvements are noticeable in the last quarter of 2005. The most important findings, however, are the deteriorating cycle times of regulars. Clearly, a performance gap can be identified regarding the performance dimension speed. The cycle times refer to the process of DN to PGI, as described in Section 1.3.3. As mentioned in the section, DN to TO can not be influenced, because this process is firstly dependent upon the timing of the order placement by the customer and secondly by the capacity of the computer network. However, the process between TO (the generation of the transfer order in the warehouse) and PGI (the formal booking before shipment) comprises of several processes, which can be influenced. These processes are order picking, packing and checking and will be discussed in Section 3.3.2.

It needs to be mentioned, that optimum performance can only be realized by a combination of desired performance of both dimensions quality and speed. For example, if a down order is send to a production plant, where a production line is idle, only an item in the right quantity at the right time can achieve high service levels. An item, which is received at the right time, but in the wrong quantity (e.g. too small quantity of items), can further increase the idle time of the production line.

1

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3.1.4.3 Dependability

As previously discussed in paragraph 3.1.2, indicators for the performance on the dependability dimension have not been determined. However, according to the management of the ECDC, a measurement system for on time delivery is currently being developed. Preliminary results indicate a score of approximately 98 percent, which can be considered as good.

3.1.4.4 Costs

As mentioned in Section 3.1.2, indicators for costs have not been established by the ECDC. Because labour costs represent the majority of the variable costs (see Section 1.6), the development of the labour hours has been compared to the development of the handled quantities in the inbound as well as the outbound department. Based on the data, it can be stated that the handled quantities increased over the entire fiscal year 2005, while the quantity of labour hours remained stable. This can also be noticed in figure 3.3, which provides an overview of the comparison of labour hours and demand over the last weeks of the fiscal year.

Figure 3.3: comparison of labour hours and demand (last weeks of fiscal year 2005)

This implies a decrease in labour costs as well as an increase of productivity.

3.1.4.5 Flexibility

Although no performance levels regarding the flexibility dimension have been prescribed by W, some conclusions can be drawn. Firstly, the warehouse utilization indicates the ability to respond to changing volumes and/ or changes in the dimensions of items. For example: if more crates than expected arrive at the ECDC, the management of the ECDC should have the ability to store these items. For this, certain flexibility in the utilization of the crate storage area is needed. Also, an increase in items requires general storage flexibility. The warehouse utilization is relatively constant (around 70 %) as can be noticed from figure 3.4. An exception can be noticed for the first weeks of the fourth quarter of 2005. According to the management, this was caused by the sending back of scrap (discarded items) to W.

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Figure 3.4: warehouse utilization

The utilization of the warehouse is, however, measured only for all storage types together. This means that information about the utilization of a certain storage type is not available (e.g. utilization of the pallet racks). Thus, a valid conclusion about the utilization can not be drawn. Also, the utilization of bins is not measured. This means that a bin can be filled for example for 10 percent, but SAP measures this as a utilization of this bin of 100 percent. SAP is able to register the utilization of the bin, but the management of the ECDC does not use this function because there is a large variance in the volume of packing materials for items.

The operational personnel within the ECDC are currently working in three shifts. This means that all possible shifts are currently used.

As depicted in figure 3.5, the average breadth of qualifications per operative employee increases due to received trainings, which creates greater flexibility, because employees are increasing their ability to handle more tasks (Friedrich-Alexander-Universität Erlangen-Nürnberg; 2005).

Figure 3.5: development of qualifications of operational personnel ECDC

Flexibility 54,0% 56,0% 58,0% 60,0% 62,0% 64,0% 66,0% 68,0% 70,0% 72,0% 1 2 34 5 6 7 8 9₁0 1₁ ₁2 ₁3 ₁4₁5 ₁6 7₁ ₁8 ₁9₂0 ₂1 ₂2 ₂3 ₂4 ₂5 ₂6₂7 ₂8 9₂ ₃0 ₃1₃2 ₃3 ₃4 ₃5 ₃6 ₃7 ₃8₃9 ₄0 ₄1 ₄2₄3 ₄4 ₄5 ₄6 ₄7 ₄8₄9 ₅0 ₅1 ₅2 Q1 Q2 Q3 Q4 Quarter (2005) P e rf o rm a n c e ( % )

Warehouse location utilization

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32 The previous figure is based on the trainings matrix, shown in appendix 4. As can be

seen from the appendix, personnel of the inbound department has only received training on inbound activities and the personnel of the outbound department has only received training for outbound activities. This implies that the quantity and diversity

in tasks one can handle, increases, but only within his/ her own department.

3.1.4.6 Demand development

As can be seen in appendix 3, another set of data which has been measured is the demand development over the past fiscal year of W. From figure 3.6 it can be noticed that the demand shows a linear trend.

Figure 3.6: demand development (fiscal year W 2005)

As shown in the figure, the upper line in the graph represents the amount of lines which have been shipped while the second line represents the quantity of lines received by the ECDC. The former is an indicator for the workload of the outbound department and the latter indicates the workload of the inbound department. Firstly, it is remarkable to see that about two times more lines have been shipped than have been received. This could point out that there is an excessive stock (Schönsleben; 2004: 5580). However, the ECDC receives a certain amount of lines, but these lines are occasionally being de-kitted, which results in a greater amount of lines. But, a second conclusion, which can be drawn from the graph, is the different timing of peaks and valleys over time between the inbound and outbound department of the ECDC. This implicates that it is possible that the outbound department has to deal with a full utilization of resources in a certain week or during a certain day, while the inbound department is underutilized in that same week or day. This is an important discovery, due to the fact that the ECDC hires temps on a regular basis to increase capacity of the departments.

The detected difference of workload peaks between the two main departments raised questions about the planning capabilities of the departments, or to be more specific: the planning capabilities of the section chiefs, which are responsible for the planning of resources. After interviews with the management and the section chiefs, it has been found that the planning capabilities of the section chiefs are very limited due to the lack of forecasts. In the Statement of Work (SOW), the contract between X and W, it

Demand development 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2 1 3 1 4 1 5 1 6 1 7 1 8 1 9 2 0 2 1 2 2 2 3 2 4 2 5 2 6 2 7 2 8 2 9 3 0 3 1 3 2 3 3 3 4 3 5 3 6 3 7 3 8 3 9 4 0 4 1 4 2 4 3 4 4 4 5 4 6 4 7 4 8 4 9 5 0 5 1 5 2 Q1 Q2 Q3 Q4 Quarter (2005) Q u a n ti ty ( L )

Total DN line items PGI'd (downs & regulars)

New daily inbound lines (downs & regulars)

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33 is mentioned that the ECDC and W agreed to implement a volume forecast model for

the expected ECDC warehouse services (SOW: 9). However, such a model has not been implemented. Currently, the section chiefs don’t have quantitative data on which they can base their capacity planning decisions. However, according to Schönsleben the efficient use of capacity is an extremely important factor, because it enables the company to cut costs, ensure prompt delivery and increase flexibility (Schönsleben; 2003: 673). Thus, another important gap can be identified here.

3.1.5 Overview

Before starting the last part of the second stage of the analysis, an overview will be provided of the main performance gaps.

As can be read in the previous Sections, the following performance gaps have been detected:

• Deteriorating performance on the dimension of speed. This regards regular orders as well as down orders

• Limited planning capabilities. Limited planning capabilities for the section chiefs are available due to the lack of a forecasting model

• A difference in workload peaks between the in- and outbound department

• Limited information about the storage utilization in the warehouse

These performance gaps will be the basis for the next steps in the process analysis.

3.2 Identification of relevant processes

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Figure 3.7: processes in the ECDC

Next, all components of the previous figure are examined whether they contribute to the performance gaps detected. This will be done in Section 3.3 by means of a process flow chart. According to Riezebos, the 20/80 rule can be expected to be valid, indicating that only a small portion of all sub processes will have to be considered in detail, as they contribute for the largest part to the main performance gaps (Riezebos; 2003: 5). The analysis helps to identify the necessity of including specific processes in the detailed analysis of the last two stages of the process analysis.

3.3: Within-process gap analysis per performance dimension

In the third stage of the analysis, a deeper understanding for the detected performance gaps will be gained. Furthermore, a decision will be made about the type of process redesign, which will be needed.

3.3.1 Introduction to process analysis

According to Slack (2004: 664), a useful tool for gaining a detailed understanding prior to improvement, is the process map, also called flow chart. Flow charts record each stage in the process and quickly show up poorly organized flows. These charts can also clarify improvement opportunities and shed further light on the internal mechanics or workings of an operation. Also, they highlight problem areas where no procedure exists to cope with a particular set of circumstances. Most importantly, flow charts are able to show delays and bottlenecks within the total process. According to Riezebos (2003: 8), the analysis generally leads to the discovery of redundancies or incompatibilities within the processes and the planning and control applied to them (either in the way performed or in their design). The flow chart has been generated based on the detailed process descriptions of the ISO quality certification documents and the actual process steps, which have been identified during field research and the time measurements. Slack (2004: 664) and other authors only discuss a single measurement for the establishment of the process flow chart. However, to increase the validity of the flow chart, four different measurements have been taken within a timeframe of four weeks. An advantage of the multiple measurements is that different employees performing the same activity could be observed. This is important, because the productivity of employees is likely to vary.

Receiving Quality assurance Internal transport Internal transport Internal transport Internal transport Internal transport Cross-docking

Process optimizations

Process optimizations

A research regarding process optimizations within the European

Continental Distribution Center of a logistics service provider in

Frankfurt, Germany

Process optimizations

A research regarding process optimizations within the European

Continental Distribution Center of a logistics service provider in

Frankfurt, Germany

Preface

Management summary

Table of contents

Chapter 1: Company profile

1.1 Y

1.2 X

1.3 X Frankfurt (ECDC)

1.3.1 Service Centre

1.3.2 Warehousing operations

1.3.3 Main process steps

1.3.4 Warehouse layout

1.3.5 Storage types

1.3.6 Operating costs

1.3.7 Performance measurement

Chapter 2: Research design

2.1 Research motive

2.2 Typifying the research

2.2.1 Scientific research versus empirical research

2.2.2 Process definition and product

2.3 The problem definition

2.3.1 Research objective

2.3.2 Main research question

2.3.3 Demarcations

2.4 Theoretical framework

2.4.1 Theoretical concepts

2.4.2 Sub questions

2.5 Information sources

2.6 Methods for measurement and analysis

2.7 Reporting procedure

2.8 Project planning

Chapter 3: Process analysis

3.1 Objectives and performance

3.2 Identification of relevant processes

3.3: Within-process gap analysis per performance dimension