Lade Inhalt...

Six Sigma in Logistics

Hausarbeit 2007 33 Seiten



Index of content


2.2.1 Leadership
2.2.2 Organizational Structure
2.3.2 Tools


4.1.1 Wastes of space and facilities
4.1.2 Wastes of transportation
4.1.3 Waste of inventory
4.1.4 Packaging waste
4.4.1 Define
4.4.2 Measure
4.4.4 Improve
4.4.5 Control



1 Introduction

1.1 Initial situation

Supply chain management is a key strategic factor for increasing organisational effectiveness and for better realisation of goals such as enhanced competitiveness, better customer care and increased profitability (Gunasekaran/ Patel/ Tirtiroglu 2001, p. 71). There has been activity in both academic and industrial circles to generate improvements in this area. The principal focus of this activity has been in waste reduction. Little effort has been expended on the reduction of variation. Six Sigma has shown to be successful in delivering business benefits through variation reduction (Knowles/ Whicker/ Femat 2005, p.51).

Six Sigma is a comprehensive system to achieve, sustain and maximize business success of companies. With this system it is possible to understand customer needs, to use facts, data and statistical analysis more disciplined, and to manage, improve and reinvent business processes (Pande/ Neuman/ Cavanagh 2000, p.21).

On the whole it is interesting to see how the linkage between Six Sigma and Logistics is developed. While Six Sigma has traditionally been associated with manufacturing and product quality, leading manufacturers are using it nowadays to improve their Logistics capabilities. Applying Six Sigma methodology to complex and challenging Logistics processes, can decrease variation and optimize the processes (Selzer 2006, p.54).

1.2 Aim and structure of the paper

The aim of this paper is to describe some relevant binding elements between Six Sigma and Logistics and to make clear the benefits of this combination. The paper consists initially in a description of general basic principles of Six Sigma and the definition of vital concepts. In chapter 2 and 3, an overview about functions, features and the importance of Logistics is given. Following this principles, Six Sigma is linked with Logistics as a tool to optimize processes, while reducing variation of key process measurements. Finally Six Sigma is applied to transport function of Logistics in a hypothetical example. This work closes with a conclusion and an outlook.

2 Six Sigma - An overview

In the early 80’s American manufacturers were threatened by competition from foreign industry, mainly the Japanese. The high quality and low price of these new goods forced the manufacturing industry to increase their quality in production. At this stage, Motorola realized that they were losing part of their business and productivity due to the lack quality in their products. Motorola had a quality system of three sigma, allowing 2,600 defective parts per million (Raisinghani et al 2005, p. 492). This became more evident when a Japanese firm took over a Motorola television set factory. Using the same workforce, technology, and design, the Japanese management made the factory able to produce TV sets with lower number of defects than they had produced under last management; demonstrating that the problem was Motorola’s management (Pyzdek 2003, p. 4). In order to solve their problem, Motorola created Six Sigma, which was a response to the customer demand claims issued by their sales department, due the great number of unsatisfied customers claiming the guarantee of defective products and the pressure made by the competitor companies.

Motorola's most significant contribution was to change the discussion of quality levels measured in percentages (parts per hundred) to a discussion of parts per billion. Motorola pointed out that modern technology was too complex to keep working with only acceptable quality levels. Motorola realized that the quality level associated with a measure of Six Sigma corresponds to a failure rate of two parts per million opportunities, standard measure that finally made of their own. However, Six Sigma has evolved over the last two decades and so has its definition. According to the Motorola University, Six Sigma has literal, conceptual, and practical definitions. Nowadays it is possible to think about Six Sigma at three different levels (Motorola University, 2007):

- As a metric
- As a methodology
- As a management system

Six Sigma as a Metric

The main goal of Six Sigma is to achieve a performance of zero defects, where a defect is understood as anything that contributes to unsatisfied customers. Six Sigma was developed to eliminate variations in the service and quality of the products and processes (Ramberg, 2000). The term "Sigma" is often used as a scale for quality. Using this scale, "Six Sigma" equates to 3.4 defects per one million opportunities (DPMO). Therefore, Six Sigma started as a defect reduction effort in manufacturing and was then applied to other business processes for the same purpose (Motorola University, 2007). In figure 1 we can see represented the area under the curve of a normal distribution that corresponds to each of the sigma from 1 to 6 according to Barringer and Associates.

illustration not visible in this excerpt

Figure 1: Distribution o sigma values (Barringer 1999)

According to Ramberg “Six Sigma is a quality objective that specifies the variability required of a process in terms of the specifications of the product so that product quality and reliability meets and exceeds today's demanding customer requirements”(Ramberg 2000).

Six Sigma as a Methodology

Six Sigma can also be seen as a business improvement methodology that helps an

organization to focus on (Motorola University, 2007):

- Understanding and managing customer requirements
- Aligning key business processes to achieve those requirements
- Utilizing rigorous data analysis to minimize variation in those processes
- Driving rapid and sustainable improvement to business processes

Once other companies realized the success that Motorola had with Six Sigma, they started to implement the system. The best example is General Electric. These are the results achieved within the implementation of Six Sigma in the first two years (1996-1998), saving money and raising profit (Kotelnikov 2007)

- Revenues rose to $100 billion, up 11%
- Earnings increased to $9.3 billion, up 13%
- Earnings per share grew to $2.80, up 14%
- Operating margin rose to a record 16.7%
- Working capital turns rose sharply to 9.2%, up from 1997's record of 7.4

These results achieved by General Electric in such a short period of time proved that Six Sigma is really efficient and contributed to make of it a highly recognized system and encouraged other companies to implement it worldwide.

Six Sigma as a Management System

Since Six Sigma as Metric and Methodology could not be implemented within a company without the help of an organizational strategy, Six Sigma as Management System is a high performance system for executing business. Six Sigma is a top-down solution that helps organizations to achieve the following goals (Motorola University, 2007):

- Align their business strategy to critical improvement efforts
- Mobilize teams to attack high impact projects
- Accelerate improved business result

Govern efforts to ensure improvements are sustained.

2.1 Six Sigma and Total Quality Management

With Six Sigma, quality is redefined as the value added by a productive effort. Thus quality can be divided in to potential quality and actual quality. Potential quality is the maximum possible value per unit of input while actual quality is the real value per unit of input. The difference between potential and real quality is called waste. Since Six Sigma focuses on improving quality, this means also to reduce waste and this is possible by helping organizations produce products and services better, faster and cheaper. Six Sigma focuses on defect prevention, cycle time reduction, and cost savings. The goal of Six Sigma is to identify and eliminate costs that provide no value to customers: waste costs (Pyzdek 2003, p. 224).

At the same time, Six Sigma is a rigorous, focused and highly effective implementation of proven quality principles and techniques. Incorporating elements from the work of many quality pioneers, Six Sigma aims for virtually error free performance. Six Sigma and Total Quality Management (TQM) are indeed very similar, since both refer to methodologies implemented top down which embrace self-improvement within organizations, starting from the upper management. However, Six Sigma present an advantage over traditional TQM programs, since with TQM, people were unable to point specific bottom-lines benefits and sometimes the programs got lost in difficult times, while with Six Sigma it is possible to see dramatic results within a short period of time, leading to a change in the company’s culture. This is possible since the Six Sigma approach, which could be defined as a Strategic Initiative, has several advantages compared to the Quality Initiative of TQM as showed in table 1 (Pyzdek 2001).

illustration not visible in this excerpt

Table 1: Differences between TQM and Six Sigma (adapted from Pyzdek 2001)

2.2 Main Components of Six-Sigma

If we take into consideration the three different approaches of Six Sigma we mentioned before, as metric, methodology and management system, it is possible to say that Six Sigma more than a quality initiative, is a business initiative, which leads to improve quality and productivity, therefore, to increase profit. Thus, as management system, Six Sigma has three main components, which are described in the following chapters.

2.2.1 Leadership

Since Six Sigma provides the means through which the company is going to achieve strategic goals, it is important that top management become responsible of the performance and thus, implement Six Sigma from top down. There is no chance of success if it is implemented without the commitment of the leaders, since Six Sigma focuses on cross-functional processes and not in local improvements. Moreover, Six Sigma is a management philosophy focused on setting really high objectives, collecting data, and analyzing results to a degree for reducing defects in products and services. The philosophy behind Six Sigma is that if you measure how many defects are present in a process or a service, you can figure out how to eliminate them systematically and get as close to perfection as possible.

2.2.2 Organizational Structure

Once the leaders of the company had decided to implement Six Sigma, they gather a group of people committed with the improvement (usually they are technical leaders) and train them to a high level of proficiency in the application of the techniques used within the methodology involved in Six Sigma. These technical leaders have the duty of implementing Six Sigma at the different levels of the company; thus, they are divided hierarchically. Table 2 shows how these hierarchies are organized to the within the company as well as the responsibilities and skills of each, according to the Motorola University (Motorola University, 2007):

illustration not visible in this excerpt

Table 2: Structure of Six Sigma (adapted from Pyzdek 2003 & Motorola University 2007)

2.3 Six Sigma Methodology and Tools

As we already said, Six Sigma uses a myriad of tools already available, which can be applied within DMAIC and DMADV models which are going to be explained in this section. However, the most important tools used within Six Sigma are the Statistical Methods and Quantitative Analyses.


DMAIC Method

Six Sigma relies on tried and true methods that have been around for decades and puts a new twist on these, which are applied within a simple performance improvement model known as DMAIC, within an intense use of statistical computer software. DMAIC is an acronym for Define-Measure-Analyze-Improve-Control can be described as follows:

D Define the goals of the improvement activity. What is important?

M Measure the existing system. How are we doing?

A Analyze the system. What is wrong?

I Improve the system. What is wrong?

C Control the new system. How do we guarantee performance?

DMAIC is used when a project’s goal can be accomplished by improving an existing product, process or service.

DMADV Method

A different approach is used when the goal is the development of a new or radically redesigned product, process or service. Then the DMADV method or Define-Measure- Analyze-Design-Verify is used. Basically the only difference between DMAIC and DMADV is the Design part instead of Improve and Verify instead Control, since it is related to a new approach within the company and not to an already existing one.

2.3.2 Tools

Some of the Tools used by the methodology of Six Sigma are listed according to the step in which they are most commonly used within the DMAIC methodology according to Knowles (adapted from Knowles 2005, p.57):

illustration not visible in this excerpt

These tools are applied at once on real projects designed to deliver tangible results for an identified stakeholder.

3 Basic Principles of Logistics

Logistics is a science that nowadays is part of almost every modern company. A reliable and cost effective logistical support has gradually become vital in companies, if those want to stay competitively and sustainable in the market for the long term. Poirier has estimated that “(…) between 65%-85% of total costs can be related directly to supply chain operations” (Poirier 1999, p.1). That is why “(...) Logistics have the potential to become the next governing element of strategy as an inventive way of creating value for customers, an immediate sources of savings, an important discipline on marketing and a critical extension of the production flexibility” (Fuller/ O’Connor/ Rawlinson 1993, p.1).

3.1 Definition

Finding a general concise definition of Logistics on the literature is not an easy task. In order to understand the concept better, we have to differentiate Logistics from supply chain management (SCM) and define how these two sciences relate to each other. This subject is a matter of discussion: there is no single universal definition about these concepts. The following, are some definitions of Logistics and Logistics management:

a) Logistics recognize the difficulties associated with getting the right product to the right place at the right time in the right quantity and condition at the lowest possible cost. (Goldsby/ Martichenko, 2005 p.3).
b) Logistics management is that part of supply chain management that plans, implements, and controls the efficient, effective forward and reverse flow and storage of goods, services and related information between the point of origin and the point of consumption in order to meet customers' requirements (Council of Supply Chain Management Professionals, 2007).
c) Beyond management of physical inventories and information in the domain of logistics is the way that products are developed, marketed and sold. Add in the relationships with suppliers and customers and you have supply chain management (Lambert/ Knemeyer 2004, p.114).

The further development of the concepts of Logistics and SCM are based on the definitions b) and c) respectively. When these concepts are referred, these two definitions should be taken into account.

3.2 Development of Logistics and its general functions

Historically seen, Logistics was first used in the military. Logistics was needed to provide the troops with necessary goods at any time and any place. Nowadays Logistics has another meaning and tasks since this science has been having big developments parallel to the economy in the past few decades.

Modern Logistics concepts date back to the 1960s in the USA. In that former time, the marketing started to focus on two factors: lowering the cost of distribution and improving the delivery service. Later, the introduction and realization of some philosophies like lean production, Total Quality Management and Just in Time in American and European industries had (and currently still have) a big influence on the development of Logistics. These Logistics developments promise concrete to help on some features such as zero defect strategies, improvements on quality, better use of resources according to demand (made to order), focus on value adding while avoiding waste time, inventory reduction, and finally having a better customer orientation.

Since the 1980’s another concept has had a major influence on the Logistics: the concentrating on core competencies. Companies started to remove the focus from their weak business areas and therefore strongly specialize on the areas, where they considered being superior and predominant than their competitors. A reduction of the vertical production and an increase of outsourcing was the result.

Nowadays companies tend to look and choose few but reliable suppliers, which are capable to deliver good quality of supplies. On this special supplier-to-customer relationship a tendency to transfer the research and development responsibilities upstream is rising. These types of company cooperation described above are subsequently giving Logistics a new quality dimension as illustrated by the following quote: “for Logistics, (…) the beginning of a new phase of cross-corporate concepts for which the terms ´Logistics chain`, ´value chain` or ´supply chain` have been coined” (Bode/ Preuss 2004, p.2).

According to Bode and Preuss, the term of modern Logistics can be classified on three levels. First level: Logistics is understood as a function of bridging time and space to transfer objects. Second level: Logistics is the planning, realisation and control of the facilities and processes serving the flow of goods and material. Logistics management is a company cross- section function (Figure 2). It is characterized because it links single operational functions of procurement, production and sales systematically. It strives a holistic development of the operational functions named above; i.e. not to optimize the individual functions but to maximize the (cost) optimization of the company as a whole. The background of this mindset is that an action/measurement can lead to a cost reduction on single company function while the adjacent function is suffering a cost boost (higher that the reduction) as a result of this action/measurement.

illustration not visible in this excerpt

Figure 2: Logistics as an operational cross section function (Bode/ Preuss 2004, p.3)

Third level: all business processes within a corporation and in the division of labour across companies include a logistical dimension. This dimension should be used in a way that the customer requirements are fulfilled the best in order to improve the competitive situation of the company, of their suppliers and finally of the customers.

3.3 Features of Logistics

There are five main features of Logistics:

1. Logistics is function-overlapping: Logistics has a function-overlapping way of thinking that goes far beyond the traditional departmental way of thinking on corporations.
2. Logistics is applied integrally: Actions that lead to (economical, technological and social) optimizations consider the corporate system as a whole.
3. Logistics is company-overlapping: This feature should be understood as an extension of features 1 and 2 from the corporate level to the whole suppliers-company-customers level.
4. Logistics is value and benefit-oriented: The value of the product/service can be augmented by making it more suitable for the respecting purpose and by improving the availability.
5. Logistics is service oriented: Logistics assures the availability of the good (delivery service).

3.4 Importance of information in Logistics

“The flow of information is an elementary part of Logistics concepts” (Bode/ Preuss 2004, p.8). This comprises the information flow within the company functions as well as the external information flow between corporation and suppliers, clients, authorities, etc. Figure 3 shows a closer overview of the materials and information flow. The importance of information in Logistics is reflected in various ways. The one way is that information increases transparency on the whole value chain: A constant tracking of the current placement of the materials is any time possible guaranteeing accuracy for prediction of delivery times. Another way is that information replaces unnecessary inventory by increasing the accuracy on demand forecast and reducing the handling time for disposition of the stocks. Steady lower average inventory levels will reflect on the long term on big cost cuts.

illustration not visible in this excerpt

Figure 3: Flow of material and information (own source)

3.5 Present-day challenges in Logistics

There are many factors that have a direct and indirect impact on a company’s Logistics. The challenges of Logistics are, to manage all these input factors in a way that assures long term and sustainable customer satisfaction as well as the highest possible processes efficiency within the company. Figure 4 summarize the challenges in Logistics in one picture. Notice that the upper blue balloons represent the most important factors influencing logistics and the lowest yellow balloons the outputs that increase the customer’s acceptance of your products and services. The large amount of input/output factors, the managing and coordination of this factors and the high demanded process reliability make the challenges in Logistics a hard task for the company. These challenges should be managed on the context of the whole company since (as we have seen in the previous chapter 3.3) Logistics is function-overlapping and function integrally. As a solution the Six Sigma methods can be applied to Logistics in order to facilitate, improve and control the managing of these challenges.

illustration not visible in this excerpt

Figure 4: Challenges of Logistics (own source)

4 Linkage between Six Sigma and Logistics

In the last two chapters the basics of Logistics and Six Sigma methodology were described. In this chapter we establish the linkage between both concepts. There are three relevant binding elements, see Figure 4. The first link describes the types of waste that can be found in Logistics in order to achieve financial savings when implementing Six Sigma methodology. The second link is about the measurements that should monitor the Logistics processes; in such a way that achievement of variability reduction could be quantifiable. The third element refers to the strategic alignment that Six Sigma projects require to have significant impact in the business and it is directly related to the key performance indicators that should be in place in a Logistics organization (see figure 5).

illustration not visible in this excerpt

Figure 5: Six Sigma - Logistics relevant binding elements (own source)

When these three binding elements are in place, it becomes easier to a company to create a synergy and reach Logistics’ goals using Six Sigma methodology. Obviously there are some other important links between both concepts for example the organizational structure needed to implement Six Sigma (previously described in chapter 2), and the Logistics organizational chart, training and integration of continuous improvement culture; but the focus lies on the three elements mentioned above.

A very simple example: A plant controller -when checking the quarterly results- discovers that the inventory obsolescence (Costs associated with obsolete inventory; sometimes includes spoilage) is increasing since the last year. He talks with the supply chain manager about this issue and asks him to take immediate action. The supply chain manager forms a team and launches a project to find the root causes and to reduce the inventory obsolescence in 5% for the next quarter. To reach this goal the team should start by analyzing deeply the historical data and try to find a cause for this increase, then to measure the actual status of the inventory and the lifetime of the products on the warehouse, they need a lot of quantitative data. For the inventory that is close to obsolesce they should find the causes of having this inventory in the storehouse (over-production, forecast inaccuracy, wrong production planning, etc). To prove one of this causes a lot of quantitative analysis should be performed not just vague suppositions. There is no doubt that supply chain has become a major factor that contributes to the success of companies, therefore they are concerned about: How to improve supply chain performance?

4.1 Financial benefits - Logistic wastes

“You cannot make something out of nothing” (Goldsby, Thomas / Martichenko, Robert 2005, p.19). Resources are necessary to accomplish, but problems arise from using resources unproductively, applying the wrong resources, failing to tap into necessary resources, or directing resources toward the wrong outputs. In each of these instances, waste is created. Costs are incurred, people’s time is consumed, opportunities for value creation and growth are lost, and customers are left less than satisfied.

These inefficiencies create higher accumulated costs that eventually make the product expensive and non-profitable. Muda (as is waste addressed by the Kaizen terminology) is one important improvement target of the Six Sigma methodology, which has long been associated with Lean Manufacturing. While Lean serves to eliminate waste, Six Sigma reduces process variability in striving for perfection. Aberdeen Group (2006, p.19), states that these combined principles are the foundations of Lean Six Sigma, a modern approach of the original Six Sigma methodology that focuses on the improvement of processes and waste reduction.

Waste creation is a crucial unwanted element that affects fundamentally the Logistics environment. The evaluation of this interaction is made, assisted by Six Sigma principles and its new approach; with the purpose of obtain significant savings and furthermore creating efficiency improvement within the Logistics activities.

4.1.1 Wastes of space and facilities

Warehousing plays an important role in the dynamics of the Logistics. Given the interest and ability to acquire materials and build products in advance for the demand, it is understandable that facilities are needed to ensure the integrity and value of materials and goods. Often they are located near to the needed infrastructure with the purpose of achieving an excellent transportation. In modern times, the characteristics of the warehouses exceed what the production facilities really need, creating wastes of space and facilities. The infrastructure for roads and utilities, the high tech equipment and information systems of not only one but multiple sites aiming the storage of useless inventory sum as a whole tens of millions of dollars. A massive quantity of inventory does not necessarily translate into better service and consumer satisfaction, but it does carry more costs and warehousing space.

In order to do not incur in facility wastes “(…) a Lean Six Sigma Logistics warehousing system should be applied: first by evaluating which inventory and characteristics of the warehouse are really needed; consequently it should be analyzed which equipment is the correct one to be used. The basic question is to analyze whether the facility is covering up the inefficiencies of the Logistics operations or if is providing a false comfort to customers” (Goldsby/ Martichenko 2005, p.19).

4.1.2 Wastes of transportation

Another type of corporative expenditures results from the wastes of transportation. Transportation like inventory is a necessary activity within Logistics. It is fundamental to achieve the availability of products near to the hand of the customers in order to satisfy specific needs for speed, reliability, flexibility, availability, safety, capacity and cost efficiency. It takes a great effort from the companies for moving goods and services by truck, rail or sea in order to meet modern on time delivery commitments. These activities make companies incur big investments (improving transportation equipment, training), without considering the time that goods find themselves in transit thus increasing the order lead time and order cycle time variances which results in customer dissatisfaction and higher costs.

illustration not visible in this excerpt

Figure 6: Wastes - In transit time (Goldsby/ Martichenko 2005, p.28)

Linkage between Six Sigma and Logistics

Companies do not visualize that the inefficiencies that create waste are rooted in the poor utilization of equipment, operators, and the non-optimized usage of limited resources that exist within transportation operations. Enterprises must be committed to “(…) remove obstacles that prevent work processes and data from flowing seamlessly across the organization and throughout the supply chain” (Aberdeen Group 2006, p.19). The purpose of a Six Sigma initiative in the transportation is to minimize the average time to move the goods and to minimize the variation around the average. It is possible to visualize this effect in the right shape of figure 6. Here the average times decrease and consequently also the frequency of occurrences around the new average. The left shape of figure 6 refers to events in which the average of transit time is exceeded. The events shown in the left shape are concerning observations because they are long transit times that overpass the average (e.g. probably never reached the destination). In these type of situations is where Logistics opportunities to improve exist, in order to avoid missed deliveries service and keep customer satisfaction, by focusing in increasing the company reliability. Instituting efficient Logistics can minimize Logistics wastes by reducing the in transit times, resulting in an improvement of reliability and creating savings by finding the optimal price for the transportation of goods.

4.1.3 Waste of inventory

One impacting type of waste is encountered in the inventory management, originated by the need of maintaining product availability. The waste of inventory results from the uncertainty of companies to know how much inventory is really needed. Handling high levels of inventory create capital, service and risk costs (as summarized from Lambert 1976, p.68 in figure 6). At the contrary, having a low inventory level drive companies to do not achieve customer orders in a timely way. An efficient supply chain works with shorter planning horizons in order to obtain several important benefits: First it allows companies to rely less on long-range forecasts (which will be inevitable inaccurate); and secondly it reduces the risk of miscalculating the future by relying less in forecasts and more in the actual demand. Goldsby and Martichenko state that “(…) the Six Sigma goal is to control variation and to improve supply chain processes so that the job gets done better on a consistent basis” (Goldsby/ Martichenko 2005, p.19). The Six Sigma strategy captures the experiences and expectations of the customer, reducing the likelihood of developing products and services that are inconsistent with market wants and need, but also alleviating the risk of being caught off guard by unplanned demand. By instituting the Six Sigma methodology in inventory management, an efficient right sizing of the volume of in stock volumes is achieved.

Furthermore, this results in the establishment of a lean level of inventory where customer requirements support is efficiently covered at a lowest total cost for the company.

illustration not visible in this excerpt

Figure 7: Wastes - Inventory carrying costs, (Lambert 1976, p.68)

4.1.4 Packaging waste

Another area of opportunity for savings is packaging, which is a broad term that characterizes all forms of containerization of an item. Packaging is of primary importance because it represents the fundamental physical unit of analysis within the logistics system. The design of a Logistics system begins with the packaging databases that record all the dimensions and capacity of all packages that flow through a company’s facilities. Second, it influences the matter of which the transport analysis is done according to the dimensioning of each package. A type of packaging waste is found when the package fails to protect its contents adequately, damaging the characteristics of the product. Also, the inefficient product packaging dimensions leads to a greater holding capacity that in turn creates higher costs.

Goldsby and Bullock suggest “(…) through a lean approach of the Six Sigma methodology savings can be achieved, by critically focusing on the optimization of the product package due to the high cost that will eventually incur if a greater holding space than needed is utilized. The package it self can be considered as a source of waste, taking in account the environment effects that creates. Furthermore, supply chain recycling strategies should be enforced to avoid ecological penalties and embrace social acceptance toward the product” (Goldsby/ Bullock 2000, p.11).

It has to be kept in mind that savings will come when improvements are made in the different waste generation sources, in order to increase logistical efficiency by using less resource as exemplified by Beardsley in figure 8. This visual acknowledges that waste reduction is accomplished when companies reach a maturity level in their processes by exercising Six Sigma principles; that is, when their procedures leave behind repeatable and organizational echelons (where considerable quantities of waste is created), an achieve an optimized level (where zero or no considerable waste creation exists) by minimizing variation in their processes.

Concluding, it must be stated that the biggest waste from today’s companies comes from packaging, considering that the trade off between protection and waste generation is often negative. Additionally, when a greater package volume is utilized, transportation costs are also influenced triggering total costs.

illustration not visible in this excerpt

Figure 8: Waste generation according to the maturity of the process (Beardsley 2005, p.17)

4.2 Reduction of variation - Process measurements

Six Sigma projects are concerned about variability reduction; because when variation is reduced processes are more stable and predictable, the chance of errors and non- conformances is reduced, and therefore financial benefits are created. The question is which variables should be controlled? It is necessary to go very deep until the proper metrics of the causes of the problem are found (aim of our project). Processes should be decomposed into sub-processes and these into activities, each level shall have its own metric. This process provides the opportunity to re-examine and re-design the processes (Chan/ Qi 2003, p.184). In every single echelon of the supply chain variability is present, it is added up until the end customer receives our product, and perceives the final quality. See figure 9.

illustration not visible in this excerpt

Figure 9: Supply Chain Process Model (Chan/ Qi 2003, p.182)

The total variability (figure 10) is the sum of the process variability and the measurement system variability, for each of these types the variation should be quantified, the sources of variability should be identified, and the variation should be controlled and removed.

illustration not visible in this excerpt

Figure 10: Variability (own Source)

Quantifying the variation is not always an effortless job; sometimes there is insufficient or inadequate data because of numerous reasons. First the need for additional data was not identified prior to the process-measurement effort, and simply the data was not collected (sometimes it is not recoverable). Second, the labour and other costs of acquiring the data circumvented the efforts to obtain it. Finally, the measurement systems required to capture and store the data are often not in place (Sullivan 2005, p. 54). In supply chain for example, manual scanning of barcodes and most recently radiofrequency identification (RFID) technology are used to provide visibility and process insights that can identify input measurement of Six Sigma process.

Once the variability is quantified, the sources of variation should be identified, there are some useful techniques as Sources of Variation, multi-vary analysis, Analysis of Variance (ANOVA), Measurement System Analysis, Failure Mode and Effect Analysis (FMEA), and correlation and regression analyses. After several analyses and large amount of collected data, the root causes of the variation of the analysed processes might be identified.

Afterwards, is possible to set the path of improvement, reducing the variability and controlling it for long term results. To reduce the variability, there are several statistical tools, the most famous are the statistical process control (control charts) and process capabilities.

4.3 Project Strategic Alignment - Key Performance Indicators

From chapters 4.1 and 4.2 the decision of which projects to develop to increaseLogistics performance is becoming simpler. As Brewer has suggested if firms take action by linking their performance measurement system to their supply chain practices, then they will be better positioned to succeed in their supply chain initiatives (Brewer 2005, p.75).Generally speaking, most of today firms have strategic objectives, but they are not usually understood by normal employees, and consequently improvement projects have dispersed goals. The task of cascading the strategy downstream in a company, until reaching the level of projects, is not an easy task; the most common tool to help organizations to do this is called Balanced Scorecard, by providing a framework for strategic measurements and management system. People in an organization should be held accountable for the overall performance, and not only to the entity to which they are responsible (Gunasekaran et al 2000, p. 86).

Innovative companies are using the measurement focus of the scorecard to accomplish critical management processes:

1. Clarify and translate vision and strategy into a set of comprehensive performance measures (and gain consensus)
2. Communicate and link strategic objectives and measures: educating, setting goals, linking rewards with performance measures
3. Plan, set targets, and align strategic initiatives: allocate resources and establishing milestones
4. Enhance strategic feedback, review and learning: articulating the shared vision (Kaplan/ Norton 1997, p. 11).

Which KPIs should measure the supply chain? Given the inherent complexity of the typical supply chain, selecting appropriate performance measures for supply chain analysis is particularly critical, since the system of interest is generally large and complex (Beamon 1999, p. 276). Supply chain requires cooperation, integration, partnership and information sharing; this integration requires a new kind of measurement indicators that show the performance of the chain not of single departments. These integrative indicators will foster members to cooperate and focus attention. Beamon suggest that supply chain measurement system must place emphasis on three separate types of performance measures: resources measures, output measures, and flexibility measures. See table 3 for more detail.

illustration not visible in this excerpt

Table 3: Performance measure types (adapted from Beamon 1999, p.281)

The balanced scorecard has its greatest impact when it is deployed to drive organizational change; providing us with front-end justification, as well as focus and integration for continuous improvement, reengineering and transformation programs, translated in our case to Six Sigma projects see figure 11.

illustration not visible in this excerpt

Figure 11: Strategic alignment of Six Sigma Projects (own source)

As soon as a project has influence on a KPI, the benefits become clearer, the accountability of the project is defined as we know who is responsible for the improvement of the indicator and maybe also the possible team members. Management gets involved as they are interested in improving the KPI, so that they can easily support the project assigning resources and monitoring the development.

4.4 Six Sigma in transport function of Logistics

So far, in this work, a general foundation describing implementation of Six Sigma in Logistics was laid. Further, the usage of this methodology is illustrated by combining a Six Sigma method and a Logistics function. The work towards this can be considered as an adaptation of the research paper by Andrew Chapell and Helen Peck, “(…) the application of a Six Sigma methodology to military supply chain processes (…)” (Chapell/ Peck 2005).

Use of Six Sigma in Logistics functions like transportation, warehousing, inventory control, etc. primarily targets reduction in costs and improvement in reliability. And in order to realize true benefits of such a methodology, it is required that data is available and that the levels of activities involved are sufficiently high (Chapell / Peck 2005, p.10). Furthermore, selection of a particular target Logistics function and the extent of implementation depend upon organization’s goals and available resources. The effect of globalization on transport function of Logistics is profound. Organizations continuously explore opportunities for reducing costs or improving reliability in transportation. In this work, therefore, an approach of implementing Six Sigma in the transport function of Logistics is illustrated. The transport function of Logistics comprises of a wide range of activities. It involves analyzing needs like customer demand, delivery requirements and equipment utilization. Activities like carrier negotiation, audit and payment across all transportation modes also falls within its scope. The challenges faced usually involve reduction of the cycle time and the cost. In this work further, an approach for implementing Six Sigma to investigate the nature and causes of variability in the downstream transport-chain delivery-times is described. For the purpose of exemplification, a hypothetical automotive spare-parts company interested in improving its delivery-time performance is considered. The total time for transportation of spare-parts from factory depot to a local dealer can be divided into four high-level activities as shown in table 4.

illustration not visible in this excerpt

Table 4: Physical distribution process steps for spare-parts (adapted from Chapell/ Peck 2005)

Instead of transport-chain wide implementation of Six Sigma, the focus is further narrowed down, by implementing Six Sigma only within the company, specifically material handling time (MHT) activities for spare-parts within company’s own depot. Because of its aptness for the application at hand, the DMAIC method of Six Sigma can be employed to investigate the nature and causes of variability in material handling times. The framework for application of such a methodology is highlighted further.

4.4.1 Define

The scope and purpose of the project is set by listening to the needs of the customer - regional distributor(s). One such a need can be reduction in variability in delivery time, enabling regional distributor(s) to be sure about their further commitments. Company’s Management will therefore be interested in understanding the nature and causes of such a variability in delivery time. Furthermore, it will be interested in elimination of these causes and also in overall reduction of average delivery time to gain advantage over competition.

4.4.2 Measure

This phase involves establishing and validating the baseline dataset. For the problem at hand, there is need of time-data pertaining to all the activities from demand acknowledgement to consignment dispatch. While table 4 gives a naive sub-division of the material handling activity, in real world this high-level activity can comprise of a large number of sub-activities involving different company functions like production and finance. An initial analysis of data availability should be made to determine what data is already available within the existing company framework, and what data needs to be obtained by appending new systems into the existing framework. For a ‘live’ Six Sigma project, data capture points using Auto-ID strategy and/or web-based technologies could be set up. However, this is influenced by the resources available with the company. For the problem at hand, it should be assumed that all the required data can directly or indirectly be obtained through the company’s already existing ERP system. A hypothetical representative ‘time-continuous’ section of MHT data is shown in figure 12.

illustration not visible in this excerpt

Figure 12: Hypothetical MHT graph at company depot for spare-parts in June (own source)

Similarly, different time-data related to different material handling activities should be collected to form the baseline dataset which serves as inputs for the ‘Analyze’ phase.

4.4.3 Analyze

In this phase quantitative analytical techniques are applied to interpret the dataset using statistical software(s). Thereafter, a Six Sigma practitioner is required to adopt an expansive, imaginative and enquiring approach to identify root causes of unacceptable variation (Chapell/ Peck 2005, p.6). With the problem at hand, the aim can be to assess whether the process is capable as well as under control. ‘Control’ implies stability, which in turn implies a normal distribution of process performance variations around the mean, and ‘Capable’ requires it to be performing in a controlled way at a desired level (Chapell/ Peck 2005, p.6).

illustration not visible in this excerpt

Figure 13: Hypothetical MHT Frequency Distribution for a spare-part (own source)

Figure 13 shows a hypothetical frequency distribution for a spare-part generated using statistical software, and based on data obtained from the ERP system. It can be seen that the distribution is characterized by a left-hand skew. One of the goals of Six Sigma implementation will be the normalization of the MHT frequency distribution i.e. the material handling activities are performed only with random variation in time. In order to achieve this, the root causes affecting the skew in frequency distribution should be identified and addressed.

A shift from quantitative to qualitative analysis is made by using the ‘five-whys’ technique for root-cause analysis. A hypothetical example is provided below:

- Why do regional distributor(s) complain most about delivery time of spare-parts? - Because their perception is mostly shaped by the undesired long tail in the MHT frequency distribution.
- Why do we have undesired long tail in the frequency distribution? - Because the frequency distribution is skewed on left-hand.
- Why is the frequency distribution skewed? - Because we have unaddressed causes affecting the delivery times.
- Why do we have unaddressed causes? - The analysis shows it is because of human factors and ‘non-natural’ variations at work.
- Why do human factors come into picture? - Some orders are relatively low in value and so sales people don’t give priority to them.

The example provides a simplified understanding of how root-cause analysis can be applied to understand the causes of variation in MHT. Having determined the root-causes of variation, the next step will be to improve the process by eliminating the root-causes.

4.4.4 Improve

In this phase improvement initiatives need to be taken to eliminate identified root causes. It is possible that the number of root causes identified in the ‘Analyze’ phase is quite high, and therefore it may not be economically justified to address all of them. For the problem at hand, Impact-Effort matrix tool can be used to identify which root-causes needs to be addressed. The Impact-Effort matrix is a 2 x 2 matrix with ‘low effort’ & ‘high effort’ marked on one axis and ‘low impact’ & ‘high impact’ marked on the other. The identified root causes are clustered in one of the four cells of the Impact-effort matrix. It then becomes quite clear that the root-causes to be addressed first are the ones that fall in the cell marked by ‘low effort’ and ‘high impact’. The improvement in the process should then be brought by finding out new ways to do things faster, better or cheaper. Statistical methods should be used to validate the improvement.

4.4.5 Control

The improved system should be institutionalized by modifying procedures, policies, budgets, operating instructions, compensation and incentive systems and other management systems. Thereafter, regular process measurement should be taken to verify long term capability and/or to continuously improve the process.

5 Conclusion and outlook

Six Sigma has been at the forefront of the quality movement in recent years. On the way to get more and more importance, Six Sigma has conquered many areas by improving the performance of several processes. Six Sigma thinking gives the potential to refine current approaches to Logistics improvement. In addition to elimination of waste, it offers benefits by delivering reduced variation. However, in order for this approach to be successful, it needs strong linkages to strategy, a clear collaborative framework and a combination of tools for addressing the twin goals of waste and variation reduction. The benefits for a company by application of Six Sigma can be manifold. These benefits, for example, can be increase in customer satisfaction, increase in revenues, reduction in cycle times and higher flexibility to capitalize on present-day market demands.

Providing the reader with an overview of Six Sigma and Logistics, the main aim of this paper was to realize a link between them. At first, the importance of Six Sigma was emphasized and responses were given to the question, as why this tool is necessary to get optimized and continuously improved processes. An introduction to the DMAIC and DMADV methodologies was also provided. In the next step, overview of logistics was presented with its features, functions and challenges. The core of this paper dealt with the linkage between Six Sigma and Logistics. It was described how Six Sigma can bring financial benefits to Logistics processes, along with reduction in process variations.

On the whole, ‘Six Sigma in Logistics’ should be considered as a promising approach to optimize the present-day Logistics processes. Despite the fact that the implementation of this approach is a challenge in itself, when successfully applied it holds a considerable potential to leverage the results for global corporations.

6 References

Aberdeen Group (2006): “The Lean Six Sigma Benchmark Report”;, status 01.09.2006, accessed 22.06.2007

Barringer & Associates (1999):, accessed 25.06.2007

Beardsley, Gregg (2005): “SEPG - Pitfalls to avoid while accelerating your CMMI implementation with Six Sigma”;, status 01.03.2005, accessed 22.06.2007

Beamon, B. M. (1999): “Measuring supply chain performance”; In: International Journal of Operations & Production Management, Vol. 19, No. 3, pp. 275-292. MCB University Press.

Bode, W./ Preuss, R. W. (2004): “Comprehensive introduction to Intralogistics” Norderstedt, Germany

Brewer, P. C./ Spech.T. W. (2000): “Using the balanced scorecard to measure supply chain performance; In: Journal of Business Logistics; 21, 1; ABI/INFORM Global; p.75-93

Chan, F.T.S./ Qi, H.J. (2003): “Feasibility of performance measurement system for supply chain: a process-based approach and measures”; In: Integrated Manufacturing Systems 14/3, pp. 179-190

Chapell, A./ Peck, H. (2005): “The Application of a Six Sigma Methodology to Military Supply Chain Processes”; Cranfield University, UK

Council of Supply chain management professionals:; accessed 20.06.2007

Fuller, J.B./ O’Connor, J./ Rawlinson, R. (1993): “Tailored logistics: the next advantage”; In: Harvard Business review; Vol. 3

Goldsby, T./ Martichenko, R. (2005): “Lean Six Sigma Logistics - Strategic development to operational success”; J.Ross Publishing, USA.

Gunasekaran, A./ Patel A./ Tirtiroglu E. (2001): “Performance measures and metrics in a supply chain environment”; In: International Journal of Operations & Production Management; Vol 21 No. 1/2, p. 71-87. MCB University Press

Kaplan, R. S./ Norton ,D. P. (1997): “The Balanced Scorecard: translating strategy into action”; Harvard Business School Press Boston, Massachusetts, USA

Knowles, G./ Whicker, L./ Femat, J.H. (2005): “A conceptual model for the application of Six Sigma methodologies to supply chain improvement”; In: International Journal of Logistics; Vol. 8, No. 1, pp 51-65.

Kotelnikov, V. (2007): “Six Sigma and the Quality Revolution at GE”;; accessed 06.06.2007.

Lambert, D.M./ Knemeyer, A. M. (2004): “We are in this together: the 21st-century supply chain”; In: Harvard business review; Boston, Massachusetts; Vol. 12; p. 114-122

Motorola University:; accessed 10.06.2007.

Pyzdek, T. (2001): “Why Six Sigma is not TQM”;; accessed 10.06.2007.

Pyzdek, T (2003): “The Six Sigma Handbook”; Mc. Graw Hill; New York.

Poirier, C.C. (1999): “Advanced supply chain management: how to build a sustained competitive advantage; San Francisco Calif.; USA

Raisinghani, M./ Ette, H./ Pierce, G./ Cannon, G./ Daripaly, D. (2005): “Six Sigma: concepts, tools and applications”;; p.491-505

Ramberg, J.S. (2000): “Six Sigma: Fad or Fundamental?”;, accessed on 10.06.2007.

Selzer, G. (2006): “Supply Chain Management”; Aachen, Nordrhein-Westfalen Sullivan, M. (2005): “Six Sigma and RFID- Enabling process improvement”; UPS Supply Solutions. USA, p. 1-5


1.8 MB
Institution / Hochschule
Technische Universität Hamburg-Harburg
Sigma Logistics



Titel: Six Sigma in Logistics