Six Sigma News Update

GE's Wealth of Free Advice

NK Khoo Managing Consultant — Sun, 11 Jun 2006 11:12:00 +0000

By Steven Pearlstein
Wednesday, June 7, 2006; Page D01

Five years ago, Warren Coopersmith's family-owned distribution firm in Takoma Park was at one of those crucial "grow-or-die" junctures. Its biggest customers, movie theaters and video-rental outlets, were consolidating and looking for suppliers big enough to provide all popcorn, candy, soda pop and cleaning supplies to their expanding empires.

Coopersmith decided that his company, Marjack, was going to be a survivor. He began by recruiting experienced professionals to his management team. He made a few acquisitions, expanded his business with such existing customers as Regal Cinema, and developed new lines, such as providing candy and snacks to Office Depot and Kinko's outlets. He even embarked on a bit of vertical integration, buying his own popcorn company.

But as Marjack's revenue grew toward $150 million, five times what it had been, Coopersmith and his team realized that there were problems. Their profit margins weren't what they should have been and their systems weren't up to handling the increase in volume. A small but annoying number of orders were going out incomplete or incorrect.

That's when the folks at General Electric's Commercial Finance unit, which had just financed Marjack's new warehouse in Landover, knocked on Coopersmith's door with an unusual offer: Would he be interested in having a team of GE's famed Six Sigma management experts come out, perform their rigorous statistical analyses of warehouse operations, and find ways to cut costs and improve quality? And here's the thing: It would be absolutely free, with no strings attached.

You might well ask why a $25 billion division of a global corporate behemoth would want to go through the time, hassle and money of helping Marjack pick and pack Milk Duds and red licorice. The answer is pretty simple: For the $15 million that Six Sigma costs a year, GE Commercial Finance buys a ton of customer loyalty and sets itself apart in what is otherwise a commodity-service business. Perhaps even more important, the program increases the odds that the mid-size firms to which GE is lending money will not only stay in business long enough to pay back the loans, but will be more likely to grow in the future -- as will their need for capital. "We know instinctively that the benefits to us are substantial," said Sharon Garavel, who heads up the program. "Our customers have told us that they intend to give us a larger share of their business." By her reckoning, it has already generated 350,000 hours of free consulting services to more than 3,000 customers since 2002, saving them collectively more than $1.2 billion.

In fact, under chief executive Jeffrey Immelt, who started offering Six Sigma assistance to customers when he ran GE's medical equipment division, all of General Electric's units have an "At the Customer, for the Customer" program. It is a brilliant example of how a company has taken an internal skill -- in this case, change management and continuous improvement, for which it is world-renowned -- and turned it into a marketable product.

Among those who sing the program's praises are Mike Woods, chief knowledge officer at Red Robin Gourmet Burgers, a Denver-based restaurant chain. Red Robin uses GE for 80 percent of its franchisee financing. Woods, who became part of the Six Sigma cult after spending a week at GE's Crotonville, N.Y., management training center, invited GE's gurus in to solve one of the chain's most vexing problems: getting patrons their milkshakes within four minutes of their orders.

This had long been a goal of a company catering to families with young children, but it was meeting it only 36 percent of the time. When the staff at restaurants was asked why, they said there weren't enough mixers or enough bartenders (yes, that's who makes the milkshakes). But after a GE team analyzed the problem, more important facts turned out to be that the first orders in weren't necessarily the first ones out, and that because of uneven workload among the wait staff, shakes were sitting undelivered for longer than they should have. The purchase of a minor piece of equipment, and introduction of procedures requiring any waiters passing by the bar to deliver finished drinks to any table, got the success rate up to 77 percent.

Another happy customer is Stephen Carter, president of the American subsidiary of Komori, a Japanese maker of printing presses. An important part of Komori's business involves getting replacement parts to customers when their machines are down, which they had been doing within 24 hours for 87 percent of their customers. GE's Six Sigma "black belts" saw that most of the orders that took longer involved items that were out of stock. After analyzing more than a decade of parts orders, they found a way of ensuring that the most-sought items, or those with long lead times, were never out of stock, while reducing inventory for slow-moving and less hard-to-replace components. The result: 95 percent of orders now go out on time.

At Marjack, GE's experts meticulously analyzed the steps taken by the warehouse staff members as they moved their carts up and down the aisles, filling the weekly orders from movie theaters and retail outlets. As is often the case, there weren't any major fixes -- just a whole bunch of little things, like collecting all the used carts in one place, clustering all the most-used items near the packing stations, dispatching forklift drivers with walkie-talkies. But in the end, according to in-house strategist Chris Paladino, the warehouse staff improved productivity by 35 percent while cutting in half the number of customer complaints. As a result, Marjack now dispatches 500 boxes to customers each day with almost the same size staff that used to send out 350.

Coopersmith says that as a result of the culture change and confidence that GE's collaboration has generated, he'll invest heavily in new scanning and truck routing technology that will further enhance productivity while allowing the company to push into new product lines.

"The process with GE was a real catalyst in getting our brains going again," he said -- a fact he says he won't forget the next time Marjack's inventory financing goes out to bid.

Mumbai's Dabbawalas

NK Khoo Managing Consultant — Sun, 11 Jun 2006 03:35:00 +0000

Rajen Nair (rajennair)

Published 2006-06-11 00:16 (KST)

A colorful assortment of dabbas

A dabbawala is a person whose job is to collect lunch boxes from homes, which are packed in an aluminum container, known locally as dabba, which they deliver to customers in their respective offices. How it came into existence was a matter of necessity for the British during the Raj, who, for want of good hygienic food scarcely available on the streets of Mumbai, had to depend on meals prepared at home. They would hire locals to carry the lunch boxes from home to their workplace. Since then, these lunch box carriers have become popularly known as dabbawalas.

Mumbai is densely populated, and traffic fairly bursts out at its seams. It is the financial hub of India and has a large number of corporate offices, concentrated in south Mumbai. The working class, residing in far-off suburbs and who relish homemade dishes, patronize the dabbawalas.

This wide network, a unique human chain, is instrumental in bringing mother's recipe to the worker's desk. Every morning the dabbawala visits each home client, collects the lunch boxes, and then transports them through the suburban rail network. They are then handed over to another group of dabbawalas assembled at different railway stations. Each container of lunch boxes bears a distinguishing number and is then sorted out, allocated to each pick-up man for the onward journey, and handed out to the rightful owners.

Balancing wooden cart on a dabbawala's head

©2006 Rajen Nair
It is a common sight to see the dabbawalas attired in their traditional white kurta (pajama) and a topi (hat), wheeling a bicycle with loads of cylindrical aluminum containers tucked on either side. These lunch boxes are delivered on every working day without fail, despite deluges during the monsoon season or a strike announcement made by a political party. Again, in the evening the empty containers are collected from offices and delivered back to homes for another round of errands the next day morning.

More than 200,000 lunch boxes are transported to and fro every day by a dabbawala force of about 5,000 strong. In today's globalization that boasts of modern transport systems, this unique human feat of delivering lunch boxes, using a non-polluting and cost-effective primitive mode of transport like bicycles and pullers of wooden carts, is unparalleled anywhere in the world.

The dabbawalas may be semi-literate, but their efficient delivery and time management skills would shame some professionally managed corporations. The American business magazine Forbes has given a six-sigma performance rating to them. The dabbawalas were also featured in a BBC documentary.

The dabbawalas achieved worldwide fame when Prince Charles, during one of his visits to Mumbai, paid a special visit to them and evidenced keen interest in how they worked. He was so impressed with them that later, during his wedding, he extended an invitation to these dabbawalas. In a way, the dabbawala does yeoman service in maintaining healthy food habits for workers in Mumbai by keeping them away from fast food joints.

Fundamentals of Six Sigma

NK Khoo Managing Consultant — Sun, 11 Jun 2006 03:17:00 +0000

Fundamentals of Six Sigma

Date: Jun 9, 2006 By David M. Levine. Sample Chapter is provided courtesy of Financial Times Prentice Hall.

Six Sigma management is a quality improvement system originally developed by Motorola in the mid-1980s. Six Sigma offers a prescriptive and systematic approach to quality improvement and places a great deal of emphasis on accountability and bottom-line results. Many companies all over the world use Six Sigma management to improve efficiency, cut costs, eliminate defects, and reduce product variation. This chapter offers an introduction to Six Sigma.

Introduction
1.1 What Is Six Sigma?
1.2 Roles in a Six Sigma Organization
1.3 Statistics and Six Sigma
1.4 Learning Statistics for Six Sigma Using This Book

Summary

References

Learning Objectives
After reading this chapter, you will be able to

Know what the acronym DMAIC stands for.
Understand the difference between the role of a Six Sigma green belt, black belt, and master black belt.
Understand the role of statistics in Six Sigma management.

Introduction
Six Sigma management is a quality improvement system originally developed by Motorola in the mid-1980s. Six Sigma offers a prescriptive and systematic approach to quality improvement and places a great deal of emphasis on accountability and bottom-line results. Many companies all over the world use Six Sigma management to improve efficiency, cut costs, eliminate defects, and reduce product variation.

1.1 What Is Six Sigma?

The name Six Sigma comes from the fact that it is a managerial approach designed to create processes that result in no more than 3.4 defects per million. One of the aspects that distinguishes Six Sigma from other approaches is a clear focus on achieving bottom-line results in a relatively short three- to six-month period of time. After seeing the huge financial successes at Motorola, GE, and other early adopters of Six Sigma management, many companies worldwide have now instituted Six Sigma management programs [see References 1, 2, 3, and 5].

The DMAIC Model
To guide managers in their task of improving short- and long-term results, Six Sigma uses a five-step process known as the DMAIC model, named for the five steps in the process: Define, Measure, Analyze, Improve, and Control.

Define. The problem is defined along with the costs, benefits, and impact on the customer.

Measure. Operational definitions for each critical-to-quality (CTQ) characteristic are developed. In addition, the measurement procedure is verified so that it is consistent over repeated measurements.

Analyze. The root causes of why defects occur are determined, and variables in the process causing the defects are identified. Data are collected to determine benchmark values for each process variable.

Improve. The importance of each process variable on the CTQ characteristic are studied using designed experiments (see Chapter 8, "Design of Experiments"). The objective is to determine the best level for each variable.

Control. The objective is to maintain the benefits for the long term by avoiding potential problems that can occur when a process is changed.

1.2 Roles in a Six Sigma Organization
The roles of senior executive (CEO or president), executive committee, champion, process owner, master black belt, black belt, and green belt are critical to the Six Sigma management process.

The senior executive provides the impetus, direction, and alignment necessary for Six Sigma’s ultimate success. The most successful, highly publicized Six Sigma efforts have all had unwavering, clear, and committed leadership from top management. Although it may be possible to initiate Six Sigma concepts and processes at lower levels, dramatic success will not be possible until the senior executive becomes engaged and takes a leadership role.

The members of the executive committee are the top management of an organization. They should operate at the same level of commitment for Six Sigma management as the senior executive.

Champions take a very active sponsorship and leadership role in conducting and implementing Six Sigma projects. They work closely with the executive committee, the black belt assigned to their project, and the master black belt overseeing their project. A champion should be a member of the executive committee or at least a trusted direct report of a member of the executive committee. He or she should have enough influence to remove obstacles or provide resources without having to go higher in the organization.

A process owner is the manager of a process. He or she has responsibility for the process and has the authority to change the process on his or her signature. The process owner should be identified and involved immediately in all Six Sigma projects relating to his or her own area.

Master Black Belt
A master black belt takes on a leadership role as keeper of the Six Sigma process and advisor to senior executives or business unit managers. He or she must leverage his or her skills with projects that are led by black belts and green belts. Frequently, master black belts report directly to senior executives or business unit managers. A master black belt has successfully led many teams through complex Six Sigma projects. He or she is a proven change agent, leader, facilitator, and technical expert in Six Sigma management. It is always best for an organization to develop its own master black belts. However, sometimes it is impossible for an organization to develop its own master black belts because of the lead time required to become a master black belt. Thus, circumstances sometimes require hiring master black belts from outside the organization.

Black Belt
A black belt is a full-time change agent and improvement leader who may not be an expert in the process under study [see Reference 4]. A black belt is a quality professional who is mentored by a master black belt, but who may report to a manager for his or her tour of duty as a black belt.

Green Belt
A green belt is an individual who works on projects part-time (25%), either as a team member for complex projects or as a project leader for simpler projects. Most managers in a mature Six Sigma organization are green belts. Green belt certification is a critical prerequisite for advancement into upper management in a Six Sigma organization.

Green belts leading simpler projects have the following responsibilities:

Refine a project charter for the project.
Review the project charter with the project’s champion.
Select the team members for the project.
Communicate with the champion, master black belt, black belt, and process owner throughout all stages of the project.
Facilitate the team through all phases of the project.
Schedule meetings and coordinate logistics.
Analyze data through all phases of the project.
Train team members in the basic tools and methods through all phases of the project.
In complicated Six Sigma projects, green belts work closely with the team leader (black belt) to keep the team functioning and progressing through the various stages of the Six Sigma project.

1.3 Statistics and Six Sigma
Many Six Sigma tools and methods involve statistics. What exactly is meant by statistics, and why is statistics such an integral part of Six Sigma management? To understand the importance of statistics for improving quality, you can go back to a famous 1925 quote of Walter Shewhart, widely considered to be the father of quality control:

The long-range contribution of statistics depends not so much upon getting a lot of highly trained statisticians into industry as it does in creating a statistically minded generation of physicists, chemists, engineers, and others who will in any way have a hand in developing and directing the production processes of tomorrow.

This quote is just as valid today as it was more than 75 years ago. The goal of this book is not to make you a statistician. The goal is to enable you to learn enough so that you will be able to use the statistical methods that are involved in each phase of the DMAIC model. Using Minitab and/or JMP statistical software will help you achieve this goal while at the same time minimize your need for formulas and computations.

Table 1.1 summarizes the statistical methods that are commonly used in the various phases of the DMAIC model.

Table 1.1 Phases of the DMAIC Model, Statistical Methods Used, and Chapters in This Book
Phase of DMAIC Model
Statistical Methods
Chapters

Define Tables and Charts 3
Descriptive Statistics 4
Statistical Process Control Charts 11

Measure Tables and Charts 3
Descriptive Statistics 4
Normal Distribution 5
Analysis of Variance 6, 7, 8
Statistical Process Control Charts 11

Analyze Tables and Charts 3
Descriptive Statistics 4
Analysis of Variance 6, 7, 8
Regression Analysis 9, 10
Statistical Process Control Charts 11

Improve Tables and Charts 3
Descriptive Statistics 4
Analysis of Variance 6, 7, 8
Regression Analysis 9, 10
Design of Experiments 8

Control Statistical Process Control Charts 11

1.4 Learning Statistics for Six Sigma Using This Book
This book assumes no previous knowledge of statistics. Perhaps you may have taken a previous course in statistics. Most likely, such a course focused on computing results using statistical formulas. If that was the case, you will find the approach in this book very different. This book provides the following approach:

Provides a simple nonmathematical presentation of topics. Every concept is explained in plain English with a minimum of mathematical symbols. Most of the equations are separated into optional boxes that complement the main material.
Covers statistical topics by focusing on the interpretation of output generated by the Minitab and JMP software.

Includes chapter-ending appendices that provide step-by-step instructions (with screenshots of dialog boxes) for using Minitab Version 14 and JMP Version 6 for the statistical topics covered in the chapter.
Provides step-by-step instructions using worked-out examples for each statistical method covered.

Summary
Six Sigma management is used by many companies around the world. Six Sigma uses the DMAIC model that contains five phases: Define, Measure, Analyze, Improve, and Control. Many different roles are important in a Six Sigma organization. Statistics is an important ingredient in such an organization. The purpose of this book is to enable you to learn enough so that you will be able to use statistical methods as an integral part of Six Sigma management.

References

Arndt, M., "Quality Isn’t Just for Widgets," Business Week, July 22, 2002, 72–73.
Gitlow, H. S., and D. M. Levine, Six Sigma for Green Belts and Champions, (Upper Saddle River, NJ: Financial Times Prentice Hall, 2005).
Hahn, G. J., N. Doganaksoy, and R. Hoerl, "The Evolution of Six Sigma," Quality Engineering, 2000, 12, 317–326.
Hoerl, R., "Six Sigma Black Belts: What Do They Need to Know?" Journal of Quality Technology, 33, 4, October 2001, 391–406.
Snee, R. D., "Impact of Six Sigma on Quality," Quality Engineering, 2000, 12, ix–xiv.

Summary
Six Sigma management is used by many companies around the world. Six Sigma uses the DMAIC model that contains five phases: Define, Measure, Analyze, Improve, and Control. Many different roles are important in a Six Sigma organization. Statistics is an important ingredient in such an organization. The purpose of this book is to enable you to learn enough so that you will be able to use statistical methods as an integral part of Six Sigma management.

Foundations of Six Sigma Management

NK Khoo Managing Consultant — Mon, 05 Jun 2006 20:22:00 +0000

Date: Jun 2, 2006 By Howard S. Gitlow, David M. Levine, Edward A. Popovich. Sample Chapter is provided courtesy of Prentice Hall.

This chapter is about getting you comfortable with Six Sigma management. It accomplishes this objective by providing you with strong anecdotal evidence that Six Sigma is a very successful style of management, explaining how it must be emphatically led from the top of the organization, and, finally, introducing you to the Six Sigma models for improving and inventing/innovating products, services, or processes. This chapter could serve as a brief introduction to Six Sigma management for any stakeholder of your organization.
Sections

Introduction
1.1 Successful Applications of Six Sigma Management
1.2 Key Ingredients for Success with Six Sigma Management
1.3 Benefits of Six Sigma Management
1.4 Fundamentals of Improving a Product, Service, or Process
1.5 Fundamentals of Inventing–Innovating a Product, Service, or Process
1.6 What Is New about Six Sigma Management?
1.7 Six Sigma in Non-Manufacturing Industries

Summary
References

Learning Objectives

After reading this chapter, you will be able to:

Present strong evidence of the value of Six Sigma style of management.
Understand the key ingredient for success with Six Sigma management.
Appreciate the benefits of Six Sigma management.
Review the fundamentals of improving a product, service, or process.
Appreciate the DMAIC model for improvement.
Introduce the fundamentals of inventing and innovating a product, service, or process.
Appreciate the DMADV model for invention and innovation.
Know what is new about Six Sigma management.
Appreciate the significance of Six Sigma management in non-manufacturing industries.
Introduction

This chapter is about getting you comfortable with Six Sigma management. We accomplish this objective by providing you with strong anecdotal evidence that Six Sigma is a very successful style of management, explaining how it must be emphatically led from the top of the organization, and, finally, introducing you to the Six Sigma models for improving and inventing/innovating products, services, or processes. This chapter could serve as a brief introduction to Six Sigma management for any stakeholder of your organization.

1.1 Successful Applications of Six Sigma Management
Manufacturing organizations have experienced great success with Six Sigma management. Selected manufacturing organizations that use Six Sigma management include the following:

Asea-Brown-Boveri
AT&T
Bombardier
Eli Lilly
Foxboro
General Electric
Honeywell/Allied Signal
IBM–UK
Lockheed Martin
Motorola
Raytheon
Seagate
Texas Instruments

Additionally, non-manufacturing organizations have had excellent results with Six Sigma management. A few non-manufacturing organizations using Six Sigma management include the following:

Allstate Insurance
Amazon.com
American Express
Bank of America
Bankers Life and Insurance
Capital One Services
Intuit
J. P. Morgan Chase
Merrill Lynch
Microsoft
United Health Group
University of Miami

Jack Welch, Chairman emeritus and CEO of General Electric, was so committed to and impressed with Six Sigma that he stated:

"Six Sigma GE Quality 2000 will be the biggest, the most personally rewarding, and, in the end, the most profitable undertaking in our history."

"...we plunged into Six Sigma with a company-consuming vengeance just over three years ago. We have invested more than a billion dollars in the effort and the financial returns have now entered the exponential phase." (GE’s letter to shareowners, February 12, 1999)

1.2 Key Ingredients for Success with Six Sigma Management
The key ingredient for a successful Six Sigma management process is the commitment of top management. Executives must have a burning desire to transform their organizations. This means total commitment from the top of the organization to the bottom of the organization. An executive’s commitment is shown in part by how she or he allocates time and resources, and by the questions she or he asks of others. Many Six Sigma executives spend at least 25% of their time on Six Sigma matters and allocate major organizational resources to drive the Six Sigma style of management. If an executive asks: "What was yesterday’s production volume?," she or he is saying: "I care about quantity, not quality." If an executive asks: "What is happening with the Production Department’s Six Sigma projects to increase production volume?," she or he is saying: "I care about quality and quantity."

1.3 Benefits of Six Sigma Management
There are two types of benefits from Six Sigma management: benefits to the organization and benefits to stakeholders. Benefits to an organization are gained through the continuous reduction of variation and, where applicable, the centering of processes on their desired (nominal) levels. The benefits are as follows:

Improved process flows
Reduced total defects
Improved communication (provides a common language)
Reduced cycle times
Enhanced knowledge (and enhanced ability to manage that knowledge)
Higher levels of customer and employee satisfaction
Increased productivity
Decreased work-in-progress (WIP)
Decreased inventory
Improved capacity and output
Increased quality and reliability
Decreased unit costs
Increased price flexibility
Better designs
Decreased time to market
Faster delivery time

Increased ability to convert improvements and innovations into hard currency
In essence, Six Sigma is a roadmap for an enterprise to become more effective and efficient. An "effective" enterprise is one that does the "right" things "right" the first time, and an "efficient" enterprise is one that uses minimum resources to accomplish the "right" thing. The "right" thing is judged by the perception of customers and the marketplace. Simply put, the Six Sigma enterprise focuses on providing a value-added experience to current and future customers through its processes, products, and services. Processes that do not add value to the customer’s experience are candidates for elimination by management. A value-added process is a process that the customer is willing to pay for, does not involve rework or fixes, is done "right" the first time, and is not wasteful to the enterprise.

Louis Schultz, President of Process Management International, a consulting firm in Minneapolis, Minnesota, states that:

"The perception and performance of an enterprise determines its value. Six Sigma management focuses on driving effective and efficient performance across the total enterprise to increase the perception of the marketplace of its ability to deliver value-added processes, products, and services. The perception of the marketplace of the value of an enterprise is indirectly measured by market share, shareholder value, and the willingness of customers to recommend these processes, products, and services to other potential customers."

Benefits to stakeholders are a by-product of the organizational benefits. The benefits to stakeholders include the following:

Shareholders receive more profit due to decreased costs and increased revenues.
Customers are delighted with products and services.
Employees experience higher morale and more satisfaction from joy in work.
Suppliers enjoy a secure source of business.

1.4 Fundamentals of Improving a Product, Service, or Process
Process Basics (Voice of the Process [VoP])

Definition of a Process
A process is a collection of interacting components that transform inputs into outputs toward a common aim, called a mission statement. The job of management is to optimize the entire process toward its aim. This may require the sub-optimization of selected components of the process. Sometimes a particular department in an organization may have to give up resources in the short run to another department to maximize profit for the overall organization. This is particularly true when one department expends effort to correct the failings or omissions of another department working on the same process. Inspection, signature approvals, rework areas, complaint-resolution areas, etc. are all evidence that the process was not done effectively and efficiently the first time. The consumption of resources utilized in correcting the failings and omissions would have been avoided if the process was done "right."

The transformation, as shown in Figure 1.1, involves the addition or creation of value in one of three aspects: time, place, or form. An output has "time value" if it is available when needed by a user. For example, you have food when you are hungry. Or material inputs are ready on schedule. An output has "place value" if it is available where needed by a user. For example, gas is in your tank (not in an oil field), or wood chips are in a paper mill. An output has "form value" if it is available in the form needed by a user. For example, bread is sliced so it can fit in a toaster, or paper has three holes so it can be placed in a binder.

Figure 1.1 Basic Process

Processes exist in all facets of organizations, and our understanding of them is crucial. Many people mistakenly think only of production processes. However, administration, sales, service, human resources, training, maintenance, paper flows, interdepartmental communication, and vendor relations are all processes. Importantly, relationships between people are processes. Most processes can be studied, documented, defined, improved, and innovated.

An example of a generic assembly process is shown in Figure 1.2. The inputs (component parts, machines, and operators) are transformed in the process to make the outputs (assembled product).

Figure 1.2 Production Process

An organization is a multiplicity of micro sub-processes, all synergistically building to the macro process of that organization. All processes have customers and suppliers; these customers and suppliers can be internal or external to the organization. A customer can be an end user or the next operation downstream. The customer does not even have to be a human; it could be a machine. A supplier could be another organization supplying sub-assemblies or services, or the prior operation upstream.

Variation in a Process
The outputs from all processes and their component parts may be measured; the measurements invariably fluctuate over time, creating a distribution of measurements. The distribution of measurements of the outputs from a process over time is called the "Voice of the Process (VoP)." Consider a process such as getting ready for work or for class in the morning. Some days you are busier than usual, while on other days you have less to do than usual. Your process varies from day to day to some degree. This is common variation. However, if a construction project begins on the highway you take to work or school, you might drastically alter your morning routine. This would be special variation because it would have been caused by a change external to your "driving to work or school" process. If the traffic patterns had remained as they were, your process would have continued on its former path of common variation.

The design and execution of a process creates common causes of variation. In other words, common variation is due to the process itself. Process capability is determined by inherent common causes of variation, such as hiring, training, or supervisory practices; inadequate lighting; stress; management style; policies and procedures; or design of products or services. Employees working within the process cannot control a common cause of variation and should not be held accountable for, or penalized for, its outcomes. Process owners (management) must realize that unless a change is made in the process (which only they can make), the capability of the process will remain the same. Special causes of variation are due to events external to the usual functioning of the process. New raw materials, a drunken employee, or a new operator can be examples of special causes of variation. Identifying the occurrence of special and common causes of variation is discussed extensively in References 2 and 3.

Because unit-to-unit variation decreases the customer’s ability to rely on the dependability and uniformity of the outputs of a process, managers must understand how to reduce and control variation. Employees use statistical methods so that common and special causes of variation can be differentiated; special variation can be resolved and common variation can be reduced by management action, resulting in improvement and innovation of the outputs of a process.

The following fictionalized case history demonstrates the need for management to understand the difference between common and special causes of variation to take appropriate action. In this case history, an employee comes to work intoxicated. His behavior causes productivity, safety, and morale problems. You, as the supervisor, speak to the employee privately, try to resolve the situation, and send the employee home with pay. After a second instance of intoxication, you speak to the employee privately, try to resolve the problem again, and send the employee home without pay. A third instance causes you to refer the employee to an Employee Assistance Program. A fourth offense results in you terminating the employee. As a good manager, you document the employee’s history to create a paper trail in case of legal action. All of the above is necessary and is considered to be good management practice.

The thought process behind the preceding managerial actions assumes that the employee is the problem. In other words, you view the employee’s behavior as the special cause of variation from the desired sober state. However, this is true only if there is a statistically significant difference between the employee in question and all other employees. If the employee’s behavior is part of a process that allows such behavior to exist, then the problem is not a special cause, but rather a common cause; it requires a different solution. In the latter case, the employee must be dealt with as before; but, additionally, organizational policies and procedures (processes) must be changed to prevent future incidents of intoxication. This new view requires a shift in thought. With the new thought process, if existing organizational policies and procedures allow employees with drinking problems to be present in the workplace, an intoxicated employee must be dealt with according to the original solution, and policies and procedures must be improved to prevent future incidents of such behavior on the job.

Feedback Loops
An important aspect of any process is a feedback loop. A feedback loop relates information about outputs from any stage(s) back to other stage(s) to make an analysis of the process. Figure 1.3 depicts the feedback loop in relation to a basic process.

Figure 1.3 Feedback Loop

The tools and methods discussed in this book provide vehicles for relating information about outputs to other stage(s) in the process. Decision making about processes is aided by the transmission of this information. A major purpose of quality management is to provide the information (flowing through a feedback loop) needed to take action with respect to a process.

There are three feedback loop situations: no feedback loop, special cause only feedback loop, and special and common cause feedback loop. A process that does not have a feedback loop is probably doomed to deterioration and decay due to the inability of its stakeholders to rejuvenate and improve it based on data from its outputs. An example of a process without a feedback loop is a relationship between two people (manager and subordinate, husband and wife, or buyer and seller) that contains no vehicle (feedback loop) to discuss issues and problems with the intention of establishing a better relationship in the future. A process in which all feedback information is treated as a special cause will exhibit enormous variation in its output. An example of a process with a special cause only feedback loop could be a relationship between two people; but in this case, the relationship deteriorates through a cycle of successive overreactions to problems that are perceived as special by both members of the relationship. In fact, the problems are probably repetitive in nature due to the structure of the relationship itself and to common causes of variation. Finally, in a process in which feedback information is separated into common and special causes—special causes are resolved and common causes are reduced—products, services, or processes will exhibit continuous improvement of their output. For example, the relationship problems between a superior and a subordinate can be classified as either due to special and/or common causes; statistical methods are used to resolve special causes and to remove common causes, thereby improving the relationship in the future.

Consider the following example. Paul is a 40-year-old, mid-level manager who is unhappy because he wants his boss to give him a promotion. He thinks about his relationship with his boss and wonders what went wrong. He determines that over a period of 10 years, he has had about 40 disagreements with his boss (one per quarter).

Paul thinks about what caused each disagreement. Initially, he thought each disagreement had its own special cause. After studying the pattern of the number of disagreements per year, Paul discovered that it was a stable and predictable process of common causes of variation. Subsequently, he wrote down the reason for as many of the disagreements as he could remember (about 30). However, after thinking about his relationship with his boss from the perspective of common causes, he realized his disagreements with his boss were not unique events (special causes); rather, they were a repetitive process, and the reasons for the disagreements could be classified into common cause categories. He was surprised to see that the 30 reasons collapse down to four basic reasons—poor communication of a work issue, a process failure causing work not to be completed on schedule, unexcused absence, and pay-related issues—with one reason, poor communication of a work issue, accounting for 75% of all disagreements. Armed with this insight, he scheduled a discussion with his boss to find a solution to their communication problems. His boss explained that he hates the e-mails that Paul is always sending him and wished Paul would just talk to him and say what is on his mind. They resolved their problem; their relationship was greatly improved, and, eventually, Paul received his promotion.

Definition of Quality (Voice of the Customer [VoC])Goal Post View of Quality
Quality is a concept whose definition has changed over time. In the past, quality meant "conformance to valid customer requirements." That is, as long as an output fell within acceptable limits (called specification limits) around a desired value or target value (also called the nominal value, denoted by "m"); it was deemed conforming, good, or acceptable. We refer to this as the "goal post" definition of quality. The nominal value and specification limits are set based on the perceived needs and wants of customers. Specification limits are called the Voice of the Customer. Figure 1.4 shows the "goal post" view of losses arising from deviations from the nominal value. That is, losses are minimum until the lower specification limit (LSL) or upper specification limit (USL) is reached. Then, suddenly, losses become positive and constant, regardless of the magnitude of the deviation from the nominal value.

Figure 1.4 Goal Post View of Losses Arising from Deviations from Nominal

An individual unit of product or service is considered to conform to a specification if it is at or inside the boundary (USL or LSL) or boundaries (USL and LSL). Individual unit specifications are made up of a nominal value and an acceptable tolerance from the nominal. The nominal value is the desired value for process performance mandated by the customer’s needs and/or wants. The tolerance is an allowable departure from a nominal value established by designers that is deemed non-harmful to the desired functioning of the product or service. Specification limits are the boundaries created by adding and/or subtracting tolerances from a nominal value; for example:

USL = upper specification limit = nominal + tolerance

LSL = lower specification limit = nominal – tolerance

A service example of the goal post view of quality and specification limits can be seen in a monthly accounting report that must be completed in 7 days (nominal), no earlier than 4 days (lower specification limit—not all the necessary data will be available), and no later than 10 days (upper specification limit—the due date for the report at the board meeting). Therefore the "Voice of the Customer" is that the report must be completed ideally in 7 days, but no sooner than 4 days or no later than 10 days.

Another example of the goal post view of quality and specification limits is to insert a medical device into the chest of a patient that is 25 mm in diameter (the nominal value). A tolerance of 5 mm above or below the nominal value (25 mm) is acceptable to the surgeon performing the operation. Thus, if a medical device’s diameter measures between 20 mm and 30 mm (inclusive), it is deemed conforming to specifications. It does not matter if the medical device is 21 mm or 29 mm; they are both conforming units. If a medical device’s diameter measures less than 20 mm or more than 30 mm, it is deemed as not conforming to specifications and is scrapped at a cost of $1,000.00 per device. Therefore, the "Voice of the Customer" states that the diameters of the medical devices must be between 20 mm and 30 mm, inclusive, with an ideal diameter of 25 mm.

In this section, you assumed that there is a reasonable target from which deviations on either side are possible. For situations in which there is only one specification limit—such as time to deliver mail in hours, with the target of 0 hours and an upper specification limit of 5 days—the objective is not to exceed the upper specification, and to deliver the mail on a very consistent basis (little variation) to create a highly predictable mail delivery process. In other words, whether there are two-sided specifications or a one-sided specification, the goal is to have increased consistency, implying minimal variation in performance and, thus, increased predictability and reliability of outcomes.

Continuous Improvement View of Quality
A more modern definition of quality states that: "Quality is a predictable degree of uniformity and dependability, at low cost and suited to the market" [see Reference 1]. Figure 1.5 shows a more realistic loss curve in which losses begin to accumulate as soon as a quality characteristic of a product or service deviates from the nominal value. As with the "goal post" view of quality, once the specification limits are reached, the loss suddenly becomes positive and constant, regardless of the deviation from the nominal value beyond the specification limits.

The continuous improvement view of quality was developed by Genichi Taguchi [see Reference 10]. The Taguchi Loss Function, called the Loss curve in Figure 1.5, expresses the loss of deviating from the nominal within specifications: the left-hand vertical axis is "loss" and the horizontal axis is the measure, y, of a quality characteristic. The loss associated with deviating (y – m) units from the nominal value, m, is:

L(y) = k(y – m)2 = Taguchi Loss Function (1.1)

where

y = the value of the quality characteristic for a particular item of product or service.

m = the nominal value for the quality characteristic.

k = a constant, A/d2.

A = the loss (cost) of exceeding specification limits (e.g., the cost to scrap a unit of output).

d = the allowable tolerance from the nominal value that is used to determine specification limits.

Figure 1.5 Continuous Improvement View of Losses of Deviations from Nominal

Under this Taguchi Loss Function, the continuous reduction of unit-to-unit variation around the nominal value is the most economical course of action, absent capital investment (more on this later). In Figure 1.5, the righthand vertical axis is "Probability" and the horizontal axis is the measure, y, of a quality characteristic. The distribution of output from a process before improvement is shown in Curve A, while the distribution of output after improvement is shown in Curve B. The losses incurred from unit-to-unit variation before process improvement (the lined area under the loss curve for Distribution A) is greater than the losses incurred from unit-to-unit variation after process improvement (the hatched area under the loss curve for Distribution B). This definition of quality promotes continual reduction of unit-to-unit variation (uniformity) of output around the nominal value, absent capital investment. If capital investment is required, then an analysis must be conducted to determine if the benefit of the reduction in variation in the process justifies the cost. The capital investment for a process improvement should not exceed the single lined area under the Taguchi Loss Function in Curve A, but not in Curve B, in Figure 1.5. This modern definition of quality implies that the Voice of the Process should take up a smaller and smaller portion of the Voice of the Customer (specifications) over time, rather than just being inside of the specification limits. The logic here is that there is a loss associated with products or services that deviate from the nominal value, even when they conform to specifications.

To illustrate the continuous definition of quality, return to the example of the medical device that is to be inserted into a patient’s chest. Every millimeter higher or lower than 25 mm causes a loss that can be expressed by the following Taguchi Loss Function:

L(y) = k(y – m)2 = (A/d2)(y – m)2 = ($1,000/[52])(y – 25mm)2 = (40)(y – 25mm)2

if 20 ≤ y ≤ 30

L(y) = $1,000 if y <> 30

Table 1.1 shows the values of L(y) for values of the quality characteristic (diameter of the medical device).

Table 1.1 Loss Arising from Deviations in Diameters of the Medical Device

Diameter of the Medical Device (y)
Value of Taguchi Loss Function (L[y])

18
1,000

19
1,000

20
1,000

21
...640

22
...360

23
...160

24
...40

25
...0

26
..40

27
...160

28
...360

29
...640

30
1,000

31
1,000

32
1,000

Under the loss curve shown in Table 1.1, it is always economical to continuously reduce the unit-to-unit variation in the diameter of medical devices, absent capital investment. This will minimize the loss of surgically inserting medical devices.

If a Taguchi Loss Function has only one specification limit, such as an upper specification limit, the preceding discussion applies without loss of generality. For example, if in the opinion of customers, 30 seconds is the maximum acceptable time to answer phone calls at a customer call center and the desired time is 0 seconds, any positive deviation will result in loss to the customer. Moreover, the greater the process variation (above the nominal time of 0), the greater the loss to the customer. In the case where there is no natural nominal value (e.g., 0 seconds), deviation between the process average and the desired time results in a process bias. The loss function can be used to show in these cases that the loss is a function of the bias squared plus the process variation. This implies that the goal is to eliminate the bias (i.e., move the process average toward the desired time) and to reduce process variation. For example, customer call centers not only wish to reduce their time to answer phone calls from their customers, but they want to have uniformly short answer times. Why? When management determines staffing requirements for the customer call center, it needs to be able to have enough staff to meet its specification for time-to-answer. The more variation in the time-to-answer per call, the more unpredictable the process, and the less confidence management will have in its staffing model. Management may actually overstaff to ensure it meets its specifications. This introduces more cost to the customer call center, which is indirectly passed on to the customer.

Definitions of Six Sigma Management (Relationship Between VoC and VoP)
Non-Technical Definitions of Six Sigma Management
Six Sigma management is the relentless and rigorous pursuit of the reduction of variation in all critical processes to achieve continuous and breakthrough improvements that impact the bottom line and/or top line of the organization and increase customer satisfaction. Another common definition is that Six Sigma management is an organizational initiative designed to create manufacturing, service, and administrative processes that produce a high rate of sustained improvement in both defect reduction and cycle time (e.g., when Motorola began its effort, the rate it chose was a 10-fold reduction in defects in two years, along with a 50% reduction in cycle time). For example, a bank takes an average of 60 days to process a loan with a 10% rework rate in 2004. In a Six Sigma organization, the bank should take no longer than an average of 30 days to process a loan with a 1% error rate in 2006, and no more than an average of 15 days to process a loan with a 0.10% error rate by 2008. Clearly, this requires a dramatically improved/innovated loan process.

Technical Definitions of Six Sigma Management
The Normal Distribution. The term Six Sigma is derived from the normal distribution used in statistics. Many observable phenomena can be graphically represented as a bell-shaped curve or a normal distribution [see Reference 3], as illustrated in Figure 1.6.

Figure 1.6 Normal Distribution with Mean (μ) and Standard Deviation (σ)

When measuring any process, its outputs (services or products) vary in size, shape, look, feel, or any other measurable characteristic. The typical value of the output of a process is measured by a statistic called the mean or average. The variability of the output of a process is measured by a statistic called the standard deviation. In a normal distribution, the interval created by the mean plus or minus 2 standard deviations contains 95.44% of the data values; 45,600 data values per million are outside of the area created by the mean plus or minus 2 standard deviations (45,600 = 1,000,000 x [4.56% = 100% – 95.44%]). In a normal distribution, the interval created by the mean plus or minus 3 standard deviations contains 99.73% of the data; 2,700 defects per million opportunities are outside of the area created by the mean plus or minus 3 standard deviations (2,700 = 1,000,000 x[0.27% = 100% – 99.73%]). In a normal distribution, the interval created by the mean plus or minus 6 standard deviations contains 99.9999998% of the data; 2 data values per billion data values are outside of the area created by the mean plus or minus 6 standard deviations (2 = 1,000,000,000 x [0.0000002% = 100% – 99.9999998%]).

Relationship Between VoP and VoC. Six Sigma promotes the idea that the distribution of output for a stable normally distributed process (Voice of the Process) should be designed to take up no more than half of the tolerance allowed by the specification limits (Voice of the Customer). Although processes may be designed to be at their best, you assume that the processes may increase in variation over time. This increase in variation may be due to small variation with process inputs, the way the process is monitored, changing conditions, etc. The increase in process variation is often assumed to be similar to temporary shifts in the underlying process mean. In practice, the increase in process variation has been shown to be equivalent to an average shift of 1.5 standard deviations in the originally designed and monitored process. If a process is originally designed to be twice as good as a customer demands (i.e., the specifications representing the customer requirements are 6 standard deviations from the process target), then even with a shift in the Voice of the Process, the customer demands are likely to be met. In fact, even if the process mean shifted off target by 1.5 standard deviations, there are 4.5 standard deviations between the process mean and closest specification limit, resulting in no more than 3.4 defects per million opportunities (dpmo). In the 1980s, Motorola demonstrated that in practice, a 1.5 standard deviation shift was what was observed as the equivalent increase in process variation for many processes that were benchmarked.

Figure 1.7 shows the "Voice of the Process" for an accounting function with an average of 7 days, a standard deviation of 1 day, and a stable normal distribution. It also shows a nominal value of 7 days, a lower specification limit of 4 days, and an upper specification limit of 10 days. The accounting function is referred to as a 3-sigma process because the process mean plus or minus 3 standard deviations is equal to the specification limits; in other terms, USL= μ + 3σ and LSL = μ – 3σ. This scenario will yield 2,700 defects per million opportunities, or one early or late monthly report in 30.86 years [(1/0.0027)/12].

Figure 1.7 Three Sigma Process with 0.0 Shift in the Mean

Figure 1.8 shows the same scenario as in Figure 1.7, but the process average shifts by 1.5 standard deviations (the process average is shifted down or up by 1.5 standard deviations [or 1.5 days] from 7.0 days to 5.5 days or 8.5 days) over time. This is not an uncommon phenomenon. The 1.5 standard deviation shift in the mean results in 66,807 defects per million opportunities at the nearest specification limit, or one early or late monthly report in 1.25 years [(1/.066807)/12], if the process average moves from 7.0 days to 5.5 days or from 7.0 days to 8.5 days. In this discussion, only the observations outside the specification nearest the average are considered.

Figure 1.8 Three Sigma Process with a 1.5-Sigma Shift in the Mean

Figure 1.9 shows the same scenario as Figure 1.7, but the Voice of the Process takes up only half the distance between the specification limits. The process mean remains the same as in Figure 1.7, but the process standard deviation has been reduced to one half-day through application of process improvement. In this case, the resulting output will exhibit two defects per billion opportunities, or one early or late monthly report in 41,666,667 years [(1/.000000002)/12].

Figure 1.10 shows the same scenario as Figure 1.9, but the process average shifts by 1.5 standard deviations (the process average is shifted down or up by 1.5 standard deviations [or 0.75 days = 1.5 x 0.5 days] from 7.0 days to 6.25 days or 7.75 days) over time. The 1.5 standard deviation shift in the mean results in 3.4 defects per million opportunities at the nearest specification limit, or one early or late monthly report in 24,510 years [(1/.0000034/12]. This is the definition of 6-sigma level of quality.

Another Look at the 1.5-Sigma Shift in the Mean. The engineer responsible for creating the concept of Six Sigma at Motorola was Bill Smith. Bill Smith indicated that product failures in the field were shown to be statistically related to the number of product reworks and defect rates observed in production. Therefore, the more "defect and rework free" a product was during production, the more likely there would be fewer field failures and customer complaints. Additionally, Motorola had a very strong emphasis on total cycle time reduction. A business process that takes more steps to complete its cycle increases the chance for changes/unforeseen events, and the opportunity for defects. Therefore, reducing cycle time is best accomplished by streamlining the process, removing non-value added effort, and as a result, reducing the opportunities for making mistakes (defects). What a concept! Reducing cycle time by simplifying a process will result in fewer defects, lower remediation/warranty/service costs, and ultimately increased customer satisfaction with the results. This last concept is not new to those who are familiar with Toyota production system concepts, Just-In-Time philosophy, or what many call "Lean Thinking." Six Sigma practitioners concern themselves with reducing the defect or failure rate while Lean practitioners concern themselves with streamlining processes and reducing cycle time. Defect reduction and lean thinking are "flip sides" of the "same coin." The integrated strategy of considering both sides at the same time was the basis of the original work in Six Sigma.

Figure 1.9 Six Sigma Process with a 0.0 Shift in the Mean

Figure 1.10 Six Sigma Process with 1.5-Sigma Shift in the Mean

Some proof of this was gained in the period from 1981 to 1986 when Bob Galvin (CEO of Motorola) set a goal of a tenfold improvement in defect rates over those five years. During those five years, positive results were demonstrated in field failures and warranty costs. However, some of Motorola’s key competitors improved at a faster rate. In 1987, Motorola indicated it would increase the rate of improvement to tenfold improvement every two years rather than five years. What was the target? The target was called Six Sigma quality (which was defined to be 3.4 defects per million opportunities) by 1992.

Of course, the key question was whether there was a tradeoff between reducing defect rates and implementation cost. Bill Smith and others were not advocating increasing costs by increasing inspection, but rather that engineers design products and production processes so that there would be little chance for mistakes/defects during production and customer usage. The focus was on the upstream X variables that would be indicators of future performance and process problems that were observed. The Y variables were the downstream defect rates, rework rates, and field failures that were observed and measured.

Motorola’s strict focus on the rate of improvement challenged engineering, supply management, and production to develop materials, production equipment, and products that were more robust to variation, and as a result, less sensitive to processing variation. Hence, the focus was on understanding the X variables.

What is interesting about the preceding two paragraphs is that often the initial focus of Statistical Process Control (SPC) was limited to monitoring Y variables or average/target values of process variables. Six Sigma did not really change the tools, but instead focused the tools on their usage upstream on X variables; in particular, on understanding the relationship of the variation in the X variables on the variation of the Y variables, and finally, using the tools in such a sequence as to uncover the relationships and be able to improve and control the results of the Y variables.

Studies did show that Bill Smith’s insights were valid: defects per million opportunities (dpmo) and defects per unit (dpu) measures calculated in production facilities did predict field performance, customer complaints, and warranty costs. Therefore, dpmo and dpu became metrics of emphasis at Motorola.

Around the same time that these studies were done, employees at Motorola gathered empirical evidence that even when the Y variables were in statistical control, the X variables might not be in statistical control. Additionally, SPC as practiced in many operations was more of a monitoring method on the Y variables with the only "out of control" indicator being a point beyond a control limit. Consequently, run tests1 were not used as indicators of "out of control." Empirical evidence indicated that a process could shift within the 3-sigma control limits as much as 2 standard deviations and stay there for some run of points before a point outside 3 standard deviations was observed. In fact, if a process with stable variation shifts 1.5 standard deviations, there is an average run of 16 points that would be observed before one point was beyond the 3 standard deviation control limits.

In addition to dpmo and dpu measures, Motorola was also concerned about upstream X variables that could be measured (rather than attribute variables). To control measurement data, a focus on means (i.e., targets) and spreads (i.e., standard deviations) was needed. If the Voice of the Process (VoP) is equal to the Voice of the Customer (VoC), the process’s mean output plus or minus 3 standard deviations equals the specification limits; about 0.27% of the process output is "defective" given a normal distribution. If SPC were utilized to track that variable, and the mean shifted halfway to the control limits (i.e., this assumes an individual—moving range type control chart that is discussed in References 2 and 3), then there could be an average run of 16 observations before a point beyond a control limit would be noted. Another way of saying this is there could be an increase in dpmo from 2,700 to 66,807 with no points being beyond a control limit. If various run tests were conducted, then the shift in the mean would be detected; but in practice, production personnel rarely shut down a process for failure of a run test, if no points were outside the control limits.

So, why does Six Sigma often reference a 1.5 standard deviation shift in the mean of a process? Studies of various production lines at Motorola Corporation showed that even in a state of control, where the only out-of-control condition to be checked was observations outside the 3 standard deviation control limits, there often would be uncontrolled shifts of between 1 to 2 standard deviations. For example, for some manual assembly processes, the shift averaged between 1.2 and 1.8 standard deviations at the time an out-of-control observation was recorded. Of course, for automated processes, this degree of shift is frequently not allowed.

A statistical purist would argue that the genesis of the sigma metric is flawed because it is based on a shift factor. The engineers viewed the metric as a worst-case dpmo for a process because they assumed that any shift factor significantly larger than 1.5 would be caught by the common usage of statistical process control (a point beyond a 3-sigma control limit). If there is a shift less than 1.5 sigma, that is all to the good since the dpmo is less.

From a practical standpoint, Six Sigma seems to be an effective form of management. Moreover, the argument against the 1.5-sigma shift in the mean seems similar to the claim that a yard is not really three feet. Some say a yard was based on the distance from the tip of the nose to the tip of the middle finger on an outstretched arm for an average male. What is an "average" male? Is that similar to knowing an "average" shift? It turns out that eventually everyone accepted the definition that a yard is equal to three feet, and few remember the original definition. At Motorola, the story is similar in that only a few folks remember the original reason for the definition of the sigma levels, and it is accepted that the dpmo levels can be equated with sigma levels.

Interestingly, many of those who continue to argue about the derivation of sigma levels are those who have learned about Six Sigma in the last seven years. It seems that they are trying to understand the "legend" of Six Sigma rather than seeing the upside and benefit. We can continue to argue about this, but practitioners are continuing to improve their organizations regardless of any technical flaws in the derivations of the methods.

Does Six Sigma Matter? The difference between a 3-sigma process (66,807 defects per million opportunities at the nearest specification limit) and a 6-sigma process (3.4 defects per million opportunities at the nearest specification limit) can be seen in a service with 20 component steps. If each of the 20 component steps has a quality level of 66,807 defects per million opportunities, assuming each step does not allow rework, then the likelihood of a defect at each step is 0.066807 (66,807/1,000,000) or 6.68 percent. By subtraction, the likelihood of a defect-free step is 0.933193 (1.0 – 0.066807) or 93.3 percent. Consequently, the likelihood of delivering a defect-free final service is 25.08 percent. This is computed by multiplying 0.933193 by itself 20 times ([1.0 – 0.066807]20 = 0.2508 = 25.08%). However, if each of the 20 component parts has a quality level of 3.4 defects per million opportunities (0.0000034), then the likelihood of delivering a defect-free final service is 99.99932% ([1.0 – 0.0000034]20 = 0.9999996620 = 0.9999932 = 99.99932%). A 3-sigma process generates 25.08% defect-free services, while a 6-sigma process generates 99.99932% defect-free services. The difference between the 3-sigma process and the 6-sigma process is dramatic enough to certainly believe that 6-sigma level of performance matters, especially with more complex processes with a greater number of steps or components.

The DMAIC Model for Improvement
The relationship between the Voice of the Customer, the Voice of the Process, and the DMAIC model is explained in Figure 1.11. DMAIC is an acronym for Define, Measure, Analyze, Improve, and Control. The left side of Figure 1.11 shows an old flowchart with its 3-sigma output distribution. The right side of Figure 1.11 shows a new flowchart with its 6-sigma output distribution. The method utilized in Six Sigma management to move from the old flowchart to the new flowchart through improvement of a process is called the DMAIC model.

The Define Phase of a Six Sigma DMAIC project involves identifying the quality characteristics that are critical to customers (called CTQs) using a SIPOC analysis and a Voice of the Customer analysis, and for preparing a business case for the project with a project objective. SIPOC is an acronym for Supplier, Input, Process, Output, and Customer. The Measure Phase involves operationally defining the CTQs, conducting studies of the validity of the measurement system of the CTQ(s), collecting baseline data for the CTQs, and establishing baseline capabilities for CTQs. The Analyze Phase involves identifying input and process variables that affect each CTQ (called Xs) using process maps or flowcharts, creating a cause-and-effect matrix to understand the relationships between the Xs and the CTQs, conducting an FMEA analysis (Failure Mode and Effects Analysis) to identify the critical Xs for each CTQ, operationally defining the Xs, collecting baseline data for the Xs, establishing baseline capabilities for the Xs, conducting studies of the validity of the measurement system of the Xs, identifying the major noise variables (MNVs) in the process, and generating hypotheses about which Xs affect which CTQs. The Improve Phase involves designing appropriate experiments to understand the relationships between the Xs and MNVs that impact the CTQs, generating the actions needed to implement optimal levels of critical Xs that minimize spread in CTQs, and conducting pilot tests of processes with Xs set at their optimal levels. The Control Phase involves avoiding potential problems in Xs with risk management and mistake proofing, standardizing successful process changes, controlling the critical Xs, developing process control plans for the critical Xs, documenting the control plans, and turning over the control plan to the process owner.

Figure 1.11 Relationship Between the VoC, the VoP, and the DMAIC Model

1.5 Fundamentals of Inventing–Innovating a Product, Service, or Process
Invention
Introduction
I’ll bet at some point in your life you had a great idea for a new product or service. All your friends agreed that it was a great idea. Well, that great idea was the beginning of the invention and innovation processes.

Lee Kaplowitz of Los Angeles had a great idea. His was to invent a litmus paper test for the presence of caffeine in decaffeinated coffee. Lee noticed that most decaffeinated coffee drinkers ask of the waitperson, "Is that decaf?" Lee had an inspiration that could lead to an invention and innovation.

Definition
Invention is the process of creating new products, services, or processes that are usable in accomplishing human objectives that were formerly difficult or impossible. The first club used by a caveman to kill animals to feed his family is an example of an invention.

Inventions and History
Some of the most significant inventions were created before recorded history; for example, crude tools, weapons, speech, cultivation of plants, domestication of animals, building techniques, production and control of fire, pottery, political systems, and the wheel. The period of recorded history began with the invention of cuneiform script by the Sumerians of Mesopotamia in about 3000 b.c.

Innovation
Definition
Innovation is the process by which invention is put to use for the betterment of humanity. Thomas Edison was both an inventor (of the electric light bulb) and an innovator because he was critical to the electrification of New York City and the establishment of the General Electric Company.

Reasons for Innovation
Innovations are created for five reasons. They are discussed next.

Reason 1: Build competitive advantage in target markets, and increase market share by offering products, services, or processes that are preferred above those of competitors. Innovation offers an organization the opportunity to take a step ahead of its competitors for the customer’s positive attention and resources.

Reason 2: Increase profitability by introducing more profitable lines. Innovation aids organizations in creating products, services, and processes that yield higher profit margins than those of their competitors.

Reason 3: Build a reputation for technological excellence by introducing state-of-the-art products. Innovation provides an opportunity for organizations to enhance their image of being a provider who is on the frontier of their core discipline.

Reason 4: Counteract the effects of downsizing on stakeholders by creating new employment opportunities through upsizing [see Reference 7]. Downsizing is a term used to describe an organizational layoff policy whose purpose is to reduce costs. Upsizing is a term used to describe an organizational product creation focus whose purpose is to create new employment opportunities to mitigate the uncertainties caused by downsizing. Innovation provides an organization with the opportunity to create products, services, and processes, and hence, upsize.
Reason 5: Creating exportable products for developing countries. Frequently, developing countries experience great economic difficulties due to unstable governments, an uneducated work force, variable and poor quality raw materials, and rampant inflation. In the face of such unfavorable conditions for economic health, developing countries need to export products that enjoy a non-competitive marketplace. They need protection from industrialized countries that do not suffer from the same economic woes. This can be accomplished by creating, producing, and selling innovative products, services, and processes that enjoy the legal protection of patents, copyrights, and trademarks.

Eight Methods for Invention and Innovation
There are eight methods available for creating inventions and innovations.

Method 1: Exploit core technologies; for example, using excellence in electrical engineering and physics to create new electronic products.
Method 2: Capitalize on particularly excellent common operating elements; for example, using unusually excellent repair service or unusually short delivery times.
Method 3: Pray for an inspiration; for example, luckily thinking to put an eraser on the end of a pencil.
Method 4: Conduct scientific research; for example, studying computer science to develop a laptop computer.
Method 5: Use expertise in specialized functional areas; for example, using excellence in quality control to create dependability and reliability (e.g., McDonald’s or Marriott).
Method 6: Identify the unmet needs of known customers; for example, conducting market research to provide faster delivery time of office supplies or longer battery life for laptop computers.
Method 7: Study "lead users" to identify the unknown needs of customers. Lead users are consumers of a product, service, or process who are months or years ahead of regular users in their use of the item and who will benefit greatly by the innovation. For example, a lead user of a hair dryer may attach a portable battery pack and use it as a body warmer at football games played in cold weather. In this example, studying lead users resulted in the invention of a "personal body warmer."
Method 8: Study the unstated (or unknown) problems of existing users through observational studies. Ideas to surpass customers’ unknown needs and wants do not come from direct queries to customers, but rather from the manufacturer’s observations of the problems customers encounter while using products and services. An example of a product created using this method is a camera with automatic load [see Reference 8].

In 1974, the camera market was saturated with cameras that satisfied customers’ current needs; cameras were reliable, relatively inexpensive to use, and produced good pictures. This created a nightmare for the camera industry. Consequently, Konica decided to ask consumers: "What else would you like in a camera?" Consumers replied that they were satisfied with their cameras. Unfortunately, asking consumers what else they would like in a camera did not yield the information Konica needed to create a breakthrough. In response to this situation, Konica studied negatives at film-processing laboratories and discovered that the first few pictures on many rolls were overexposed, indicating that users had difficulty in loading film into the cameras. This presented an opportunity to innovate camera technology. The customer could not have been expected to think of this innovation. In response to this analysis, Konica developed the automatic-loading camera. This is an excellent example of the eighth method for innovating current products, services, or processes.

Simple Examples of the Invention and Innovation Process
All inventions and innovations do not have to be generated from complex, theoretical, and radical ideas. Sometimes, they come from the simplest of ideas. For example, whoever thought it was possible to create an improved corkscrew? Yet, in the last decade or two, a new corkscrew was invented. This corkscrew has wings or handles that allows the corkscrew to pull the cork out of the bottle.

Another example of a product that you might not think could be improved is the teabag. Surprise! Lipton invented a teabag with two strings that allow the user to squeeze the last drops of tea out of the bag without burning his or her fingers. Ingenious!

Design for Six Sigma (DFSS)
Design for Six Sigma (DFSS) is the method used by a Six Sigma project team to invent and innovate products, services, and processes. DFSS can be used to design entirely new products, services, and processes, or major new features of existing products, services, or processes that are consistently reliable and able to be produced, delivered, or carried out and uniformly surpass customer requirements. Additionally, DFSS creates designs that are: (1) based on stakeholder needs and wants; (2) resource efficient; (3) minimal in complexity; (4) capable of generating high yields; (5) robust to process variations; and (6) quick to generate a profit.

An organization can reap many benefits from employing the DFSS methodology. The list of benefits includes: launching projects on time and on budget; reaping additional incremental revenues sooner; achieving greater market share; minimizing problems uncovered at launch; improving rolled throughput yield (RTY) significantly; ensuring quality and efficient production; and differentiating products, services, and processes due to a customer focus.

Fundamental Principles of "Design for Six Sigma"
DFSS is a method that embodies several principles. The first principle is for all areas within an organization to simultaneously design the product, service, and/or process to minimize future problems. The second principle is to design the product, service, and/or process to minimize variability in CTQs and maximize customer satisfaction. The third principle is to design a process capable of delivering the quantity and quality of products or services desired by customers in a timely fashion. The fourth principle is to include suppliers early in the design process. These four principles are the bedrock of the DFSS method.

Leverage from Professional Design Methods
Research has shown [see Reference 5] that 70% of the cost influence (or total cost) of a product or service (including warranty costs and insurance costs) incurred by a producer or supplier is due to poor design. This cost is largely avoidable if producers and suppliers would invest more resources into designing their products and services. In other words, if suppliers and producers would increase their actual cost expenditures in the design function, then their total costs would decrease. Table 1.2 shows the relationships between actual costs and total costs for the different components of products and services.

Table 1.2 Cost Comparisons

Actual Cost
Cost Influence (Total Cost)

Overhead
30%
5%

Labor
15%
5%

Material
50%
20%

Design
5%
70%

Total
100%
100%

The DMADV Model for Invention and Innovation
The DMADV model is the Six Sigma method for innovating existing products, services, or processes; or for creating entirely new products, services, or processes. DMADV is an acronym for Define, Measure, Analyze, Design, and Verify/Validate.

The Define Phase of a Six Sigma DMADV project involves developing a business case with a project objective and establishing a schedule and guidelines for the design review process. The Measure Phase involves identifying the market segments for potential designs, developing critical parameters for high-level designs, developing targets and tolerances for the critical parameters, preparing design scorecards for the critical parameters, and reviewing intellectual property. The Analyze Phase involves generating high-level conceptual designs, evaluating the high-level conceptual designs, and selecting the best design. The Design Phase involves developing detailed designs. This requires that team members construct detailed specifications, schematics, and blueprints for processes, services, and products. Additionally, team members develop detailed designs for ancillary processes (i.e., Human Resources and Information Technology, to name a few). Finally, the Verify/Validate Phase involves conducting a pilot test of the detailed design; confirming the design outputs will yield product or service specifications; reviewing designs with respect to all potential users and possible uses, and, if necessary, improving designs; establishing appropriate control and monitoring systems to ensure designs meet and maintain goals throughout production or ongoing service life; and transferring the design to the process owner with a functioning control plan.

1.6 What Is New about Six Sigma Management?
Many people think that Six Sigma management is an "old wine in a new bottle." This notion is both false and true. It is false for several reasons. First, it is false because Six Sigma projects are far more structured and formatted than projects in most previous Quality Management processes. Second, it is false because Six Sigma management provides metrics for discussing the quality of processes that can transcend ownership of the processes (i.e., finance, human resources, engineering, and service processes can be compared). It creates "apples to apples" metrics for understanding process improvements. Other Quality Management approaches do not have such metrics. Third, it is false because Six Sigma is very focused on impacting the bottom line or top line of an organization, and it has a specific method for accomplishing this objective. Most other Quality Management approaches do not have such a clear financial focus. The cost of poor quality and other similar concepts have been investigated by the quality profession, but they have not been well utilized outside the quality profession until Six Sigma management. Fourth, it is false because Six Sigma is focused on ongoing rapid improvement of the enterprise. Most other Quality Management processes are focused on incremental continuous improvement, whereas Six Sigma demands breakthrough improvement. Fifth, it is false because past Quality Management efforts were initially spurred on by quality professionals, consultants, or academics, while Six Sigma is being promoted by executive managers such as George Fisher (Motorola) and Jack Welch and Jeffrey Immelt (General Electric). Finally, it is false because Six Sigma is facilitated by an infrastructure of Six Sigma experts overlaying the current organizational structure. Other Quality Management approaches use supervisors, managers, or workers to facilitate teams. Expert facilitation of teams is a big step forward in rapid process improvement that impacts the bottom line of an organization.

On the other hand, it is true that Six Sigma management is an "old wine in a new bottle" because most of the tools, methods, and theories were borrowed from the Quality Management predecessors of "Six Sigma." The authors believe that Six Sigma is more an example of evolutionary management than revolutionary management. The founders of Six Sigma management stood on the shoulders of the giants who preceded them in the quality movement, such as W. Edwards Deming, Joseph Juran, and Kaoru Ishikawa.

1.7 Six Sigma in Non-Manufacturing Industries
Six Sigma management is equally applicable in manufacturing and service industries, education, and government. Most people in manufacturing organizations are employed in service functions such as Human Resources, Payroll, Food Services, and Risk Management. General Electric has been very successful utilizing Six Sigma theory and methods in its non-manufacturing functions such as GE Capital. Additionally, service organizations such as American Express, HSBC, and the University of Miami have successfully used Six Sigma management.

Granted, service transactions are frequently "one-of-a-kind" transactions that take place on demand (zero inventories) in the presence of the customer (zero time between production and use of service) with subjective service quality characteristics. Still, Six Sigma is appropriate in this type of environment. For example, a subjective quality characteristic in a restaurant is how patrons feel about the taste of cheesecake. One way to measure this is to ask patrons how they feel about the taste of cheesecake on a 1 to 5 scale, where 1 = very dissatisfied, 3 = neutral, and 5 = very satisfied. This type of measurement is subject to inaccuracies caused by factors such as embarrassment at telling the "truth." Another way to determine how a patron feels about the taste of cheesecake is to instruct one busboy to collect the first cheesecake dessert eaten by a patron each of the six evening hours each day, and to weigh the cheesecake left on the plate. All cheesecake slices are 4 ounces, so 4 ounces minus the weight of cheesecake returned is the weight of cheesecake eaten by the patron. With the preceding information, the chef can estimate the average ounces and range (maximum–minimum) of cheesecake eaten by patrons each day. Consequently, the chef can modify the recipe for preparing cheesecake and determine from the statistics if the patrons eat more cheesecake (higher average) with less variation (smaller range) per day. If they do, the chef assumes that the patrons like the taste of the cheesecake better with the new recipe than with the old recipe.

Summary
A process is a collection of interacting components that transform inputs into outputs toward a common aim, called a mission statement. Two kinds of variation exist in a process: special variation and common variation. Common causes of variation are due to the process itself. Special causes of variation are due to events external to the usual functioning of the process. A feedback loop relates information about outputs from any stage(s) back to other stage(s) so that an analysis of the process can be made.

The goal post view of quality states that as long as a unit of output falls within acceptable limits (called specification limits) around a desired value (called the nominal or target value), the process is deemed conforming, and there is minimum cost. The continuous improvement view of quality states that quality is a predictable degree of uniformity and dependability, at low cost and suited to the market. This is a more realistic view in that losses begin to occur as soon as a quality characteristic of a product or service deviates from the nominal value, even within specification limits. The pursuit of quality requires that organizations globally optimize their process of interdependent stakeholders.

Six Sigma management is the relentless and rigorous pursuit of the reduction of variation in all critical processes to achieve continuous and breakthrough improvements that impact the bottom line and top line of the organization, and to increase customer satisfaction. Another common definition of Six Sigma management is that it is an organizational initiative designed to reduce defects tenfold while simultaneously reducing processing time by 50% every two years. Finally, the objective of Six Sigma management is to create processes that are twice as good as the customer demands so that if the process mean shifts down, the process will not generate more than 3.4 defects per million opportunities.

The methodology utilized in Six Sigma management to lead to breakthrough improvement in current existing processes is the DMAIC model. DMAIC is an acronym for Define, Measure, Analyze, Improve, and Control. The methodology used to create new products, services, or processes or to substantially innovate broken processes is Design for Six Sigma (DFSS). DFSS uses the DMADV model. DMADV is an acronym for Define, Measure, Analyze, Design, and Verify/Validate. The key ingredient for a successful Six Sigma management process is the commitment of top management.

Six Sigma management is equally applicable in manufacturing and service industries, education, and government.

Pursuing Pharmaceutical Quality and Economy

NK Khoo Managing Consultant — Tue, 06 Jun 2006 02:25:00 +0000

Forward-looking pharmaceutical companies build continuous improvement techniques into their processes from day one.

Jun 1, 2006
By: Bikash Chatterjee
BioPharm International

Bikash Chatterjee

The pharmaceutical industry's recent emphasis on continuous improvement, operational excellence, and process analytical technology has motivated us to evaluate the basic tenets of our approach to quality. Historically, the ability to ensure that a drug meets its intended form, fit, and function has been achieved through the application of the quality infrastructure, i.e., standard operating procedures, policies, specifications; qualification or validation, i.e., commissioning, installation qualification (IQ), operational qualification (OQ), performance qualification (PQ), process validation; and testing, i.e., in-process and final release. However, despite these processes, the number of drug recalls continues to rise, escalating from 176 in 1998 to 354 in 2002, according to the US Center for Drug Evaluation and Research.1

The use of regulations as a primary means of ensuring product quality began to decline in early 2000, when industry pushed back on FDA's Part 11 compliance requirements for electronic signatures and electronic data exchange, challenging the cost and effort associated with implementation, versus the actual benefit to product quality. Today, however, industry and regulatory agencies are moving toward a more scientific approach to ensuring product quality.

The International Conference on Harmonization (ICH) Q8 and Q9 guidance documents2,3 , for example, define a scientific approach to process characterization, advocating a quality by design framework. Risk management is an integral part of this approach.

Similarly, the US FDA's "GMPs for the Twenty-First Century" initiative focused on quality by design, risk management, continuous process improvement, and quality systems. Rolled out in 2004, this initiative challenged industry's traditional approaches to ensuring product quality by encouraging employees to look beyond traditional inspection methodologies for ensuring product performance. The early process and product characterization emphasized in the quality-by-design and risk-management approaches do not inherently conflict with validation. On the contrary, by deepening the level of scientific understanding of a manufacturing process, the approaches ensure that a process is well understood before it is considered "validated." Methods that involve continuous improvement and real-time control, however, do pose a significant question: Are these quality methods inconsistent with the basic tenets of validation that have served as the backbone of the industry's quality structure for so many years? Once you have "validated" a manufacturing process, how much can you improve it—through real-time control or any sort of continuous improvement step incorporated into Lean, Six Sigma, etc.—without having to file manufacturing supplements with FDA? How much of an impediment are those filing requirements?

THE VALIDATION PARADIGM

The challenge of validation is that it has been viewed as a necessary evil—a regulatory activity that cannot be avoided when manufacturing regulated products. The effort and cost associated with validation continue to escalate as industry and regulatory groups increase their understanding of pharmaceutical processes and identify an increasing number of process variables that must be controlled. Biotech adds another layer of complexity by introducing the qualified pilot or intermediate-scale model as an integral component of the validation equation.4

The prohibitive cost of characterization studies at full scale requires us to establish clear, scientific arguments to show how process development studies relate to full-scale validation lots. The complexity of biotech processes demands an even higher level of scientific argument. As we increase our understanding of biopharmaceutical processing, the value associated with traditional validation diminishes, and industry responds accordingly.

The integration of equipment validation and process validation provided incentive to measure the capability of our processes and analytical methods. However, somewhere along the way, the incentive for validation shifted from a need to measure processes, to a need to satisfy a regulatory requirement as quickly and as cheaply as possible.

Over time, industry came to believe that validation had to include a broader range of equipment and processes and a greater level of detail, and as a result, validation costs went up. In response, the industry attempted to distribute the responsibility for validation among participants in the quality process. For example, industry suddenly decided that validation had to include commissioning activities and engineering pre-cursor activity to equipment qualification, so they started requiring that contractors and subcontractors test and document various aspects of IQ. The approach of requiring increased involvement from vendors also extended to factory acceptance tests. Such tests—which have ranged from simple vendor testing and certification to constructing simulator panels to mimic the actuation of automated components—have also ranged in their true relevance to the validation process.

Market drivers completely unrelated to the field of validation often have determined the amount of effort put into validation. For example, when equity markets dried up in the late 1990s, emerging biotech companies shifted their emphasis from scientific investigation to bringing product to market as quickly as possible. The industry looked for cheaper and faster ways to push through the validation process to move programs forward quickly. The result was simpler process validation studies that focused on building three validation lots to demonstrate process predictability, rather than focusing on true process understanding. Likewise, companies began buying more equipment from suppliers who offered "canned" validation protocols that could be purchased and implemented, rather than developing their own protocols to challenge the equipment and thus increase the probability the equipment would meet the needs of the process. The implication of these shifts was that validation was necessary, but not essential to sound process development.

This short-cut approach to validation resulted in processes that were less stable at the commercial scale. FDA's recent revelations about high-profile, approved products that may be unsafe, such as Vioxx and Serevent, and Congress's pressure on industry to find ways to reduce the cost of drugs to the general public, have impacted both Big Pharma and biotech. In response, the industry has recognized the need for a better way to reduce process and product risk.

The answer was a shift to a more scientifically driven development approach, often referred to as "Operational Excellence," or "Process Excellence." This approach integrates process, quality, and business requirements to promote the science of development.

These quality initiatives integrate Six Sigma, Lean Manufacturing, Kepner-Tregoe, Theory of Constraints, Design of Experiments, and Balanced Scorecards to establish process understanding. These methodologies emphasize the need to objectively define, measure, and characterize critical variables that affect a process. While testing and data collection are integral components, verification is the final culmination of the quality assessment—not the basis of quality.

Looking closely at these approaches, however, reveals that they based in a large part upon an approach that has been integral to our quality systems for over 70 years—Walter Shewhart's cycle of Plan, Do, Check, Act (PDCA).

PLAN, DO, CHECK, ACT

Figure 1. PDCA "The Shewhart Cycle"

Walter Shewhart, an enterprising statistician who worked at Bell Laboratories in the US during the 1930s, developed the science of Statistical Process Control. An offshoot was the PDCA Cycle, often referred to as "the Shewhart Cycle." This tool was adopted and promoted from the 1950s on, by W. Edwards Deming, the renowned quality management authority, and as a result the tool also became known as "the Deming Wheel" (Figure 1).

The PDCA Cycle was the first tool broadly adopted as a framework for continuous improvement. PDCA is a four-step quality improvement cycle that promotes continuous improvement based on the method of design (plan), execution (do), analysis (check), and evaluation (act). Sometimes referred to as plan/do/study/act, the cycle emphasizes the constant attention and reaction to factors that affect quality.

The chief advantage of the PDCA cycle—flexibility in moving through each phase of the cycle—is also its biggest challenge, because it left the door open for subjectivity. Subjectivity has long been the downfall of our industry. Without a clear vision for success or a defined method for evaluation, the potential exists to rely on unscientific process development and characterization activities, which can lead to incorrect or incomplete conclusions. For example, univariate analysis methods—often called One-Factor-at-a-Time (OFAT) studies5 —have been the backbone of the small-molecule pharma industry, as well as the biopharm industry. Such studies, however, do not possess the power to fully characterize a process. The result is a false sense of security that the process characteristics are understood.

Figure 2. Cube Plot for Protein Recovery

An analogy would be that of trying to solve the popular "Rubik's Cube" puzzle. It may be relatively simple to get one side of the cube all one color, thus providing the impression of progress towards your goal. However, the reality is that you are actually further from success than when you started the exercise (Figure 2). Because of these limitations, other industries abandoned the OFAT approach 30 years ago, deeming it ineffective for process characterization and verification.

The biopharmaceutical industry, too, has come to recognize that the OFAT approach is insufficient. The industry has also realized that to be successful in combining quality, technical, and business requirements in the drug development lifecycle, it must realign not only its scientific approach to process understanding, but also its thinking within the organization. As a result, Operation Excellence initiatives have moved to frameworks such as Six Sigma to provide a roadmap that can meet this need.

SIX SIGMA AND ITS ROADMAP

Figure 3. Six Sigma as an organizational development and leadership tool

In 1986, Motorola established a framework designed to integrate quality, process, and business requirements into the product development lifecycle. Motorola recognized that variation is the death knell of any process, so the company set out to establish a methodology to identify and eliminate variation. They called this approach Six Sigma6 (Figure 3).

Figure 4. The DMAIC Roadmap

In the late 1990s, CEOs Jack Welch from GE and Larry Bossidy from Allied Signal adapted the Motorola model to a set methodology called the DMAIC roadmap. DMAIC is an acronym for Define, Measure, Analyze, Improve and Control. These are the five phases necessary to measure, characterize, and control a process (Figure 4).

Within each step of the road-map, a defined set of tools is applied. Each phase in the DMAIC process is intended to guide the members of an improvement team through the project in a manner that provides relevant data and in-depth process understanding. The DMAIC project management approach allows businesses to make the best possible decisions with the available data and resources. The five-steps of the DMAIC process are as follows:

1. Define: Clearly define the problem and relate it to the customer's needs (generally, with a cost benefit to the organization identified).

2. Measure: Measure what is key to the customer and know that the measurement is good.

3. Analyze: Search for and identify the most likely root causes.

4. Improve: Determine the root causes and establish methods to control them.

5. Control: Monitor and make sure the problem does not come back.

Within each DMAIC phase, there is a set of deliverables that must be completed to ensure all project requirements are met. A summary of the deliverables and typical activities for each phase of the DMAIC process is shown in Table 1.

Looking closely at the tools within the DMAIC methodology reveals elements that have been part of the quality toolkit since its inception. Cause and effect diagrams, Failure Mode and Effects Analysis (FMEA), and process capability analysis, among others, have been used broadly by process and quality engineers in multiple industries for years. What separates the DMAIC roadmap from the isolated application of these individual tools is the methodology around the application of the tools. In DMAIC, the process evaluation is based on the objective acquisition and analysis of data, in lieu of representative testing and inference.

LEAN MANUFACTURING

Although Six Sigma and the DMAIC toolkit focused on eliminating process variability, there still remained the need to bring products to market faster and more cheaply. As a result, the biopharmaceutical industry has turned to the principles of Lean Manufacturing to increase the efficiency of our processes. The ideas of Lean Manufacturing are based on the Toyota Production System approach of eliminating waste in every aspect of a company's operation. Lean focuses on time variability, in contrast to Six Sigma's focus on process variability. In their book Lean Thinking, Jim Womack and Daniel Jones7 recast the principles of Lean into five principles:
1. Value: Every company needs to understand the value customers place on their products and services. It is this value that determines how much money the customer is willing to pay for them. This analysis leads to a top-down, target-costing approach that has been used by Toyota and others for many years. Target costing focuses on what the customer is willing to pay for certain products, features, and services. From this, the required cost of these products and services can be determined. It is the company's job to eliminate waste and cost from the business processes so that the customer's price can be achieved at great profit to the company. In the biopharmaceutical and pharmaceutical world, value is often associated with quality and data, rather than with standard cost.

2. Value Stream: The value stream is the entire flow of a product's lifecycle, from the origin of the raw materials used to make the product through to the customer's cost of using, and ultimately disposing of, the product. Only by studying and obtaining a clear understanding of the value stream (including its value-added and waste) can a company truly understand the waste associated with the manufacture and delivery of a product or service.

3. Flow: One significant key to the elimination of waste is flow. If the value chain stops moving forward for any reason, then waste occurs. The trick is to create a value stream in which the product (or its raw materials, components, or sub-assemblies) never stops in the production process, because each aspect of production and delivery is in harmony with the other elements. Carefully designed flow across the entire value chain will minimize waste and increase value to the customer. Achieving this kind of flow is a challenge in our industry because many of our processes are batch processes. Even so, within the context of the total value stream, there are significant opportunities to move towards continuous flow.

4. Pull: A traditional Western manufacturer uses a style of production planning and control whereby production is "pushed" through the factory based upon a forecast and a schedule. A pull approach dictates that we do not make anything until the customer orders it. To achieve this requires great flexibility and very short cycle times of design, production, and delivery of the products and services. It also requires a mechanism for informing each step in the value chain what is required of them today, based on customers' needs.

5. Perfection: A lean manufacturer sets perfection as a target. The idea of total quality management is to systematically and continuously remove the root causes of poor quality from the production processes so that the plant and its products move toward perfection. This relentless pursuit of the perfect is the key attitude of an organization that is "going for lean."

Lean has been enthusiastically embraced by our industry because the tools are simple and improvement can be realized quickly. Although Lean is often initiated because of cost or efficiency reasons, there is another perspective to Lean that is often overlooked: quality.

Figure 5. DMAIC and Lean tools deployed in the Shewhart Cycle

Our industry should think of Lean as a quality initiative—not a business-driven one. While it is true that the basis for Lean is to eliminate waste and maximize the value-added activities of a process, another benefit of Lean is the way it simplifies and standardizes the process. The result is improved predictability. If you map the DMAIC and Lean tools together against the Shewhart PDCA Cycle, you find they follow the same framework; the tools within both toolkits are designed to address the same basic requirements of the PDCA cycle (Figure 5).

VALIDATION AND PLAN, DO, CHECK, ACT

Table 1a. Summary of DMAIC phase deliverables (continued)

Mapping validation, as applied by the biopharmaceutical industry today, may seem inconsistent with the principles of the Shewhart PDCA Cycle, DMAIC, and Lean. The basis of traditional validation is verification against predetermined acceptance criteria. How-ever, if we divide the validation process into its components, there is more similarity than difference between validation and these improvement methods. The steps of the validation life cycle map well to the Control, Measure, and Analyze phases of the DMAIC roadmap. What is missing is the Improve stage.

Table 1b. DMAIC phase deliverables

Six Sigma and Lean principles are predicated on the absolute requirements of demonstrating that the process is in control. By building on an efficient and objective framework for characterizing, measuring, and optimizing a process, it is possible to achieve a level of confidence that the process will be predictable and reproducible. No amount of testing will ever approach this level of confidence; heightened testing and large sampling can still only infer the process is in control. (As many have said, you cannot test quality into the product.) The irony in applying validation to the PDCA model is that its efficacy is only as good as one's understanding of the key process input variables that steer the process. In the absence of this, validation degenerates to a paper exercise.

CONCLUSION

Quick Recap

The twenty-first century GMP initiative advocates the need for building process understanding throughout the process development lifecycle. Tools such as Six Sigma, DMAIC, and Lean Manufacturing provide a framework for objective characterization and analysis of a process's key parameters. This knowledge, coupled with a quality system framework for specification, in-process, and release testing, can significantly elevate the level of quality built into the final product or process. While at first glance validation might appear to be inconsistent with these improvement initiatives, the elements of the validation lifecycle map to the control, measure, and analysis phases of the PDCA lifecycle. The most effective application of validation is achieved by using these optimization tools in the process characterization and development phases of a process long before validation. Until characterization and evaluation frameworks are more fully integrated into the drug development lifecycle, validation will remain a costly and time-consuming exercise capable only of providing limited assurance of process and product stability.

Bikash Chatterjee is the chief operating officer of Pharmatech Associates, 1098 Foster City Blvd., Foster City, CA 94404; tel 650.227.0177 fax 650-227-0176; bchatterjee@pharmatechassociates.com

REFERENCES

1. US Food and Drug Administration, Center for Drug Evaluation and Research, http://fda.gov/CDER.

2. International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use, ICH Harmonized Tripartite Guideline, Pharmaceutical Development Q8, November 2005.

3. International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use, ICH Harmonized Tripartite Guideline, Quality Risk Management Q9, November 2005.

4. Gibson M. Technology Transfer: An International Good Practice Guide for Pharmaceutical and Allied Industries. Illinois: DHI Publishing, 2005.

5. Schmidt SR, Launsby RG. Understanding Industrial Designed Experiments, 4th Ed. Colorado: Air Academy Press, 2000.

6. Brefogle FW. III. Implementing Six Sigma. New Jersey: Wiley and Sons, 1999.

7. Womack JP, Jones DT. Lean Thinking. New York: Simon & Schuster, 1996.

Snuffing Out Scrap

NK Khoo Managing Consultant — Mon, 05 Jun 2006 23:02:00 +0000

Realistically, scrap is difficult if not impossible to eliminate. But manufacturers that acquiesce to scrap are missing opportunities to cut wasteful material and save on labor costs.

By Jonathan Katz
June 1, 2006 -- Plant operators frequently play the role of garbage collectors at the expense of manufacturers. Instead of producing, they're gathering scrapped parts and materials to be recycled, reused or discarded. Facing foreign competitors who already are able to produce parts and materials at a significantly lower cost, U.S. manufacturers cannot afford the additional labor costs incurred from handling excess scrap.

Although manufacturers expect some scrap will be generated during the production process, truly lean operations strive for little or no scrap. These companies employ a variety of continuous-improvement methodologies, including Six Sigma, Multivariable Testing (MVT) and simple chart analyses, to reach their scrap-reduction goals.

Manufacturers tend to be more successful in their scrap-reduction efforts when they use some type of scientific approach rather than basing their plans of action on experience, says Ralph Rio, research advisor, ARC Advisory Group, Dedham, Mass. "Unfortunately, most manufacturers are going by tribal knowledge, meaning someone has an opinion about how to fix a particular operation or to reduce scrap and, by dominance of their personality, has a change implemented," he says. "Sometimes it works, but usually it doesn't."

Instead, Rio says manufacturers should depend on fact-based knowledge, often derived from information entered into databases by plant-floor operators that is then represented on a simple Pareto chart -- a bar graph with values plotted in descending order starting from the left-hand side.

The quick and simple approach to solving scrap problems is what David Cochran, vice president of operations for QualPro Inc., an MVT training and consulting firm based in Knoxville, Tenn., stresses to his clients. MVT involves a brainstorming process in which several people with different roles throughout the company and plant operations list ideas to address inefficiencies. Manufacturers then narrow down the list based on which ideas are the most practical to implement, usually depending on how costly or time consuming the project will be, says Cochran, who co-authored with Charles Holland "Breakthrough Business Results with MVT."

"If something is not easy to test and implement, we set that aside because what we found is that these easy and quick and inexpensive changes very often can create these big breakthrough results," he says. The next step with MVT is to test the ideas in live situations. The ones that produce positive results are implemented while the ones that fail are dropped.

Using these tools to analyze processes at the operations level is a common way to measure and identify scrap problems, but material waste also can be prevented by implementing changes at the engineering stage. In the auto industry the first line of attack against scrap often is taken at the engineering stage, says Ron Krupitzer, vice president of automotive applications for the American Iron and Steel Institute.

For instance, stamping plants sometimes use steel blanks that are larger than needed to ensure there's enough workable material during the tryout process. Over time, auto manufacturers have found ways to fine-tune the engineering process so they can use the smallest-size blank possible. One way Tier One auto parts suppliers have trimmed blank sizes is by using more computer modeling applications to predict and simulate the stamping operation, Krupitzer says. This gives them a better idea of what steel grade will produce the least amount of scrap.

Auto manufacturers also have experimented with stronger steel to reduce scrap, sometimes in the assembly of inner-door panel hinges where the need for additional reinforcement parts results in more waste. Now automakers can use laser-welded blanks, or blanks made from higher-strength steel to eliminate the need for hinge supports, Krupitzer says. Higher-grade steel may also be used in the stamping process to prevent splitting and lower defect rates.

For the Hexacomb division of Pregis Corp., an $850 million protective packaging company based in Lake Forest, Ill., the scrap problem was paper and glue used to create die-cut packaging. When Hexacomb President Bill McBee joined the division in 2003, he was looking for ways to reduce costs. He started by focusing on the most obvious cost-cutting opportunity: waste. During the process of converting paper into die-cut packaging, Hexacomb was scrapping the equivalent of approximately one out of every four rolls of paper it purchased, according to McBee. He estimated the cost of wasted paper, glue and labor at $4.5 million.

McBee started his scrap-reduction initiative by selecting Hexacomb's top-performing plant in Trenton, Ill., for an MVT experiment. A brainstorming session with all the plant's hourly and salaried employees resulted in 350 to 400 ideas. McBee says it's critical to involve the people who are most familiar with the plant-floor processes in these sessions. "You start off by shooting all the engineers -- they don't really have the answers," jokes McBee. "Then you get all the operators and material handlers and everyone you can who really understands what's going on in the process . . . and you go through four days of SPC (statistical process control) training, using statistics from the plant that you're going to work with."

From there, the plant staff narrowed the 350 or so ideas down to 24 variables to test by eliminating duplicate suggestions and less-practical ideas. Over a 48-hour period, plant-floor operators conducted the tests and recorded the results. The plant found three factors that reduced scrap, three that increased waste and 15 that had no effect at all, McBee says.

The changes that worked -- replacing old glue rollers with new ones, setting scheduled speeds for the machines that make the cores and tweaking the speed of the saws that cut the paper -- reduced scrap at the Trenton facility by half.

Hexacomb has extended MVT to other plants and achieved further scrap savings. In 2005, the company conducted an MVT of 17 machines at eight different plants, but McBee cautions that the method is more effective when it's narrowly focused. "MVT works best if you have a situation where you focus on one process -- for example, one machine, one plant," he says. "When you try to combine all of them, you get a lot of averaging, so you don't get nearly the impact when you do a whole bunch of them with the same factors on the same days."

About six years ago, Cummins Inc., a Columbus, Ind.-based manufacturer of large diesel engines, began making Six Sigma part of the company culture. One of Cummins' goals with Six Sigma was to reduce the amount of scrap at its fuel systems plant. Through the Six-Sigma process of defining, measuring and analyzing, the company found several opportunities to reduce material waste. One of the key people in implementing these improvement projects was account manager Ginger Lirette. In 2005, Lirette received one of the company's first J. Irwin Miller awards -- named after the company's former CEO -- for completing 13 quality improvement projects that saved the company nearly $14 million.

One project headed by Lirette was to analyze the gauging on the fuel systems injector line where the company was experiencing a high defect rate. Using the Six Sigma methodology, Lirette discovered that the gauging was not accurately simulating an operating engine. "Based on that study, we were able to rework our gauge to be more real-world like, and we were able to save quite a bit of time, scrap and labor," Lirette says.

Another Six-Sigma project the company undertook revealed that one of the operations intended to improve the roundness of injector plungers actually was causing defects. By removing this step from the process, the company was able to improve the quality of the plungers and reduce scrap. "How often does that happen?" Lirette asks, then answers: "[It's] probably not very often that you actually get to take an operation out, so you're reducing your inventory, you're reducing your labor time and getting a quality improvement."

In 1999, General Cable Corp.'s 56,000-square-foot Moose Jaw, Saskatchewan, Canada, plant was operating at approximately 4% gross waste, according to plant manager Ray Funke. At the time, the factory, which was a winner of IndustryWeek's 2005 Best Plants award program, was using some rudimentary tools to measure scrap, but it wasn't providing the detail that was needed to produce significant results. So the plant developed detailed metrics of every cause of scrap from every workstation in the plant using several lean tools.

The plant utilized a Pareto-analysis chart to engage its workforce in its scrap-reduction efforts by showing them where scrap was occurring. Funke says getting production workers involved in the scrap-reduction process was a key turning point for the plant. "It was a major initiative because our company in 1999 wasn't in a very good position from a financial standpoint with the market downturn in wire and cable, and we were obviously trying to cut costs in any way possible, and scrap was clearly a big opportunity for every plant within our company," Funke explains.

By using the charts and involving employees in the process, the plant was able to significantly cut scrap at its extrusion line, reducing approximately $140,000 of wasted material in 1999 to between $12,000 and $15,000 in 2005. The plant ended 2005 with a gross scrap rate of about 1.1%. Its 2006 goal is 0.85% and as of April was on track to reach that mark, according to Funke.

"I think the big thing is we have frequent metrics that get in front of the people who run the equipment at least once a week, so they see these metrics as far as what are the major drivers, they understand what the cost of a quality defect is or what the inherent scrap is, and we use the Pareto 80/20 rule -- that we'll just focus on the big hitters until we can't theoretically drive anything out any further," Funke says.

The World According to TRIZ

NK Khoo Managing Consultant — Mon, 05 Jun 2006 22:55:00 +0000

By Reena Jana

The World According to TRIZ
Blue-chip American companies are embracing a 60-year-old innovation theory pioneered by a Russian inventor

With "innovation" such a hot buzzword in business circles these days, companies are scrambling to find the magic formula for creating inventive products and services. One method that's gaining converts -- and breeding skeptics -- is a 60-year-old theory known as TRIZ.

TRIZ is the brainchild of late Russian inventor Genrich Altshuller (1926-98), who worked as a patent inspector. In the process of observing invention after invention, Altshuller sought to identify a consistent formula for innovation. In 1946, he published an article laying out his theory of structured innovation, which he titled "Teoriya Resheniya Izobretatelskikh Zadatch." That translates roughly into "Theory of Inventive Problem Solving," or TRIZ, for short.

Fast-forward to 2006. The list of American companies that have applied Altshuller's recipe for innovation includes Boeing (BA ), Hewlett Packard (HPQ ), IBM (IBM ), Motorola (MOT ), Raytheon (RTN ), and Xerox (XRX ), among others.

HAPPY OUTCOMES. In the U.S., one of the main evangelists for TRIZ has been Brooklyn (N.Y.)-based futurist and innovation consultant Andrew Zolli of Z + Partners, who has advised such blue-chip companies as General Electric (GE ). The TRIZ gospel is also being spread through a newly published book, Insourcing Innovation, by innovation coach David Silverstein, author Neil De Carlo, and TRIZ Journal editor and scientist Michael Slocum.

Here's a brief tutorial on TRIZ. Begin by defining your ideal outcome -- what function you want the product or process to perform. The next step is to figure out how to best utilize your organization's resources to work toward that goal. Next, run scenarios and devise models to try to achieve the desired outcome.

To help guide the process, Altshuller devised a matrix of 39 basic problems and 40 possible solutions. The former includes such tech-y considerations as "energy spent by non-moving object" or "tension, pressure." But others are more general, like "speed" or "level of automation." The list of possible fixes include categories such as "pneumatics and hydraulics," but also more common-sense principles such as "other way around" (as in, why not try the opposite of the approach that isn't working?).

MIX AND MATCH. One company that successfully applied TRIZ to arrive at an innovative product is San Diego-based OnTech. In 2004, OnTech debuted a single-serving, self-heating container that can be used as packaging for soup, coffee, tea, or even baby formula. Among the brands that have licensed the technology are a line of gourmet coffees produced by celebrity chef Wolfgang Puck and Hillside soups and coffees.

OnTech's product developers faced more than 400 technical and engineering dilemmas in trying to devise a sturdy, yet portable container that could warm drinks and stews, but could also contain and withstand the chemical reaction used to generate heat. The team surveyed TRIZ's list of 39 problems and identified those that applied, and then selected fixes from the parallel list of 40 inventive principles.

For example, they chose No. 14 from the first list -- "temperature" -- and applied No. 30 from the second list, "use of composite materials," as well as No. 40, "flexible shells and thin films." By using TRIZ's mix-and-match lists as a springboard, the engineers quickly arrived at a suitable material for their container: a ceramic and carbon-fiber composite that's both durable and conducts heat efficiently. Presto, a new product was born.

ASIAN ACCEPTANCE. Although TRIZ has been around for half a century, it's only in the past decade that it began to infiltrate the research & development departments of American companies. Silverstein recalls that he first learned of TRIZ six years ago, during a consulting gig with Navistar International (NAV ), a manufacturer of heavy-duty trucks. "One of their PhDs introduced me to a Russian group in Detroit, and they told me about TRIZ. And I thought, 'This could be a parallel to Six Sigma,'" he says, referring to the system for gauging defects and boosting quality pioneered by Motorola (MOT ) in the mid-1980s and later popularized by companies like GE.

Silverstein acknowledges that TRIZ has found greater acceptance in Asia than in the U.S. His Asian client base has more than doubled in the past 18 to 24 months, he says. "It's hard for some companies to see innovation as something that can be structured," he says. "People want to think that innovations occur as the result of really smart people's ideas. When you structure that and say anyone can innovate, well, this idea becomes threatening."

Still, TRIZ is making inroads stateside. Davin Stowell, founder and chief executive of New York-based Smart Design, a leading product-design firm, only recently discovered TRIZ. Although he has yet to put the theory into practice, Stowell admits that he sees its merits. "When I first read about TRIZ, I found it a little offputting at first. I was a slight skeptic," he says. "Then I saw that it wasn't that different from what we do in product design."

COOKIE-CUTTER SOLUTION? According to Stowell, the main difference between TRIZ and the methods used by design-cum-business-strategy firms such as Smart Design, Palo Alto (Calif.)-based IDEO, or Boston's Design Continuum, though, is that they also rely heavily on another trendy concept: ethnography (see BW, 6/5/06, "The Science of Desire"). In other words, they engage in intensive consumer research to figure out whether their inventions will be well-received or not.

When asked if "structured innovation" à la TRIZ is a contradiction in terms, Stowell defends the general idea. "You need structure to step out of the box. While TRIZ is clearly much more applicable for engineering and science, its core principles are helpful. Innovation absolutely needs to be structured to finish a project. Or else you wander all over the place," he says.

Some product-design firms approach TRIZ with caution. One of them is Design Continuum. "It seems to me that TRIZ is trying to create an equation for innovation," says Harry West, the company's vice-president of strategy & innovation. "I think it's a great aspiration. But if there's an equation for innovation out there, your competitor can do the same -- which means the competitive challenge can easily be lost."

TRIZ's proponents contend that they aren't trying to sell a modern-day version of snake oil. Says Silverstein: "Look, TRIZ is not the answer to everything. It's just one approach to innovation." And it's an approach more companies are turning to.

Zeroing In On The Customer: IW Best Plants Profile - 2004

NK Khoo Managing Consultant — Mon, 05 Jun 2006 22:50:00 +0000

To improve its products, Northrop Grumman's flagship Defensive Systems Division plant goes to war -- literally.

By Tonya Vinas
Oct. 1, 2004 -- Northrop Grumman Corp. Defensive Systems Division, Rolling Meadows, Ill.

At a Glance

Total square feet: 1 million

Start-up: 1967

Achievements: With ongoing process improvements, the Rolling Meadows operation achieved $13 million in cost savings in 2003 and a 39% increase in cash flow over the past three years. Additionally, it has reduced average time-to-market for new products by more than 50%.

Benchmarking Contact: Tom Fallon, 847/259-9600, Ext. 5681, tom.fallon@ngc.com

Talk about customer service.

It's not unusual for engineers to visit customers in the field, especially these days with manufacturers focusing on service as a strategic advantage. But when your customer is a soldier, preparing for war or in live combat, customer service takes on a whole new meaning.

"I'd like you to assume that this land mass over here is the United States -- good guys," says Jim Cameron, a man whose streamlined language and patient explanations come in handy when explaining the intricacies of war on a faux map. "This land mass over here is some bad guy. Unfortunately, the nature of man is such that there are always good guys and bad guys. The only thing that's common is that we're always the good guys."

Cameron, vice president and general manager of the Defensive Systems Division (DSD) of Northrop Grumman Corp., uses the map to explain what his division manufactures -- complex defense electronic systems that give soldiers the ability to find hidden dangers, confuse enemies and their "smart" weapons, and zero in on precise targets when using their own weapons.

The DSD division is headquartered at a sprawling, million-square-foot compound in Rolling Meadows, Ill., one of this year's IW Best Plant's winners. The plant's 2,000 employees use a variety of methods to achieve world-class status, but all are driven by a focus on the customer that's as sharp as the sensors of the products they produce.

"What discriminates us is that we believe if we can understand our customer's mission as well as they do, we can help them be more effective," says Cameron, who has held his current post for six months and previously worked at ITT Industries. "We don't wait for our customer to say, 'Will you give us this?' We find out what our customer is trying to do, and then we develop solutions. As a result of that, we get out ahead of the competition and give our customers the things that are the most beneficial for them to execute their mission."

The crux of this customer interaction takes place in the field through user conferences, extensive testing at customer sites, training at customer sites and, at times, during war.

"The field service engineer is out there to maintain and service our products in the field," explains Greg Schmidt, vice president of engineering and manufacturing at Rolling Meadows. "By maintaining and supporting that product, they are working hand-in-hand with the user. Sometimes we don't have enough field service engineers to go everywhere they need to be at the same time. So we actually have [design] engineers and our operations test engineers volunteer to go into theater to support our products."

These engineers are deployed in teams and include people who've been with the products "from the electrons on our IT system to the real hardware," Schmidt says. "They take that experience and learning and bring it back for the next program."

DSD's customer focus is apparent throughout the high-mix, low-volume Rolling Meadows plant. Rather than focus on one omnipresent improvement philosophy -- such as lean or Six Sigma or value-stream mapping -- Rolling Meadows using all of these and more techniques, all with an eye toward customers, customers, customers.

To please customers, DSD must develop innovative, mission-critical products and manufacture them faster and cheaper. DSD's achievements in this area enabled the division to win 80% of proposals submitted in 2003 and maintain a 100% repeat-business rate.

Sure, the wars in Iraq and Afghanistan have increased demand for the plant's products, but Rolling Meadows has customers other than U.S. armed forces and has been laying the building blocks for the past five years that gave it an advantage when the U.S. declared war. Some of those building blocks include:

Adding automated testing and other process improvements that reduced overall manufacturing cycle time by 62%.

Establishing the Operator Self-Acceptance and Product Assessment Program, which empowered production workers to make accept/reject decisions about products throughout the manufacturing process. "This approach helps build quality into the product rather than trying to inspect quality into the product," the plant management stated in its Best Plants application. On one of its complex electronic devices, the plant has seen a 300% increase in first-pass yield improvement.

Deploying 17 Six Sigma black belts to use their tools throughout the plant to make singular-but-significant improvements in business practices and engineering processes. In the case of one infrared sensing system, Six Sigma techniques allowed for a tripling of units produced annually by adding fewer than five employees and a nominal increase in production. On the same product, engineers used Six Sigma to determine that using a different method to apply a drop of reactive liquid during production reduced drying time from 24 hours to 3.5 hours, cutting 20 hours out of cycle time.

Emphasizing modular design and agility. For instance, in its Litening targeting system line -- which was used in the rescue of Pvt. Jessica Lynch from an Iraqi hospital -- engineers can customize each pod with a few software programming changes. The hardware remains largely the same.

So the pods going to one branch of the military are different than those going to another, but the customization takes minimal time and overhead. (The pods, shaped like bloated missiles the length of a large surf board, attach to the underbelly of aircraft.)

Using IT to integrate product design and manufacturing and to track process improvements. The Rolling Meadows plant was an early adopter of product lifecycle management (PLM) software and uses it to communicate design plans and changes immediately to manufacturing staff so that they can begin planning for capacity, raw materials and other needs. PLM also enables intense supplier/partner collaboration. Additionally, a robust, home-grown portal runs on top of all applications and gives team leaders and managers a real-time view of significant metrics across the plant and its market segments via a variety of charts and graphics. The entire system is integrated and updates simultaneously.

"The information is not added again and again," says Lisa Strama, manager of operations systems at the plant. "It flows automatically so that people can focus on strategies."

Cameron meets monthly with managers to review the metrics point-by-point via the portal. He insists upon the meetings and a manager's report, although he could review the data himself, because he sees it as a learning experience and a way to ensure that managers know their knitting.

The data is not only used for tracking improvements but for planning, e.g., capital equipment purchases. In that way, Cameron says there's a "closed-loop" system from the engineers in the field with the customer to the executive decisions he and his staff make.

"It gets that guy-who-is-closest-to-the-customer's current view of the world that helps us focus on where we're going in the future," Cameron says. "It's a very powerful thing."

Six Sigma In A Small Business

NK Khoo Managing Consultant — Mon, 05 Jun 2006 21:36:00 +0000

Tony Jacowski
Expert Author
Published: 2006-06-01

As a small business owner, you will eventually sense the need for Six Sigma implementation in your business.

Typically, yours is a 3-5 year old company on the threshold of expanding your operations to meet the growing customer expectations but is cornered to optimize your resources on generating more sales than anything else. Small companies in the bracket of 50-100 employees (most of them being non technical) and revenue of $10-15 million find themselves in this fix. The predicament at this stage is one of a person who is caught between a tiger and cliff.

Finding A Way Out Of The Jam

The situation needs to be given a rational thought concerning how many resources can be afforded and whether the time has really come for Six Sigma. The cost of hiring consultants being hardly affordable, you have to explore options like hiring a Black Belt and having some of your employees trained in-house for Green Belt positions.

What you probably don't want to miss out on in hiring an experienced Black Belt, although expensive, are the benefits you get because of her/his domain knowledge and experience. Her proven track record will have the best chances of outweighing the initial cost benefit of grooming in-house Black Belts. An experienced Black Belt helps by bringing the focus immediately into a pressing issue on hand which is crucially important to the organization. Alternately, your best man with brilliant analytical and leadership skills may be trained as a Black Belt, and you may enroll in a Champion Session.

The trouble with this kind of an arrangement is whether you can afford to lose your best person from his current job. Enrolling Black Belts, can be an option for you, but you must realize that it takes some time before the new Black Belts get acclimatized with your scheme of things. At the same time, Green Belts, most often being part-time, don't need to be of high skill. Choosing a few reasonable persons from your organization will suffice. A great Black Belt can take minor shortcomings of Green Belts in stride and things will eventually balance out.

Resolving The Issue Of The Master Black Belt

Even an experienced Black Belt will need the support of a Master Black Belt. The vacuum can be felt typically when the Black Belt finds herself in a logjam. A typical case could be one of technical or organizational reasons. But hiring Master Black Belts is a costly proposal. Secondly, growing and training Master Black Belts in house is also impractical. You will have to hire a consulting Master Black Belt.

But getting a professional is not easy, especially when many of them are more interested in increasing 'their-hours-in-work' than in the task. You can consult your state's 'Manufacturing Extension Programs' or a trusted contact to refer you to a consulting Master Black Belt. In any case, with you at the helm of affairs, you will know when to pull the plug when something is not working out.

Caution Is The Word

Probably you would want to go one project at a time. Assessing your progress at intervals should direct the course of action. Brainstorm with your internal team to decide on activities to go for Six Sigma and which of the activities are measurable. Establishing measurability and metrics beforehand is important.

Dow Honored for Energy Efficiency Leadership

NK Khoo Managing Consultant — Mon, 29 May 2006 15:29:00 +0000

Source: GreenBiz.com

NEW ORLEANS, La., May 25, 2006 - The Organizing Committee of the 28th Annual Industrial Energy Technology Conference, (IETC) has presented Dow with an award for leadership in energy management.

Sponsored by the Energy Systems Laboratory, Texas A&M University System, Louisiana Dept. of Natural Resources, the U.S. Department of Energy, and the Texas State Energy Conservation Office, the conference brought together members of the industrial energy community from regions of the world such as North America, Europe, and the Middle East to share best practices and the latest industrial innovations in energy management and waste reduction.

This award recognized Dow for its strong global focus on energy efficiency and recent results, including:

achieving aggressive EH&S 2005 goals related to energy efficiency -- reducing our energy intensity by 22% from 1994 -- 2005

maintaining strong corporate support and an energy efficiency organization to drive results at the site and business levels

using proven Six Sigma methodology and industry best practices to accelerate energy efficiency improvements

supporting external energy efficiency programs to help other energy consumers save energy, such as the Alliance to Save Energy's "Power is in Your Hands" residential energy efficiency campaign and the U.S. Department of Energy's "Save Energy Now" industrial energy efficiency campaign.

"Dow has long been an industry leader in energy efficiency, and this award not only recognizes our efforts and achievements but also enables us to further lead by example among our peers in industry," said Joe Almaguer, global energy efficiency leader, who accepted the award on Dow's behalf at the IETC conference today. "Collectively, all energy consumers can make a significant impact on energy consumption and energy independence."

From 1994 to 2005 Dow saved approximately $4 billion through energy efficiency efforts, helping to mitigate the impact of rising energy costs, while reducing greenhouse gas emissions. On May 3 Dow announced a new corporate goal to further reduce its worldwide energy intensity by 25% from 2005 to 2015.

"Effective energy management is critical to the global competitiveness of any energy-intensive manufacturer," said John Dearborn, global vice president for energy. "Energy efficiency is a win-win for the environment and the economy."

An independent case study of Dow's energy efficiency efforts employing Six Sigma methodology is available online (PDF).

Companies With Mature Six Sigma Deployments Apply Six Sigma to IT Processes More Often Than Less Experienced Practitioners, Survey Says

NK Khoo Managing Consultant — Mon, 29 May 2006 15:08:00 +0000

BAINBRIDGE ISLAND, WA -- (MARKET WIRE) -- 05/24/2006 -- "Whether IT processes were the target of improvement efforts seemed to depend on two factors," said Michael Marx, Research Manager for iSixSigma Magazine.: "the experience level of the company and the perceived role of IT."

According to the Information Technology and Six Sigma survey released in the May/June 2006 issue of iSixSigma Magazine (www.isixsigma-magazine.com), "Companies that had been using Six Sigma for seven or more years were nearly four times more likely to focus projects on improving IT processes than those that had been using Six Sigma for less than three years," said Marx. "They were also much more likely to integrate IT methods with Six Sigma and to align IT projects with business priorities."

Similarly, companies that viewed IT as a key strategic component accounted for 86% of the respondents who "always" used Six Sigma to improve IT processes. Conversely, companies that viewed IT as merely another "staff role" accounted for 72% of the respondents who "never" used Six Sigma to improve IT processes.

"Only 17 percent of the more than 950 respondents said that their companies always or usually use Six Sigma to improve IT processes," said Marx, "And when other projects led to IT-based solutions, they were rarely implemented -- either because of the perceived cost or a lack of priority placed on IT."

"Overall, it was surprising to us that for the majority of respondents, IT was the main focus of a project less than 10% of the time," said Marx. "Another surprising result was that companies that outsource more of their IT functions were more likely to use Six Sigma on IT process. We speculate that they may view Six Sigma as a valuable tool in the planning and prework required to properly outsource IT."

Six Sigma spells success for BPOs

NK Khoo Managing Consultant — Mon, 29 May 2006 15:00:00 +0000

PRADEEP KAPUR

[THURSDAY, MAY 25, 2006 12:00:00 AM]

These are exciting times for India, given its positioning as the most favored destination for outsourcing in the world. The nation has made significant progress and established itself as a preferred outsourcing destination owing to factors like availability of vast talent pool, good telecom infrastructure, conducive government policies, stable economic environment and, above all, cost arbitrage benefits.

While there are reasons to rejoice, there are other countries like Australia, China, the Philippines and Ireland that are fast emerging as close competitors in the ITES/BPO sector. To sustain its competitive advantage, particularly in the IT/ITES sector, India needs to move up the value chain by offering a twin advantage of superior quality along with cost arbitrage.

Some of the most successful companies today have adopted Six Sigma as a mean to achieve the end of providing a value proposition to clients that encompasses superior quality and competitive pricing.

Six Sigma is a business strategy that seeks to identify and eliminate causes of errors or defects in business processes by focusing on outputs that are critical to customers. It is a measure of quality that strives for near elimination of defects using the application of statistical methods.

A defect is defined as anything which could lead to customer dissatisfaction. The fundamental objective of the Six Sigma methodology is the implementation of a measurement-based strategy that focuses on process improvement and variation reduction.

It has two major thrusts — one that is directed toward significant innovation or improvement of an existing product, process or service that uses an approach called DMAIC (define-measure-analyse-improve-control) and a second one that centres on product, system or service design called DFSS (design for Six Sigma).

Six Sigma integrates various strategies and tools from statistics, quality, business and engineering with the adoption of new ones likely as its use expands to more business sectors and areas of application.

Over the years, Six Sigma has added multiple billions of dollars to the financial bottom line of numerous organisations and is used in many arenas, including financial, healthcare, military and general manufacturing.

Among the leading companies that emphasise Six Sigma are GE, Motorola, American Express, 3M, Raytheon, Sun Microsystems, DuPont, Bank of America, Rolls Royce and Boeing.

At American Express, Six Sigma has proven to be a key enabler in our reengineering and quality efforts. Application of the Six Sigma methodology has given us the competitive advantage, enabling us to focus on continual improvement. To drive results through Six Sigma by widening its reach and application, we have fostered a culture of employee participation in Six Sigma initiatives at an organisational level.

The Six Sigma team comprising of Black Belts supports different business verticals in identifying, reengineering and process improvement opportunities and then works closely with business leaders and employee groups to ensure that these opportunities are addressed by well-structured Six Sigma projects. A significant percentage of our employees are formally trained in Six Sigma and are engaged in Six Sigma projects that are currently underway in the organisation.

We have an extraordinary pool of talent at American Express and we believe that keeping them intellectually engaged is one of the key responsibilities of senior management. For us, Six Sigma is not just a tool for driving excellence but it’s a great platform to unleash the collective intellect of our very talented workforce to drive innovation.

We are now embarking on a new phase of Six Sigma called Business Performance Excellence (BPE). Through the use of integrated scorecards, BPE will increase our ability to measure, monitor and manage the quality of products and services we provide to our customers, whether we connect with those customers directly or indirectly through our business processes.

Additionally, this enables us to clearly identify areas that impact the customer experience and then target improvement efforts on those critical to quality areas. By taking this customer-centric approach, American Express has been able to differentiate itself from the competition as we fully integrate quality into our core offering.

For companies which are contemplating to embark on the Six Sigma journey, it just takes three basic steps to maintain and improve their competitive position:

• Define competitiveness for the business:
• What are your customer expectations?
• How are your competitors performing?
• Determine the gaps between your competitors’ performance and your own.
• Close the gaps.

Companies which have not yet embraced Six Sigma may argue that approaches like TQM, business process reengineering (BPR), benchmarking and business excellence are the key to unlock the potential in organisations. With the current interest in Six Sigma, there may be skepticism that it is just one more buzzword in the long line of quality offers.

However, while Six Sigma’s pedigree can indeed be traced to TQM, it is differentiated from these earlier approaches by the bottom-line focus and intensity of its application. Experience has shown that Six Sigma works and if applied appropriately, it can be the key to enhance customer experience by adding to the bottom line. This can provide you a winning edge.

In the Lead: Executives must stop jumping fad to fad

NK Khoo Managing Consultant — Sun, 21 May 2006 11:34:00 +0000

Monday, May 15, 2006

By Carol Hymowitz, The Wall Street Journal

Consultants make their living trying to convince executives to buy the latest idea in management. These days, there aren't any hot, new trends, just a lot of repackaged ones from the past.

Executives have been treated to an overdose of management guides that mostly haven't delivered what they promised. Many bosses have adopted them all, regardless of their company's business model, balance sheet, competition, employee bench strength or any other unique qualities. They have become copycat managers, trying to find a one-stop, fix-it-all answer to their various problems.

Some ideas, of course, will never go out of style. W. Edward Deming's advice to companies to "drive out fear" so managers can act on what they know, admit what they don't know and change decisions that aren't working, is just one example of an idea as relevant today as when first proposed nearly a quarter of a century ago.

But even in this case, a 1990s reinvention of Mr. Deming's total-quality movement in manufacturing, called Six Sigma, improved efficiency at scores of plants, but couldn't help companies meet another great need -- more innovation.

Executives need to be more skeptical about anything billed as the next big idea. The smartest will learn how to cherry pick what is right for their businesses, rather than follow what they heard about from their golf buddies the previous weekend.

Stanford University business professor Jeffrey Pfeffer, co-author of "Hard Facts, Dangerous Half-Truths & Total Nonsense," urges executives to strive to be more independent. He advises them to "systematically examine evidence about what's gone right and what's gone wrong," instead of following what everyone else is doing.

George Hansen, CEO of Corporate Lodging Consultants, a huge manager of hotel-room purchases, says that in prior jobs at multinational companies he had to adapt to whatever the flavor of the month in management happened to be. "I lived through every flavor," says Mr. Hansen, adding that his employers often embraced a fad "just because other companies were doing it."

He heard a lot about "changing the corporate culture," although no one could define what that meant. He also was told to "get closer to the customer," which translated into streamlining and cutting jobs.

"No one ever asked, 'What are we giving up and what will we gain by doing this?' " he complains. "At the end of the day, if you weren't in the in-crowd or were gray-haired, you went; and then when we started growing, we didn't have enough people who really knew the business."

Consultants hired by these former employers conducted employee surveys that always produced the same results. Employees would say they wanted more communication. In response, his bosses would say, "Let's put out a newsletter" -- missing the message that they wanted to be heard, he says.

Mr. Hanson himself admits: "I've fallen victim to the latest management theory as many times as the next guy." But he has learned since there is "no perfect structure and you have to find what fits you."

At privately owned CLC in Wichita, where he has worked for the past two years, he has tried to make employees' jobs interesting and challenging, so they know they're valued, he says.

Last September, the Red Cross called Mr. Hanson to ask for help relocating thousands of victims of Hurricane Katrina. He declined initially, saying he didn't have the resources, then rallied his 125 employees. In 48 hours over Labor Day weekend, they sent faxes to every hotel in their system asking them to accept victims and bill the rooms at discounted rates through CLC so victims wouldn't have to pay immediately. They found hotel space for 250,000 people.

"None of those management books with cute phrases could have helped us do this," says Mr. Hansen. "It was a wonderful lesson in how people who know they are doing something important will put their heads together, find solutions and do more than you ever imagined."

An operations manager at a Silicon Valley technology company complains that consultants hired by his bosses produce stunning charts but bungle answers to his production problems. "They tell my superiors we should produce parts only on demand -- 1,000 on Monday and 5,000 on Thursday -- capacity our suppliers can't handle," he says. Instead of offering complicated analyses, he wishes they'd spend time on the factory floor "and understand how equipment really works."

Stanford's Mr. Pfeffer hopes executives realize that the basic rules of management are as straightforward as the basic rules of dieting -- and haven't changed over time. "Whether you are on South Beach or North Beach, you have to use up more calories than you take in to lose weight," he says. In business, "if you take care of employees, they do good work and take care of customers, and then you're successful."

Performance Measurement: GE Asks The Ultimate Question

NK Khoo Managing Consultant — Sun, 21 May 2006 11:28:00 +0000

Would the customer recommend GE to friends?

Thursday, June 01, 2006
By John Teresko

Want to maximize business growth? Factor in a customer-focused continuous-improvement process. A key challenge for management is to monitor customer relationships as rigorously as profits are scrutinized, says Richard Wargo, vice president of marketing and strategic initiatives for a unit of GE Capital Solutions, Danbury, Conn. "Those relationships build the future."

The GE business unit, which focuses on equipment-based financing and leasing, provides an example of how the corporation engages the customer experience in a continuous-improvement process.

The survey system GE selected emphasizes one initial question: "Would you recommend us to a friend?" That rapidly and easily identifies problem areas for lean/Six Sigma engagement, adds Wargo.

"The process gives us a market-focused view of our performance relative to the competitive alternatives the customer could choose. Customer-identified problems become easy targets for corrective action. The result: greater potential for growth and future success," adds Wargo.

GE's surveys ask that customer responses to the question be scaled from zero to 10 with 10 being the highest ranking a customer can bestow. Customers giving GE a rating of nine or 10 are categorized as "promoters," seven to eight as "passives" and zero to six as "detractors."

Survey responses are tallied to produce a Net Promoter Score (NPS) as set forth in the system devised by consultant Fred Reichheld, Bain & Co., New York. (See his new book, "The Ultimate Question, Driving Good Profits and True Growth," 211 pages, Harvard Business School Publishing Corp.) Calculating the NPS requires subtracting the percentage of detractors from the percentage of promoters.

GE's first implementation of Reichheld's NPS system started in 2004 at the company's health-care equipment operations. Then, in 2005 NPS caught the attention of Chairman and CEO Jeffrey Immelt at the company's annual management meeting in Boca Raton, Fla. His response, as cited in Reichheld's book: "This is the best customer-relationship metric I've seen. I can't understand why any of you wouldn't want to try it." He had just heard the NPS presentation that Joe Hogan, GE Healthcare's CEO, made to the 650 GE executives attending the Boca event.

Immelt demonstrated his NPS commitment to continuous improvement and growth by mandating that up to 20% of the annual bonus of senior executives would have an NPS connection.

Reichheld emphasizes the implementation advantages. "Unlike conventional customer-satisfaction studies, NPS is a simple process that links up with what drives growth." He says it is almost impossible to profitably grow without scoring more promoters and fewer detractors among customers. "All we're saying is that we need to be systematic and rigorous in tracking how many customers we're turning into promoters and how many we're turning into detractors."

Like the concepts of lean manufacturing and Six Sigma, NPS has to start at the top of an organization and go all the way through and involve front-line employees, adds Reichheld.

How is the growth- and metric-conscious GE doing? First-quarter 2006 revenue was $37.8 billion, up 10% from a year earlier, with organic revenue growth of 9%.

In God We Trust, Everyone Else Bring Data

NK Khoo Managing Consultant — Fri, 12 May 2006 21:28:00 +0000

May 08, 2006 by Lara Jones

Listen to MP3 audio >>>

Six Sigma Business Training Nets Results for Military

(KCPW News) Earlier today on KCPW's weekly business show, The Bottomline focused on Six Sigma Training and how it can save money for both public and private enterprises -- even the military.

Moderated by KCPW's Lara Jones, today's panel included Professor Don Wardell, Management Department Chair at the David Eccles School of Business; Kaelyn Fife, Executive Education and Custom Programs manager at the biz school; and three officers from a unique Six Sigma client -- the Army Reserve's 96th Regional Readiness Command, including Colonels Adele Connell, Dave Schroeder, and Mike Petrash. First, a definition of Six Sigma training with Professor Wardell.

Data slipups

NK Khoo Managing Consultant — Fri, 12 May 2006 20:40:00 +0000

Rick Whiting , 10-May-2006

Inaccurate business data lead to botched marketing campaigns, failed CRM projects--and angry customers. Fortunately, there are fixes in the offing.

A home valued at US$121,900 somehow wound up recorded in Porter County's computer system as being worth a whopping US$400 million. Naturally, the figure ended up on documents used to calculate tax rates. By the time the blunder was uncovered in February, the damage was done.

It's a nightmare scenario--and one like it could be yours. Bad data remains a major cause of botched marketing campaigns, failed CRM and data warehouse projects, angry customers, and lunkhead decisions. Despite all we know about the importance of data scrubbing and quality management, many companies are still using data that's redundant, incomplete, conflicting, outdated, and just plain wrong.

Bad data isn't a new problem, but urgency in dealing with it is at an all-time high. Customers are voicing anger at the mistargeted marketing pitches and poor service that result from off-the-mark data, and they're taking their business elsewhere. Companies are investing billions of dollars in CRM applications and data integration projects to gain a better view of their customers--only to discover that conflicting data makes them blind. "Our marketing effectiveness leads to our sales effectiveness, which leads to our service effectiveness. Data quality is key to the success of that," says Chuck Scoggins, VP of customer solutions at Hilton Hotels. "If you don't have quality data, that whole chain breaks down."

Managers and employees increasingly base decisions on insights gleaned from performance management applications and dashboards. But business intelligence tools are only as good as the data that goes into them; faulty data leads to ill-informed decisions. The ramifications range from ticked-off customers to misled investors to testy regulators. Executives can face jail time under the Sarbanes-Oxley Act if they don't have financial data in order. Bad data can even increase the cost and time involved in completing mergers by making it more difficult to integrate operations and combine customer lists.

The problem is getting harder to manage as the amount of data generated and maintained by many businesses doubles every 12 to 18 months. And as more businesses share information with outside partners and customers, more bad data is being exposed to others. Lax quality is familiar to anyone with a mail box: Consumers get credit card pitches from issuers with which they already have cards, mailings from charities in triplicate with slightly different name spellings, and warranty extension offers from auto dealers for cars they no longer own.

Occasional inconvenience for consumers aside, low-quality data is foremost a problem for the company holding it. Bad data can be an embarrassment--companies are loath to talk openly about internal data disasters. Businesses may be legally bound to share information about security breaches that result in consumers' personal information being compromised, but that's not the case with bad data. As a result, tales of mishaps are hard to come by, even as the problem persists.

The biggest obstacle to fixing the mess is that business managers view data quality as a technical problem, when business processes are really what's broken. IT has little control over the sales rep who gets a customer address wrong on an order or the manufacturing manager who enters an incorrect part number in an inventory database. A Gartner survey of 600 executives in November found that 49% think the IT department is responsible for their organizations' data quality; much smaller numbers say responsibility lies with top execs, data quality teams, line-of-business managers, and others.

"Business has to accept the fact that it has primary responsibility for data quality. Data is a business asset," says Nigel Turner, who as project lead manager for data quality programs at BT Group (formerly British Telecom) in the late '90s helped get that company's data cleanup efforts off the ground.

Gartner estimates that more than 25% of critical data within large businesses is somehow inaccurate or incomplete. And that imprecise data is wreaking havoc. Fifty-three percent of the 750 IT professionals and business executives surveyed by the Data Warehousing Institute late last year said their companies had experienced problems and suffered losses or increased costs because of poor-quality data, up from 44% in a similar survey in 2001.

While IT managers may not own the processes that spew bad data, they can make the business case to change those processes to improve data quality. Moreover, they can provide the technology to support those improved processes and, since no process is perfect, operate the tools needed to automate the downstream steps of identifying and correcting bad data.

Data quality champions

Though BT began adopting data quality practices 20 years ago, its real effort began in 1997 as it struggled with customer billing errors and poor product inventory information. The company's efforts to improve interactions with suppliers and customers using EDI and self-service applications were also being hindered by bad data.

Turner, then in BT's corporate strategy division, recognized that the telecommunications company was spending a great deal of effort correcting data. Rather than create a top-down, companywide program, Turner targeted line-of-business operations and identified a data quality "champion" in each to lead an information management forum. The groups targeted specific projects with demonstrable returns on investment, such as improving names and addresses in marketing data to reduce the number of letters sent to the wrong people and improving private-line inventory record keeping to increase the number of disconnected circuits returned to stock for reuse.

"We had to prove to BT that these things were worth doing," Turner says. "Data quality isn't very sexy." The original budget for the data quality efforts was a measly US$30,000. As the project expanded, Turner's group developed a data quality methodology incorporating best practices gleaned from inside the company and from outside experts, and centralized data quality management. Recognizing that errors will creep into databases despite its best efforts, BT uses data profiling and cleansing tools from Trillium to identify and remove errant data.

The efforts have paid off: BT has realized as much as US$800 million in aggregate savings by improving inventory management, boosting productivity through improved automated interactions with suppliers and customers, and reducing revenue leakage through more accurate billing. BT has parlayed its data quality know-how into a consulting business headed by Turner.

Still, data quality problems are legion and seem to exist to some degree at all manner of companies that manage large quantities of information. Darren Cunningham, product marketing director at Business Objects, shares the story of a consumer technology manufacturer that routinely sent half of its catalogs to the wrong addresses until a manager pointed out the high number of catalog returns and customer complaints. Taking steps to correct the problem saved the company US$12 million a year, Cunningham says.

Data quality initiatives can be part of broader data governance programs. Data governance, a relatively new concept, applies best practices to how information is managed, secured, and used across an organization. It requires establishing a formal set of business processes and policies to ensure that data is handled in a prescribed fashion. Data governance includes standard definitions for data elements to be used throughout a company--just what a "lost customer" is, for example--and metrics for measuring data quality, says Terry Haas, director of the enterprise data management practice at PricewaterhouseCoopers. Data governance also defines the data management roles and responsibilities of managers and employees and limits the ability to change data to designated "data stewards."

There's no standard way of measuring data quality. Bank of America and Cintas use Six Sigma as a yardstick. (Six Sigma is a methodology for measuring and removing defects from everything from data to manufactured products.) Hilton Hotels uses the probability of correctness indicator, or PCI, which assigns data a rank of one through nine based on its trustworthiness. Hilton rates 95% of its customer data at the high end, in the one through four categories. But, reflecting an emphasis on measuring data quality projects by their ROI, BT's Turner says the one metric that matters is money.

Duplication dangers

Bank of America has long collected account data in a centralized data warehouse for a variety of marketing and cross-selling applications. The bank's data quality efforts began in earnest in 2002 to comply with the anti-money-laundering provisions in the USA Patriot Act. Data on new accounts is collected in the multiterabyte warehouse from several lines of business, so Bank of America established common practices for capturing, integrating, and managing it, says Donald Carlson, who heads up the bank's anti-money-laundering program and has become its de facto data quality manager.

The bank designated data stewards in business units and the IT department, and some with companywide responsibility. Data quality managers meet monthly to resolve problems. Bank of America uses commercial and custom-built data profiling and matching tools to examine and, when necessary, correct data sent to the warehouse. Today, in addition to regulatory compliance, the bank's data quality efforts are driven by its risk management practices, the need to manage customer data from multiple channels, and cross-selling efforts.

Integrating data from multiple business operations has also been a challenge at Cintas, which created new divisions as it expanded beyond its core employee uniform business into areas such as providing businesses with cleaning supplies and document storage and shredding services. That has resulted in customer data silos throughout the company, database marketing manager Becki Wessel says.

To help with cross-selling, data from all divisions is collected in a data warehouse, but the information is sometimes duplicated with slight variations. Some customers are listed in multiple databases but with enough variation in name or address to be identified as different people. Those discrepancies have sometimes led to existing customers being identified as new prospects--an embarrassing situation when a sales rep shows up. An added danger is that sales reps could begin to distrust leads provided by marketing, Wessel says. Or two customers could be close enough in spelling to be tagged as the same customer, costing the company a sales opportunity.

As part of a project to overhaul its data warehouse, Cintas has been installing quality management software from Dataflux that will identify duplicate customer records and standardize customer data collected monthly from each division's database. The system is expected to be fully functional by next month, but a pilot project already has improved the company's ability to match customer names.

While Cintas is integrating customer data on a monthly batch basis, other companies do so in real or near-real time, which makes data quality even more difficult. More companies also are adding third-party data that may be erroneous or inconsistent. Bank of America's Carlson notes that the globalization of business--and data sources--further complicates the problem.

Blind data matching

In the hotel business, the data challenge is exacerbated by the fact that customers don't need to use their real names to make a reservation. The Hilton hotel chain's 4-terabyte data warehouse stores the names of 22 million customers who have stayed at a Hilton multiple times over two years and 60 million identified as infrequent guests. Data about members of the Hilton Honors frequent guest program (about 20% of all Hilton guests) is included in the 22 million, and their data is presumed to be accurate, Scoggins says.

But it's difficult to sort out which category to put all the other guests in when they make a reservation. Hilton uses a combination of custom-built tools and software from Group 1 (owned by Pitney Bowes) to match a guest's name and address with information already in the database. That includes a Soundex algorithm that matches names based on phonetic pronunciation rather than spelling. Only 40% of all customers are matched with an existing profile, and new profiles are created for the rest, Scoggins says.

Master data management projects tied to CRM, ERP, and supply chain management systems are some of the biggest drivers of data quality programs, AMR Research analyst Bill Swanton says. Master data management involves using a centrally managed database of customer names, product numbers, and other critical data. "Typically, we see people getting the data quality religion because they implement a big, expensive IT project and it doesn't work," Swanton says.

At BMW Group Canada, customer data is generated by retail and call center operations, company-sponsored events, and direct mail and Internet marketing campaigns. Since June, the company has been centralizing all that customer data in a Siebel CRM system and using data matching software from Trillium to eliminate duplicate customer records, standardize names and addresses, and fill out incomplete records. Before the system was installed, dealers, BMW financial services, and other operations had their own customer databases, and customers complained that they had no central point of contact, marketing services manager Kelly Lam says. The company is also saving on mailing costs by complying with address format standards set by Canada Post, he says.

But the ultimate goal of data quality improvement is to catch errors at the point of entry or, even better, prevent errors from occurring at all, says Philip Russom, senior manager of research and services at the Data Warehousing Institute.

Some companies already are thinking along those lines. Cintas is considering using the data matching capabilities in the Dataflux system to correct data on the fly as divisional employees enter it into the system, rather than when it enters the data warehouse. Accurate data starts at the beginning--and the work required to keep it clean never ends. Says Wessel: "As long as you're fixing things on the back end, you're not correcting the problem." -- InformationWeek

Six Sigma tech boosts HSBC custodian ops

NK Khoo Managing Consultant — Fri, 12 May 2006 19:58:00 +0000

By DALJIT DHESI

KUALA LUMPUR: HSBC Bank Malaysia Bhd, which attributed the success of its custodian and clearing services partly to the Six Sigma methodology, aims to further intensify its usage for its custodian and clearing operations this year.

HSBC, which has been registering a 20% annual growth in custody and clearing business, was recently voted the number one bank in Malaysia for this sector in 2005 in a survey carried out by Global Custodian magazine under the emerging markets category.

Senior vice-president (custody and clearing) Lim Guat Cheng said unlike in 2005, this year the bank would be adopting the methodology more specifically for all its custody and clearing operations.

“We have completed the adoption of the Six Sigma methodology in the settlement side and are now looking at employing it in the corporate action area to boost our overall efficiency. There are four main areas under the custodian and clearing division – settlement, corporate accounts, administration and reporting.

“By employing the Six Sigma practice, we are able to identify gaps and come up with solutions to improve business processes and meeting customer needs and requirements,'' she said in an interview.

Lim Guat Cheng

Comprehensive training and staff development is another factor which has helped the bank to be the number one provider for such services.

Lim said all the staff under this division had to undergo soft training skills annually in writing, handling telephone calls, time management and other motivational talks as they had to deal with high net worth foreign investors every day.

Most of HSBC Bank's clients in this business are foreign investors in which the bank acts as custodian for their assets invested in Malaysia.

According to Lim, with a staff strength of 65, it is sufficient to handle the job as the division is currently intensifying its automation systems and processes to facilitate customers' needs and requirements.

Apart from the above, HSBC had been providing such services for over 30 years, relatively longer than any other banks in the country, she said. This has given HSBC the added advantage and significant expertise in handling the local market.

In addition to Kuala Lumpur, HSBC group's extensive network provides customer access to 34 markets in the Asia Pacific, Middle East, Latin America and southern Europe regions.

Lonmin boosts dividend first time in four years

NK Khoo Managing Consultant — Mon, 08 May 2006 23:57:00 +0000

Charlotte Mathews
Resources Editor

PLATINUM producer Lonmin hiked its dividend yesterday for the first time in four years, reflecting a confident outlook for platinum and the continued growth of the business, said CE Brad Mills.

The group, which operates mines at Marikana and Limpopo, declared an interim dividend of $0,45 a share for the six months to March, up from $0,30 a share in the same period last year, as underlying earnings more than doubled to $1,10 a share from $0,438 previously.

After taking into account movements in fair value of the embedded derivative associated with Lonmin’s convertible bond, which is related to the rise in its share price, the group reported a loss of $0,471 a share from a profit of $0,515 previously.

Numis Securities analyst John Meyer said Lonmin’s underlying earnings were almost 4% better than forecasts, and the group had delivered an impressive cost performance, with Marikana showing an increase in unit costs of only 0,5% .

Globally, mining companies are experiencing pressure on input costs such as fuel, steel, cement and wages.

The group had realised $32m in savings at the level of net earnings before interest and tax (ebit) from its Six Sigma continuous improvement programme, as well as $2,3m in savings from a shared business services programme.

Production from Marikana reached a record 5,7-million tons milled from underground and 1,3-million tons milled from opencast operations.

Management is continuing to introduce mechanised mining at Marikana with the aim of 8% of production from mechanised stopes by the end of this year and 50% by end 2010.

The group’s Limpopo operations, where it consolidated control through buying out the remaining 8,5% of minorities in the past six months, produced 487000 tons milled from underground operations and contributed $8m to ebit, which was “substantially” ahead of budget, Mills said.

The ramp-up of production had progressed well and costs were coming down.

Last month the company reported a leak at its number one furnace had caused an 11-day shutdown and this would bring down the forecast sales of platinum to between 970000oz and 980000oz from the original forecast of 1-million ounces.

But forecast mine production of about one-million ounces of platinum in concentrate in the current financial year remained.

Lonmin is investigating a number of possible expansion projects, including an open-cast operation at Limpopo to add 20000 ounces of platinum a year for two years, a second phase of development at Limpopo which could add about 125000oz of platinum a year, and development of the Pandora property using mechanised mining, which could add an attributable 85000oz of platinum to Lonmin.

The group is also looking to expand its metallurgical capacity, which would require adding a new furnace and upgrading the precious metals refinery at a cost of about $300m-$350m.

Introduction to Six Sigma for Marketing Processes

NK Khoo Managing Consultant — Mon, 08 May 2006 23:22:00 +0000

Six Sigma for Marketing and Six Sigma for Sales are relatively new approaches to enable and sustain growth. They are part of the bright future offered by adapting Six Sigma to the growth arena. The linkage of Six Sigma for Marketing and Six Sigma for Sales tasks and tools to strategic, tactical, and operational processes is where the Six Sigma discipline adds measurable value to marketing and sales team performance. This chapter provides an introduction to the concept of Six Sigma for Marketing.

Introduction to Six Sigma for Marketing Processes

By Clyde M. Creveling, Lynne Hambleton, Burke McCarthy.
Sample Chapter is provided courtesy of Prentice Hall PTR.
Date: May 4, 2006.

Growth and Innovation
Imagine the possibilities if you possessed a crystal ball that let you predict the future. You would know what will work and what won't work to create and sustain growth. You would know when to correct for competitive and environmental changes and how to prevent going off-course. Is this a fantasy? Can a business predict (with some certainty) what will drive success and how to stay on the right track? We believe the answer is yes. The appropriate data can inform executives, with high probability, whether the critical elements of the business are performing as planned to achieve desired results.

Performance against plan is how a business typically defines success. Businesses gauge success by a multitude of metrics—revenue, income, profit, customer satisfaction, market share, return on equity, return on assets, return on investments, and so on. Bottom-line, planned success means reaching and sustaining goals over time—usually growth goals. The challenge lies in determining the vital few results to focus on and the critical metrics that best monitor performance. The Fortune 500 list serves as another metric of success. Of the top 100 companies, 70 have been in the top 100 for five or more years. Interestingly, 63% of those 70 companies acknowledge implementing Six Sigma to some degree. Through further analysis, we have found that these same 44 Six Sigma users also reported on average 49% higher profits (compounded annually) and 2% higher Compounded Annual Growth Revenue (CAGR) than their peers. Notice how the profits outpaced the revenue growth for this group of companies. More than likely, they employ the "traditional" Six Sigma cost-cutting approach. Imagine the benefit these firms will enjoy when they also begin to apply Six Sigma to the top line to drive revenue. If they deploy Six Sigma into marketing and sales with as much discipline and rigor as they did to eliminate waste in manufacturing and engineering, these firms' CAGR will outrun their competitors as much as their profits have, and they will easily secure a prominent spot on the Top 100 list for another five or more years.

Benchmarking tells us that successful companies, which effectively implement Six Sigma tools, methods, and best practices find the following benefits:

Systematic innovation: Generate and define more ideas linked with market opportunities in a structured way.

Manage risk better: Identify critical issues early in the commercialization process such that plans can be developed to mitigate or eliminate risk going forward.

Higher return yield from a project portfolio: Avoid overloading resources with too many low-risk, small-gain projects through a discriminating selection process. Select fewer projects—the "best fit" projects, not necessarily the easiest projects.

Business leaders often hold marketing and sales accountable for driving revenue growth—the panacea for most business ills. They want these teams to improve their accuracy rate of committing to, and achieving, their goals. Marketing executives seek new ideas to bolster their success rate. Applying Six Sigma to marketing may be a new approach, but it comes with an "insurance policy." Six Sigma has a proven track record in other parts of the business. Six Sigma concepts can provide additive elements to increase the competitive advantage marketing needs to act proactively, sustain its positive momentum, and keep pace with the ever-changing landscape.

To tailor Six Sigma to marketing, you start with an overview of how it works. We find that marketing professionals rarely view their own work as process-oriented; it often is depicted as project- or activity-based. However, the American Marketing Association (AMA) defines "marketing" as "a set of processes for creating, communicating, and delivering value to customers and . . . managing customer relationships in ways that benefit the organization and . . . stakeholders." The American Heritage Dictionary describes a "process" as a "series of actions, changes, or functions bringing about a result" and a "function" as "something closely related to another thing and dependent on it for its existence, value, or significance." Others define "marketing" as the process to identify, anticipate, and then meet customers' needs and requirements. This definition seems narrow. In a special issue of Journal of Marketing (1999, Volume 63, pp. 180–197), Christine Moorman and Roland Rust propose that

the marketing function should play a key role in managing several important connections between the customer and critical firm elements, including connecting the customer to (1) the product, (2) service delivery, and (3) financial accountability. . . . Marketing's value . . . is found to be a function of the degree to which it develops knowledge and skills in connecting the customer to the product and to financial accountability.

Hence, to fully capture marketing's value, the customization of Six Sigma should span the scope of connecting the customer to the product and to financial accountability.

Moorman and Rust's research suggests that the value of the marketing function is due to how well-developed the methodologies are for facilitating the customer-product connection. Marketing's customer-financial accountability linkage often is not well understood, but it needs to account for profitability considerations in attracting and retaining customers. It is not about cost; it is about profitable growth. Ideally, marketing should effectively and efficiently create and sustain growth for the firm. How is that best done? A challenge is to determine which marketing methodology best facilitates the customer-product-financial linkages. The marketing methodology should nurture and channel the firm's important creativity and growth capabilities.

The Six Sigma discipline gives business leaders the opportunity to drive more fact-based decisions into managing the business. Six Sigma has been successfully applied to the technical aspects of a business (such as engineering and manufacturing). A new effort is afoot to bring Six Sigma into the "softer" side of business—marketing. By adding more "science" to the "art" of marketing, the Six Sigma approach can be the next best thing to a crystal ball.

A decision-making process that lacks the appropriate facts causes leaders to fill the void with intuition. If facts are absent, statistically grounded probabilities can strengthen decision-making. Marketing executives should shed their use of intuition (or "gut feeling") to solve business issues and/or drive growth. Columnist and author Marilyn Savant said, "Not knowing the difference between opinion and fact makes it difficult to make decisions. . . ." Intuition sneaks into every business at some point. The objective is to recognize it when it appears and to deal with it directly by using facts to support or deny the "hypothesis." Bernard Baruch, an advisor to six U.S. presidents, said, "Every man has the right to be wrong in his opinions. But no man has a right to be wrong about his facts. . . ."

The Six Sigma concept has evolved over the past several decades to represent a set of fundamental business concepts that puts customers first and uses fact-based decision-making to drive improvements. It was first used in the U.S. at Motorola to cut costs by reducing variation in manufacturing. This book represents the next evolution of Six Sigma—a marketing application. We believe a unique view of Six Sigma's techniques and tools can be applied to drive income growth. It is our experience that companies are only beginning to implement Six Sigma to drive sales and marketing; however, the IDEA is increasingly discussed. In the fall of 2005, the Worldwide Conventions and Business Forums (WCBF) held its second annual conference on Six Sigma in sales and marketing. This is a cutting-edge application of Six Sigma.

This book focuses on the new frontier of applying the Six Sigma discipline to an integrated, enterprise-wide strategy to create measurable capabilities in sustaining top-line growth. This book can be read on two different levels. First, it introduces marketing managers and executives to Six Sigma (at a high level) and suggests a unique approach to applying its concepts to marketing. Second, for those familiar with Six Sigma, this book suggests a unique, flexible combination of tools and techniques tailored for marketing. Regardless of which audience you may find yourself in, we trust that this book contains new thinking and practical recommendations that will yield success.

Six Sigma has been successfully applied to engineering and manufacturing. Adding more "science" to the "art" of marketing offers a number of benefits, including project selections aligned with attractive market opportunities, a faster and more accurate product commercialization process, and better cross-functional communication. The Six Sigma approach of using proven tools, methods, and best practices across the entire marketing process can be the next best thing to a crystal ball because, with time and experience, it can deliver more predictable outcomes.

What Is Six Sigma?
The term "Six Sigma" has several meanings. At the most encompassing level, a corporation can define it as its philosophy—a way of thinking. By doing so, a company's management structure, employee roles, and operations are defined, in part, by this fact-based discipline. Or it can be defined as a method and tool set—for example, using the Define-Measure-Analyze-Improve-Control (DMAIC) technique to make improvements and solve problems within an existing process. Or, at the simplest level, it can be defined as a specific statistical quantity, describing the number of defects produced due to variation in a product or process. Technically, Six Sigma is described as a data-driven approach to reduce defects in a process or cut costs in a process or product, as measured by "six standard deviations" between the mean and the nearest specification limit. "Sigma" (or s) is the Greek letter used to describe variability, or standard deviation, such as defects per unit. Figure 1.1 shows a normal distribution of a population, with its mean (m) in the center and a data point on the curve indicating one standard deviation (1s) to the right of the mean.

Figure 1.1 A normal distribution.

How well a desired outcome (or target) has been reached can be described by its mathematical average; however, this may be misleading. The average of a data set masks the variation from one data point to the next. The standard deviation describes how much variation actually exists within a data set. An average is mathematically defined as the sum of all the data points divided by the number of data points. This is also called an arithmetic mean. The standard deviation is calculated as the square root of the variance from the mean.

Why is the number six frequently coupled with the word "sigma"? If a process is described as within "six sigma," the term quantitatively means that the process produces fewer than 3.4 defects per million units (or opportunities). That represents an error rate of 0.0003%; conversely, that is a defect-free rate of 99.9997%. That's pretty good, right? Professional marketers can relate to this because they see errors and can exploit the opportunity to reduce variation and its effects on results.

What level of variance (or error rate) in a process should you accept? If the resulting process data is within three standard deviations (3s) from the mean, is that good or bad? The answer depends on your business. Let's say you are in the shipping business, and you experience only a 1% error rate for every million deliveries. Is that good? That translates into a 99% error-free business (or a four-sigma level [4s]), or 6,210 defects per million. Is that good? In business terms, that means 20,000 lost pieces of mail per hour. That could cause some serious customer satisfaction issues. Within other industries, a "four-sigma" performance could mean 6,800 problems with airplane takeoffs per month, or 4,300 problems in common surgical procedures per week, or no electricity for almost 7 hours per month. Remember, the sigma measure compares your performance to customer requirements (defined as a target), and the requirement varies with the type of industry or business.

That is a brief technical description of Six Sigma. The concepts put forth in this book (and the literature) go beyond a mathematical discussion and extend into how companies deploy these statistical tools—as a business initiative. Successfully implementing the Six Sigma approach requires companies to consider changes in methodologies across the enterprise, introducing new linkages. Similar to the Total Quality Management (TQM) initiative, some benchmark companies create new employee roles (such as Black Belt project leaders). Some also institute a new management or organizational structure and new or revised project and operational processes to instill the concept.

Three benchmark examples of how Six Sigma permeates a corporate philosophy and becomes a business initiative can be found by studying Motorola, Allied Signal, and General Electric (GE). Motorola created Six Sigma (largely attributed to Bill Smith) as a rallying point to change the corporate culture to better compete in the Asia-Pacific telecommunications market. At that time, Motorola's main focus was on manufacturing defect reduction. Allied Signal rebuilt its business with bottom-line cost improvement using Six Sigma. Eventually Allied extended its Six Sigma implementation into its business and transactional processes for cost control. GE revolutionized how an entire enterprise disciplines itself across its operations, transactions, customer relations, and product development initiatives. GE implemented Six Sigma at the Customer for the customer and top-line growth using an approach called Design for Six Sigma, a methodology for product creation and development.

These three benchmark companies are pioneers in the traditional application of Six Sigma. They adhered to the three Six Sigma fundamentals of tool-task linkage, project structure, and, most importantly, result metrics. Before we explore the new growth-oriented Six Sigma for marketing, let's review Six Sigma's original methods (see Figure 1.2). This background information will help you understand how practitioners repair an inefficient or broken marketing process.

The Traditional Six Sigma Approach
The Six Sigma concept started out as a problem-solving process. The problems generally concerned eliminating variability, defects, and waste in a product or process, all of which undermine customer satisfaction. Six Sigma practitioners call this original method DMAIC (pronounced "duh-may-ick")—Design, Measure, Analyze, Improve, and Control. The five steps are as follows:

Define the problem.

Measure the process and gather the data that is associated with the problem.

Analyze the data to identify a cause-and-effect relationship between key variables.

Improve the process so that the problem is eliminated and the measured results meet existing customer requirements.

Control the process so that the problem does not return. If it does return, it should be controllable using a well-designed control plan.

The DMAIC process is easy to learn and apply. It provides strong benefits to those who follow its simple steps using a small, focused set of tools, methods, and best practices. The original pioneer of Six Sigma, Motorola, used the approach to eliminate variability in its manufacturing process and better meet basic market requirements. Companies that find success in using this approach train small teams to adhere to this approach without wavering in their completion of specific project objectives. These projects typically last six to nine months. Companies learn the DMAIC process and apply the tools much like a well-trained surgical team conducting an operation. They are focused, they are enabled by their project sponsors, and they deliver on the goals specified in their project charter.

The key elements in a DMAIC project are team discipline, structured use of metrics and tools, and execution of a well-designed project plan that has clear goals and objectives. When large numbers of people across a multinational company use the simple steps of DMAIC, objectives and result targets are much harder to miss. If everyone solves problems differently, nonsystematically, they become one-offs. Company-wide process improvement initiatives break down. Cost and waste reduction are usually haphazard. The corporation has difficulty integrating and leveraging the improvements across the enterprise. In this undisciplined environment, cost reduction and control are unpredictable and unsustainable.

Lean Six Sigma modifies the DMAIC approach by emphasizing speed. Lean focuses on streamlining a process by identifying and removing non-value-added steps. MIT pioneered the Lean approach in a manufacturing environment. A "leaned production" process eliminates waste. Target metrics include zero wait time, zero inventory, scheduling using customer pull (rather than push), cutting batch sizes to improve flow, line balancing, and reducing overall process time. Lean Sigma's goal is to produce quality products that meet customer requirements as efficiently and effectively as possible. This can be readily applied to the process steps to develop sales collateral or participation in a trade show.

If a process cannot be improved as it is currently designed, another well-known Six Sigma problem-solving approach can be applied. The DMADV process is used to fundamentally redesign a process. Sometimes it may also be used to design a new process or product when new requirements emerge. The five steps are as follows:

Define the problem and/or new requirements.
Measure the process and gather the data that is associated with the problem or in comparison to the new requirements.
Analyze the data to identify a cause-and-effect relationship between key variables.
Design a new process so that the problem is eliminated or new requirements are met.
Validate the new process to be capable of meeting the new process requirements.
A second redesign approach has been developed to incorporate elements from a Lean Six Sigma approach—the DMEDI process. This methodology is essentially similar to DMADV, but it uses a slightly different vocabulary and adds tools from the Lean methodology to ensure efficiency or speed. The steps are as follows:

Define the problem or new requirements.
Measure the process and gather the data that is associated with the problem or new requirements.
Explore the data to identify a cause-and-effect relationship between key variables.
Develop a new process so that the problem is eliminated and the measured results meet the new requirements.
Implement the new process under a control plan.
Whether you use DMADV or DMEDI, the goal is to design a new process to replace the incapable existing process. This is still the classic Six Sigma for problem-solving. The classic methods aim to improve processes and get them under control. They all build on similar fundamentals:

Tool-task linkage
Project structure
Result metrics
Once this is done, however, another form of a Six Sigma-enabled process is required to expand beyond problem-solving.

The new frontier for Six Sigma is in problem prevention, which should occur as part of your daily workflow. As they say, an ounce of prevention is worth a pound of cure. Six Sigma for Marketing and Six Sigma for Sales, like Design for Six Sigma and Six Sigma for Research and Technology Development, are structured tools-tasks-deliverables sets for problem prevention during the phases and gates of product portfolio definition and development, research and technology development, product commercialization, and post-launch product-line management processes.

The traditional "reactive" DMAIC and Lean methods should be used for their intended purposes—to reduce variances, cut costs, and streamline processes. We mean no disrespect when using the terms "traditional" or "old-style." We are trying to define the future of Six Sigma. By necessity, we have to draw a distinction between the original application and a new approach that transcends problem-solving, cost-cutting, and reactive methods. The emerging application of Six Sigma builds on the fundamentals but travels on a different financial journey—seeking top-line growth. Controlling costs is important, but creating sustainable growth is equally important, if not more so. When all you have is a hammer, everything looks like a nail. Use the appropriate tool for a given task. Both the traditional and new Six Sigma methods add value. Use the right tool, at the right time, to help ask and answer the right questions.

Applying Six Sigma to Marketing
Marketing professionals want to avoid suppressing creativity with tools and structure. Process-centric work may at first seem slow, routine, and burdensome. Moreover, marketing may think statistical analysis can dampen spontaneity and innovation. But our experience suggests that the opposite is true. The Six Sigma model described in this book plans for innovation and creativity to occur. If implemented correctly, a proven methodology averts rework (caused by mistakes), ensures completeness, and reinforces quality standards. A well-constructed method that requires improvement should plan for innovation and identify the appropriate participants. Moreover, Six Sigma can help tackle the new, the unique, and the difficult.

Few dispute the value of measurement. However, that which is easily measured rarely produces real or optimal value. Real value comes from measuring what others cannot or will not measure. This brings to mind a lesson from history. In 1726, Benjamin Franklin wondered if that warm swath of water he noticed crossing the North Atlantic had anything to do with the longer times it took to sail from England to the U.S. Franklin's cousin, Tim Folger, a whaler, knew that sailing around the current as if it were a mountain was much faster than sailing directly through the current to Philadelphia. In 1769, Franklin sold charts in London on "how to avoid the Gulph [sic] Stream" that cut westbound travel time up to 50%. To this day, Folger's map is surprisingly accurate. These measures gave Folger's whaling business a competitive advantage and higher revenue margins.

The benefit of integrating Six Sigma into your marketing processes includes better information (management by fact) to make better decisions. Using the more robust approach reduces the uncertainty inherent in marketing—a creative, dynamic discipline. Go-to-market processes with Six Sigma embedded in them can better sustain growth. One way to maintain growth over time is to focus on "leading" indicators of your desired goal. Leading indicators are factors that precede the occurrence of a desired result. Let's say you are concerned about dealing with a weight-induced disease such as a heart attack or diabetes. You could be reactive by regularly getting on the scale to see how much you weigh. Or you could be proactive by monitoring your caloric intake and burn rate. The latter approach of watching what you eat and how much energy you expend during exercise is harder than simply getting on the scale. The latter approach monitors "leading" indicators—critical activities that occur before weight gain. The "lagging" indicator takes a snapshot after the occurrence of an event. Lagging indicators force you into a reactive response if the results fail to meet the target. The act of losing weight may be more difficult than measuring the leading indicators of caloric intake and burn rate. The advice of "pay me now or pay me later" comes to mind.

Business lagging indicators involve measuring defects, failures, and time. Lagging indicators can include functional performance measures such as Unit Manufacturing Cost (UMC), quality measures such as Defects Per Million Opportunities (DPMO), and time-based measures of reliability such as Mean Time Between Failures (MTBF). Lagging indicators for marketing include market share and revenue—common performance metrics. A powerful leading indicator is customer satisfaction before a sales transaction (such as satisfaction with an information meeting or advertising piece). Another leading indicator may be the distribution channel's satisfaction with a product (or samples), whereby the salespeople want to use it themselves. Leading indicators help you anticipate whether you will hit the target. Since leading indicators occur before the desired result, you can be proactive in "correcting" poor performance. Armed with this knowledge, marketing can examine initiatives from a different perspective. To drive and sustain growth, performance and quality metrics need to be proactive rather than reactive. (Examples of continuous data include cycle time, profit, mass, and rank [customer satisfaction scores on a scale of 1 to 10]. Continuous variables are more informative and describe a process better than discrete or attribute data. Examples of discrete or attribute data include binary [yes/no, pass/fail] and counts [the number of defects].) Leading-indicator data, when established as a continuous variable, requires far fewer data samples to draw conclusions and make a decision as opposed to discrete-failure data.

Recall that a marketing methodology should facilitate the customer-product-financial linkages. This requirement seeks a comprehensive scope of marketing's responsibilities from offering inception, through offering development, to the customer experience. This comprehensive scope encompasses a business's strategic, tactical, and operational aspects. Marketing's role in each of these three business areas can be defined by the work it performs in each. This work can be characterized by a process unique to each. These three processes define how marketing's work links the strategic, tactical, and operational areas in a closed-loop fashion, as shown in Figure 1.3.

Figure 1.3 The strategic-tactical-operational triangle.

Let's examine the process that resides in each area. The Strategic Planning and Portfolio Renewal process defines a business's set of marketplace offerings. This strategic activity is fundamental for an enterprise, because it refreshes its offerings to sustain its existence over time. Multiple functional disciplines may be involved in this process, or the enterprise may limit this work to a small set of corporate officers, depending on the size of the enterprise and the scope of its offerings. This process generally calls for a cross-functional team composed of finance, strategic planning, and marketing, and sometimes research, engineering, sales, service, and customer support. A business with a unique strategic planning department may use it as a surrogate for the other various functional areas. If this is the case, the strategy office typically includes people with various backgrounds (research, finance, and marketing). This process can span a year and should get updated on a regular basis. Portfolio planning and management are the foundation from which to build and grow a business. Our experience tells us that successful businesses have marketing play a key role in the Strategic Planning and Portfolio Renewal process. In his book Winning at New Products, Robert G. Cooper states

There are two ways to win at new products. One is to do projects right—building in Voice of the Customer, doing the necessary up-front homework, using cross-functional teams . . . The other way is by doing the right projects—namely, astute project selection and portfolio management.

Six Sigma can help improve performance in this area.

The Product and/or Services Commercialization process defines the tactical aspects of a business. This process defines, develops, and readies a business's offering for the marketplace. The industry, market segment, and size/scale/complexity of the offering dictate the number of functional disciplines involved in this process and the amount of time it spans. The time frame ranges from several months to several years. A business usually manages this process by establishing a unique project team to develop a single product or services from the portfolio of opportunities. At a minimum, two types of disciplines are needed—technical functions to drive content and customer-facing functions. The technical experts develop the offering and may include engineering, research, and manufacturing. The customer-facing disciplines represent roles along the value chain that interface with a business's customer or client, such as marketing, sales, services, and customer support. In the Commercialization process, marketing may represent the customer-facing touch points throughout the process and may bring in the other functional areas toward the conclusion of the process in preparation for handoff to ongoing operations.

The Post-Launch Operational Management process unifies the operational aspects of a business across the value chain. This process represents long time frames (often years), depending on the life cycle of a given offering (product or service). The offering and go-to-market strategy dictate the variety of functional disciplines involved across the value chain. Again, marketing may play a representative role, integrating multiple functional areas as it manages the product line (or offering) throughout its life cycle.

Marketing professionals typically view their function as a set of activities or projects rather than a set of processes. It may seem unnatural at first to think about marketing work in terms of a process. However, process thinking provides an easily communicated road map that can describe interactivity with other processes. For example, marketing's tactical Product Commercialization process can cleanly map to the technical community's Product Design and Development process. By creating this linkage, the two functions better understand their interdependency with one another and can speak a common language as the output of one process becomes the input of the other's process. This book is a guide for leaders in the design of Six Sigma-enabled marketing processes.

The book The Innovator's Solution, by C. Christensen and M. Raynor, addresses the importance of process thinking. Similar to a business executive forecasting next quarter's performance, the authors ask the reader to predict the next two numbers in two different sequences. The first sequence of numbers is 3, 5, 7, 11, 13, 17, ___, ___. The second sequence of numbers is 75, 28, 41, 26, 38, 64, ___, ___. Do you know the answers? Without knowing the process that describes the sequence, you can only guess with little or no certainty. The answers for the first sequence are 42 and 6. This sequence was determined by tumbling balls in a drum being selected for an eight-number lottery winning. The answers for the second sequence are 2 and 122. They were determined by the sequence of state and county roads found along a scenic route in northern Michigan, heading toward Wisconsin. Christensen and Raynor point out that "results alone cannot predict future outcomes. The process itself must be understood to predict outcomes." Imagine the increased value that marketing could provide if it could improve its ability to predict the results of its work.

To recap, process thinking is used throughout this book. We explore applying Six Sigma concepts to the work of marketing. Marketing professionals' work environment on a day-to-day basis is not a DMAIC-based workflow structure. Marketing's work breaks down into the fundamental process of three key business arenas:

Strategic area: The Portfolio Renewal process.

Tactical area: The Commercialization process (commercializing a specific product and/or service).

Operational area: The Post-Launch Line Management process (managing the launched portfolio) and its go-to-market resources throughout its life cycle, across the value chain.

The natural flow of marketing work starts with strategic renewal of the offering portfolios, to the tactical work of commercializing new offerings, and finally to the operational work of managing the product and services lines in the post-launch sales, support, and service environment. Marketing professionals frequently overlook the fact that their contributions are part of a process (or a set of related processes). They view their work as part of a program or project. However, marketing work can be repeated. The time frame for repetitiveness may extend over a year or more, but nonetheless, the work is procedural in nature. (The American Society for Quality [ASQ] defines a process as "a set of interrelated work activities characterized by a set of specific inputs and value-added tasks that make up a procedure for a set of specific outputs.") Most marketers would agree that "strategic planning" and "launching a product" meet this "process" definition. The Six Sigma approach embraces a process view to communicate its structure and flow of interrelated tasks. Although it may seem unnatural to marketing professionals, the best way to describe Six Sigma for Growth is through a process lens.

The strategic and tactical areas are internally focused; hence, we refer to them as inbound marketing areas. External data is critical to successful portfolio definition and development, and product commercialization. However, the output of those processes is intended for internal use. These process outputs are not yet ready for external consumption. The outputs that are ready for prime-time market exposure are part of outbound marketing . The operational processes involving post-launch product marketing, sales, services, and support are customer-facing activities. Given the different customers of inbound and outbound marketing, the requirements for each differ. These requirements ultimately define the success (or failure) of the deliverables.

Problems can be prevented in inbound as well as outbound marketing processes. Inbound marketing focuses on strategic product portfolio definition and development, and tactical product commercialization. Inbound marketing can cause problems by underdeveloping the right data needed to renew product portfolios. The data is needed to define specific new product requirements, thereby directing commercialization activities. And inbound marketing data defines launch plans, which determine downstream operational success. You can design and launch the wrong mix of products and hence miss the growth numbers promised in the business cases that were supposed to support the company's long-term financial targets.

Outbound marketing is focused on customer-facing operations. It encompasses post-launch product line management across the value chain (sales and services, including customer support). Outbound marketing can create problems and waste by failing to develop the right data to make key decisions about managing, adapting, and discontinuing the various elements of the existing product and service lines. Outbound marketing also could fail to get the right information back upstream to the product portfolio renewal teams. They need to renew the portfolio based on real, up-to-date data and lessons learned from customer feedback and the marketing and sales experts in the field.

The importance of the comprehensive, closed-loop strategic-tactical-operational scope provided the structural underpinnings used to create the unique Six Sigma methods for marketing. Each of these arenas has a flow of repeatable work—a process context that is quite different from the steps found in the traditional Six Sigma methods. However, the fundamental Six Sigma elements from the classic approaches have been maintained: tool-task linkage, project structure, and result metrics. This new work is made up of specific tasks that are enabled by flexible, designable sets of tools, methods, and best practices. The strategic, tactical, and operational processes within an enterprise align with phases that can be designed to prevent problems—to limit the accrual of risk and enable the right kind and amount of data to help make key decisions. The traditional methods help you improve and redesign your processes and get them under control. If the objective is to renew portfolios, commercialize products, or manage product lines, a different approach is required that employs a different set of steps we call phases.

Unique Six Sigma Marketing Methods
A unique Six Sigma marketing method was created for each of the three areas: strategic, tactical, and operational. The method to guide marketing's strategic work is called IDEA. The approach for tactical work is called UAPL. The method to direct marketing's operational work is called LMAD. Each method has a chapter devoted to it, detailing its unique combination of tools-tasks-deliverables.

The strategic marketing process environment has the following four distinct phases, known as the IDEA process for portfolio renewal and refresh:

Identify markets, their segments, and the opportunities they offer.
Define portfolio requirements and product portfolio architectural alternatives.
Evaluate portfolio alternatives against competitive portfolios by offering.
Activate ranked and resourced individual commercialization projects.
The tactical marketing process environment has the following four distinct phases, defined as the UAPL process for specific product and/or service commercialization projects:

Understand the market opportunity and specific customer requirements translated into product (or service) requirements.
Analyze customer preferences against the value proposition.
Plan the linkage between the value chain process details (including marketing and sales) to successfully communicate and launch the product (or service) concept as defined in a maturing business case.
Launch: Prepare the new product (or service) under a rigorously defined launch control plan.
The operational marketing process environment has the following four distinct phases. This process is called the LMAD process for managing the portfolio of launched products and/or services across the value chain:

Launch the offering through its introductory period into the market according to the launch control plan of the prior process.
Manage the offering in the steady-state marketing and sales processes.
Adapt the marketing and sales tasks and tools as "noises" require change.
Discontinue the offering with discipline to sustain brand loyalty.
Each of these processes features distinct phases in which sets of tasks are completed. Each task can be enabled by one or more tools, methods, or best practices that give high confidence that the marketing team will develop the right data to meet the task requirements for each phase of work. A Gate Review at the end of a phase is commonly used to assess the results and define potential risks (see Figure 1.4). Marketing executives and professionals find phase-gate reviews an important part of risk management and decision-making. In the post-launch environment, gates are replaced by key milestone reviews because you are in an ongoing process arena—unlike portfolio renewal or commercialization processes, which have a strictly defined end date.

Figure 1.4 The tools-tasks-deliverables-requirements linkage.

This book describes how Six Sigma works in the context of strategic, tactical, and operational marketing processes. It focuses on integrating marketing process structure, requirements, and deliverables (phases and gates for risk management), project management (for design and control of marketing task cycle time), and balanced sets of marketing tools, methods, and best practices.

Recall that if a marketing process is broken, incapable, or out of control, you should use one of the traditional Six Sigma approaches to improve or redesign it. This book assumes that the strategic, tactical, and operational marketing processes have been designed to function properly. This book answers the question of what to do and when to do it within structured marketing processes.

Marketing processes and their deliverables must be designed for efficiency, stability, and, most importantly, measurable results—hence the importance of Six Sigma. We will work within the IDEA, UAPL, and LMAD processes, applying their accompanying tool-task sets to create measurable deliverables that fulfill the gate requirements. You may choose to call your process phases by different names—that's fine. What you do and what you measure are what really matter.

Throughout this book, the word "product" refers to a generic company "offering" and represents a tangible product and a services offering. This book discusses technology-based products frequently, because of marketing's interdependency with the technical community. In parallel, R&D, design, and production/services support engineering should use growth- and problem-prevention-oriented forms of Six Sigma in their phases and gates processes. The Six Sigma approach serves as a common language between the marketing and technical disciplines. The term "solutions" usually involves both technology and services; thus, "product" and "service" encompass the scope of a given solution. Regardless of the offering, the Six Sigma approach we are outlining is the same and can be applied to either a tangible product or a service offering.

Summary
Six Sigma for Marketing and Six Sigma for Sales are relatively new approaches to enable and sustain growth. They are part of the bright future offered by adapting Six Sigma to the growth arena. The linkage of Six Sigma for Marketing and Six Sigma for Sales tasks and tools to strategic, tactical, and operational processes is where the Six Sigma discipline adds measurable value to marketing and sales team performance. Marketing and sales professionals can custom-design what to do and when to do it to fit these three critical marketing process arenas to their organization or culture. This book's concepts can complement your company's unique marketing approach and infrastructure. Why? Because the most important goal is to communicate a common approach to manage risk and make sound, data-driven decisions as you seek to expand the company. An organization can take license to customize the methodology to fit existing processes, enhancing communication and adoption. A customized application of this book's concepts will work as long as the following are upheld: phase objectives (or requirements), the sequence, tools-tasks-deliverables combinations, and phase-gate reviews. Integrating these methods and concepts into your critical processes with adequate rigor applied to meet deliverable requirements at phase-gate reviews will lead to more predictable outcomes.

Before exploring the details of each strategic, tactical, and operational method for marketing and sales, let's examine two foundational topics that transcend these three areas. The first fundamental subject involves the criticality of reporting and tracking performance and risk. Chapter 2, "Measuring Marketing Performance and Risk Accrual Using Scorecards," introduces a system of scorecards that build on Six Sigma principles to measure marketing's use of tools, completion of tasks, and the resulting deliverables across the strategic, tactical, and operational processes. Chapter 3, "Six Sigma-Enabled Project Management in Marketing Processes," addresses the importance of project management. We suggest adding some Six Sigma tools to the traditional project management body of knowledge to better manage a project and its associated risk.

Poor-quality application development threatens four in five firms

NK Khoo Managing Consultant — Mon, 01 May 2006 03:27:00 +0000

Companies need to apply better quality assurance procedures when building business software

Phil Muncaster, IT Week 27 Apr 2006

ADVERTISEMENTEuropean firms are neglecting quality assurance (QA) in application development, and their software may fail to meet their needs as a result, according to research by Compuware.

Compuware found 78 percent of organisations did not to apply a formal quality assurance methodology. A quarter of respondents said their QA team did not have sufficiently trained or experienced members, and a third said they had no full-time team manager.

Sarah Saltzman, Compuware's technology support manager, said it was surprising that so many firms had no formal methodologies in place despite the emergence of best practice initiatives such as Six Sigma and Capability Maturity Model (CMM).

"If you don't have the correct processes and steps in place [such as quality assurance] you may not be properly prepared when it comes to testing, and may even test the wrong part of the applications," Saltzman warned. "[Firms also] need to embed business requirements into the development process [but] sometimes it gets lost in the detail."

The situation is unlikely to change unless senior IT staff and company stakeholders drive through quality assurance initiatives themselves, Saltzman added.

Competing for Customers and Winning With Value Challenges Conventional Wisdom about Both Competition and Competitive Planning

NK Khoo Managing Consultant — Mon, 01 May 2006 03:23:00 +0000

Download this press release as an Adobe PDF document.

New book from ASQ's Quality Press unites two powerful ideas, customer value and competitive planning, into a step-by-step process that makes the organization an effective and efficient machine for both retaining current customers and acquiring new ones. A unique element of the book is its integration of Six Sigma into the comeptitive planning tool set. Detailed action plans use Six Sigma to identify value-adding projects that are designed to enhance the organization's competitive value proposition and thereby increase market share.

State College, PA (PRWEB) April 26, 2006 -- The competition for achieving and sustaining a differential advantage is one of the more compelling issues facing businesses today. “Competing for Customers and Winning With Value” (ASQ Quality Press) sets forth a template that challenges much of the theory and practice of competition and planning. It unites two powerful ideas, customer value and competitive planning, into a step-by-step process that makes the organization an effective and efficient machine for attracting new customers and holding on to its current customers.

“The book is the result of our work with a number of companies that had originally hired us to develop and deploy our customer value models throughout their organizations. They challenged us with a simple but involving task. How do you use the customer value information we’ve collected to increase our market share and improve our business performance? The answer to this question is found in ‘Competing for Customer and Winning With Value’,” says Dr. Reginald Goeke, Principal and Co-founder of Market Value Solutions.

“Two aspects of this book make it a powerful tool for managers”, says Dr. Goeke. “The first is our approach to measuring and managing customer value. Customer value is a potent metric for predicting market share and business performance. It is far more effective than customer satisfaction for a number of reasons, chief of which is its ability to be linked to market performance. Second, the planning template focuses on the organizational level where customers are actually won and lost. Too often planning takes place at a level that is too abstract and therefore hard, if not impossible, to implement effectively. Competitive planning takes place at the point where products and markets intersect to produce strategic opportunities for the organization.”

The strength of the book is its systematic and logical approach to basing competitive plans on the voice of the market. It removes the randomness of many planning processes by providing tools for measurement, plan development, and monitoring. One unique element of the book is its integration with Six Sigma as part of the competitive planning tool set. Detailed action plans use Six Sigma to identify value adding projects that are designed to enhance the organization’s competitive value proposition and thereby increase its market share.

When asked of this component of competitive planning, Dr. Goeke points out that “ ‘Competing for Customers’ provides the crucial link between Six Sigma and marketing in a very concrete and highly focused way, heretofore missing in most attempts to link the two. ‘Competing for Customers’ will move Six Sigma from the factory floor, where its traditional focus has been on cost reduction, to the arena of the marketplace where it will become a powerful strategic tool, consistent with the organization’s strategy for acquiring and retaining customers.”

Market Value Solutions (MVS) is a company that specializes in the measurement and management of customer value. MVS has developed a unique and powerful process for integrating Six Sigma and Lean into the competitive planning process directed by the voice of the market.

Dangerous half-truths for managers

NK Khoo Managing Consultant — Mon, 01 May 2006 03:18:00 +0000

HARVEY SCHACHTER

Hard Facts, Dangerous Half-Truths, and Total Nonsense

By Jeffrey Pfeffer and Robert Sutton,

Harvard Business School Press,

It's considered a truism that the best organizations have the best people. Another axiom believed especially by managers is that strategy is destiny. And the belief that great leaders are in control is widespread.

But those and other familiar nostrums are dangerous half-truths, according to Jeffrey Pfeffer and Robert Sutton, two professors at Stanford University's Graduate School of Business. Unfortunately, they say, managers and the companies they lead fail to seek evidence to back up such operating practices and ignore what evidence exists.

"If doctors practised medicine the way many companies practise management, there would be far more sick and dead patients, and many more doctors would be in jail," they note.

Medicine and management both deal with unknowns. But doctors prescribe based on the available evidence. And managers ought to follow a similar, evidence-based approach, they say.

"Practising evidence-based management is neither arcane nor extraordinarily difficult -- and it can produce superior results. It can also generate sustained competitive advantage, because since so few organizations and their leaders do it, the likelihood of imitation is not high," they observe.

Take the belief that the best organizations have the best people. In fact, the authors argue, great systems are often more important than great people, as Toyota Motor Corp. has shown with its lean manufacturing. Similarly, strategy can be vital but it's not destiny; ultimately competitive success often comes down to not only knowing what to do but also having the ability to do it.

The authors suggest that great leaders aren't in control, as the mythology suggests, but in fact have quite limited powers in gargantuan organizations. Moreover, trying to be too powerful as a leader can wreck an organization. Instead, leaders need to act and talk as if they are in control, projecting confidence and talking about the future while building systems that allow others to flourish and take the organization forward.

That's a brief description of a very detailed, incisive and interesting analysis of each nostrum by the authors, showing the extent to which it is accurate and inaccurate. They also probe three other common beliefs that on closer examination prove shaky: Work should be fundamentally different from the rest of life so that we act differently in the workplace from at home; financial incentives drive company performance; and organizations must change or die.

The authors offer six guidelines for evaluating the barrage of management ideas and knowledge around us:

When old ideas are offered like laundry detergent in a new, improved format -- total quality control, for example, morphing into Six Sigma quality improvement -- ignore the rhetoric and uncover the actual roots of the idea so that you can better figure out its track record and likelihood of working for your organization.

Be suspicious of breakthrough ideas and studies. We may innately want some silver bullets, but they rarely occur. Most improvements are incremental.

In religion and politics, gurus are portrayed as extraordinary but often dangerous leaders. Business might well take a similar approach, becoming wary of the oversimplifications of management gurus.

Emphasize virtues and drawbacks. Most management ideas are presented as having no negative side. But just as every drug has a side effect, every management idea has its strong and weak points, which should be highlighted.

Vivid case studies of success and failure grab our attention, show us what to do, and inspire us. But the eyewitness accounts on which they are based are suspect, and the approach is not ideal research, so treat them with care. To overcome biases, look for failures embedded in success stories and successes embedded in failure stories. "This could mean, for example, that we should look back at what Enron and WorldCom did right rather than what they did wrong!" the authors suggest.

Take a neutral, dispassionate approach to ideologies and theories. Since people routinely ignore evidence about management practices that clash with their political convictions or idiosyncratic personal histories, we need to put aside our pre-existing beliefs in order to learn.

Ultimately, they are calling for wisdom, to separate truth from fiction so we understand the difficulties we will face after adopting a certain approach. And they present us with a wise book, sobering and illuminating, as they lead readers through some complicated issues, sifting evidence from fiction.

In Addition: In Getting Engaged: The New Workplace Loyalty (Mattanie Press, 175 pages, $21.95), Toronto-based consultant Tim Rutledge shows what organizations must do to get engaged employees and what you, as a manager, must do irrespective of your organization's zeal in this area. Top managers are highly engaged with employees and highly engaged with the work, creating an environment in which employee enthusiasm and engagement will be captured.

The editing is uneven -- the key chart has some labels wrong; the writing is loose; and a clever device in which the writer and an alter-ego converse is used only sporadically. But many of the ideas are shrewd and the tips are helpful.

Chat to open $250 NRI account

NK Khoo Managing Consultant — Mon, 01 May 2006 02:54:00 +0000

BROOKS CARDER & PATRICK RAGAN

TIMES NEWS NETWORK[ SUNDAY, APRIL 30, 2006 02:01:57 AM]

A former senior manager at Ford told us that the single aspect of Ford’s quality transformation n the 1980s that gave him the most pride was the dramatic change in management's relationship with the union. He said it was typical to see executives and hourly workers seated side by side in a classroom, something that would have been unheard of prior to the transformation.

The chairman of Ford during the early stages of the transformaton was Donald Petersen. In a memoir of that period (Petersen and Hillkirk 1991), Peterson mentions that he frequently toured Ford plants. His critical criterion for evaluation was whether the plant manager knew the hourly workers. He said it was clear that some had memorized the names just before his arrival. Managers who did not know the workers did not stay with the company.

After graduate school, I spent several years as a scientist in a university. I then entered business and spent 13 years as a Manager.Initially I tried the "my way or the highway" approach to management, but it not work for me. I began to develop more cooperative relationships with my staff, and things went much better. However, the science of management practice, including the use of strong threats as motivators, was contrary to the accepted scientfc principles I had been taught and had taught to others.

In 1988, I encountered the work of Dr W Edwards Deming, the man who created a revolution in quality management in America. I had an epiphany. Dr Deming's teachings made sense of many of the questions and confusions I had encountered in tryng to reconcile what I knew as a scientist with what I saw as common practice in Business. From 1988 to Dr seminars and form a casual acquaintance with him. By that time Dr Deming was famous ast he man responsible for the rise of Japanese industry following World War II. But who had gone unheeded in America.

Only after we had lost our industrial leadership to the Japanese was his knowledge recognized in America. In 1982 he was engaged by Ford. The programs that grew from his teachings helped move Frod from the brink of bankruptcy to far and away the most profitable U.S. auto manufacturer by 1995.

Many have suggested that quality programs were a flavor of the month that is now stale. That is probably because many companies treated them as a flavor of the month and failed to embrace the principles seriously and go through the discipline needed to establish a successful quality programs and their results in American industry.

Their findings indicate that performance measured by both accounting variables and stock returns is improved for firms adopting TQM. The improvement is consistently stronger for firms with more advanced TQM systems." Dr Deming's ideas are at the heart of lean manufacturing and Six Sigma, both very successful current approaches to the improvement of business performance.

Our experience with Dr Deming and his teachings led us to adopt the principles and methods he taught. The Deming approach depends on some fundamental shifts in thinking, away from what is still common and traditional in management. Dr Deming's assumptions are, of course, much better supported by scientific evidence than are many practices that were and still are popular in business. However, the impact of science on common belief and practice is often very late in coming.

Galileo was not the first and certainly not the last scientist to experience a rather pointed rejection of what seemed (and with the benefit of hindsight, to us) obvious scientific truth. Usually change does not happen until it is demanded by the marketplace. Einsten's theories were widely disputed until the power of nuclear physics converted everyone. Few listened to Dr Deming until the quality of Japanese products overwhelmed American products in the marketplace.

Dr Deming's approach to management s founded on two fundamental principles. Although based in science, these principles form the philosophical framework of his system.

After Caterpillar's Turnaround, A Chance to Reinvent Globalization

NK Khoo Managing Consultant — Tue, 25 Apr 2006 08:47:00 +0000

By Steven Pearlstein
Wednesday, April 19, 2006; Page D01

If you want to know how the General Motors and Delphi stories are going to turn out, you can find the answer in Peoria.

For it is there that Caterpillar has come up with the model for how a big American manufacturing company can not only survive, but prosper, in a highly competitive global economy.

As part of that process, Caterpillar has led the way in shredding the old social contract that once existed between big corporations and their workers -- the unwritten code that included lifetime employment, company-paid life insurance, rock-solid retirement benefits and above-market wages. There's no question that had it stuck with that model, Caterpillar would have gone the way of the auto and steel companies and the traditional airlines.

But now, having pulled off one of the most impressive corporate turnarounds in recent memory, Caterpillar -- like the rest of corporate America -- must confront a new question: What is the new social contract it has to offer around which a stable political business model can be built?

But first, a little history. By the early 1990s, Caterpillar's products were tired, its cost structure bloated, its market share declining in the face of stiff foreign competition. Management was determined to do something about it. The company was decentralized and restructured, and big investments were made to modernize factories and transform trucks and earth-moving equipment into high-tech machines. Work was shifted or outsourced to lower-cost regions and countries. The Six Sigma quality improvement program became a corporate obsession.

Perhaps most significantly, the back of the once-mighty United Auto Workers, which represented most of Caterpillar's unionized workers, was broken. Over a period of nearly seven years, the company took two strikes, operating its plants with management and replacement workers, rather than renew a contract whose cost structure would have either driven it out of the country or into bankruptcy. When it was over, the union was forced to accept a new two-tiered pay structure that called for wages for the lowest-skilled workers to start as low as $13 an hour, with more limited pension benefits, no job security for at least a decade, and a pay scale based more on skills than seniority. Existing workers agreed to minuscule annual pay increases and a first-time-ever 20 percent contribution to the cost of health insurance, along with a cap on retiree health benefits.

Today, Caterpillar is going like gangbusters. Its workforce has grown about 25 percent in the past two years, including thousands of new jobs in the United States. Its share price has more than tripled. Last year alone, its profit increased 40 percent, to $2.85 billion, on a 20 percent increase in sales. With more than half of its sales now outside the United States, it has become one of the country's largest exporters.

Much of the credit for this success goes to chief executive Jim Owens, who likes to use his experience to make a pitch to anyone who will listen for why American businesses and workers should embrace globalization. But reading through Owens's recent speeches, op-ed columns and letters to shareholders, what is most striking is how little appreciation he seems to show for the middle-class dreams that have been shattered to make Caterpillar's success possible -- or how those shattered dreams now translate into political opposition to globalization.

Imagine, for example, what the public reaction would have been if Owens had announced that, in recognition of the year's spectacular results, each of Caterpillar's 22,000 unionized employees would get a special bonus of, say, $3,000. I can assure you it would have been widely noted in the press and praised as a significant first step toward a new social contract. And who knows how much extra loyalty and commitment it would have engendered from Caterpillar's blue-collar employees.

But, instead, what those employees know is that Owens took home a performance-based pay package with an estimated value between $18 million and $38 million. They know that 50,000 nonunion employees split a bonus pool of $445 million. They know that the top executives were awarded options with an estimated value of between $80 million and $206 million. They know that shareholders earned spectacular returns.

Oh, yes, I can just hear the dismissive response from corporate types now. They'd point out that Caterpillar investors who earned a record $4.21 a share would hammer the company stock if that figure were reduced by even a penny. They'd point out that unions like the UAW have traditionally opposed performance pay, or traded it away for higher guaranteed pay or benefits. And they warn ominously that this kind of "excess" compensation would quickly render the company uncompetitive again.

But none of that really matters. Because the real world choice for the corporate elite is now quite clear -- not just here in the United States, but in Europe, Latin America and Japan, as well. Either the members of the business community will have to come up with an improved social contract that allows them to run competitive companies while ensuring that the gains of globalization are spread more equitably, or they will have to face the almost certain prospect that angry and anxious voters will roll back globalization in ways that will hurt the global economy and their newly globalized companies.

Or to put it another way: It's time for the Jim Owenses of the world to show the same backbone and ingenuity in dealing with the excessive and unreasonable demands of Wall Street that they previously showed in dealing with workers and labor unions.

BPOs: Looking beyond the cost factor

NK Khoo Managing Consultant — Tue, 25 Apr 2006 08:41:00 +0000

CHIRANJOY SEN
TIMES NEWS NETWORK[ THURSDAY, APRIL 20, 2006 12:00:43 AM]

What started off as pure cost game, is now evolving into a process gambit. Cost has been the main reason for turning to India-based offshore business process outsourcing. However, technology experts and analysts feel that global enterprises should now also factor process improvement and enhancement into their sourcing decisions.

According to IT research firm Gartner, offshore BPO started as pure ‘lift and shift’ deals to exploit the labour cost advantage of lower cost locations. But now, BPO is evolving into a sophisticated delivery mechanism where Indian offshore service providers are using their acquired process knowledge to deliver a range of enhancements and modifications to the inherited process.

They are no longer just doing work at a lower cost, but they are also contributing ideas and suggestions on how to do the work more effectively and differently. This is especially true of third-party BPO vendors.

Says S Nagarajan, COO, 24/7 Customer, “We believe that generation III in offshoring is beginning. Companies in offshoring have evolved from generation I which was pure cost play to generation II that has been productivity play to generation III which will be value creation (not value addition) through innovation.”

In fact, Gartner in a recent report says by 2010, offshore service providers will be as well-known for their process innovation capabilities as they are today for their process cost advantages. Says Sujay Chohan, research vice-president, Gartner: “To overcome natural resistance to performing core business processes halfway around the world, some Indian-based service providers feel they need to increase their added value to compete more effectively with onshore outsourcing providers.”

Although not yet mainstream, there is increasing evidence during the last two years to show that Indian players are offering proc-ess enhancement in their services.

Process Innovation: How IT Helps

But what then is process innovation, one that is expected to drive the next level of BPO growth? “Process innovation, in essence, implies making substantial improvements to the client’'s business performance. Innovation in business processes encompasses a lot of factors like providing value-added cost savings to customers through tangible increases in efficiency and outcome; re-engineering business processes through effective utilisation of technology, workflow and resources,” says Ranjit Narasimhan, CEO & President, HCL BPO.

Ananda Mukerji, CEO, ICICI OneSource, points out that process innovation is the redesigning of existing business processes to achieve breakthrough improvements in performance measures. Mukerji goes on to add that Indian BPO companies have made real head-way in differentiating themselves from other outsourcers by not just high-quality delivery but a strong focus on continuous process improvement by using Six Sigma, Kaizen and a number of other techniques.

“Today, Indian offshore providers have developed significant process management expertise that results in real business impact. For example, in CRM processes delivering increased customer retention, helping increase average revenue per customer, identifying gaps in the customer’s product offering based on market intelligence and so on and so forth," he explains.

So the real differentiator will be managing and transforming processes so that customers’ business objectives are met and exceeded. Echoes Nagarajan of 24/7 Customer: “Many Indian companies have already been demonstrating on minor innovations that improve existing processes. We have not only focused on minor innovations but also on major innovations that enhance performance effectiveness. The most important aspect of major innovations is that they transcends boundaries in terms of onshore/offshore and creates true value for the customer on a long-term basis.”

“To sustain India’s number one position as an outsourcing destination, companies will have to focus on enhancing customer interaction and solution delivery (effectively influencing customer thinking and decisions), improving resource management (hiring people with the right skills at the right tenure); and upgrading support processes (accurate and quick financial reporting to facilitate decision making),” points out Susir Kumar, CEO, Intelenet Global Services

Cost Vs Process

But if process dominates the future, will cost remain the prime differentiator? And what benefit does process innovation bring to the client, as well as to the offshore service provider?

“Cost will always remain an important business differentiator. However, the customers will not be content with pure cost arbitrage,” says Narasimhan of HCL BPO. Ananda Mukerji of ICICI OneSource has a similar view: “Cost is an important factor but certainly not the main driver to offshore. Customers are looking at Indian operations to deliver better quality and process improvement and innovation.” Susir Kumar of Intelenet Global Services says a paradigm shift in the customer acquisition process is becoming evident.

Customers are demanding solutions based on domain familiarity that extend beyond technology services and enhance their business competitiveness.

All that’s fine, but what are the benefits to the customers? Narasimhan says companies look to partner with organisations that can provide innovative solutions to help ensure reliability and enhanced performance of their mission-essential operations. Further, he says companies looking to outsource have a straightforward approach to quality control by identifying parameters that are ‘critical to quality’.

Ananda Mukerji is more specific: “Such process improvements can help companies attain greater flexibility in operations, faster go-to-market delivery and potentially new revenue streams which were not possible without an offshore operation”.

But there’s a twist in the tale. Gartner says that s everal of the companies offer their process innovation knowledge free of charge to clients for evaluating possible process improvements, enhancements and transformation prior to bidding on potential deals. More-over, when considering their offshore strategies, global companies rarely factor in the savings and additional revenue that these hidden benefits generate.

Emphasises Gartner’s Sujay Chohan: “Potential clients must calculate the savings potential possible from transferring their business processes to India-based offshore service providers that have demonstrated competency in process innovation.” But wouldn’t cost go up once the BPO firms start charging for it.

“No,” says Chohan because the charge is for a value-addition, an incremental service — and not for the existing offerings.” Further, costs wouldn't go up simply because Indian BPO companies are increasingly improving and transforming processes, as well as automating them or performing them for less money than domestic (read: US-based) providers, according to the Gartner report.