|Book Review: Design for Lean Six Sigma|
Design for Lean Six Sigma: A Holistic Approach to Design and Innovation
Written by: Rajesh Jugulum and Philip Samuel. Hoboken, NJ: John Wiley & Sons, Inc., 2008. 300+xx pages.
The authors preface their book by citing two key business areas in which corporations compete against rivals: (1) managing its current business for maximizing profit; and (2) finding the future of its business for maximizing growth. Most companies designing new products, processes, or services fail to sustain long-term growth, attempted either by mergers and acquisitions or by organic growth. The focus of the book is energizing the innovation process with a holistic Design for Lean Six Sigma (DFLSS) roadmap that provides improved and effective revenue productivity through understanding and leveraging key variables for growth to establish a predictable, scalable, and repeatable process. The book offers a structured, systematic, and disciplined methodology and covers many tools and techniques. The authors hope to reach and change the mind-set of a broad audience—executives, Six Sigma and Lean leaders, statisticians, and the academic and industrial community—with this unique roadmap and newer tools showcased therein.
The book outlines this holistic DFLSS approach addressing the end-to-end DFLSS deployment process with a roadmap offering a methodology that is structured, systematic, and disciplined striking a balance between rigor and creativity delivering optimal design cycle times. The DFLSS roadmap is described as an eight-phase approach in accordance with define, measure, analyze, design, and verify (DMADV) requirements. The eight phases are as follows: (1) customer expectations; (2) concept design; (3) preliminary design; (4) final design; (5) product validation; (6) process validation; (7) product launch; and (8) postlaunch.
The authors provide context for the book by explaining that success in the marketplace requires mastery of two sets of activities: managing the present and creating the future. And a third activity—selectively abandoning the past—is indicated as necessary to bridge between short- and long-term objectives. Companies proficient at one activity may be deficient in another based on company culture and characteristics. Some companies with risk aversion and orientation toward stability, details, and efficiency may thrive at doing things better and perfecting current paradigms (i.e., Kodak's mastery of analog photography) but often lack the skills and competencies required to identify new opportunities and create new promises where embracing change, dissatisfaction with status quo, risk taking, and less regard for rules is the culture (e.g., Xerox is adept at pioneering inventions but failed to capitalize on innovations). Companies must balance these activities to stay on the growth curve over a long period of time (e.g., Apple executes flawlessly managing both preservation and evolution). The pace of discontinuity is happening at a faster pace; companies are rewarded in the market that can maintain and find new promises.
The objective of innovation is to create new value, which can be new and enhanced products, services or business models or behind-the-scenes enabled processes. Two major activities feed growth through innovation: (1) creation of a new or superior promise, achieved through ideation and design processes; and (2) fulfillment of the promise through production and delivery processes. Mastering growth demands mastering preservation and evolution; tension between these two sets of activities exists due to the structures, culture, and systems that enable each of them. Paradoxes that must be embraced to manage both preservation and evolution are articulately described with successes obtained through integration and separation of opposing forces—not an easy challenge. Setting the stage for a systematic innovation process requires understanding, managing, and leveraging the underlying process that enable innovation. Variables that impact the process of innovation are discussed in detail (pp. 30–40).
Taking a step back, the authors present the origins and definitions of Lean and Six Sigma and highlight that the combination fuels operational excellence and has evolved to a multifaceted business management system originating as a system for improvement purposes. Six Sigma, first developed as a statistical technique with a virtually defect-free performance target, has evolved to become a metric, improvement methodology, management system, and customer-centric strategy. Six Sigma addresses variation (controlled and uncontrolled)—identifying areas of variation, isolating root causes, optimizing processes, and reducing and minimizing the impact of variation. Lean originates with mass production and industrial engineering. The main themes behind the Lean approach are improving process speed and reducing cost by eliminating waste. The five principles of Lean are (1) value, (2) value stream, (3) flow, (4) pull, and (5) continuously improve. Lean thinking uses Kaizen events, in which a small group convenes to improve business through quick, focused sessions, thereby producing what is needed, when needed, with minimum resources. These two competing approaches were combined to become a more responsive, effective operational strategy—faster, better, cheaper, safer, and greener.
The traditional focus of Lean Six Sigma is on improvement activities; in contrast, DFLSS is focused on creation processes, enhancing the quality of the design process, and reducing development cycle times. DFLSS design phases are integrated against product-specific activities and deliverables to ensure that the design process is optimized. Key decisions and questions are illustrated in a six-phase example: customer need, concept design, preliminary design, final design, testing and validation, and production and launch. Key roles are covered (executive sponsor, champions, design black belt, core and extended teams). The infrastructure to manage, scale up, and sustain DLFSS activities include program management, finance, information technology, human resources, communications, and training.
Collecting customer expectations was discussed as a means to deepen understanding and learning and to accelerate innovation. Creating unique value for customers to satisfy certain unmet needs, establishing the value proposition, and asking the question what critical processes do we need to excel to deliver flawlessly on the promise we made to the consumer require identifying, monitoring, managing, and improving essential processes. “The question is, then, how do we create the best experience for the customer that meets or exceeds their expectation through the delivery of the promise?” (p. 75) Key elements are illustrated and discussed, the most important being deliverables to the customer. Three types of consumer expectations—performance (objective, unambiguous, and measurable), perception (subjective, ambiguous, and difficult-to-measure), and outcome (results customers want to achieve by using the product or service, such as health, fun, market share, wealth, and return on investment or jobs to be done, which may exist even in the absence of products) and the degree to which they are satisfied form the basis for customer satisfaction. Customer expectations can be converted into functional requirements and then to design parameters. Exploring jobs to be done in an unoccupied market space is an innovation objective. Ideality (defined as the ratio of desired outcomes to undesired outcomes) is a convenient and superior measure to assess an innovation. Combining desired outcomes to create a new set of values for customers can increase the ideality of the innovation.
The four purposes of axiomatic design (AD) are (1) systematic way of designing products; (2) reducing random search process; (3) determining best designs among those proposed; and (4) creating systems architecture that completely captures construction of the systems functions. AD can be effective in translating customer needs into functional requirements through relationships between functional requirements and design parameters with design equations. The authors elaborate on AD with multiple examples. Here they step into calculation of Mahalanobis distances and design equations, decoupled designs and decompositions—the content of which will lose readers not versed in matrix notations.
The authors argue that to achieve the ideal final result we must understand the stakeholders and all their levers and what depletes value for the stakeholders. Levers that deplete value for stakeholders should be minimized—high manufacturing cost, difficult maintenance, or expensive up-front investments are a few value-depleting levers for stakeholders. Value-enhancing levers might include ease of installation, operation, maintenance, and disposal. Examples of items that don't add value are listed (p. 118), and strategies for maximizing value and minimizing costs and harm are summarized in table format (pp. 119–120). Value engineering is defined as seeking to optimize performance by balancing cost and performance (functionalities). A lean enterprise is achieved during production by simultaneous progression of production process and product design phases.
A chapter was devoted to the Theory of Inventive Problem Solving (TRIZ), which is put into use in conjunction with DFLSS. TRIZ case examples are provided. Robustness invention was covered fairly technically including research methodology, patent searches, classification schemes, and types of robust inventions—signal-based, response-based, noise-factor based, and control-factor based.
Designing robustness was covered encompassing Taguchi's robustness designs (Taguchi, 1993; Taguchi, Jugulum, and Taguchi, 2004) aimed at improving product or service performance by reducing variability across usage conditions. Additional topics in designing robustness include the parameter diagram, which is helpful to represent a product or system, and the design of experiments, the role of simulations, and numerous examples. Robust system testing was also covered using software examples. And, finally, the authors closing chapter is an illustration of a multivariate measurement system using the now popular Mahalanobis–Taguchi pattern analysis strategy (MTS). Case studies using MTS are provided. The appendices support technical details for TRIZ, orthogonal arrays, equations for signal-to-noise ratios, and matrix theory.
This book provides the historical context of Lean and Six Sigma then delivers on the evolution to holistic DFLSS—what it is, why, and how and when to apply it. DFLSS principals are covered in the context of designing and developing processes, products, services, and systems. The technical examples and strategies provide conceptual depth and definition, helping the reader appreciate the complexity and rigor that can be brought to bear for competitive innovation.