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Improving the NPD Process by Applying Lean Principles: A Case Study

Article  in  Engineering Management Journal; EMJ · April 2015

DOI: 10.1080/10429247.2011.11431910

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52 March 2011Vol. 23 No. 1Engineering Management Journal

Improving the NPD Process by Applying Lean Principles: A Case StudyBimal P. Nepal, Texas A & M University

Om Prakash Yadav, North Dakota State UniversityRajesh Solanki, RTI International Metals

sequentially. Past studies show that to reap the full benefits from best practice techniques, such practices should be implemented across the board, with inclusion of suppliers and customers in an integrated manner (Nepal et al., 2007).

Furthermore, flexibility of the product development system is considered an important enabling factor for success in a volatile and rapidly changing marketplace (Sobek et al., 1998). According to Yadav et al. (2007), “flexibility and effectiveness of PD processes depend on various other factors, such as design activities and tools used, their planning and scheduling, information flow structure, quality and availability of information, and decision-making approaches.” While design tools and techniques are critical enablers, an integrated PD process or system is pivotal to the overall success of any PD factory.

To cope with increasing pressure for time and cost reduction, manufacturers have successfully embraced lean and Six Sigma principles in PD projects. The lean thinking business strategy emphasizes elimination of waste to create the most value for customers while consuming the fewest resources (Walton, 1999). These same principles can be equally applied to PD (Walton, 1999; Morgan, 2005). In particular, reduction in excessive process variability, creation of pull-based flow driven by customer requirements, and the elimination of waste are seen as key elements of lean product development. While application of these techniques offers the potential for significant improvements in development cycle time and cost, in reality this transfer is complex (Karlsson and Ahlstrom, 1996). Unlike manufacturing, PD is a non-repetitive, non-sequential, unbounded activity that produces information, and where cogent risk-taking might be a key to adding value (Browing, 2003; Reinertsen, 2009). Variability is inherently and necessarily higher in product development than manufacturing. Similarly, due to low expense and long cycle time, the relative economic importance of wasted cycle time enabling earlier accrual of revenue from new products compared to wasted expenses can be much higher in PD than it is in manufacturing (Cooper and Edgett, 2008).

This article presents a “reflective case study” (Kotnour and Landaeta, 2004) of a lean PD transformation framework used at a U.S.-based manufacturing company. Furthermore, the transformation framework integrates traditional lean manufacturing tools like value-stream mapping (Womack and Jones, 2003) with other Six Sigma and project management tools, such as the cause and effect matrix and the design structure matrix (DSM). The DSM advantageously allows design engineers to understand the underlying complexity of the PD process by identifying dependency among design activities. By doing so, engineers can determine root causes for wasteful iterations. An implementation timeline and strategies to transform the traditional (or current) PD process into a leaner PD process by embedding lean principles are also presented. The remainder of the article is organized as follows: the evolution of PD processes

Refereed research manuscript. Accepted by Special Issue Editor Geert Letens.

Abstract: This article extends the new product development (NPD) literature by presenting a case study of a lean product development (LPD) transformation framework implemented at a U.S. based manufacturing firm. In a departure from typical LPD methods, in this article the design structure matrix and the cause and effect matrix are integrated into the lean transformation framework, allowing analysis of the underlying complexity of a product development (PD) system, and thus facilitating determination of the root causes of wasteful reworks. Several strategies to transform the current PD process into a lean process are discussed. Besides the two-phase improvement plan, a new organizational structure roadmap and a human resources plan are also suggested to support the recommended changes in the NPD process. The results of the first phase show a 32% reduction in PD cycle time due to the proposed NPD process. The article concludes with lessons learned and implications for engineering managers based on the case study.

Keywords: Lean Product Development, New Product Development, Case Study, Design Structure Matrix

EMJ Focus Areas: Innovation & New Product Development

Advances in manufacturing and operations management have succeeded in shrinking the manufacturing productivity gap. For instance, in the automotive

industry, this gap has shrunk from 16.5 hours per vehicle in 1996 to 7.33 hours per vehicle in 2005 (Teresko, 2007). This trend essentially suggests that manufacturing efficiency will no longer be an order-winning strategy, although its importance should not be underestimated. On the other hand, researchers argue that the success of any company depends on the organization’s ability to innovate and introduce new desirable products at a much faster rate than their competitors (Kearney, 2005; Yadav et al., 2007). There is undeniable evidence that an efficient and effective product development (PD) process is key to the survival of any manufacturing company in today’s globalized economy. If managed and executed properly, an efficient PD process enables a manufacturer to bring to market new products more quickly than their competitors. The potential for individual best practices, design activities, tools, and techniques to boost performance measures can be fully realized only if these components are integrated into an effective overarching system. It is, therefore, essential that integrated PD processes be developed and implemented as coherent systems. All aspects of the PD process should be coordinated and developed simultaneously, rather than being viewed as separate sets of PD activities occurring

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is presented, including a brief review of the lean product development literature; next is a case study on the lean PD transformation framework; following that is a description of key improvement areas and lessons learned from the case study; and, the article concludes with some thoughts and implications for engineering managers.

Overview of Product Development ProcessesThe most generic PD process, the stage-gate process (Cooper, 2008), was developed and implemented in many U.S. industries during the late 1980s and early 1990s (Holmes and Campbell, 2004; Yadav et al., 2007). The stage-gate process consists of discrete phases from product planning to product release as illustrated in Exhibit 1. The term stage-gate refers to a design review process undertaken at the end of each phase. Based on the status of earlier milestones (and also inputs from the senior management), the course for the next development stage is determined.

The major goal of the stage-gate process is to improve business performance and to develop higher quality products for enhanced revenue growth (Thomke, 2007; Cooper, 2008). This process provides a mechanism for controlling quality and reliability issues during the gate reviews. In the traditional version, however, neither feedback nor cross-stage iterations are planned, making the stage-gate inflexible (Unger and Eppinger, 2009). It is important to note that the back arrows in Exhibit 1 indicate the learning process for future development projects, not the feedback of information for the ongoing product development project. A serious limitation to the efficiency of this process is the lack of control of time and schedule within each phase. In today’s globalized competition, where time-to-market is a winning strategy, efficiency complements traditional factors such quality and reliability (Rosas-Vega and Vokura, 2000). The traditional stage-gate product development process requires long design review cycle times and an excessive amount of documentation, and gives less attention to early stages of PD, thereby causing further reduction in design productivity (Minderhouds, 1999; Unger, 2003; Cooper and Edgett, 2008; Nepal and Monplaisir, 2009).

Furthermore, in a linear development process such as a stage-gate process, incorporation of new information (in design terms, engineering change) becomes expensive due to resulting reworks and process delays (Summers and Scherpereel, 2008). To deal with this issue, some companies have adopted a spiral product development process (Cooper and Edgett, 2008). The spiral PD process has a faster development cycle than the traditional stage-gate process (Unger and Eppinger, 2009). It follows build-test-feedback-and-revise loops multiple times until the final product is developed per the desired specification and quality level.

Concurrent engineering (CE), another product development process widely described in the PD literature, requires the involvement of cross-functional teams starting with initial development stages to plan for product development and manufacturing processes simultaneously (Quesada et al., 2006). Concurrent PD processes can also be classified as point-based concurrent engineering and set-based concurrent engineering, depending on how soon the initial set of conceptual ideas converge to a final design (Sobek et al., 1999; Ford and Sobek, 2005). In the point-based approach that most U.S. original equipment manufacturers (OEMs) follow, the best conceptual design is selected and frozen early on during the end of conceptual stage design review process based on criteria minimizing the complexity and limiting production cost. On the other hand, in set-based CE developed and implemented by Toyota, rather than selecting the so-called best alternative design, the company develops a set of viable alternatives from multiple perspectives. As they progress to the next stage, they gradually eliminate the relatively poor alternative based on multiple criteria such as quality, reliability, manufacturability, and cost, and eventually converge to a final design (Ford and Sobek, 2005).

Over the years, product development literature has evolved from a traditional sequential, technology push-and-market-pull model to a more overlapped and integrated process, employing internal cross-functional teams and early supplier involvement to reduce time-to-market (Yadav et al., 2007). In other words, companies are now moving toward applying lean thinking, viewing product development from a system perspective (Cooper and Edgett, 2008). Although lean principles originated from the manufacturing domain, they can produce even greater results in a PD environment given that the product development process typically exhibits a wider variability than that of manufacturing (Smith, 2008). Further, while aerospace and automobile industries were among the first to adopt lean principles in PD, recently many other industries have also followed suit (Cook and Semouchtchak, 2004; Czabke, 2008; Broring and Cloutier, 2008; Carleysmith et al., 2009).

Issues in New Product DevelopmentNew product development issues highlighted in the PD literature can be broadly classified into three categories – management issues, technical issues, and relational issues – as described in the following sections.

Management Issues. Product development is a complex process that is best managed as a project. Both internal and external issues drive the efficiency of the PD process. Internal process

1

Exhibit 1. A Generic Stage-Gate Product Development Process (adapted from Yadav et al., 2007)

Exhibit 2. Proposed Lean Product Development Transformation Framework

Problem definition

Formulation of lean process strategies

Implementation and continuous improvement

Analysis of the current state NPD Process

Creation of the future state (Lean) PD Process

NeedRecognition MarketingProductionTesting and

RefinementDetail Design

DesignSpecifications

ConceptDevelopment

NeedRecognition MarketingProductionTesting and

RefinementDetail Design

DesignSpecifications

ConceptDevelopment

Gate 1 Gate 2 Gate 3 Gate 4 Gate 5 Gate 6

Exhibit 1. A Generic Stage-Gate Product Development Process (adapted from Yadav et al., 2007)

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management involves planning activities and coordinating resources among multiple players across various functional departments; however, unlike classical construction management-type projects, PD projects at times involve planning iterations to improve quality, making the scheduling of design activities a difficult task because of rework and dependency among key activities. Since PD process consists of several (desirable as well as undesirable) iterations, the management of smooth flow of information (design flow) is a critical issue, especially when quality of information and execution time fall short of required targets. The management of the workflow (or information flow) is closely associated with technical and relational issues and therefore requires a comprehensive approach to deal with it.

External management issues primarily include supplier management, involving setting clear goals for suppliers, clearly communicating expectations and requirements, setting targets and prototypes in order to enforce goals, managing supplier PD processes, and making unambiguous connections between people. Furthermore, supply base management has far-reaching effects beyond PD time and cost in terms of an OEM’s overall success in the market. For example, in the automotive industry, suppliers contribute more than 70% of the vehicle content, or total vehicle value (Leenders et al., 2002); therefore, the quality and performance of parts from a supplier significantly determine the final vehicle quality (Froker, 1997). Womack et al. (1991) suggest that working simultaneously with suppliers can not only shorten product development time but also improve product quality and product costs. Binder et al. (2007) highlight the paradigm shift in automotive product life cycle practices. The authors argue that after “Fordism” and “Toyotism,” current business philosophy in the automotive industry is characterized by a partnership and relational model, as opposed to traditional adversarial and contractual models. Despite these efforts by the large companies, research shows that many companies are still not successful in terms of early supplier integration into NPD projects (Handfield and Lawson, 2007), thereby affecting the overall productivity of the PD process.

Technical Issues. Numerous tools, such as quality function deployment, design of experiments, design optimization, risk management, and reliability analysis are used at various stages of product development process. Achieving seamless integration of these tools in the PD process, however, has been a great challenge. The outputs (data) from one set of tools are not compatible with supporting the analysis of other tools, causing the loss of information during transition and transformation, or sometimes failing to convey relevant information to the succeeding tool. Thomke (2006) points out the weakness of automotive companies “using new tools merely as substitutes, adding (instead of minimizing) interfaces, and changing tools, but not people’s behavior.” In addition, it is extremely important to integrate tools, technology, knowledge, and hardware/software with suppliers (Hobday et al., 2005), since supplier content is normally higher in any moderately large and complex product (Monczka et al., 2008).

Relational Issues. One of the widely cited problems in design factories is late design change and its impact on overall development time and cost. As a major step to minimize these problems, researchers and practitioners have underscored the need for early tracking of problems through collaboration and front loading (Brown and Eisenhardt, 1995; Griffin and Hauser,

1996; Thomke and Fujimoto, 2000). These problems are internal relational issues that occur due to lack of trust and clarity in information sharing. For example, in order to ensure smooth and instant flow of information, it is important to clearly specify the source of information, the mechanism of information exchange, the format of information sharing, the information request procedure, and finally, the means of getting information directly from the source to the point of need. This process requires clearly defined pathways in order to avoid inefficiencies of routing information exchange through management hierarchy and the requirement of many approvals to get information.

On the other hand, external relational issues involve mainly suppliers. We believe that an effective supplier performance measurement and relationship management process should include the following: 1) clarity of expectations, 2) gathering of suggestions for concept design improvement to achieve lower cost and higher reliability, 3) target dates (time frame), 4) mechanism for observing or monitoring progress, 5) mechanism to address design specification deficiencies, 6) supplier development program, and 7) training and development to improve competencies. While there is an agreement on the need for collaboration between organizations, a structured framework for such collaboration is still lacking (Binder et al., 2007). By establishing internal customer and supplier interaction, the same partnership and relational model approach can be applied to intra-organizational performance improvement. Certainly, having a new set of tools and technologies is not enough for successful implementation of innovative ideas. The new tools and techniques should be properly integrated across the PD process to provide seamless flow of information by implementing lean principles (Yadav et al., 2010). The lean product development case study presented in this article illustrates how lean thinking can help integrate design tools and techniques to accomplish the ultimate goal of reducing time to market and overall cost of the NPD process.

Lean Thinking in Product DevelopmentLean principles, widely recognized as the essential principles of the Toyota Production System (TPS) (Ohno, 1988), have been successfully embraced by the manufacturing arm of Toyota Motor Corp. While the application of lean techniques offers the potential for significant improvements in product development cycle time and cost, in reality this transfer is complex (Larlsson and Ahlstrom, 1996). In order to make the transformation process easy and effective, it is important to clearly understand and define non-value added activities in the PD processes. Just as in manufacturing processes, the non-value added activities in the PD process can be defined as follows (Ohno, 1988; Liker, 2004; Morgan, 2005; Reinertsen, 2009):

overproduction: designs turning faster than testing •capabilities, or overdesign. defects: misunderstood customer requirements resulting •into unacceptable specifications. transportation: many handoffs of information and too many •required approvals. overprocessing: • not invented here; rework as a result of late problem discovery (undesired iterations). inventory: queues of unprocessed information (poor •sequencing of design tasks). unnecessary movement: poor data organization. •waiting: resource conflicts; late information, hardware, •software (poor sequencing).

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underutilization of staff knowledge and skills: problems not •solved at the lowest levels; decisions taken without consulting local experts; customer and employee feedback ignored in new designs.

Furthermore, in order to accomplish this transformation of PD processes into a lean PD process, Ward (2007) describes five pillars of lean PD: 1) value focus, 2) entrepreneur system designers, 3) set-based concurrent engineering, 4) flow-based pull systems, and 5) cross-functional teams with experts. Similarly, Browning (2003) also emphasizes the importance of defining value of the PD activities before eliminating waste, while adding that in order to accomplish the real benefits of a lean process, it should be looked at from a system’s perspective.

Lean PrinciplesIn this section, we present a few lean principles that can be adapted to a PD environment. Womack and Jones (2003) describe the following five principles related to lean thinking: 1) specifying value from the customers’ perspectives, 2) identifying the value stream, 3) making the value-creating activities flow, 4) customer pulled-value, and 5) pursuit for perfection. Toyota has been implementing these principles in both manufacturing and product development (Liker, 2004). In particular, the reduction of excessive process variability, the creation of flow, and the elimination of waste are seen as key elements of lean principles in product development (Reinertsen, 2009). This section highlights the application of those principles in the context of a PD environment based on a benchmarking study of Toyota Product Development Systems.

Standardization of Processes. At Toyota, all activities are highly specified with respect to content, sequence, timing, and outcome (Spear, 1999). Through standard operations in manufacturing, Toyota achieves multiple goals such as high productivity, balanced production lines, minimum level of work-in-process inventory, and reduced variability in operations (Monden, 1997; Spear and Bowen, 1999). Furthermore, this approach increases learning efficiency, allowing new employees to learn to perform their jobs in just three days (Shingo, 1989). In product development, standardization implies maintaining a standard format or reporting system for information exchange and other routine tasks. Toyota has successfully standardized much of its product development process as well. Routine work procedures – such as design blueprints, A3 reports, and feedback forms for design reviews – are also highly standardized (Sobek et al., 1998). All reports follow the same format, allowing employees to easily locate the definition of the problem, the responsible engineer and department, the results of analysis, and the recommendations (Yadav et al., 2010).

Simple and Specified Pathways for Information Flow. The objective of this principle is to develop a clear connection between the teams and activities so that a leveled flow of information can be maintained throughout the PD process (Yadav et al., 2010). Simple and specified pathways encourage PD organizations to create a standard format for information request and information exchange by identifying the source and the mechanism for information flow. It ensures that all pathways are set up in such a way that every product, as well as all information, flows along a simple and specified path; however, the stipulation that every product follows a simple and pre-specified path doesn’t mean that each path is dedicated to only one particular product. For

example, at Toyota plants, each production line typically can accommodate more than one type of product (Spear and Bowen, 1999). A consistent motto of Toyota engineers is to simplify and to specify the paths to be followed by the product regardless of whether designing or manufacturing the product.

Teaching and Learning. In lean product development organizations such as Toyota, teaching and learning evolve through unique relationships among managers, supervisors, and workers. While supervisors and higher-level managers are deeply involved in the details of engineering design, they rarely tell their subordinates what to do, instead answering questions with questions (Sobek et al., 1999). They force engineers to think about and understand the problem before pursuing an alternative, even if the managers already knew the correct answer. Supervisors normally come to the worksite and ask series of questions (Spear and Bowen 1999), such as: How do you do this work? How do you know you are doing this work correctly? How do you know that outcome is free of defects? What do you do when you have a problem? The iterative questioning and problem-solving approach leads to effective learning and builds knowledge implicitly. Further, Toyota uses checklists to ensure that the proposed design follows standard process and testing procedures during design reviews and final approval. Thus, the tacit knowledge of an experienced engineer is transferred to the new generation of engineers through active learning, and checklists become the “playbooks” to minimize variation between different managers across a large organization such as Toyota Motor Corp. The result of this unusual manager-worker relationship is a higher degree of sophistication in problem solving and learning at all levels of the organization (Yadav et al., 2010).

Coordination and Rich Communication. To transform an idea into an innovation, it is important to have effective coordination among groups and individuals who are sufficiently knowledgeable about the problem at hand. Lack of communication can cause rework and late design changes during product development. In one study conducted on the product development process of a U.S. car company, we found that over 70 percent of rework was due to lack of communication and poorly defined engineering specifications (Yadav et al., 2010). The primary reason for poor communication is the lack of effective coordination among people within organizations.

It is argued that the best mode of communication and coordination in product development is a face-to-face talk with people from other functional areas and suppliers. Communication in the form of written reports and memos lacks the richness of information and the interactive qualities needed for problem solving (Yadav et al., 2010). On the other hand, face-to-face meetings are costly in terms of time and efficiency, and usually involve limited value-added work per person. Also they easily lose focus and drag on longer than necessary. In lieu of regularly scheduled meetings, therefore, Toyota emphasizes written communication supported with visuals and, where possible, captured in an A3 format (Sobek et al. 1998). If there are disagreements, then it is considered best to hold a well planned, agenda-based meeting to hammer out a decision face-to-face. In fact, to improve communication and minimize waste specifically due to rework because of misinformation or communication gaps, Toyota uses the principle of “go-see” and involves suppliers early on during the concept phases of the product development process.

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Continuous Improvement. Standardization, learning, coordination, rich communication, and path simplification are the essential building blocks for improvement of a PD process and provide a specific base to continuous improvement. These principles provide vehicles and preconditions for improvement. The Toyota product development system encourages its engineers to look at problems closely and experiment to improve their own work systems through a scientific problem-solving approach for minimizing risk. This “catch ball” system between managers and workers implicitly teaches people how to improve while not expecting them to learn from personal experience (Yadav et al., 2010). The distinctive feature of Toyota’s continuous improvement effort on product activities, supplier-customer relationship, or any other process is that the pathways must be made in accordance with a scientific method under the guidance of a teacher and at the lowest possible organizational level (Spear and Bowen, 1999). To make changes, people are expected to communicate the explicit logic of the hypothesis using the problem-solving format, which requires that employees fully explore all their improvement opportunities with their manager/teacher through a series of catch-ball discussions.

Supplier Relationships. The Toyota principle fosters suppliers’ and partners’ growth for mutual benefit (Liker, 2004). Toyota ensures that every connection between people is standardized, direct, and unambiguous. It specifies the form and quantity of the goods and services to be provided, the way requests are made by each customer, and the expected time in which the request will be met. It creates a direct supplier-customer relationship between the individuals who are responsible for providing and receiving a particular good or service. This clarity of how people connect with one another leaves no gray zones in deciding who provides what to whom and when (Sobek et al., 1998). As mentioned in Yadav et al. (2010), for outside suppliers, Toyota manages its supplier relationships very tightly. It sets clear and understandable goals, communicates consistently to suppliers, and subsequently uses targets and prototypes to enforce these goals. These targets play different roles in different supplier relationships and in determining the nature of relationship. Toyota maintains different types of relationships with suppliers

based on its requirements, the suppliers’ capability, its willingness to share information with the supplier, and on both companies’ strategic requirements. Kamath and Liker (1994) identify a range of postures that Toyota and suppliers can adopt within a long-term cooperative relationship.

In summary, lean thinking has been garnering significant attention in product development organizations because of its potential to save both time and cost. The precedent lean literature, however, is largely limited to industries producing very large products, such as the automotive and aerospace industries. This article extends the lean literature by demonstrating the application of lean PD in different types of products varying in size and complexity. More importantly, the lean approach adopted in this article integrates other process optimization tools, such as the design structure matrix, to be better able to explore disconnects within the PD systems. This examination of disconnects cannot be accomplished by value-stream mapping alone. In other words, the current state-of-the-art process is analyzed by using tools such as the design structure matrix and the cause and effect matrix, in addition to value stream mapping (VSM), for determining waste, rework (undesired iterations), and other non-value added activities. Based on findings from the analysis of the current state process, we apply lean principles mentioned earlier to create the future state process. The next section details the approach adopted for the lean PD transformation framework.

Lean Product Development Transformation Framework: a Case StudyIn this article, we present a case study of a lean product development project for a moderately large and complex product used in office buildings. This product is developed and manufactured by a U.S.-based company, which is referred to here as ABC Manufacturing. In order to protect the identity of the company, further details of the company and its product are not revealed. The proposed lean PD transformation process utilizes a five-step framework for transforming a traditional product development process into a lean product development process (see Exhibit 2): 1) problem definition, 2) analysis of current state PD process, 3) lean strategy formulation, 4) development of future state or lean PD process, and 5) implementation of the new PD process.

1

Exhibit 1. A Generic Stage-Gate Product Development Process (adapted from Yadav et al., 2007)

Exhibit 2. Proposed Lean Product Development Transformation Framework

Problem definition

Formulation of lean process strategies

Implementation and continuous improvement

Analysis of the current state NPD Process

Creation of the future state (Lean) PD Process

NeedRecognition MarketingProductionTesting and

RefinementDetail Design

DesignSpecifications

ConceptDevelopment

NeedRecognition MarketingProductionTesting and

RefinementDetail Design

DesignSpecifications

ConceptDevelopment

Gate 1 Gate 2 Gate 3 Gate 4 Gate 5 Gate 6

Exhibit 2. Proposed Lean Product Development Transformation Framework

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While this framework clearly shows similarities with classical process improvement frameworks, such as the Six Sigma DMAIC approach, Deming’s PDCA-cycle, as well as the five improvement steps defined by Womack and Jones (2003), the following sections illustrate how the application of specific tools in each step of the proposed framework is important to support the creation of a lean product development process; therefore, the following section details each step of the proposed framework.

Step I: Problem DefinitionA key step in the problem definition phase is to benchmark or identify gaps in the as-is (current state) process as compared with the best-in-class industry leaders. The benchmarking process was divided into two phases. The first phase was limited to reviewing internal documents and interviewing stakeholders of the PD process, including major suppliers. In the second phase focus was on learning best practices from the company that is a leader in lean PD. Following is a brief description of both internal and external benchmarking studies.

Benchmarking of Internal Process of ABC Manufacturing. In 2006, the senior management of ABC Manufacturing challenged its product development organization to reduce their time-to-market cycle time by 50% for the next development cycle. With the help of their Lean Six Sigma colleagues, the NPD team identified methods to reduce cycle times by implementing lean methods. The current PD process was highly disintegrated and poorly coordinated, causing long waiting times. Although good processes were in place, they were not standardized; therefore creating an imbalance in the workflow, and ultimately, tremendous waste. The senior leadership tasked the NPD organization with the following expected deliverables:

create value-stream map of the current process and identify •value-added versus non-value-added activities consider all past projects for compatibility to the VSM findings •develop a future-state VSM by eliminating non value added •activities provide rationale as to how and why these activities are “non-•value adding” determine what must change in the process, methods, or •organization, etc. establish cycle time bands, current and target •develop a project and change management plan by identifying •sponsor, team, key elements and timeline

Benchmarking of Best-in-Class PD Process. Considering Toyota being the industry leader in lean product development, this section presents the findings of studies on Toyota. The major sources of this benchmarking were published literature (Ward et al., 1998; Sobeck et al., 1998; Liker, 2004; Morgan, 2005) and interviews with researchers of the Toyota Product Development System (TPDS). TPDS is the result of an evolutionary process for improving the company’s PD process via continuous learning and improvement. There are three primary subsystems within the TPDS that form a complex socio-technical product development system and are worth mentioning here.

Process Subsystem. The process subsystem contains all tasks and the sequence of tasks required to bring the product from concept to the start of the production, that is, information, customer needs, past product characteristics, competitive product data, engineering principles, and other inputs that are transformed

through the product development process into the complete engineering of a product to be built by manufacturing (Liker, 2004). The Toyota process subsystem can be characterized by the following principles (Morgan and Liker, 2006): 1) development of a value-stream map to separate customer–defined value-added activities from waste; 2) front-loading of the PD process to minimize expensive engineering change; 3) creation of a leveled process flow by identifying tasks and dependencies so they can be scheduled as parallel, sequential, or integrated; 4) standardization of processes to increase flexibility and reduce variations; and 5) set-based concurrent engineering.

People Subsystem. The people subsystem includes the selection and recruitment of engineers and their training and development in the organization’s leadership style, structure, learning process, and other subtle interactions that are critical for success, such as corporate culture. A measure of the strength of the culture is the degree to which these interactions are truly shared across all members of the NPD organization. Toyota has a very strong lean culture compared with most companies (Liker, 2004). Toyota develops a chief engineer role to lead product development efforts, and its PD teams are composed of cross-functional experts, including suppliers (Oppenheim, 2004). The other key characteristics of people subsystems are: 1) cross-functional integration, 2) higher-level technical competence in all engineers, 3) building on learning and continuous improvement, and 4) full integration of suppliers into the PD process (Morgan and Liker, 2006). Supervisors and higher-level managers significantly influence the learning and problem-solving skills of the people system by playing the role of coaches and mentors.

Tool Subsystem. Tools and technology are embedded into a scientific approach to bring a vehicle into being. This subsystem not only includes CAD systems, machine technology and digital manufacturing, and testing technologies, but the tools that support the efforts of people involved in the development project, whether for problem solving, learning, or standardizing best practices and values (Liker and Morgan, 2006). The idea is to embed the scientific problem-solving approach into tools and into the process itself. While Toyota uses only reliable and thoroughly tested technology, it is still a believer of the old-fashioned method of visual control tools (e.g., boards). The company uses technology to enhance visuals controls but not to replace them (Liker 2004). Toyota has successfully embedded appropriate tools and techniques into its scientific problem-solving approach to develop an integrated problem solving approach.

Based on the benchmarking studies, the following objectives were set for improving the current PD process of ABC Manufacturing:

reduction of the product development cycle time by 50%•improving electronic product development capability•increasing the number of ideas with high market share •and payback potential by driving “big win” innovation and understanding market needsincreasing the number of products launched per year•improving the quality of new product launches by reducing •the number of defects and overall warrantydeveloping system standards and process enablers•

Step II: Analysis of the Current State PD ProcessThe current process was analyzed using tools such as VSM, the cause-and-effect matrix, and DSM. The VSM was mainly

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employed for identifying the non-value-added activities (NVAs), such as reworks and waiting. Once NVAs were identified, the DSM in the next stage was created to facilitate understanding of the nature and the root causes of those NVAs. In addition, we also used the cause-and-effect matrix to prioritize the root causes by determining the significance level of an activity with respect to its impact on PD process performance. The following paragraphs describe how these tools were applied to improve the current ABC PD process.

VSM is a proven technique for displaying processes and information flows during the product development process and for identifying waste in the system. It is a powerful analytical tool for reducing waste and synchronizing activities in manufacturing and product development. Before mapping the current value stream of any process, we define the “value” of activities based on process objectives and the role of each activity in satisfying customer requirements. Thus, any unintended additional design or engineering work that would not add any value to the customer (either internal or external) was considered as waste.

For data collection, several face-to-face workshops were conducted with the corresponding engineering and marketing teams. Based on these workshops and project data, an engineering activity log was created, as shown in Exhibit 3. The activity log captured the list of activities occurring during product development; that is, after the project scope was defined based on market potential through the program close or product launch.

The activities in Exhibit 3 are listed in a chronological order. Further, two types of timing are documented in the activity log: total time spent on an activity and the corresponding cycle time reduction opportunities. The time spent is defined as the duration of time between receipt of information and delivery of the design to the next level of customer. The difference (time spent in the system less actual activity time) highlights the opportunity for reduction of time for that activity. Although one could have directly created a value-stream map without creating an activity log, we propose to have both, because the activity log on a separate spreadsheet allows us to construct the DSM for further analysis.

The as-is process steps shown on the activity logs were transferred into VSM icons as shown in Exhibit 4.

Major Instances of Waste. Our analyses on the current state of the VSM for the project under study showed several opportunities for cycle time reduction by eliminating the NVA activities. For example, there were six instances that caused major delays in the process:

no business case process (30 weeks), •incomplete VOC data (19 weeks), •non-standard tolerance stack methods (12 weeks), •inaccurate cost modeling (15 weeks), •supplier pricing quoted from models (6 weeks), and •resource changes (5 weeks). •

Using DSM to Analyze the Rework. In the NPD processes, information exchange, which involved feedback and iteration of activities, is the lifeblood of experimentation and innovation. Excessive iteration or continual back-and-forth of work, however, unnecessarily consumes time and resources. Additionally, the increasing pressure of global competition is forcing organizations to manage PD processes more effectively and eliminate the necessity of iterations or rework, if possible, to save time and resources. The careful analysis of existing PD processes indicates that an iterative process may turn out to be marginally beneficial or even wasteful; therefore, to understand the necessity of rework and to map the current PD process, we propose to use a DSM. Since a DSM (Eppinger, 2001) focuses on the representation of information flow in a project rather than work flow, it will clearly reveal information exchanges involving design driven iteration and those that do not. Depending on the information flow requirements, it further helps classify the tasks into three different categories:

sequential tasks: tasks which rely on information generated •by earlier tasks; parallel tasks: tasks that can be carried out simultaneously, as •there is no information exchange between them; and,coupled tasks: interdependent tasks that share information •among each other (require iterations).

2

Exhibit 3. A Sample List of the Engineering Activity Log and Cycle Time Reduction Opportunities for Project 1

Exhibit 3. A Sample List of the Engineering Activity Log and Cycle Time Reduction Opportunities for Project 1

59March 2011Vol. 23 No. 1Engineering Management Journal

Further, DSM is a tool proven to optimize information flow by rearranging the sequence of tasks. By doing so, we can minimize iterations, plan concurrent activities for interdependent tasks, and reduce information exchanges by either transferring key knowledge between teams, or by adding one or more new tasks. In this article, we used DSM to first map the current PD process (see Exhibit 5a), which allowed us to gain insights about existing tasks, including their sequence, and number of iterations being performed. Based on that knowledge, we were able to distinguish essential iterations from non-value added ones. For example, DSM-Before in Exhibit 5a shows the very first task, define project scope, does not feed any (useful) information to succeeding tasks. Moreover, defining project scope before even carefully identifying customer and market requirements is not a useful exercise. During our discussion with the design team, therefore, we agreed that this redundant task can be eliminated. We also discovered several iterations – X marks above the diagonal represent iterations – among concept design, design verification, testing tasks, and few other tasks as shown in the DSM-Before. The main causes of these iterations were insufficient identification of customer requirements and lack of alignment in customer and business requirements while developing new concepts. In the current PD process, this deficiency gets exposed at later stages during the design verification and testing phase only when designs fail to fulfill functional requirements. The impact of these iterations was that few people worked carefully on capturing customer requirements in the early stage because everyone knew that extensive rework would occur down the line.

In order to streamline the PD process and reduce development time, we redesigned the PD process by eliminating tasks, added new tasks, and/or combined tasks, as shown in the DSM-After (see Exhibit 5b). We added few tasks in the beginning to ensure effective mapping of customer and business requirements while generating new concepts in an effort to avoid later design changes and iterations. Although we still expect some iteration between design validation and testing and the concept of the design phase, the frequency and intensity of rework will be very low. The first two tasks, determine customer requirements and identify business case, are parallel tasks with no mutual information exchange, and, therefore, can be carried out simultaneously. Additionally, supplier selection and integration and determine product specifications are coupled tasks, sharing information, and thus we recommend that they be performed concurrently in close collaboration to avoid any design changes later, saving time and effort. We have added another task, program execution plan, and combined it with define marketing plan as a major gate to ensure that all previous tasks have been performed effectively and that selected design concept(s) possess all required characteristics before undertaking last three major tasks. Furthermore, this effort has also helped us in planning and scheduling of tasks and in assigning the key knowledge (expert) between teams to reduce necessity of information exchange. For further understanding and application of DSM, readers are advised to refer to Eppinger (2001). It is important to note that integration of the DSM into the lean PD transformation framework supports the principle (c) of the process subsystem discussed in section above.

Exhibit 4. Current State VSM for the Development of a New Large and Complex PD Project (Product 1)

3

Exhibit 4. Current State VSM for the Development of a New Large and Complex PD Project (Product 1)

60 March 2011Vol. 23 No. 1Engineering Management Journal

Causes of Waste. Based on analysis of the various instances of waste and the relationship among the activities identified through the DSM, the sources of waste were characterized as being due to either waiting or rework. Waiting times were primarily due to the need for resources and information, whereas the reworks were mainly caused by lack of appropriate business processes,

standard procedures, and NPD capabilities. We used a cause and effect matrix for identifying causes of longer NPD process lead times and their effect on the overall PD cycle time. A cause and effect matrix is a Six Sigma process improvement tool that helps identifying activities responsible for generating non-value added activities. Causes for delay in the PD process were found to be poor

Exhibit 5a. DSM Showing the Dependency Among the Activities – DSM Before (As-Is)

Exhibit 5a: DSM Showing the Dependency Among the Activities – DSM Before (As-Is)

Defin

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Plan

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Early

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Define project Scope

Determine Customer Requirement X X X X

Generate Concepts X X X X

Select Concepts X X X X X X X

Justify NPD project X X X X X

Define Marketing Requirements X X X

Define product Specifications X X X X X X X

Design Manufacturing Planning X X X

Early Prototype Testing X X

Design Verification & Testing X

Exhibit 5a: DSM Showing the Dependency Among the Activities – DSM after (To-Be)

Dete

rmine

Custo

mer

Requ

irem

ents

Iden

tify B

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ss Re

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Determine Customer Requirements X X X

Identify Business Requirements X

Project Planning & Business Case(QFD mapping) X X

Concept Generation (QFD mapping) X X X X X

Concept Selection X X X X X X

Supplier Selection and Integration X X X X

Determine Product Specs. X X X X X

Program Execution Plan (Define Mktg Plan) X X

Advance production Plan X X X

Detailed Design X X X

Design Verification and Testing X X X

Exhibit 5b. DSM Showing the Dependency Among the Activities – DSM after (To-Be)

Exhibit 5a: DSM Showing the Dependency Among the Activities – DSM Before (As-Is)

Defin

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Define project Scope

Determine Customer Requirement X X X X

Generate Concepts X X X X

Select Concepts X X X X X X X

Justify NPD project X X X X X

Define Marketing Requirements X X X

Define product Specifications X X X X X X X

Design Manufacturing Planning X X X

Early Prototype Testing X X

Design Verification & Testing X

Exhibit 5a: DSM Showing the Dependency Among the Activities – DSM after (To-Be)

Dete

rmine

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Determine Customer Requirements X X X

Identify Business Requirements X

Project Planning & Business Case(QFD mapping) X X

Concept Generation (QFD mapping) X X X X X

Concept Selection X X X X X X

Supplier Selection and Integration X X X X

Determine Product Specs. X X X X X

Program Execution Plan (Define Mktg Plan) X X

Advance production Plan X X X

Detailed Design X X X

Design Verification and Testing X X X

61March 2011Vol. 23 No. 1Engineering Management Journal

alignment of priorities, poor decision making with incomplete information, and lack of accountability (see Exhibit 6).

The causes of waste were then prioritized for the PD process improvement based on their importance to the customers. The cause and effect matrix in Exhibit 6 prioritizes root causes at a higher level of the PD process; however, similar matrices can be developed at each stage of the PD process to prioritize the root causes of the problem.

Step III: Optimization of the New Product Development Process to Reduce the Cycle TimeThe optimization phase deals with the creation of the future-state value-stream map by eliminating waste as much as possible. From the current state VSM, it was revealed that out of 166 weeks between Month 1-Year 1 and Month 1- Year 3, only 27% of time was spent on value-added activities; the rest was spent on some form of muda, a Japanese term for non-value added activities. The remaining 73% (or 121 weeks) wasted time comprises 33% (55 weeks) for waiting, 28% (46 weeks) for rework, and the rest 12% (20 weeks) can be assigned to other non-value added activities as defined in the lean principles. While creating a future state NPD process for the given project, the following five strategic areas were targeted for improvement:

product portfolio management: idea to project kick-off 1. (roadmaps, MRD, VOC, and business case) design and development hand-offs: project start to close-out 2. (design, test, source, process, and launch) supply chain management: idea to project close-out (sourcing 3. strategy, supplier selection, supplier development, tooling) resource and overall NPD process: idea to close-out (manage/4. maintain the overall process and resources management) NPD systems: tools to automate process and manage data 5.

Formulation of Lean Strategies to Optimize the NPD Process. To eliminate the cycle time waste out of the NPD process, some basic concepts of lean philosophy were employed in the case study presented here. These included minimizing stages, single piece flow, takt time-based scheduling, dedication, and continuous flow driven by a customer pull system. The new optimized process eliminated many intermediate non-value-added stages in the project definition and concept generation phase by creating a business cell – the same concept as U-shaped cells in lean manufacturing – in which quality function deployment was applied to capture the voice of customer (VOC) to generate a new design concept along with the business case. The business cell consisted of dedicated associates with multiple skills. The formulation of a standard business process for capturing the VOC and generating design concepts resulted in reducing iterations between design testing and concept design tasks of the PD process to avoid rework.

Further, a design flow stream was created by employing the concept of single-piece flow to eliminate waiting time (Sarkar, 2008). The single-piece flow results in reduction in lead times, proper load distribution among process associates, and faster detection of problems; however, FIFO due dates were assigned where the single-piece flow model was not achievable due to practical circumstances. The pace of the PD process was modified based on the takt time, and Heijunka (Liker and Morgan, 2006) boxes were used to visually display and level work schedules. While determining the number of associates for each task, the complexity of the task was considered so that a balanced work flow could be created and maintained. The iteration requirement between coupled tasks (or teams), identified by activity mapping in the DSM, was another critical consideration while assigning the technical expert associates to tasks (or teams). Finally, at each

Exhibit 6. Cause and Effect Matrix at the Higher Level of the PD Process

Exhibit 6. Cause and Effect Matrix at the Higher Level of the PD Process

NA

9 3 1

Inadequate Direction

Inadequate Resourcing / Communication

Non Standard Process

Total

Poor Alignment of Priorities in Business 9 1 82

90

87Started without Full team 1 9 3 39Poor Collaboration between Functional Groups 1 9 1 37Lack of Accountability 1 9 9

45

Lack of / Level of Communication –Stakeholders Not Engaged, Different Expectations

28

33

12No Process to Create a Business Case 3 1 3

33

27

37

37

3 1 3

Started Without Approved Business Case or MRD 1 3

1

9

NVA Reviews after Fact 9 1

Engineering Picked Final Concept Prior to MRD or Prod Spec Being Written

9 1 3

Resource Changes (People & Capacity) 1 9 1

Rating of Importance to Customers

Effects

Cau

ses

Concept Generated/Selected at Phase 0 9 3

Big Difference between “Assigned” Resources and “Dedicated” Resources

1 9

Poor Cost Model / Target

NA

NA

NA

NA

62 March 2011Vol. 23 No. 1Engineering Management Journal

stage, information (in this case the design of the product) was processed (or developed) based on the demand of its immediate customer; in other words, to produce what is needed and when is needed by the customer continuously without any interruption. This phenomenon in lean thinking is known as a pull system. Exhibit 7 depicts some key terms employed in formation of lean strategies to optimize the NPD process. The output of the optimized DSM provided very useful information in planning activity sequencing and scheduling. Moreover, the front-loading of the PD process and assigning technical experts to teams enabled changing attitudes and beliefs of employees towards the previously considered necessity of rework closer to launch dates. This built confidence and encouraged the teams to meet necessary requirements as defined in the project plan.

Lean Management Structure. The NPD organization was redesigned to match the lean management structure. The objective of a lean structure is to ensure alignment, ownership, teamwork, communications, and visibility across the PD process. The key notable changes in the process management structure were: standardization of tasks, use of the Heijunka visual board for leveling the work flow, creation of cross-functional teams to improve the quality and productivity and enhance flow by resolving difficult technical issues (Lovelace et al., 2001; Liker, 2004), instilling a teamwork culture by teaching individuals how to work together as teams towards common goals, and ensuring that the team leader understands the daily work in detail so he or she can be the best teacher of the company culture and philosophy. The expertise and knowledge of leaders play a crucial role in mentoring and motivating other team members.

Step IV: Future State Value-Stream MapAs mentioned earlier, the future-state VSM was developed by employing lean principles. The future-state VSM for the NPD project under study (Exhibit 8) consists of a streamlined NPD process with cellular functional departments. For instance, the business case cell is tasked to develop a business case and create a project plan. The project pipeline plan is visually displayed

through an Heijunka box. Supplier selection is done early in the development stage so that suppliers are fully integrated into the system during the PD process itself. Similarly, concept specification generation and selection, detail design and test, tooling and design verification and testing are all part of a bigger cell. The cellular workplaces are composed of cross-trained developers who can perform multi-functional tasks. Within each cell, the teamwork is balanced internally by considering the task complexity levels. While project designs are processed as packages, single project launch dates are determined using a FIFO model. Each task is scheduled using takt time under a pull system, thereby maintaining the continuous flow. The output of the revised DSM was used to determine the sequence of each task within each cell, as well as at each stage of the PD process. Similarly, the iteration requirements between tasks or teams were managed by planning those tasks concurrently, adding more tasks/resources, or sharing technical expertise (technical specialist) to reduce iteration requirement and development time. For example, the development of standard business processes that capture VOC and generate design concepts by adding few more tasks at the front-end (concept generation) stage demonstrates how the addition of few tasks can eliminate iterations and avoid necessity of rework.

Step V: Process Implementation StrategiesThe process implementation strategies adopted in this case study can be divided into four strategies as described below.

First Strategy: Launch Lean Improvement Strategies in Two Phases. The first strategy ABC Manufacturing’s process improvement team took was to launch the lean improvement strategies in two phases. The phase 1 goal was to stabilize and implement “quick win” improvements – in other words, low-hanging fruits. In phase 2, the target was to complete 80% of NPD in less than 18 months with an average cycle time of 12 months. The primary improvement strategy was to redesign process and organization by applying lean principles. Exhibit 9 provides a comparative analysis of current and target performance levels upon the implementation

Exhibit 7. Key Lean Concepts Used in Creation of the Future State VSM

Exhibit 7. Key Lean Concepts Used in Creation of the Future State VSM

Cycle Time - Time from Business Case started to Launch- Will track projects through closure for seamless transition and quickly free resources

Continuous-Flow - No waiting between tasksFIFO - First in Fastest Out

Pull & Sequencing - Next project is pulled when resources for the entire project are available- The order for starting projects is defined by Product Roadmaps - Active projects are not prioritized, rarely need to expedite, the pipeline is right-sized- If an urgent “disruptive” project is pushed, other projects are stopped

Core Teams (committed) -Follow each project from start to close, for accountability and minimize handoffs- Can work on multiple project if they have capacity and projects are sequenced

Cells - Work elements with cycle-time entitlements, a group of resources, tasks & deliverables- Can be very cross functional and cross trained teams (break down organizational barriers)- Can be dedicated to a cell (for example: expert cells for financial modeling, rapid prototyping)

Scalable - Most process steps, cells and resource will apply to most project- Project effort and cycle-time will be adjusted based on scaling criteria

Cycle Time - (Launch date) – (BC start date), complexity normalized- (Finish) – (Start date), for each cell (work element)

NPD Capacity -Sum of projects completed for a given time period (complexity normalized)NPD Efficiency -(Projects completed) / (Resources consumed)

63March 2011Vol. 23 No. 1Engineering Management Journal

of lean strategies. It shows a 32% reduction in cycle time in the first phase. Further, it was expected that improvement in the cycle time reduction could be gained as much as by 68% by the end of the second phase, surpassing the original improvement target of 50%.

Several improvement projects were identified, and their relative impacts on cycle-time reduction were assessed. Of nine improvement projects identified, five were planned in phase 1 and four in phase 2 (see Exhibit 10). Phase 1 activities planned for the first year include: 1) developing and implementing a cross-functional NPD capacity-management system, 2) creating a robust front-end process, 3) supplier integration and development, 4) improving process design hand-offs, and 5) improving the project management skills set. Other improvement projects were targeted for phase 2 or within two years. In Exhibit 10, the names of the project lead have been removed to protect the identity of the people and the company.

Second Strategy: Improve the Front-End Process Through Early Stakeholder Involvement. The idea here is to front-load the tasks by initially involving all the stakeholders as much as possible to minimize waiting and rework due to lack of information. Two examples of front loading are worth mentioning here. First, NPD idea screening and a road map for new product development projects were created in less than two weeks even before the actual NPD project clock started ticking. Early accomplishment of these projects was possible due to maintenance of a product-improvement pipeline through R&D efforts outside the NPD organization. This effort required re-invigorating the R&D function, which had been sidelined over the course of several reorganizations. Second, the NPD business case with marketing requirements was approved in less than 1 to 3 months (depending upon the project size) after the NPD project was started but prior to the start of the actual PD process. It is also important to note the assumptions behind this front-end process improvement plan, which include the creation of a cross-functional team with

multiple skills and the use a new process equipped with lean tools and techniques. Furthermore, it was assumed that the project could be killed at any time if it did not seem to be feasible.

Third Strategy: Focus on Project Management. The third strategy for ABC Manufacturing was to focus on the project management aspect of the NPD process, especially related to human resources. The lean strategy formulation team suggested assigning more full-time project managers, to be overseen by a senior project manager. The NPD project organization had resembled a matrix structure and followed a program management process. Another recommendation was to make the project manager assignment at least a two-year commitment to minimize or eliminate delay-causing hand-offs. The current and proposed resource allocations for the program management organization (PMO) and functional organizations are shown in Exhibit 11.

Fourth Strategy: Improve the Front-End Process with Improved Pipeline Management. This process was jointly managed by R&D and market research teams which were both part of NPD and Marketing; however, in the new lean process the headcount was reduced compared to the current process. What is important to note here is the significant reduction in “new idea-to-product map” time as a result of an improved front end process. The cross-functional team charged with responsibility considers several factors such as technology, competitive activities, customer inputs, current product performance, and market trend to evaluate the new ideas. This pipeline based strategy allows the cross-functional team managed by R&D and marketing to kill or re-prioritize pipeline projects at any time based on potential economic value of new ideas entering the pipeline.

Key Improvement Areas and Lessons LearnedBased on the findings of the analysis of the current PD process, ABC Corporation decided to focus on five key improvement areas

Exhibit 8. Future State VSM for a Large and Complex PD Project (Product 1)

Exhibit 8. Future State VSM for a Large and Complex PD Project (Product 1)

64 March 2011Vol. 23 No. 1Engineering Management Journal

Exhibit 9. Current Versus Future Target Performance Levels

Exhibit 9. Current Versus Future Target Performance Levels

Months

Freq

uenc

y

3530252015105

2.0

1.5

1.0

0.5

0.0

Mean 18.24StDev 7.083N 6

Normal Histogram of Today

Months

Freq

uenc

y

3530252015105

14

12

10

8

6

4

2

0

Mean 12.46StDev 3.186N 100

Normal Histogram of Ideal State

Today’s Performance:Small Projects 7-14 Months

Large Projects 14-28 MonthsAverage Cycle Time is 18 Months

Improvement Phase 1:Small Projects 5-11 Months

Large Projects 11-20 MonthsAverage Cycle Time is 14 Months

Improvement Phase 2:Small Projects 5-9 Months

Large Projects 9-18 MonthsAverage Cycle Time is 12 Months

80% NPD projects complete in <18 Mo.

Average performance improvement 68% andstandard deviation improvement 122%over today’s performance

Months

Freq

uenc

y

3530252015105

2.0

1.5

1.0

0.5

0.0

Mean 13.68StDev 5.312N 6

Normal Histogram of 50% Improvement (3/4 time)

This represents Today’s Performance projecting a 50% Improvement.

Exhibit 10. Phase Wise Plan of Process Improvements Projects

Exhibit 10. Phase Wise Plan of Process Improvements Projects

Phase 1 Projects Phase 2 Projects

Project Relative Impact

2006 Q3

2006 Q4

2007 Q1

2007 Q2

2007 Q3

Improvement Area

Develop and Implement a Cross-functional NPD Capacity Management System High Wait, Rework

Develop and implement a robust front-end process High Wait, Rework

Improve Supplier NPD development system, including Supplier qualification, relationships and joint accountability.

Medium Wait

Improve implementation process (Design hands off to Production) Medium Wait, Rework

Improve Program/Project Management Skill Set Meduim Wait, Rework, NVA

Integrate a common product lifecycle management system High Wait, Rework,

NVA

Develop Standardized NPD methodologies High Rework

Create a system for continuously generating information for design development execution Medium Wait, Rework,

NVA

Improve test and simulation capability Medium NVA

Speed Impact %20% 50% 58% 61% 68%

Exhibit 11. Recommended Change in HR Allocations to Improve the NPD Process

Current State Proposed

PMO Functional PMO Functional Benefit

FTE 4 8 5 8 No significant resource growth

Full Time 4 2 6* 6 Competency development

Part Time 2 18 2 10 Less conflict in assignments

total 6 20 8 16 Long-term reduction of resources

* Includes 1 PM to lead the NPD process improvement program

65March 2011Vol. 23 No. 1Engineering Management Journal

in order to eliminate the cycle-time waste. The current and future improvement efforts in those target areas are clearly prioritized and presented in Exhibit 12.

The five improvement areas included product portfolio management, design process, supply chain management, resource management, and NPD systems. As shown in Exhibit 12, the portfolio management target for phase one has already been achieved, while other improvements have been identified as top priority. As mentioned earlier, the phase one target was to reduce cycle time by 35%, and that of phase 2, by over 50%. Overall, because of the new lean NPD process, information flow has improved significantly and the customer satisfaction

Exhibit 11. Recommended Change in HR Allocations to Improve the NPD Process

Exhibit 10. Phase Wise Plan of Process Improvements Projects

Phase 1 Projects Phase 2 Projects

Project Relative Impact

2006 Q3

2006 Q4

2007 Q1

2007 Q2

2007 Q3

Improvement Area

Develop and Implement a Cross-functional NPD Capacity Management System High Wait, Rework

Develop and implement a robust front-end process High Wait, Rework

Improve Supplier NPD development system, including Supplier qualification, relationships and joint accountability.

Medium Wait

Improve implementation process (Design hands off to Production) Medium Wait, Rework

Improve Program/Project Management Skill Set Meduim Wait, Rework, NVA

Integrate a common product lifecycle management system High Wait, Rework,

NVA

Develop Standardized NPD methodologies High Rework

Create a system for continuously generating information for design development execution Medium Wait, Rework,

NVA

Improve test and simulation capability Medium NVA

Speed Impact %20% 50% 58% 61% 68%

Exhibit 11. Recommended Change in HR Allocations to Improve the NPD Process

Current State Proposed

PMO Functional PMO Functional Benefit

FTE 4 8 5 8 No significant resource growth

Full Time 4 2 6* 6 Competency development

Part Time 2 18 2 10 Less conflict in assignments

total 6 20 8 16 Long-term reduction of resources

* Includes 1 PM to lead the NPD process improvement program

has improved as a result of shorter lead time, higher quality, and lower costs. It is important to note here that to achieve 50% reduction after the quick wins of 32% reduction, additional time and resources are required to:

implement a robust front-end process for idea generation •(three R&D full-time personnel for 12 months) improve the supplier NPD development system, including •supplier qualification, relationships and joint accountability (two supplier development engineers for 12 months), andachieve world-class managed NPD organization •transformation by using the PD lean transformation road map (Exhibit 13).

Exhibit 12. Prioritized Improvements for Cycle Time Reduction

Exhibit 12. Prioritized Improvements for Cycle Time Reduction

• Global Front-End process deployed (Idea to Business Case)– Voice of customer, business case, market

requirements document• Roadmaps and quality function deployment initiated• Std financial models, less approval iterations• Manual inventory of all NPD projects

• Full-lean front-end process, fast voice of customer, Business Case

• Product roadmaps clearly defines start sequences – Early/accurate view resource demands/capacity

• Stop prioritizing active project pipeline is fast/right-sized

• Complete/current NPD portfolio (Schedule, budget, Results)

• Sector wide design standards, eliminate rework• Advanced test and plans, learn early, less re-testing• Eliminate waiting, automate information routing• Earlier supplier collaboration, less re-design

• Advanced design simulation, reduced design-test iterations

• Greatly accelerated test methods• Fully populated design data

• Develop an NPD capable supply base• Identify suppliers/processes for much faster tooling

• Develop highly-accelerated tooling methods/suppliers• Transition to a pull partnership with suppliers

– Challenge us on speed– Active collaboration (concept, design, value)– Provide new process/technology/cost ideas

• Initial resource mgmt. estimating and control processes

• Over-arching NPD process-team coordinates speed improvements, metrics, training & communication

• Fully-lean scalable global NPD process, with regular improvements deployed in weeks not months

• Expanded skill (depth, breadth and capacity) across all NPD core-team functions

• Complete/accurate resource plans and tracking

• Manual process automated where possible • Product Data Management system, single source of product data for all teams and mgmt.

• Global project/portfolio management system, all project types, total resources/financials, information technology system interfaced

Current and Phase-1 (35% faster) Future (>50% faster)

Portf

olio

Desi

gn/D

ev.

Supp

ly C

hain

Syst

ems

Reso

urce

, NPD

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Furthermore, from a management point of view, a few other things can be noted. Rework and delays were the leading contributors of NVA activities for this case study, which reinforces the findings of the existing literature (Womack and Jones, 2003; Reinertsen, 2009). On the other hand, the root cause for rework and delays was the poor information quality that was due to a lack of appropriate business processes, standard procedures, and NPD capabilities. The DSM and the cause and effect matrix allowed us to identify and prioritize these root causes of rework and delays and prioritize them. Furthermore, sometimes it was hard to implement “one piece flow” as suggested in the above-mentioned lean PD literature because of practical circumstances. In that case, FIFO due dates were assigned to manage the sequence of the activities. Finally, the proposed LPD framework was also applied successfully to a second relatively small and simple NPD project: incremental development of a product used in homes. Six instances caused “waste” in the NPD process of this project: delays in the business case development (13 weeks), business case approval (6 weeks), first article process (26 weeks), lack of standard (4 weeks), and unavailability of exploded BOM data (3 weeks). The main objective of this exercise was to demonstrate the scalability of the proposed framework. It should be noted though, that some of the proposed tools like DSM and CE matrix may not be cost effective in relatively simpler projects which involve fewer activities and/or more obvious iterations.

Conclusions and Implications for Engineering ManagersThis article has presented a reflective case study of a real world, lean PD transformation process for moderately complex products used in office buildings. In this project, the classical lean framework (Womack and Jones, 2003) was modified by integrating Six Sigma and project management tools such as the cause and effect matrix and the DSM. The DSM allowed us to understand the underlying complexity of the PD process by identifying the dependency among the design activities. By doing so, it was possible to identify wasteful iterations, determine their root causes, and subsequently optimize scheduling of design activities. Similarly, a cause and effect matrix has been used to prioritize the causes of rework and delays. This would not have been possible with a traditional VSM only. Among the two NPD projects in which the proposed LPD transformation framework was implemented, the first case study was on a moderately large and complex NPD project whereas the second case example was from a relatively small project. To meet the objective of reducing the PD cycle time by 50% for the larger project, the improvement targets were planned in two phases. For the larger project, a 32% reduction in cycle time was achieved in the first phase itself, which indicated that there could potentially be a 68% reduction in NPD cycle time upon completion of the second phase.

Some additional managerial implications can be drawn from the case study. Although the PD situation is different from

Exhibit 13. Prioritized Improvements for Cycle Time Reduction

Exhibit 13. NPD Lean Transformation Roadmap

Behaviors Metrics

LEADING World Class Performance

World Class

NPD is resetting its expectations of the benchmark performance A proven, robust NPD process is stable and performing at

benchmark levels, including project identification and technology research

Performance is validated by continuous real-time flow of customer and supply-chain feedback and metrics

75% or greater VA activity in NPD process Achieved 68% shift in NPD project cycle time mean Average NPD project cycle time is ≤12 months ≥80% of NPD projects complete in ≤ 18 months New cross functional business scorecard evaluates NPD performance

against world-class product development performance NPD process control plan performance is consistently on target or

improving toward new targets

SUCCEEDING Extend the

Value Stream

Phase 3 NPD improvements are leveraged to improve performance in other functional groups

NPD processes and practices are adopted by other NPD groups Best practices from other sectors' NPD groups are leveraged and

adopted Suppliers are actively engaged in improving the value stream that

is NPD

62%–67% Value added activity in NPD Process Monthly tally of % improvement in functional or sector processes

leveraged from NPD process best practices Monthly tally of % improvement to NPD process leveraged from other

sector or functional best practices Supplier balanced scorecard targets benchmark performance, 80% in

range or better

IMPROVING Continuous

Improvement

Phase 2 NPD scorecard is compared to world-class benchmarks Standard operating procedures used globally Design for Six Sigma culture is rooted and growing Engineers identify and propose improvement projects/initiatives Stable ratio of proposed improvement projects to active

improvement projects

48%–53% Value added activity in NPD process Achieved 50% improvement in NPD project cycle time Cross functional Balanced Scorecard goals are based on benchmark

performance, not %improvement goals; For example, 75% Value added process

% utilization of procedures on projects globally Number of improvement projects proposed per engineer Control chart of projects in execution over projects proposed

BEGINNING Achieve Stability

Phase 1 Engineering has identified and recognizes waste in the NPD process

A business cross functional scorecard and metrics for NPD is established and progress is communicated monthly in staff meetings

Performance improvement targets are set and communicated A project road map to improve performance and eliminate waste is

established and communicated Training for engineers to engage them in improvement efforts Performance improvement targets achieved

35%–40% value added activity in NPD process Estimated % value added in process, updated and reported as

improvements are implemented; target 75% value added activity Cross functional Balanced Scorecard updated and reported monthly Target 68% improvement in mean and 122% improvement in

consistency (average cycle time = 12 months, 80% complete in less than 18)

% complete and on schedule for training and execution Balanced Scorecard is 80% in range and process performance is on

target

Ground Zero

Current State

Sector global design centers do not use common NPD procedures and do not share common systems

Best practices are a checklist driven NPD process Phase gate governed process Cross functional NPD project teams, though alignment of

priorities and commitment is variable

Average Project Cycle time is 18 months Best performance is 6–7 months ; Worst performance is 27.5 months Estimated waste in projects is 72%-78%; 22%-28% is value-added

activity Perception/expectation of world class is 75% value- added activity

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that of manufacturing, it is possible to use lean manufacturing tools and techniques in the PD environment. In particular, value stream mapping, level loading, visual Heijunka boxes, simple and specified pathways, coordination and effective team work, and early involvement of suppliers are also important to the PD process. The findings of this study suggested that the largest contributor to non-value-added activities was waiting (delays) for information. The second biggest factor to NVA was rework, which was in most part contributed by poor quality of information. Unlike in manufacturing, PD activities are generally not identical among different products; therefore, single unit flow is not an issue. However, a tendency to wait until obtaining information on multiple activities before passing it on to the next level can create a “batching” situation and therefore increase delays (Reinertsen, 2009). Like findings of many other studies in the past (Morgan, 2002), our study also suggested that frequent hands-off and simultaneously working on multiple projects could cause the delay; however, it should be noted that working on multiple projects is not necessarily a cause of waste. On the other hand, frequent hands-offs were undoubtedly a cause for rework and delay.

While this article has presented an integrated framework for enhancing the capability of product development process in terms of identifying and eliminating waste by combining LPD tools with the DSM and the C&E matrices, we believe that the proposed LPD transformation framework can be further enhanced. Some directions for future work include formulating strategies and standard operating procedures to incorporate the design reuse (Gautam et al., 2007) for developing a lean and agile PD framework.

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About the AuthorsDr. Bimal P. Nepal is an assistant professor of industrial distribution in the Dwight Look College of Engineering at Texas A & M University. His research areas include reliability, supply chain management, and new product development. He has authored over fifty research articles in these areas. Bimal has worked on several R&D projects with a number of automotive companies in the US.

Dr. Om Prakash Yadav is an associate professor in the industrial and manufacturing engineering department at North Dakota State University. He has over 25 years of teaching, research, industry, and consulting experience in India and the US. He has published over 30 research papers in the area of quality, reliability, product development, and operations management. His research interests are focused around product development, reliability and quality engineering, concurrent engineering, and manufacturing systems engineering.

Rajesh Solanki is Corporate Director for Continuous Improvement with RTI International Metals at their corporate headquarters in Pittsburgh. He received his BS in Mechanical Engineering from MS University of Baroda, and completed his MS in computer integrated mechanical systems from Temple University. He has over 30 years of teaching, research, industry, and consulting experience. His professional interests center around operational excellence, lean six sigma deployment, lean product development processes, and manufacturing systems innovation.

Contact: Dr. Bimal Nepal, College of Engineering, Texas A&M University, College Station, TX 77843; phone: 979-845-2230; nepal@tamu.edu

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