A Multilevel Framework for Lean Product Development System Design Geert Letens, Royal Military Academy, Belgium Jennifer A. Farris, Texas Tech Eileen M.Van Aken, Virginia Tech LPD systems, e.g., functional, project, and portfolio, and in order to achieve improvements in LPD, organizations must not only improve value creation and work flow efficiency within levels but also across levels. This clearly requires a holistic understanding of the characteristics of effective LPD systems both within and across levels; however, most LPD research to date has focused on only a single level. Practitioners and researchers lack organizing frameworks to capture key LPD system principles at different organizational levels, to identify effective tools and practices for implementing principles at each level, and to define effective approaches for managing the interactions between levels. This article uses literature review and a longitudinal case study from an engineering PD department within a European governmental organization—the Department for Technical Studies and Installations (TSI) of the Belgian Armed Forces (BAF)—to develop a multilevel framework that can be used to understand the characteristics of effective LPD system design both within and across levels. Specifically, the article identifies three levels to be considered in LPD system design—functional, project, and portfolio—and proposes that two specific principles need to be considered both within and across levels—value definition and work flow optimization. A contribution of the framework proposed here is, first, that it can ultimately be used to guide LPD system improvement efforts and to assist in evaluating the results, and, second, that it is strongly connected to the literature on new product development (NPD), which is typically only tangentially associated with LPD. As a final contribution, the article reports on the LPD improvement journey of a case study organization that is very different from the Japanese and aerospace best practice organizations that are traditionally studied within the literature. The remainder of this article is organized as follows: first, the development of an initial conceptual framework based on literature review is described, followed by a description of the research methodology and the case study organization, presentation of case study results, discussion of study findings and presentation of the refined framework, and, finally, discussion of lessons learned and areas for future research.
Abstract: Organizations today face intense and growing pressure to reduce cost, decrease time to market, and maximize stakeholder value in product development (PD). Many organizations have adopted lean product development (LPD) methods in an attempt to improve their PD systems; however, despite two decades of research, there is still much less understanding of the characteristics of effective LPD systems than of effective lean manufacturing systems. LPD systems are complex systems involving multiple organizational levels; however, most LPD research to date has focused only on a single level. There is currently a lack of understanding of the interactions between levels and effective means for managing these interactions. In this article, we propose a multilevel framework designed to capture key LPD system principles at the functional, project, and portfolio levels; tools and practices for implementing principles at each level; and approaches for managing the interactions between levels. A longitudinal case study is used to expand and refine a conceptual framework developed through literature review. Future research should focus on further validating the framework and applying the framework to improve LPD system design. Keywords: Product Development, Lean Engineering, Project Management, Organizational Dynamics EMJ Focus Areas: Innovation & New Product Development; Program and Project Management
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rganizations today face intense and growing pressure to introduce more new products, and at a faster pace. Barclay (2002) estimated that the number of new product introductions would double in 2002-2007 compared to 1997-2002. Several other studies have found that “new products,” i.e., three years old or younger, account for approximately onethird of corporate sales (Cooper, Edgett and Kleinschmidt, 20032004; Rahim and Baksh, 2003). This intensifying pressure has led to a growing focus on improving the product development (PD) process, which is believed to be the bottleneck in new product introductions (Martinez and Farris, 2009). The potential benefits from the adoption of lean principles and techniques (Womack, Jones and Roos, 1990) to PD activities may, therefore, be significant (Baines, Lightfoot, Williams and Greenough, 2006). This movement, often called lean product development (LPD), has resulted in benefits for some organizations such as Toyota (Cusumano and Nobeoka, 1990; Kennedy, 2003; Liker and Morgan, 2006); however, achieving effective LPD implementation has proven difficult for many other organizations (Reinertsen, 1999; Browning, 2003). Part of this may be due to the inherent complexity of PD systems. Multiple organizational layers or levels are evident in
Background and Literature Review While the beneficial effects of lean principles in many manufacturing environments have been clearly documented, the effects of applying lean to PD are much more controversial (Baines et al., 2006). In addition, although some authors argue that lean manufacturing itself has not been conclusively defined (e.g., Papadopoulou and Ozbayrak, 2005; Shah and Ward, 2007), the definition of LPD and exactly how it differs from traditional PD is even less clear (Martinez and Farris, 2007). If there is any consensus, it appears to be that LPD uses a system of engineering and work organization principles and techniques, many of which were first popularized by Toyota, to achieve shorter lead-times, reduced cost, and higher quality than traditional PD; however,
Refereed research manuscript. Accepted by Editor Toni Doolen. Engineering Management Journal
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LPD was formally introduced by Womack, Jones, and Roos in their canonical work The Machine that Changed the World (1990). Although this work focuses mainly on manufacturing and assembly processes, as mentioned previously, Womack et al., (1990) do describe some tools and methods for achieving “lean” performance in PD, including CE. As a result, it should be noted that from the very start there has been a strong connection between LPD and CE. CE has been defined by one of this literature’s most quoted works (Winner, Pennel, and Bertend, 1988) as a systematic approach that integrates the concurrent design of products with their related manufacturing and supporting processes, intending to cause developers to consider all elements of the product life from conception through disposal including quality, cost, schedule, and user requirements. Whereas CE has received significant attention both from researchers and practitioners, its application in industry seems to be far from optimum (Maylor, 1997). Survey research by Ainscough and Yazdani (1999) revealed that although 75% of aerospace companies and 62% of industry as a whole claimed to use CE in some context, only 16% reported that they had been able to fully implement CE across the company. According to Haque and James-Moore (2004a), this is due to a fragmented approach to CE implementation that focuses on improving integration, collaboration, and process compression with a strong bias toward technology, while neglecting value identification and product effectiveness. They conclude that, whereas CE tools and organizational mechanisms reduce waste and thus contribute to leaner development processes, LPD additionally needs to emphasize the importance of focusing on the identification of value and the creation of flow throughout the entire PD value stream. As the critical importance of defining value and managing flow in PD has been confirmed by several authors (Baines et al., 2006; Browning, 2003; Hines, Francis, and Found, 2006), the proposed framework shown in Exhibit 1 seeks to integrate various techniques and approaches that support the optimization of both perspectives in
the exact set of principles and techniques, as well as the extent to which the approach must be customized by industry and project type, has not yet achieved consensus in the literature. For instance, Womack, Roos, and Jones (1990) do not conceptually define LPD. Instead, they simply describe LPD as the method used by Toyota and other Japanese automotive manufacturers to achieve dramatically decreased cost and lead-times compared with Western producers. Further, Womack et al. (1990) identify what they believe to be the set of core LPD techniques: heavyweight project managers, dedicated cross-functional teams, joint decisionmaking involving all team members, and concurrent engineering (CE). Other authors have described LPD as being comprised of slightly different sets of techniques (e.g., Karlsson and Alhstrom, 1996). Meanwhile, still other authors have approached LPD from a broader perspective, as a PD philosophy focused on eliminating waste or maximizing value in development activities, although, as will be discussed later, the relative emphasis on waste elimination vs. value creation varies across authors (Baines et al., 2006). Furthermore, little attempt has been made to integrate the findings of studies that have focused on different organizational levels, tools, etc. Multi-paradigm theorists have stressed the importance of bringing together multiple perspectives so that new insights can be developed (Edwards, 2005). What is particularly important according to Van de Ven and Poole (2005) is to see the relationship between different approaches: new theories that integrate seemingly divergent views have a stronger and broader explanatory power than the initial perspectives. Further, House, Rousseau, and Thomas-Hunt (1995) argue for the need to couple theories at different organizational levels and encourage researchers to develop mechanisms that can help conceptualize the complex relationships between organizational units at different levels of analysis; therefore, it seems important first to clarify the perspectives that this article has utilized to support the creation of a multilevel framework, including the analysis of wellestablished, related literature streams (e.g., CE).
Exhibit 1. Conceptual Framework for Lean Product Development System Design Portfolio
Product Families
Project
Flow Management
Project
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Multi Project Management
Value Identification
Portfolio Management
Value Identification
Flow Management
Multi Task Management Value Identification
Task
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Flow Management
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lean work systems. This is conceptually illustrated in Exhibit 1: at each level, the framework incorporates ways to define value, while at the same time identifying techniques for internal prioritization and coordination to assure flow at each level. In order to gain an understanding of the different LPD approaches suggested by leading researchers in the field of NPD, this work relies, first, on the comprehensive literature review of lean design engineering from Baines et al. (2006), second, on the characteristics of recent best practice studies in NPD (Cooper, 2008), and third, the work of Reinertsen (2009), that categorizes 175 principles of flow in PD from his previous work (Reinertsen, 1997, 1999, 2005; Reinertsen and Smith, 1998; Reinertsen and Shaeffer, 2005) into eight themes. Exhibit 2 summarizes the findings of these prominent researchers and illustrates how their work seems to be applicable at three organizational levels: the portfolio level, the project level, and the functional level. The relevance of these three levels can also be confirmed by a more detailed analysis of the literature on LPD. Many authors have focused their attention on approaches that improve PD at the single project level. These publications discuss a variety of tools and techniques such as cross-functional cooperation and CE (e.g., the pioneering work of Karlsson and Ahlstrom, 1996), the elimination of waste (Morgan, 2002), the use of lean tools such as Value Stream Mapping (VSM) (Millard, 2001; McManus, Haggerty, and Murman, 2007), and the identification of value (Browning, 2003; Haque and James-Moore, 2004). Literature that describes practices at Toyota from this perspective emphasizes the crucial role of the Chief Engineer as a “heavyweight” project manager with total project responsibility. Given the importance of this role, it should be no surprise that the basic principles of lean find their origin through the pioneering work of its Chief Engineer, Taiichi Ohno (1988). Whereas the integrating role of the Chief Engineer is essential to successful PD, the importance of functional specialists at
Toyota should not be neglected. Functional engineers are not fully dedicated to a single project, but instead work on several projects at the same time, building knowledge about the same function over years (Haque and James-Moore, 2004). Thus Sobek, Liker, and Ward (1998) further clarify that Toyota maintains a functionally-based organization but with impressive integration that manages PD as a system. Consequently, for the purpose of this article, it seems important to consider both the functional and the project level. This will allow us to examine coordination and prioritization of both multiple functional tasks and multiple project deliverables, and thus distinguish between techniques of integration at the functional and project level. Whereas effectively managing functional queues has been recognized to be directly related to PD speed at the single project level (e.g., Reinertsen, 1997; Reinertsen and Smith, 1998; Mascitelli, 2007), several authors have further emphasized the importance of effective prioritization and coordination of functional activities when managing multiple projects (Cusumano and Nobeaka, 1998), suggesting various approaches and techniques that improve flow within the overall project pipeline (Oppenheim, 2004; Liker, 2004; Kennedy, 2003). Finally, the best practice framework for NPD developed by the Product Development Management Association (PDMA) recognizes the strategic potential of NPD and stresses the importance of managing the portfolio of new products appropriately (Kahn, Barczak, and Moss, 2006; Barczak, Kahn, and Moss, 2006). Cooper (2008) confirms the need for improved NPD management at the portfolio level, providing examples of how Toyota’s principles of lean do not apply only at operational levels. Best practice companies implement families of stage-gate systems to manage a diversity of NPD projects with various risks. While major NPD projects have to go through the full five-stage process, moderate risk projects or minor product change requests can be managed through scaled stage-gate systems. Thus, it seems
Exhibit 2. Overview of Findings from Prominent Researchers in Product Development
Exhibit 2. Overview of Findings from Prominent Researchers in Lean Product Development.
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essential for the multilevel framework to support the investigation of value identification and flow at the portfolio level as well. The framework illustrated in Exhibit 1, therefore, incorporates three different organizational levels—project, functional, and portfolio—and seeks to identify practices and tools necessary for achieving effective value definition and work flow optimization at each level. The framework illustrated in Exhibit 1, therefore, represents the conceptual model developed based on literature review, that was tested through a case study of the evolution of PD activities in an engineering department of the Belgian Armed Forces (BAF). Case study findings further highlighted the importance of taking a multilevel perspective when optimizing the performance of PD environments and demonstrated how the implementation of various LPD principles at multiple organizational levels can benefit from a holistic approach based on systems thinking. To generalize the findings of the case study, we refer to similar findings in focused literature on PD. Further, the paper aims to validate the benefits of a multilevel LPD approach based on quantitative data collected from the integrated performance measurement system within the case study organization. Although performance measurement seems to be an important characteristic that distinguishes best practice companies from others (Cooper and Edgett, 2008), it has been reported by several authors that the implementation of an integrated performance measurement system can be extremely challenging for PD contexts (JiménezZarco, Martínez-Ruíz, and González-Benito, 2006; Haque and James-Moore, 2004b). Whereas a complete description of the performance measurement system and its creation can be found in Van Aken et al. (2003), this article particularly explores the dynamics of performance results at various organizational levels to provide a deeper understanding of both obstacles and benefits faced when using performance measurement systems in PD organizations. Methodology and Case Study Environment This research used a longitudinal case study of the evolution of PD practices within a single organization—the Department for Technical Studies and Installations (TSI) of the BAF—to further develop the multilevel framework presented in Exhibit 1. This organization was an appropriate case study subject for this work given that the TSI Department performed project-based engineering work across a variety of project complexity and risk levels and, thus, can be considered similar to many other projectbased engineering environments. In addition, previous contact with the organization allowed us access to in-depth, longitudinal data across the multiple organizational levels studied. To ensure the validity of case study findings, we carefully followed established prescriptions for case study research (e.g., Eisenhardt, 1989; Yin, 1994). Multiple investigators and respondents were used wherever possible, data were collected through multiple methods (i.e., direct observation, review of organizational documents, surveys, and interviews), and findings were shared with several international researchers in order to systematically triangulate results. The initial objectives of the case study were to understand what practices were helpful for achieving value definition and work flow optimization at the functional, project, and portfolio levels in the case study organization, and what tools had been adopted to support the implementation of these practices. The remaining objectives of the case study were to understand how the organizational levels interact, how this interaction affects value definition and work flow optimization at 72
different levels, and what approaches were effective for managing interactions in the case study organization. The case study organization (the TSI Department) designs installation kits for communication and information systems (CISs) of the BAF to be used in military vehicles of all kinds, i.e., jeeps, tanks, and mobile communication shelters. At the beginning of the case study period (in 2000), the TSI Department employed 74 military and civilian personnel, who were organized into three study work groups (wheeled vehicles, tracked vehicles, and mobile communication shelters), several functional support groups (engineering, computer aided design (CAD), mechanical prototyping), and an installation work group that performed the installation of CISs or prepared installation kits for users (Van Aken et al., 2003). In 2000, the BAF underwent a restructuring effort aimed at returning focus to the “core” mission of the military, by incorporating new technology into core military units and reducing the number of personnel in support units. To facilitate this effort, the TSI Department needed to closely examine its value-added contribution to the BAF, both to justify its current staffing levels and its existence as an internal unit. Prior to this restructuring initiative, the department’s PD approach was based on sequential hand-offs between functional groups. New projects were studied first by the engineering group to assess the technical feasibility. In case of a positive feasibility assessment, prototypes needed to be developed by one of the study workgroups. Mechanical parts for the prototype installation were created by the mechanical prototyping workgroup and were then integrated into the prototypes by the study workgroups. When the prototype was completed, engineering conducted an inspection to determine if all technical requirements were met. If so, the prototype needed to be functionally validated by system users through field testing. Next, specifications were frozen in a technical definition file (TDF). This TDF is the basis for all work to be done for the series installation, containing complete information about installation parts, technical drawings, and instructions for the installation process itself. A CAD group served as an internal support group creating technical drawings for all study workgroups. Finally, an installation workgroup constructed the installation kits used by either the installation workgroup itself (if performing the installation) or by another logistic unit using the instructions. This PD approach caused several problems. Queues of development projects waiting for action between functional groups created unproductive delays. Steps that could be performed concurrently were not, increasing development lead-times. Problems with knowledge transfer due to lack of shared understanding and turnover in project personnel further increased lead-times. Product knowledge was only formally captured in the TDF produced near the end of the project, often leading to conceptual misunderstandings between groups during hand-offs in the development process, creating delays and rework to correct resulting errors. The combined effects of functional sequential work practices, waiting times in functional queues, and rework were evident in an assessment conducted in 2000, which determined that, while 70% of projects completed within the past eight years had required less than 700 hours of direct effort to complete, almost 40% of the projects had lead-times of three years or longer. Two major phases of improvement initiatives were developed during the case study period (from early 2000 to end of 2002) to address the need to improve the PD process, with later initiatives building on the results of earlier initiatives. Engineering Management Journal
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The first improvement initiative (2000-2001) focused on the project-level only, aiming to redesign the PD process for installation projects to reduce lead-times. The redesigned PD process integrated core concepts from the ISO 15288 standard (ISO/IEC 15288, 2002), that was still in draft form at the time, with CE, integrated product teams, and virtual prototyping (see Van Aken et al., 2003, for further detail). Because the project selected to pilot the new approach (which was the most technically difficult type of project within the TSI Department at the time) appeared to be a strong success, the approach was further deployed to several other installation projects of various complexities. Data on the design and impact of this initiative were collected over a period of two years by the first author, who at the time was a fulltime internal change agent in the department. Both subjective data, e.g., customer and employee satisfaction surveys, and objective data, e.g., project lead-times and budget performance, were collected. To further investigate the impact of changes to the engineering design process for development projects, we developed a quantitative approach based on Data Envelopment Analysis (DEA) to fill a gap not addressed by commonly-applied project evaluation methods (see Farris, Groesbeck, Van Aken, and Letens, 2005). DEA enables an objective comparison of projects given their difference in input parameters such as complexity and priority. Analysis of the DEA output unequivocally demonstrated that changes to the PD process were successful in reducing project lead-times: projects completed under the redesigned PD process were expected to be 22% shorter on average, with a maximum observed reduction of 48%. Despite the success of the first improvement initiative, that focused on improvement at the single project level, trying to deploy the redesigned PD approach on a full scale revealed new organizational barriers. To respond to these new challenges, the second improvement initiative (2001-2002) focused on multiple organizational levels, aiming to improve the methods used to manage the PD process at both the functional and portfolio levels, as well as to further refine project-level methods. As a result, the second initiative involved several improvement efforts. First, the department improved its performance through the visualization of functional queues and the application of traditional lean principles to exploit bottlenecks at the functional level. Next, at the multi-project level, techniques were developed to prioritize resources across various ongoing projects and, thus, to improve the Department’s performance from a multi-project management perspective. Finally, the Department developed a set of instruments to build a valuable portfolio of projects. This implied the development of long-term relationships with both customers and suppliers to increase customer knowledge (value) and optimize flow of materials, information, and knowledge from an overall supply chain perspective, as well as the creation of a performance scorecard to characterize performance at different levels. As a result of this second improvement initiative, the Department experienced breakthrough improvement on important tactical and operational performance measures (identified in italics): the number of projects completed per year (throughput) doubled; the number of ongoing projects (WIP) went from 82 to 20; 80% of projects were completed within the industry target of two years (project lead-time); and, both the proportion of value-added time to total project duration (project effort/leadtime) and customer satisfaction measures increased dramatically. Insights from these measures enabled the Department to advise leadership within the BAF to make significant policy changes, Engineering Management Journal
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further enabling the optimization of the portfolio of projects handled by the Department. Whereas the results of the first initiative illustrate how the redesigned PD process integrates principles of lean at the project level, the improvements from the second initiative point to the importance of applying lean thinking at the various levels of the PD organization. Rather than making further changes to the redesigned PD process from the first initiative, the second initiative resulted in the redesign of organizational processes at the functional, project and portfolio level. The next section further describes the content and outcomes of these two initiatives in more detail and discusses their relationship to the conceptual framework for LPD system design. This will clarify practices and tools for defining value and optimizing flow at each level and provide additional insights with regard to the interactions between different organizational levels. Case Study Results Project Level The project-level was the first organizational level targeted for improvement. Both the first and second improvement initiatives briefly described earlier revealed key practices for value definition and work flow optimization, effective tools for implementing these practices, and clarification of the relationships between the project level and other organizational levels. Practices and Tools for Value Definition at the Project Level. Both the case study results and the LPD literature suggest that identifying value-added activities in PD requires a somewhat different approach than that typically used in manufacturing environments. Like “quality,” “value” can be difficult to directly define in any context. Thus, while optimizing value is the core of any lean system, it is clearly impossible, whether in PD or manufacturing, to optimize value without the ability to distinguish between value-added and non-value added activities. Fortunately for manufacturing contexts, although directly defining value can be difficult, it is often fairly easy to identify non-value adding activities, caused by recognized types of waste, e.g., the eight wastes identified by Womack and Jones (1996). Thus, in practice, very often the majority of “value definition” activities in manufacturing actually focus on “waste definition”; however, the application of the “waste” concept to identify value is much less straightforward in PD. Many activities that reduce risk in PD, such as building interim deliverables that enable testing of product quality and scope, have more surface resemblance to non-value adding manufacturing activities such as rework and inspection, rather than core manufacturing work activities that add value. Thus, there is danger that such activities would be targeted for reduction or elimination, even though they ultimately increase the likelihood that the end product will meet customer needs. Browning (2003) and others (Reinertsen, 1999; Haque and James-Moore, 2004a; Baines et al., 2006) have argued that LPD improvements require a direct, rather than indirect (wastefocused), definition of value. Browning (2003) further argues that activities are value-adding when they are linked to the creation of interim deliverables (which he labels “atoms of value”) that increase PD value and reduce project risk. In the case study organization, it was also found that value definition efforts were most effective when they focused on identifying the necessary characteristics of interim deliverables. This was based both on the types of decisions requiring support and the decision-makers involved (i.e., preferences for information March 2011
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format and content). For instance, the first step of the PD process in the TSI Department was to create a conceptual design for the final CIS installation. As in any PD process, a large amount of uncertainty and risk can be linked to this specific type of interim deliverable, as different stakeholders, e.g., field end user, logistic support user, tactical or strategic policy makers, etc., typically expect different characteristics of the design. In particular, failure to capture end-user expectations with respect to the appearance and functionality of the product up-front represented a major source of rework further on in the TSI Department’s PD process; therefore, during the first improvement initiative, the TSI Department identified the need to create an interim deliverable during the conceptual stage that would provide value by allowing the end users to “see” and “interact” with the final product in order to verify product requirements. Full scale mock-ups turned out to be very valuable interim deliverables from a customer perspective; however, verifying the technical feasibility of the detailed requirements that are linked to the identified customer needs required the approval of the design engineers. To address uncertainties in their domain of expertise, engineers preferred to use virtual prototypes that support easy calculation of technical problems through simulation, such as location of gravity points, vibration problems, electromagnetic interference, etc. Thus, the TSI Department identified the need to develop a second interim deliverable during the conceptual stage, i.e., virtual prototypes. While potentially appearing wasteful on the surface (due to apparent duplication), careful value definition revealed that both deliverables were necessary to ultimately promote end-user value. This further suggests that defining value in PD must be a process that integrates the perspective of multiple internal and external stakeholders (Hines et al., 2006), as internal stakeholder information requirements affect their ability to ultimately fulfill customer requirements. After the required characteristics of interim deliverables have been identified, other lean improvement techniques, such as Product Development Value Stream Mapping (PDVSM) (Morgan and Liker, 2006), CE, and pull thinking, can be applied to improve the efficiency of the flow of activities needed to produce the required deliverables. The key to improving PD using lean principles is identifying and optimizing “atom of value” content, by balancing the benefits of increased value and reduced risk against additional time and cost (Reinertsen and Shaeffer, 2005). Thus, Browning’s “atom of value” can be extended into a “lean atom of value” (LAVA) concept (Exhibit 3), that describes in detail how value is created at the project-level. Under the LAVA model, for each interim deliverable, achieving maximum value requires two core activities: first, defining the value to be provided by the
interim deliverable, and then identifying the most efficient (rapid, error-free, and cost-effective) methods for producing these deliverables. An atom of value is lean when the synchronization of people and tools involved leads to a smooth flow of development activities, creating only those interim deliverables that are pulled by the involved stakeholders to support the risk/opportunity analysis that allows them to make effective decisions on a justin-time basis. Practices and Tools for Optimizing Work Flow at the Project Level. Within the case study organization, several tools, including concurrent engineering and integrated product teams, were used to improve work flow at the project level, as reflected in the organization’s redesigned PD process. Although these techniques seemed to be highly effective in promoting flow within the pilot project for the redesigned process, the organization did experience some significant and prolonged resistance to the new techniques on the part of several project managers. The case study experience suggests that the implementation of lean in PD may be more “traumatic” for organizations than the implementation of lean in manufacturing. While implementing lean in manufacturing does require significant organization-wide change in performance measures, organizational structure, managerial philosophy, etc., the majority of production process changes most directly affect shop floor workers who typically have reduced autonomy over their work compared with engineers and middle-level managers. In fact, lean implementation may even increase autonomy for shop floor workers (deTreville and Antonakis, 2006). Conversely, in engineering environments, engineers may be more likely to resist lean improvement efforts, that they may perceive as reducing their autonomy. In addition, managers in traditional functional engineering organizations, such as the TSI Department, may resist the implementation of lean in PD due to the fundamental changes it necessitates in organizational decision-making processes. Multiple, lower-level stakeholder involvement in value definition can be a particularly difficult change in non-profit organizations, as it goes against the traditional hierarchical decision making processes used in most of these organizations. The bureaucratic nature of most of these organizations may very likely oppose the horizontal work flow sought when introducing the concepts of the LAVA-model, which as in CE requires frequent and often tentative and informal communication between cross-functional team members. In addition to the barriers to implementing flow encountered within individual projects, the TSI Department encountered additional barriers to flow arising from the interactions between projects within the Department. Although a study revealed that,
Exhibit of a Lean Atom of Value (LAVA). Exhibit 3. Model of a Lean Atom3.ofModel Value (LAVA)
People Process 1
2
3
Tools FLOW
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VALUE
Decision Makers …
pull
n
Risk Analysis
Interim Deliverables
Interim Deliverables
FLOW
Decision & Actions Table
Value Assessment and Decision Making
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overall, lead-times for projects completed under the redesigned PD process were significantly shorter than similar projects completed under the old PD process (Farris et al., 2005), study results also indicated that many projects still experienced significant delays. Additional observations within the Department indicated that there was significant WIP project inventory at several points within the process (to be discussed more in the next section). In a multiproject environment, a key source of waste is inefficient resource allocation, e.g., having the wrong resources allocated to a project or the right resources allocated at the wrong times. One type of resource allocation waste arises from excessive “multi-tasking” of project personnel. As was observed in the case study organization, in many project organizations, the internal competition for resources across projects can cause project engineers to have to switch from activity to activity, and even project to project, on a daily or even hourly basis. When the multi-tasking time segments are long enough to complete atoms of value, multi-tasking may of course be beneficial (Oppenheim, 2004); however, multitasking often “requires” the interruption of activities before they are complete, thus disrupting work flow, and causing mental, and sometimes physical, rework when the interrupted activity is resumed (Womack and Jones, 1996). This type of multi-tasking is an insidious generator of waste, leading to lower throughput, and, as a result, higher WIP and increased coordination costs (Leach, 2000); therefore, it should be a priority of top management to develop a culture that accepts priorities and sees multi-tasking as a source of waste. Due to a suspicion that multi-tasking may be creating problems in the flow of multiple ongoing projects within the Department (i.e., the project pipeline), the TSI Department decided to perform value stream analysis of the current status of all PD projects within the Department to identify barriers to flow across multiple projects. VSM has become a well-defined and popular instrument in production (Rother and Shook, 1999). In addition, a significant body of literature on PDVSM exists (Liker and Morgan, 2006; McManus, 2007); however, most of this literature has focused at the single project level. These single project applications fail to visualize problems that are inherent to mismanagement of the pipeline. For example, a single project VSM does not reflect the real amount of WIP, i.e., ongoing projects, within the pipeline. As a result, the disastrous effect of multitasking on project lead-time is often underestimated, just as the effect of inventory on lead-time is poorly understood when using standard flowcharting techniques instead of VSM in production. Using a current state VSM to analyze the performance of the project pipeline, the TSI Department became conscious of several issues that impeded project flow throughout the pipeline. While a comprehensive overview of these insights can be found in Van Goubergen, Van Landeghem, Van Aken, and Letens (2003), this article briefly discusses some of the key issues identified and the lean improvement efforts used to address these issues. First, the current state of the pipeline VSM revealed that multi-tasking was indeed a source of significant delay in the project pipeline. Key to the resolution of this difficulty was the creation of a multi-project capacity plan at the Department level that established clear priorities for different project activities and provided systematic coordination of activities across projects. One difficulty in the creation of this plan was the identification of all the constraints affecting Departmental capacity. Within the TSI Department, this rough-cut capacity plan had to include both constraints imposed by the external environment, such as validation dates imposed by customers and long-term delivery lead-times from suppliers, and the consumption of internal Engineering Management Journal
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functional resources for the upcoming months, allowing identification and prioritization of bottleneck resources for the next three months. In addition, analyzing the current state VSM revealed that a significant amount of WIP within the pipeline was caused by long lead-times from interaction with external parties, i.e., external testing, purchasing and delivery lead-times, and codification of parts. To address this problem, the Department defined aggressive goals for standardization, as recommended by the Toyota Product Development System (TPDS) (Morgan and Liker, 2006). Whereas the standardization of processes and tools has been identified as an important component of Toyota’s practices (Ballé and Ballé, 2005), it was the standardization of components that offered additional benefits to improve the flow of projects within the pipeline of the TSI Department. First, it allowed managing critical parts from a pipeline perspective. As in many project-based organizations, parts were initially bought and stored on a project basis. This means missing components for one project may easily be delivered on a first-in-first-out (FIFO) basis to less critical projects, or even worse, they may already be available and reserved as contingency for other projects. The use of simplified re-supply and purchasing procedures based on kanban systems and yearly supplier contracts enabled the TSI Department to reduce external purchasing lead-times. Even more importantly for managing the overall pipeline, this allowed the Department to optimize availability of critical components and thus limit variation in lead-times throughout the different steps of the pipeline. Second, it reduced both codification and additional testing efforts, thus minimizing rework and further improving project lead-time at the same time. These example applications provide strong support for the work on multi-project management of Cusumano and Nobeoka (1998), who argue that existing management theory, including most of the LPD literature, has over-focused on single projects, while they see the key to LPD success largely as the diffusion of knowledge between projects. In summary, the TSI Department found several lean approaches to be effective for promoting flow at the project level. Work organization tools, including CE and integrated product teams, were the primary methods for promoting flow within single projects. For multiple projects, pipeline VSM, rough-cut capacity planning, kanban systems, standardization, and supplier partnerships were the primary methods for promoting flow. Implementation difficulties were primarily encountered in the form of employee resistance to lean implementation. Interactions with Other Organizational Levels. As will be discussed more in subsequent sections, the project level is clearly connected to both the functional level, in that project efficiency depends on the efficiency of value-adding work practices within functions, and to the portfolio level. While the pipeline represents the subset of the project portfolio being implemented at any given time, project portfolio management involves the identification, selection, and management of the appropriate set of projects over time in order to achieve continuous value for the organization. Next we discuss the second level proposed in multilevel framework —the functional level—along with practices and tools for value definition and work flow optimization at this level. Functional Level The LPD practices focused on improving functional-level performance were developed during the second improvement initiative. The pipeline VSM analysis initiated to explore the March 2011
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status of multiple projects within the Department led to the identification of apparent functional bottlenecks, thus leading the Department to explore means of alleviating these bottlenecks. Practices and Tools for Value Definition at the Functional Level. The LAVA-model is important at the project level in order to decompose expectations from various stakeholders into requirements for valuable interim deliverables. Defining value at the functional level first implies the translation of customerdefined value for interim deliverables into meaningful functional requirements. Many methods have been proposed for defining value in terms of detailed technical requirements. First, classical PD techniques such as Quality Function Deployment (Akao, 1990) have long been considered effective for this purpose; however, Morgan and Liker (2006) argue that these rather sequential and analytical techniques, although providing some benefit, are not sufficient to achieve the type of breakthrough improvements in value definition observed in the TPDS. Instead, Morgan and Liker (2006) claim that the key for defining value at the functional level seems to be linked to front-loading of project personnel, which requires an increased investment in the early stages of the PD life cycle and a thorough exploration of functional alternatives. Toyota relies heavily on set-based design for this purpose. Set-based design considers sets of design and manufacturing solutions concurrently and then gradually narrows the sets, helping to ensure that designs are both feasible and compatible with the requirements of end-users (Sobek, Ward, and Liker, 1999; Morgan and Liker, 2006). One of the major advantages of this approach is that it dramatically reduces the need for late engineering changes and helps to identify and resolve technical problems as early as possible. This implies significant component or subsystem testing, whether virtual or physical testing of mock-ups, to increase the understanding of crucial engineering trade-offs regarding product attributes. The significant investment behind this approach is compensated for first, through savings in costly late engineering changes, and second, through the identification of carry-over or cross-platform parts within new designs. Qualified and established components substantially reduce performance risk and variability in PD and thus contribute to an increased understanding of value at the functional level as well. Within the TSI Department, the major LPD approaches used to define value at the functional level included encouraging engineers to generate several solutions for meeting a particular design requirement during conceptual stages in order to thoroughly evaluate quality and feasibility; therefore, both virtual and rapid prototyping were used extensively by functional engineers to generate multiple alternative solutions. This also provided valuable insights on critical design trade-offs before selecting a final functional design that offered potential for cross-platform projects. It should be emphasized, however, that standardization of parts and other multi-project initiatives that stimulate re-use of methods and parts are difficult to implement in engineering environments. Standardization efforts require extensive analysis of past, present, and future projects. They demand cooperation and training of multiple functional experts as well as shared understanding by organizational decision makers of the benefits from standardization and re-use. Organizational decision makers must, therefore, clearly define policies (e.g., technology roadmaps, guidelines for over-dimensioning of design specifications) and mechanisms (e.g., optimized purchasing and replenishment
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procedures) that support the implementation of overall standardization objectives; therefore, standardization efforts must not neglect emphasizing the impact on individual projects and describing how standardized processes of both parts and methods allow the organization to reduce the amount of time and effort required to formulate expectations (e.g., required process steps) for individual projects and to thereby avoid “reinventing the wheel.” In the TSI Department, although there was clearly some resistance to standardization efforts, it became apparent that such efforts clearly produce noticeable benefits in project outcomes (Farris et al., 2005). Finally, it should be noted that many activities at the functional level can benefit from the classical approach of indirect value optimization through the elimination of the traditional forms of waste. This is in particular true for activities in the final stages of the PD process, when most design options have been made, the value definition has become tight, and the similarity to other improvement approaches in production or office environments increases. Examples within the TSI Department from this perspective include the application of set-up time reduction principles in order to improve repetitive testing, and the simplification of project reporting and product documentation through the application of lean office techniques. Practices and Tools for Optimizing Work Flow at the Functional Level. In addition to the problems described in the previous section, an in-depth analysis of project WIP (Exhibit 4) revealed that 15 of the 82 ongoing projects in the Department reported an “on hold” status, waiting for human resources to create the photo file that served as the foundation for the user manual of the installation. This function was not previously considered to be on the critical path of the development process; therefore, no attention was formerly placed on managing the workload of the two personnel performing this activity. As a result, the function quietly became a bottleneck that turned out to be responsible for several months of delay in installation projects. This example reveals a problem that can be recognized in many other projectbased organizations: organizations of this type often focus their control efforts on tracking project schedule performance, but lack mechanisms to monitor flow rates and queue sizes at the functional level. They encourage the creation of detailed projectlevel risk management plans to plan for the unknown, but miss essential instruments to maintain the flow through daily assignments of goals and resources (Reinertsen and Shaeffer, 2005). As a result, especially in low-maturity organizations such as the TSI Department that still have high variability in projects and project activities, bottlenecks can emerge in unexpected places. Waiting for the next three-month project review session to even notice (not to mention solve) this problem should be seen as a deadly form of waste for all projects. In order to achieve improved flow at the functional level, several classical lean improvement initiatives, i.e., 5S, standard work, and pull thinking, were implemented (see Van Goubergen et al., 2003). Two LPD principles were of foremost importance in the TSI Department. First was the ability to visualize functional queues, i.e., through VSM, that was needed to support both identifying bottlenecks and identifying root causes of waste at the functional level. This visualization also enabled the organization to better determine whether to pull resources to the queue or to modulate development activities to fit the availability of functional resources. Second was creating enablers
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for pull thinking to reduce functional queues at the bottlenecks. It has been known for many years that investments to relieve bottlenecks yield disproportionately large time-to-market benefits (Adler, Mandelbaum, Nguyen, and Schwerer, 1996); however, eliminating queues in PD can be more complex than in most manufacturing environments. Spikes in demand are often common in PD activities and must be compensated for through spikes in capacity. Several methods for developing the needed “extra” capacity have been proposed. For instance, traditional lean production techniques can be used to eliminate wasteful activities, reduce cycle times, or avoid errors. Another method is developing the flexibility to temporarily pull additional resources to bottlenecks as needed. Reinertsen (2005) argues that the speed of local adjustments is particularly important in queuing systems in PD as a loss of capacity can build queues much faster than regaining capacity shrinks them. This implies that a rapid response to local variation brings disproportionate benefits and demonstrates that lean principles may be even more useful in PD than in manufacturing because they show how to maintain flow in the presence of variability. Reinertsen (1997), Reinertsen and Smith (1998) and Mascitelli (2007) offer several more specific suggestions that support controlling PD queues, reducing PD batch sizes, and reducing waste; however, it was further observed in the case study organization that trying to create excess functional capacity at times led to resistance, as this went against the “traditional” inclinations (and reward system) of functional specialists. This demonstrates the importance of engaging the functional coordinators in the LPD system deployment, both to create the buy-in needed to maintain flow on a day-to-day basis and to create the breadth of in-depth technical knowledge that supports the development of excess capacity as an answer to functional bottlenecks. In summary, the organization found several “traditional” lean tools to be valuable for achieving improvement at the functional level. Implementation problems encountered primarily consisted of the resistance of functional managers to the idea of creating flexible capacity. Interactions with Other Organizational Levels. In addition to identifying the need for LPD practice implementation at the functional level, the case study results also revealed the nature of one interaction between the project-level and the functional-level: apparent delays at the project-level may be caused by functional inefficiencies. As will be discussed more in the next section, the functional level is also related to the portfolio level, although this relationship is more apparent from the top down than from the bottom up. We next discuss the practices and tools for defining value and optimizing work flow at the portfolio level – the third level in the framework. Portfolio Level Lean practices focused on improving the portfolio level were also deployed during the second improvement initiative. As the TSI Department gained a better understanding of its competitive position in the market, they further enhanced their performance through both improved project selection and project outsourcing strategies as well as long-term oriented external cooperation and partnership. Practices and Tools for Value Definition at the Portfolio Level. While at the project and functional level, the focus of the lean projectEngineering Management Journal
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based enterprise seems to be more operationally oriented to optimize value and flow of existing projects, at the strategic level, the objective is to select and deploy a valuable portfolio of projects that guarantees long-term success in a global environment. One of the challenges here is to develop an approach for accurately defining and assessing the value of potential projects in order to develop a sound basis for selecting and prioritizing projects that overcomes political pressures that might favor certain projects over others. Cooper et al. (2003, 2004) describe many organizations today as being in a “resource crunch”—that is, finding themselves with insufficient resources to achieve their objectives of increasing product variety, increasing product quality, and decreasing product lead-times. To address this problem, Cooper and Edgett (2005) emphasize the importance of using both a marketing and resource perspective to assess NPD productivity as a means to increase overall business value. This provides a strong mechanism for controlling entry to the pipeline and even for eliminating ongoing projects when needed—a requirement that was established several years ago by Adler et al. (1996), who showed that projects get done faster if the organization takes on fewer at a time. Several new practices within the TSI Department supported the definition of portfolio value, following principles that have been identified as best practices in a recent study by Cooper and Edgett (2008). First, the Department gained better insight with regard to its potential unique value added through an analysis of strengths, weaknesses, opportunities, and threats (SWOT). Market research revealed the Department’s privileged position to develop prototypes for high-uncertainty projects, i.e., projects with a high degree of technical, conceptual, or budgetary risk, and for small volume projects where regulation and administrative overhead have an important impact on price and lead-time of outsourced projects. As this SWOT analysis also pointed to the relatively weak position of the Department when competing for large volume projects, the Department revised its mission statement and developed guidelines for leadership within the BAF to further define the value of potential projects in terms of the Department’s strengths. In addition, an improved outsourcing strategy was developed for installation projects with relatively low potential value, i.e., those that did not align with organizational strengths. Although the application of this policy led to a significant reduction in the number of projects allocated to the Department, it also provided a strong foundation for the more successful completion of the remaining high-value projects. Moreover, it should be noted that this funneling approach broadens the concept of value from a customer/stakeholder perspective at the project level, to a market and business perspective at the strategic (portfolio) level. The effectiveness of the value definition for each potential project was also improved by significant changes in the concept development for new potential projects. As described in a previous section, the preparation of sophisticated concept design deliverables enabled performing the essential value definition of the project in a sound and accelerated format. Following the principles of a Kaizen event approach (Melnyk et al., 1998), all members of the project team focused solely on concept development tasks during typically one week of intense crossfunctional cooperation, allowing the completion of the concept development phase (including preparation, administration, and reporting) in less than three weeks. Only projects that offer a substantial value potential at an acceptable risk level were then allowed entry to the project pipeline. Other projects were March 2011
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eliminated, outsourced, or investigated in further detail. This approach, which is similar to the principle of “front-loading” used within the TPDS (Morgan and Liker, 2006), required an increased investment in the early stages of projects, even for projects that, after a significant effort in concept exploration, needed to be refused access to the project pipeline. Whereas this investment was easily recovered through improvements in project, functional, and portfolio management, it became clear within the TSI Department that the implementation of this new strategic orientation required extensive internal and external communication. While internal stakeholders (i.e., senior project managers) needed to be convinced of the internal benefits of the additional efforts of front-loading, external stakeholders (i.e., higher-level hierarchy and external customers) required convincing arguments of the external benefits: first, to demonstrate the importance of the initial investment in concept development, and second, to clarify the positive impact of refusing unattractive projects entrance to the pipeline, even despite their investment in up-front exploration. Practices and Tools for Optimizing Work Flow at the Portfolio Level. The improved project-level value definition activities not only helped optimize the overall value of the project portfolio, they also enabled the optimization of project work flow by decoupling high uncertainty activities, i.e., R&D-oriented project tasks from other PD work with lower risk levels. Limiting lead-time variability throughout the different steps of the project pipeline can be key to improving flow throughout the pipeline (Oppenheim, 2004). Other work flow optimization techniques at the portfolio level included the establishment of long-term relationships with customers and suppliers, both to increase the flow of knowledge between the organization and its customers and to further optimize flow of materials, information and knowledge with supply chain partners. Another work flow optimization technique at the portfolio level involved long-term planning of critical resources. Gaining better insight regarding the market value of its products and services, the TSI Department also came to understand weaknesses in specific technologies (i.e., lack of knowledge regarding fiber optics) and competencies (i.e., shortage of design engineering skills), leading to additional investments and training to acquire the essential knowledge to support future installation projects based on these technologies. Technology roadmaps and analysis of bottleneck competencies can be valuable instruments to overcome structural shortages of critical resources. Whereas at all other levels, lean principles support optimal use of existing resources, from a portfolio perspective, it is equally important to find mechanisms that allow pulling strategic knowledge and resources to the organization to ensure long-term growth. Interactions with Other Organizational Levels. The case study clearly revealed the interaction between the project level and the portfolio level. Improved value definition and work flow at the portfolio level improved value definition and work flow at the project level. In addition, improved value definition and work flow at the project level further improved the organization’s ability to define and optimize value at the portfolio level. Thus, cyclical effects appear to be in existence between the two levels. Furthermore, portfolio-level value definition and work flow optimization activities also impacted functional efficiency, e.g., the identification of the need for investment in functional capacity to alleviate bottlenecks. 78
Observed Effects of the LPD System Improvements The previous sections have described some of the impacts of LPD tools and concepts at different levels, as well as the types of interactions between levels; however, this section describes how an effective performance measurement system quantified the impact of different LPD improvements, and revealed delays and feedbacks both within and across levels. Despite acknowledgement of the importance of performance measurement in both the general management literature and the PD literature, there is very limited literature on the design and use of performance measurement systems to support PD from an organizational perspective (Haque and Moore, 2004b). Effective performance measurement efforts seem to be the exception rather than the rule in current PD businesses. Cooper and Edgett (2008) even suggest that the use of formal scorecards or measures to optimize the portfolio is still rare in even the best firms. As part of its second improvement initiative, the TSI Department introduced a performance measurement system aimed at identifying and tracking key indicators of “lean” performance at different levels. A complete description of the performance measurement system can be found in Van Aken et al. (2003); however, in this article, we discuss what the performance measurement system revealed about the multilevel dynamics of the LPD system in the TSI Department. Quantification of Delays Within Levels. The measure that allowed the Department to better understand improvements in work flow performance at the functional level, effort/lead-time, is portrayed in Exhibit 5a. (Note this Exhibit uses a boxplot where the median is represented by the line inside the box and the mean is represented by the point inside the box.) Effort/lead-time was defined as person-days spent working directly on a project as a percentage of the total project lead-time in days, and was determined using data entered by all personnel in the computerized tracking system of the Department. This measure is analogous to valueadded time/total lead-time , which is typically used as an overall measure of performance in classical VSM. The higher the value of effort/lead-time, the less waiting time is occurring within projects. Effort/lead-time was measured for both completed projects and ongoing projects, using project lead-time to date as the denominator for ongoing projects. Following the first improvement initiative, actual project lead-times were observed to decrease under the redesigned PD process; however, effort/ lead-time had not increased (see Farris et al., 2005), indicating there was still substantial waiting in most projects. To further investigate the causes of waiting for ongoing projects, a drilldown analysis was initiated beginning in March 2002 to identify the categories of delays for all ongoing projects (see Exhibit 4). March 2002 represents the first quarter in Exhibit 5a. Of the three primary categories (material, information and decisions, and personnel), 42% of the ongoing projects (22) were identified as waiting for personnel to accomplish a task. As mentioned earlier, 15 of the 22 were found to be waiting for personnel to make and integrate the photographs needed to produce the installation manual (also called the “photo file”). This allowed the Department to identify the photo file group as a current functional bottleneck and to define a focused improvement effort aimed to increase the bottleneck capacity (see Van Aken et al. 2003, and previous sections of this article). The impact of this effort became visible once the change had been applied across enough projects. This can be observed through analysis of effort/lead-time (Exhibit 4 and Exhibit 5a), that clearly shows improvement in the quarter after Engineering Management Journal
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Drill-down on causesof waiting
Exhibit 4. Cause and Effect Relationship in a Functional Improvement Effort. Exhibit 4. Cause and Effect Relationship in a Functional Improvement Effort
Focused initiative to improve bottleneck management: concurrent approach on photo installation manual
Engineering
Photo Installation Manual
Exhibit 5. Dynamic Characteristics of the LPD System: Improvement Cycle Between Functional Flow Exhibit 5. Dynamic Characteristics the LPDFlow System: Improvement Cycle Flow (Effort/Lead-time - a), Project Flow (Project (Effort/Lead-time - a),ofProject (Project Lead-timeb),Between Project Functional Throughput (Completed Projects - c), Lead-time- b), Project Throughput (Completed Projects c), and Project Work-in-Progress (d) and Project Work-in-Progress (d).
d. Project Work-In-Progress
c. Project Throughput
ONGOGING PROJECTS STUDY 1
Completed projects 18 16 14 12
Study 3
10
Study 2
8
Study 1
6 4 2 0 dec/01
mar/02
jun/02
sep/02
dec/02
16 14 12 10 8 6 4 2 0 35 30 25 20 15 10 5 0
13
14
31/12/01
11
30
30
31/12/01
9
31/03/02 30/06/02 ONGOING PROJECTS30/09/02 STUDY
21
6 2
31/12/02
18
31/03/02 30/06/02 ONGOING PROJECTS
12
30/09/02 STUDY 3
31/12/02
25
Periode
20 15 10
21
5 0
Dec/01
b. Project Flow
21 Mar/02
17 Jun/02
17
13
Sep/ 02
Dec/02
a. Functional Flow
LEAD-TIME ONGOING PROJECTS STUDY 1
EFFORT/ LEAD-TIME ONGOING PROJECTS STUDY 1
1600
80
1400
70
1200
60 50
1000
40
800
30 600 400 200 0
Target
20
450 Working Days
10 0
Mar/02
Engineering Management Journal
Jun/02
Sep/02
Target 15 %
Mar/02
Jun/02
Sep/ 02
Dec/02
Dec/02
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the drill-down analysis, June 2002 (which is the second quarter in Exhibit 4). Thus, the case study results revealed an expected delay between LPD improvement implementation and realized improvement; however, this delay was shorter than many may have predicted: less than one quarter (three months). This indicates that, despite the inherent complexity of lean systems, improvements might be realized faster than common wisdom suggests; however, it should be noted that the delay here may be shorter than that of changes impacting other PD lifecycle stages due to the fact that the creation of the installation (photo file) manuals is one of the last steps in the project lifecycle. This explains why the improvement results also become shortly visible in the measure of completed projects (Exhibit 5c). In general, one might expect more of a lag in results in these measures for improvement efforts focused on earlier stages of the project life cycle. Quantification of Feedback Between Levels. As indicated, the impact of the photo file improvement can also be seen in other performance measures, such as the lead-time of ongoing projects (Exhibit 5b) and number of completed projects (Exhibit 5c). Thus, in addition to revealing the delays between improvements and performance changes within the targeted levels, the performance measurement system also revealed important feedback structures across levels. Improved performance of functional bottlenecks resulted in improved performance at both the project-level (reduced project lead-times) and portfolio level (increased project throughput in terms of completed projects). Further, it became evident from performance measurement system results that an increased number of completed projects (Exhibit 5c), in turn decreased project work-in-progress (Exhibit 5d), which helped the Department alleviate the temptation to multi-task and reduced waiting time (queue lengths) at functional bottlenecks. The fact that improved performance at one level can ultimately lead to performance improvement at all other levels is an important finding, as the understanding and quantification of inter-level dynamics allows better prediction of the potential benefits from various approaches and tools applied at different levels. For instance, as the focused improvement efforts to optimize flow at a bottleneck function (the photo file group) were shown to have impacts on both the project and portfolio levels, it can be further hypothesized that other “local” improvements focused on reducing waiting at bottleneck functions may have similar effects on project and portfolio level results. Similarly, the effects of changes at the project or portfolio level on other levels could potentially be estimated based on the observed dynamics. For instance, it could be expected that better control at the entrance of the pipeline at the portfolio level will improve workflow at the project and functional levels. As more relationships between levels are identified and quantified, they can be portrayed as causal loop diagrams (Sterman, 2000), and potentially used for simulation and experimentation within the Department. In fact, the observed impact of LPD system improvements on the dynamics of different organizational levels suggests that LPD systems are well-characterized as complex systems as defined by Forrester (1971). This recognition supports further understanding of the LPD system by using existing systems theory. As was observed in the LPD system of the TSI Department, cause and effect in complex systems are often separated both in time and space, making it more difficult to demonstrate improvement and to learn from mistakes. While improvements in the case study had relatively quick and measurable effects, this may be due at least in part to the specific processes targeted. The effects 80
of changes on other organizational levels were also delayed and, due to the “separation” from the targeted systems, may have been missed unless, as in the case study, the organization had recognized the relationship between organizational levels a priori. A second key characteristic of a complex system is thus also apparent in the case study organization: all subsystems and parts interact using multiple, nonlinear feedback loops. This characteristic, which seems likely to hold in other organizations as well as the case study organization, helps explain why LPD systems are often so hard to understand and improve. For instance, organizations may experience unintended consequences when LPD improvements on one level result in sub-optimization in other levels. Due to their nature as complex systems, effective LPD system management clearly requires both dynamic and closed-loop thinking when attempting to improve the performance of the system. Dynamic thinking focuses on understanding how shifts in performance occur as the result of different system behavior, e.g., interventions, over time. That is, organizations must seek to understand the nature of expected delays in different parts of the system. Meanwhile, closed-loop thinking seeks to understand how the parts of a system react and interact with each other and external factors (Atwater, Kannan, and Stephens, 2008), i.e., causal structure of the organization. The performance measurement system was found to be invaluable for both purposes in the TSI Department. The process of acknowledging and explaining performance results not only helped the Department evaluate the effects of changes and select better improvement initiatives over time, it helped build a participative management culture. The focus on the scientific evaluation of the effects of changes on different levels helped functional managers, project managers, and executives focus on understanding the dynamics of the system, rather than trying to justify performance within their own domains. This helped managers at all three levels jointly commit to improving the overall performance of the organization over time. Finally, as mentioned, as the dynamics of the system are more fully revealed through organizational experimentation and the performance measurement system, formal system dynamics models could be constructed to further experiment with the effects of proposed changes over time. Discussion and Revised Framework The creation of the initial, multilevel framework (Exhibit 1) was based on an analytical approach, that attempted to use current literature and organizational theory to explain the different parts of a lean project-based enterprise and how they would be expected to interact. The evidence provided by the case study validated and enabled us to refine the initial framework. Rather than applying lean principles only at the single project level, the TSI Department identified a clear need to optimize flow and value from an organizational perspective (that is, at the project, functional, and portfolio levels) and effectively used a number of LPD tools to achieve this improvement. The multilevel framework presented in Exhibit 6 further clarifies the initial framework by including typical LPD principles and practices that appear to be effective for optimizing flow and maximizing value at specific organizational levels, based on the case study experience. At each level, new and higher-order tools are needed to fit both the purpose of the level and the need to integrate parts of the lower levels. From this perspective, the framework strongly aligns with the construct of holons, as developed by Koestler (1967) and used extensively by systems theorists (Checkland, 1981; Engineering Management Journal
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Exhibit 6. Lean Product Development Principles and Practices Applied
Exhibit 6. Lean Product Principles and Practices Applied by the Case Study Organization by the Development Case Study Organization.
Lane and Olivia, 1998). The word “holon” is a combination of the Greek ‘holos’, which means whole, and the suffix ‘on’ which refers to a particle or part. A holon represents a part-whole in a nested hierarchy, that can be seen and described in terms of its holistic and independent nature as well as of its “partness” and dependent nature (Edwards, 2005). Exhibit 6 depicts the nested quality of holons, representing the various concepts discussed throughout this article and their relationship to three nested series of holons at the function, project, and portfolio level. One of the most important features provided by holons is the transcend-and-include principle. This allows holons to represent new emergent processes that lead to more complex systems, that include and add to the qualities defined by the previous systems (Edwards, 2005). The higher level differentiates itself from the preceding lower level as it represents a higherorder structure—more complex and therefore requiring more integration and unification. As a result, LPD organizations need to pay close attention to processes that manage flow (and, thus, prioritization and coordination) of development activities at multiple organizational levels. Tools and techniques focusing on the integration and coordination (such as visual management of functional queues and VSM at the pipeline level) are essential to improve flow within the organization as a whole. The importance of value identification is widely recognized within the PD literature (Baines et al., 2006; Martinez and Farris, 2009). From a value perspective, the framework proposed here reveals that at each level, it is essential to understand the larger Engineering Management Journal
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(external) context of the different PD activities in order to enable proper value identification. The importance of such an external perspective has already been recognized by Womack and Jones (1990) when they argued for a redefinition of the role of the technical experts in a firm from inward-looking to outward value-seeking; however, the results from the case study provide strong arguments to generalize this insight to all levels of the framework. At each level, specific processes are needed to focus on the identification of value, from an end-user, customer, and business perspective. Next, the effectiveness of the implementation of the principles and practices of the multilevel framework for LPD within the TSI Department is supported by quantitative performance results. The integrated performance measurement system that was created in the TSI Department to study the impact of LPD practices enabled the organization to: (1) gain an understanding of performance at different levels, (2) demonstrate the benefits of specific focused improvement efforts, and (3) gain an understanding of the inter-level dynamics. As the performance measurement system brought attention to performance at the various levels of the organization, it provided protection to the organization for potential sub-optimization of specific functions and inappropriate prioritization of politicallypreferred projects. This seems to be an inherent danger in inappropriately-managed matrix organizations. That is, if the various objectives of the overall organization and its subsystems at the functional, project, and portfolio level are not March 2011
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recognized, inter-functional and inter-level conflicts may easily undermine the implementation of the various principles and approaches that are hosted within the multilevel framework. As a result, performance measurement systems are identified as critical for the introduction of systems thinking in PD organizations. Performance measurement systems stimulate dynamic and closed-loop thinking, which are essential to accomplish the paradigm shift required to move from a focus on single project success to enterprise performance. The design, implementation, and use of performance management systems for PD organizations can be extremely challenging; however, as this requires the use of systems thinking, that may only be discovered through long and difficult learning cycles (due to feedback delays). This may explain why in general PD organizations are so hard to manage and why, despite their importance, scorecards are still rare, even in the best performing organizations (Cooper, 2008; Cooper and Edgett, 2008). Lessons Learned and Future Research As discussed earlier in the article, analysis in 2003 revealed that, over a three-year period, the Department experienced breakthrough improvement on a number of key performance measures, including: project throughput (the number of completed projects per year) doubled; project WIP (the number of ongoing projects) decreased from 82 to 20; the percentage of projects that were completed within the targeted lead-time of two years increased from 25% to 80%; and, effort/lead-time (the proportion of value-added time to total project duration) increased from 5% to 20%. As up to this point, empirical data on LPD remains fairly limited with most studies still having a strong focus on describing PD practices at Toyota or in aerospace organizations, these results should be encouraging to other types of PD organizations which aspire to become “lean” in the full sense of the word: it appears that organizations in other settings are equally capable of decreasing time to market while increasing stakeholder value in PD. In addition, as previous studies left unanswered how an organization wishing to leverage the benefits of LPD should go about implementing an organizationwide, multilevel LPD system, this article makes a contribution to research and practice by providing new insight into how to best achieve significant improvements at the project, functional and portfolio levels. First, the article provides insight into the key practices for value definition and work flow optimization at different organizational levels. For instance, it proposes the LAVA concept, building on Browning’s (2003) atom of value concept, that emphasizes how to complete two core principles required to implement lean at the project level, i.e., value definition and work flow optimization. In the LAVA-model, optimizing value requires first integrating the perspectives of multiple internal and external stakeholders to identify what information must be supplied by interim deliverables, and then producing the required interim deliverables in the most effective and efficient manner by employing other lean tools where helpful. Aligning both the decision-making process and the activities that lead to the creation of interim deliverables creates synchronized flow of information, materials, and knowledge in PD, meeting the objectives of the Process–People–Tools framework of the TPDS. Second, this article further demonstrates the dynamics of LPD systems, and indicates how every PD project is a complex horizontal process that takes place within the vertical structure 82
of the organization; therefore, optimizing flow at the project level ultimately requires consideration of the complex set of interrelationships between the project level and other levels of the organization. As most of the current LPD literature has focused on only part of the multilevel framework proposed in this article, a secondary contribution of this article is the inclusion of literature from NPD that is typically only tangentially associated with LPD, in order to create a multilevel framework that (1) integrates insights from recognized NPD authorities such as Cooper and Reinertsen, and (2) aligns with trends in project management practice communities such as the Project Management Institute, which recently acknowledged the importance of multilevel project management through the creation of new standards for program (PMI, 2006a) and portfolio management (PMI, 2006b). A single level focus is not capable of providing the full improvement potential that a multilevel approach can offer. It lacks the essential integration of horizontal management concerns, i.e., multiple stakeholder perspectives of value at the project level, with vertical management concerns, such as the coordination and prioritization of resources at the functional and portfolio levels. As a result, the limited number of cases that describe the transformation process toward LPD outside of Toyota tend to simplify the complexity that goes along with transforming an entire PD system. Whereas one of the contributions of this article is to provide in depth knowledge and understanding of a three year lean change journey outside of the typical Toyota automotive industry, one of the key insights from this case study is that implementing a few techniques at a single organizational level is not sufficient for creating an effective LPD system. Instead the emphasis should be on the creation of a coherent whole. The paradigm shift that is required to move from a focus on single project success to enterprise performance and long-term business health represents a tremendous challenge. This case study demonstrates the instrumental role of performance measurement in overcoming this barrier. Performance measurement systems can guide the successful implementation of the proposed multilevel framework when they stimulate systems thinking and thus allow managers to develop a richer understanding of the complexity that is inherent to managing PD organizations. Feedback loops within the multilevel performance management system can reveal how all parts of the overall organization work together and, therefore, enable learning about the behavior of the organization over time. Whereas a performance measurement culture has been identified as an important part of many lean transformations, the role of performance measurement systems to support PD from an organizational perspective remains largely unstudied (Haque and Moore, 2005). Without the appropriate performance measurement system, it will not be possible to gain the insights that are essential to understand the relationship between improvement actions and project, departmental, and enterprise success. Failing to address this need may very well be just as serious as failing to change ways of thinking and behaving in order to create the cultural shift needed to achieve maturity in the LPD organization. The multilevel framework for LPD that was introduced in this article provides a structure for organizing knowledge about value definition, work flow optimization, and LPD system dynamics. It thus offers potential for guiding LPD system improvement efforts in a variety of organizations. More research is needed, however, to further validate and refine the present framework. Additional literature review and case studies in companies Engineering Management Journal
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from various sectors can be used to further test the proposed framework, as well as to extend the set of potential “best practice” concepts, tools, and techniques that can be applied at each level to maximize value and optimize flow. The framework can further be extended to develop a systemic assessment approach to allow organizations to understand the current state of their PD practices and propose solutions for problems identified at each level. Such an assessment approach is essential to prevent the proliferation of both lean and project management tools and techniques that, with the best intentions, all aim to improve PD, but cannot claim to present a valid alternative for the many problems of PD organizations that seem to be systemic and structural rather than partial and local. Furthermore, based on the set of interesting dynamics demonstrated in the case study, it seems especially important for organizations and researchers to gain a better understanding of dynamics of LPD systems. Finally, it should be noted that whereas the current multilevel framework is structured around the first two classical tenets of lean, i.e., value and flow, the overall improvement journey of the case study environment clearly demonstrates the importance of learning and continuous improvement through experimentation, problem-solving, and discovery as well. As result, future research may want to further expand the current framework through the identification of additional LPD system components that facilitate continuous improvement from a systems and multilevel perspective. References Adler, P.S., A. Mandelbaum, V. Nguyen, and E. Schwerer, “Getting the Most Out of Your Product Development Process,” Harvard Business Review, 74:2 (1996), pp. 134-147. Ainscough, M.S., and B. Yazdani, “Concurrent Engineering Within the British Industry,” Proceedings of Advances in Concurrent Engineering (1999), pp. 443-48. Akao, Y., Quality Function Deployment: Integrating Customer Requirements Into Product Design, Productivity Press (1990). Atwater, J.B., V.R. Kannan, and A.A. Stephens, “Cultivating Systemic Thinking in the Next Generation of Business Leaders,” Academy of Management Learning and Education, 7:1 (2008), pp. 9-25. Baines, T., H. Lightfoot, G.M. Williams, and R. Greenough, “State-of-the-Art in Lean Design Engineering: A Literature Review on White Collar Lean,” Proceedings of the Institution of Mechanical Engineers, 220(B) (2006), pp. 1539-1547. Ballé, F., M. Ballé, “Lean Development,” Business Strategy Review, 16:3 (2005), pp. 17-22. Barclay, I., “Organizational Factors for Success in New Product Development,” Science, Measurement, and Technology, IEE Proceedings, 149:2 (2002), pp. 105-112. Barczak, G., K.B. Kahn, and R. Moss, “An Exploratory Investigation of NPD Practices in Nonprofit Organizations,” The Journal of Product Innovation Management, 23:6 (2006), pp. 512-527. Browning, T., “On Customer Value and Improvement in Product Development Processes,” Systems Engineering, 6:1 (2003), pp. 49-61. Checkland P., Systems Thinking, Systems Practice, Wiley (1981). Cooper, R.G., “Perspective: The Stage-Gate® Idea-to-Launch Process - Update, What’s New, and NexGen Systems,” The Journal of Product Innovation Management, 25:3 (2008), pp. 213-232. Engineering Management Journal
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About the Authors Geert Letens is a Major - Engineer Military Materials of the Department of Economics, Management and Leadership at the Royal Military Academy, Belgium. He received an M.S. degree in telecommunications engineering from the RMA, an M.S. degree in mechatronics from KULeuven, and an M.S. degree in TQM from Hasselt University. He holds a PhD in applied economics from Ghent University and a PhD in social and military sciences from the RMA. His research interests include organizational development and change, performance measurement, project management, and crisis and disaster management. He is a Research Fellow of the Vlerick Leuven Gent Management School. Jennifer A. Farris is an assistant professor in the Department of Industrial Engineering at Texas Tech University. She received her BS in industrial engineering from the University of Arkansas and her MS and PhD in
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industrial and systems engineering from Virginia Tech. Her research interests are in performance measurement, product development teams, lean systems, and healthcare performance improvement. Eileen M. Van Aken is an associate professor and associate department head in the Grado Department of Industrial and Systems Engineering at Virginia Tech. Her research interests include performance measurement, organizational improvement methods, lean work systems, and team-based work systems. She received her BS, MS, and PhD degrees in industrial and systems engineering from Virginia Tech. She is a Fellow of the World Academy of Productivity Science and ASEM. Contact: Geert Letens, PhD, Department of Economics, Management & Leadership, Royal Military Academy, Renaissancelaan 30, 1000 Brussels, Belgium; phone: +32475-32-64-06;
[email protected]
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