Organizing complex product development: outsourcing, performance integration and the role of product architecture
Markus C. Beckera and Francesco Zirpolib1 a
Strategic Organization Design Unit University of Southern Denmark,
Campusvej 55, DK-5230 Odense M, Denmark Phone 0045-65503316 Fax 0045-61155129
[email protected] b
University of Salerno, Italy
Dipartimento di Ingegneria Meccanica Via Ponte don Melillo, 84084, Fisciano (SA), Italy Phone 0039-089964068 Fax 0038-089964037
[email protected]
1
Authors’ names are in alphabetical order because both have contributed equally. The research was funded by the Italian Ministry of Higher Education and Research (MIUR) under the PRIN 2004 program (project 2004135057_004).
1 Electronic copy available at: http://ssrn.com/abstract=1087236
Organizing complex product development: outsourcing, performance integration and the role of product architecture
Abstract
Several streams of recent literature emphasize the involvement of external sources of innovation in the process of developing complex products (Powell et al., 1996; Helper et al., 2000; Sturgeon, 2002; Chesbrough, 2003). The question we tackle in the present article is ‘What are the key micro organizational decisions for seizing the benefits of a networked innovation strategy?’ Building on empirical evidence gathered over a ten-year period at a major European automotive manufacturer, the article presents empirical insights on the organizational challenges that firms face when they decide to rely on external sources of innovation in developing complex products. The empirical evidence highlights two aspects that are important: The role of component specific knowledge in addressing the integration of overall product performance, and the role of learning by doing opportunities in accumulating component specific knowledge. The article shows how managers can greatly benefit from focusing their attention on the organizational aspects of leveraging external sources of innovation and adjusting their innovation strategy, including ‘make or buy’ choices, accordingly. Strategic and micro organizational decisions, hence, should be considered as tightly coupled and mutually influencing in the context of complex product development. This quite intuitive outcome has been partially neglected in current innovation literature and management practice due to an overemphasis given to product architecture and the possibilities in terms of organization that it enables.
Key words: Innovation management, New product development organisation, Outsourcing, Performance Integration, Product architecture, Open Innovation, Automotive industry
2 Electronic copy available at: http://ssrn.com/abstract=1087236
1. Introduction
Several streams of recent literature emphasize the advantages of involving external sources of innovation in the process of developing complex products (Powell et al., 1996; Helper et al., 2000; Sturgeon, 2002; Chesbrough, 2003). As we argue below, the question how to organize such an involvement has, however, only be answered incompletely. The question we tackle in the present article is therefore ‘What are the key micro organizational decisions for seizing the benefits of a networked innovation strategy?’ This article presents empirical insights on the organizational challenges that firms face when they decide to rely on external sources of innovation in developing complex products. It builds on empirical evidence gathered over a ten-year period at a major European automotive manufacturer (from now on ‘OEM’ for original equipment manufacturer). This longitudinal study allowed tracing the evolution of the OEM’s strategy regarding the involvement of suppliers in the new product development process and how it was implemented: in a sharp departure with past practices, the OEM started to heavily involve suppliers in the design and engineering of new products, rather than just in manufacturing. In so doing, the OEM was consistent with the idea of leveraging external sources of innovation in the new product development process, an idea very prominent in the innovation management literature at the time (Chesbrough, 2003).2 The OEM we studied has reached extreme levels of outsourcing. It thus can serve as a showcase example of a firm implementing an innovation management strategy that emphasizes leveraging external sources of innovation. Yet, in great contrast to the optimism of the firms’ management and to theory alike, after a few years, important negative consequences materialized. The negative consequences by far outweighed the positive ones, raising important questions on how to leverage external sources of innovation. In particular, the contrast between powerful promises on the conceptual level and negative consequences when such concepts are implemented raises questions. Most importantly, it is crucial to know whether there are problems, flaws, or lacunae in the theory, or whether the problem regarded how to implement the theory. The example provides an occasion to investigate these questions, which are important for how such strategies will be applied in the future.
Our data shows that the main problem was neither managerial mistakes, nor flaws in the theoretical frameworks. Rather, they point to important gaps in the theoretical frameworks on the management of networked innovation. The literature leaves managers with a blind spot 2
The notion of ‘leveraging external sources of innovation’ is linked to the notions of ‘open innovation’ and ‘network innovation’.
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regarding how to implement the innovation strategies the theories advocate, i.e., the microorganizational decisions that make such a strategy sustainable. The blind spot, we argue, has its roots in a lack of integration of different approaches to managing networked innovation. It results in too vague advice on what to focus on in implementing such approaches, and how to organize complex product development when involving external sources of innovation. We fill this gap by identifying the organizational decisions that can contribute to successfully implementing a networked innovation strategy for complex products. Moreover, we provide empirically grounded insights for how to make such decisions in order to leverage external sources of innovation successfully.
The article is structured as follows: section 2 presents the state of the literature on managing network innovation, section 3 identifies the research gaps. Section 4 presents the method, followed by the empirical findings in section 5. We then turn to discussing the findings in section 6 and drawing conclusions in section 7.
2. Received wisdom on managing network innovation
2.1 Network innovation brings many advantages in product development: an operational perspective
Since the early nineties, the innovation literature has emphasized that suppliers can hold a key role in successfully developing complex products (Clark and Fujimoto, 1991; Wheelwright and Clark, 1992; Womack et al., 1990). The common emphasis of this research was on the development practices of Japanese firms, whose success in terms of product development was seen in large part due to the heavy involvement of suppliers in the NPD process. Considered best practices (Imai, Nonaka and Takeuchi, 1985), they became targets for replication in Western firms (Womack et al., 1990). Early supplier involvement (‘ESI’) is amongst the most studied concepts in exploring different forms of networked innovation in the innovation process (Helper, 1991, Lamming 1993, Smitka, 1991, Nishiguchi, 1994, Helper and Sako, 1995, Helper et al. 2000, Sako, 2004). Involving specialized suppliers heavily and early in the product development process has many advantages, both for OEMs and suppliers. First, combining complementary knowledge, as well as more highly specialized knowledge leads to improvement of quality and reliability, both of the development process and its output (Clark 4
and Fujimoto, 1991). Second, drawing on complementary expertise and more varied ideas in the early stage of development should lead to the generation of more alternative design ideas (Ward et al., 1995). Third, the higher degree of specialization, additional resources and the opportunity of concurrent engineering should diminish development lead time (with consequences on development cost) (Clark, 1989). Fourth, major strategic flexibility and market adaptability should be achieved through sharing updated market and technological information (Nishiguchi, 1994, Bensaou, 1999)3.
2.2 Network innovation requires a new focus for the innovating firm: a strategic perspective
The literature on the operational benefits of involving suppliers in the product development process has triggered a profound reflection on the role of the innovating firm and the strategic implications of the new NPD practices. In the case of complex product innovation, the sources of industry expertise are widely dispersed, and the knowledge base that firms need to draw on is rapidly expanding (Freeman, 1991, Powell et al., 1996, Grandori and Kogut, 2002; Christensen, 2006). The advantages of leveraging external sources of innovation were thus increasing. Moreover, there were increasing pressures for involving external sources of innovation built up through changes in external conditions (Sturgeon, 2002) and the evolution of markets for technology and technological development services (Arora et al., 2001). The result has been a tendency towards vertical disintegration, modularization, outsourcing and networking in product development (Langlois, 2002).
Chesbrough (2003) has synthesized and popularized the superiority of business models that hinge on the contribution of external sources of innovation (‘open innovation’). Innovating firms are advised to invest in their capabilities of drawing on external sources of innovation. In the same vein, Iansiti and Levien (2004) observe that the sustainability of a firm’s profitability is linked to the success of the ecosystem it belongs to. Firms thus should attempt to achieve an important (‘keystone’) position within the ecosystem. Iansiti and Levien (2004) concur with Chesbrough (2003) that firms should adapt their business models in order to make use of external resources and competences. Expanding the seminal contribution of Teece (1986), Jacobides et al. (2006) add to the literature on strategic aspects of innovation management by pointing to the importance of value appropriation conditions as a guide for a 3
For a comprehensive review of the advantages of involving suppliers in the NPD process see Bidault et al.,1998.
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profitable innovation strategy. Their advice for firms is to secure a bottleneck in their ecosystem, simultaneously leveraging complementarities and mobility.
In conclusion, the literature reviewed above indicates that involving external sources of innovation does not just have operational benefits, but can also generate important strategic advantages.
2.3 Network innovation needs to be managed: an organizational perspective
The diffusion of NPD practices and business models that hinge on external sources of innovation has, of course, required adjustments to intra- and inter-organizational product development practices. Network innovation, too, needs to be managed. How to do so became a question in the wake of the diffusion of the popularity of external sources of innovation. The theoretical discussion on how to manage network innovation has been very much influenced by the seminal contribution of Sanchez and Mahoney (1996). Sanchez and Mahoney’s (1996) advice on how to organize innovation focused primarily on product architectures as the main lever: Modular product architectures are seen as deciding on the most appropriate organizational design. In particular, the idea was that modular product architecture would provide more possibilities of allocating tasks to suppliers, and for loosely coupled organizations. Sanchez and Mahoney (1996: 73) explicitly argued that ‘the creation of modular product architectures … enables the design of loosely coupled, flexible, ‘modular’ organization structures’. Modular product architecture thus can lead to organizational flexibility, i.e., firms can separate groups of activities by standardizing the interfaces through which they transfer tasks to each other (Langlois, 2002; Schilling, 2000). Such flexibility then provides the opportunity to allocate tasks outside the firm boundaries (Siggelkow and Levinthal, 2003; Jacobides, 2005; Ethiraj and Levinthal, 2004). Sanchez and Mahoney’s (1996) thought-provoking hypothesis has resulted in a strong emphasis on a direct link between product architecture and organization architecture (and, arguably, industry architecture) (Jacobides, 2005). Strangely, the consequence of establishing a direct link from product architecture to organization architecture was to draw attention away from decisions about other organizational issues. Product architecture seemed to address a whole range of organizational issues at once by influencing an important strategic and organizational lever. As the empirical analysis will show, however, there are a number of issues and decisions that product architecture simply cannot address. Because of this feature, coupled with the strong 6
focus on product architecture, some organizational decisions on how to organize the involvement of external sources of innovation in the development process were bypassed and did not receive attention in the frameworks.
Sanchez and Mahoney’s idea that organization structure follows product architecture was highly influential but has also been criticized for being deterministic4. The critique has moved along two directions. First, literature has emphasized industry specificities. While industries such as the PC and other electronic products seem particularly prone to modular architectures and few evidences show that firms experience problems in organizing the innovation activities (Sturgeon, 2002, Baldwin and Clark, 2000), this does not hold in other contexts. In the automotive industry, for example, the effects of modular product architectures in product development have turned out to be much lower than expected (notwithstanding benefits in manufacturing and assembly) (Takeishi and Fujimoto, 2003, MacDuffie, 2006). Second, the literature based on Sanchez and Mahoney has been criticized for having neglected knowledge-related aspects. Scholars have argued that the link between product architecture, knowledge and task partitioning (Brusoni et al., 2001, Takeishi, 2001) is not always simple, in the sense that these dimensions are not automatically aligned (Brusoni et al., 2001; Chesbrough and Kusunoki, 2001; Takeishi, 2001; Brusoni, 2005). The reason is that the knowledge held by firms is the consequence of learning by doing opportunities connected to the allocation of design and engineering tasks along the supply chain (Fine, 1998, Lincoln, Ahmadjian and Mason, 1998). This critique identifies a precise organizational task that firms have to address in leveraging external sources of innovation. One key answer pursued in the literature is that firms should maintain a knowledge base that is broader than the immediate knowledge required for the development of the products and services produced (Brusoni et al., 2001). Building on the limits of modularity (Brusoni, 2005), the literature on system integration5 has developed advice on how to organize by taking into account organizational issues arising from product architecture (in particular, from using modular product architectures) and its link with knowledge-related issues (Brusoni and Prencipe, 2001; Staudenmeyer, Tripsas and Tucci, 2005; Frigant and Talbot, 2005; Ernst, 2005; Miozzo and Grimshaw, 2005; Mikkola, 2006). 4
Sako (2003: 230), in this respect, has argued there is ‘no simple deterministic link between the type of product architecture and organization architecture’. Puranam and Jacobides (2006), in the same vein, have criticized the ‘carry-over of ideas’ on technological architecture (including interfaces) to organizational architecture. 5 As Hobday, Davies and Prencipe write, systems integrators are firms that ‘bring together high-technology components, subsystems, software, skills, knowledge, engineers, managers, and technicians to produce a product in competition with other suppliers’ (2005, p. 1110). This requires ‘design[ing] and integrat[ing] systems, while managing networks of component and subsystem suppliers’ (Davies, Hobday and Prencipe, 2005, p. 1109).
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2.4 Gaps in the literature and research question
The brief overview shows that there is a converging conviction that relying on external sources of innovation is a necessary condition for managing complex product innovation and bears the potential to generate both operational and strategic benefits. However, much empirical evidence shows that in the case of complex products there is a risk of lack of architectural knowledge and loss of control over product performance that only vertical integration can prevent (Fine, 1998). In this vein, the literature indicates that the link between task partitioning (who does what) and knowledge partitioning (who knows what) cannot simply be managed by relying on modular product architectures (Brusoni, 2005), i.e. as a mechanistic consequence of a given product decomposition scheme. The link is much more complex and to manage it represents a key organizational challenge for firms that develop complex products. A second open question the literature identifies regards the reasons for such complexity. As Takeishi (2002) pointed out, such complexity derives from the way in which OEMs manage the development of architectural knowledge: product architecture and the related knowledge (Henderson and Clark, 1990) cannot be controlled without underlying component specific knowledge (Takeishi, 2001).
Theories on the involvement of external sources of innovation have not provided answers to these questions on how to benefit from knowledge specialization of external sources of innovation without suffering the drawbacks it might produce. To our knowledge, neither the literature that has emphasized the operational benefits of ESI nor the literature with a strategic focus has addressed these issues directly (Figure 1). The first literature has been concerned with operational aspects and governance matters (supplier governance). It is very focused on micro-mechanisms for improving intra and inter-firm organizational practices (such as the use of cross-functional teams, co-location etc.). Generally speaking, it has not systematically explored the wider-ranging strategic and more long-term implications of such organizational micro-details. The second literature has been concerned with macro questions (strategy), and has sought answers on the macro level offering only one (narrow) answer to the (broad) question how to implement a networked innovation strategy. These two literatures have focused their attention much more narrowly than the problems that are posed by organizing the involvement of external sources of innovation in the development process would have required, leaving certain questions uncovered as figure 1 illustrates. 8
Strategic aspects New Business Models (e.g. Chesbrough, 2003)
Firms’ knowledge/competence scope (e.g. Brusoni et al., 2001)
Research gap How to put strategy into action? Root of the gaps: Integration of the micro & macro perspectives What are the strategic and broader organizational implications (competence scope and knowledge domains) of lean product development practices?
Research gap Supplier integration (e.g. Helper and Sako, 1995)
OEM’s organization for NPD (e.g. Clark and Fujimoto, 1989)
Operational aspects
Figure 1 – Dominant approaches and research gaps
Several contributions have started building bridges between the macro- and micro-aspects by observing that decisions concerning the allocation of design activities along the value chain impact the development of the firm’s capabilities and strategic positioning (Jacobides and Winter, 2005). Others, such as Helper et al. (2000), have linked aspects of inter-firm governance with those concerning the boundary of the firm. However, despite such attempts no comprehensive advice is available so far on the issue of how to organize in order to draw on external sources of innovation. In particular, the question of how the OEM (the hub of the value chain) nurtures the right organizational competences to involve external sources of innovation has been addressed only indirectly so far, leaving managers that need to draw on external sources of innovation with little explicit advice on how to organize the nurturing of such competences (for an exception see Brusoni and Prencipe, 2006).
What has not yet been done sufficiently is to answer the macro questions by focusing on operational details. Arguably, doing so holds the key to providing operational advice on how to implement the leveraging of external sources of innovation. After all, operational details are important causes of strategic and macro effects. Tackling the macro questions by focusing 9
on operational details is precisely what we do in the present study. The research question addressed is the following: What are the key micro organizational decisions for seizing the benefits of a networked innovation strategy? In order to address this question, we have systematically observed, on the one hand, the consequences of a lean product development approach on the firm’s competences and knowledge domains. On the other hand, we have observed to what extent the way in which design outsourcing was implemented in practice (organizational processes and structures) has affected the sustainability of such a strategy.
3. Method
The nature of the research questions and the gaps in the literature identified above led us to choose the case study method. Our qualitative field work is based on a data gathering process that has had both a micro/operational and a strategic focus. The nature of the research question – concerning how micro organizational decisions contribute to the successful implementation of a networked innovation strategy – made the use of longitudinal empirical evidences the most appropriate (Pettigrew, 1990, Yin, 1994). The motivations for choosing this approach are the following: (1) the nature of the research question (‘how’ questions, Yin, 1994), (2) the goal of understanding knowledge related issues (by definition path dependent and cumulative, Polanyi, 1958 and Nonaka and Takeuchi, 1995), (3) the explicit call for qualitative research in the innovation management literature (Pavit, 1988, 2002, 2003) and (4) a perfect fit between the epistemology of qualitative research and the conditions characterizing the study (Mohr, 1982, Pettigrew, 1990, Yin, 1994) 6. As our unit of analysis, we chose the New Product Development (NPD) process of a technology-intensive firm developing complex products. In particular, we focused on: (1) the decisions (and the rationale applied in making those decisions) concerning the allocation of innovation tasks along the value chain, with a specific focus on the outsourcing of design and engineering tasks to suppliers; (2) the effects that task allocation produced on the firm’s and its suppliers’ knowledge and competence base; and (3) the firm’s organization for product innovation (organizational structure, NPD project management, inter-firm and intra-firm coordination mechanisms).
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It would be interesting to analyze to what extent such gaps are a consequence of the methods used in previous research. In fact, the type of research gap we have identified has been previously attributed to the methodological limits of observing inter-firm differences on the basis of industry averages, derived, for examples, from patent analyses (Pavitt, 1998, 2002, 2003, Christiansen, 2006). This limit has greatly influenced innovation management literature which, during the last decade, has started to employ different methods mostly based on qualitative analyses (see for example, Brusoni and Prencipe, 2006).
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As far as sampling is concerned, we deliberately decided to choose a case that was “very special in the sense of allowing one to gain certain insights that other organizations would not be able to provide” (Siggelkow, 2007: 20). Of course, we were aware of the fact that investigating a single company in great depth would not lead to normative results. We chose this sampling approach following the argument that “cases are selected because they are particularly suitable for illuminating and extending relationships and logic among constructs” (Eisenhardt and Graebner, 2007: 27). Furthermore, our research does not intend to perform any theory testing (Eisenhardt and Graebner, 2007). The sampling process was influenced by the unit of analysis we chose to adopt. It was based on three steps. First, we decided to focus on a specific industry. We chose to gather our empirical observations in the context of the automotive industry. The automotive industry is one of the most complex industries in terms of technologies and players involved in innovation processes (Maxton and Wormald, 2004). Moreover, the auto industry offers an extensive variety of situations regarding the effects of product architecture on the division of innovation tasks and their coordination (Takeishi and Fujimoto, 2003). Second, we selected the OEM. The main reasons for this choice is that the OEM is an example of clear and extreme task allocation decisions: a previously fully vertically integrated company (as far as design tasks are concerned) that became an extreme outsourcer and subsequently decided to once more reverse its task allocation scheme. These changes were observable within a time-span of only 10-15 years.7 The description of these changes and the in-depth analysis of their triggers were well-suited to address our research questions. Third, the two research centers of the OEM, as well as eight first-tier suppliers belonging to the OEM’s value chain, were included in the field work. Suppliers were chosen on the basis of the following criteria: (1) relevance in terms of contribution to the OEM’s development activities, (2) heterogeneity of their industry, technologies, dimension, ownership, and nationality, and (3) their independence from the OEM. The objective of this third step was to observe the same units of analysis from the angle of the car maker, its research centers and its suppliers. This is a distinctive characteristic of the present study that fits well with the nature of the research questions (and the nature of the phenomenon of networked innovation that, by definition, relates to the interactions between different actors). As will be clarified below in
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The case, therefore, offers at least as much insight into industry evolution as the electronics industry – the paradigmatic example of an industry where changes are observable in a relatively short time span (Fine, 1998). This point is a matter of interest in itself and makes the case intriguing for analyzing industrial and organizational change. For this reason we believe our sampling choice seizes, as good single-case research does, the “opportunities to explore a significant phenomenon under rare or extreme circumstances” (Eisenhardt and Graebner, 2007, p. 27).
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detail, such a sample enabled triangulation between the quantitative and qualitative data, and between what managers belonging to different organizations had to say on the same units of analysis. Moreover, the sample also addressed the research question from both the OEM and supplier sides. Concerning data collection, this article builds on in depth qualitative empirical evidence gathered over a ten-year period. Data collection on the automotive industry, the OEM and its first tier suppliers started in 1997 (Table 1). The data were gathered using multiple sources: industry publications, archival data, company documentation and employee interviews. The study of industry publications was mainly aimed at acquiring information on recent developments in the sector (e.g. technological developments characterizing the industry, history of the industry, etc.). The analysis of archival data and company documentation provided a comprehensive overview of the formal procedures regulating the NPD process of the OEM and the tools and processes the OEM uses to involve suppliers. About 2000 pages of the official OEM documents (including norms and procedures) were analyzed. The norms and procedures range from the description of engineering solutions for technical problem solving to the procedures concerning the organization of NPD to the definition of contracts with external sources of innovation, the segmentation and classification of suppliers, etc. Finally, we carried out interviews at the OEM and its suppliers
Table 1 - Research timeline and focus over time 1997: 14 hours of interviews at the OEM and four first tier suppliers Main research focus: The role of suppliers in NPD processes 1999 – 2003: 44 hours of interviews at the OEM, one research centre and 7 first tier suppliers Main research focus: The nature of buyer-supplier relationships. Fit between internal and external organization of NPD 2004 – 2005:
e ni l e m i T
8 months spent on a OEM’s NPD project Main research focus: Organizational routines in development projects and the use of virtual development tools 2006 – 2007: 81 hours of interviews at the OEM, two research centre and eight first tier suppliers Main research focus: The strategic and organizational aspects of managing complex products
Overall, between 1997 and 2007, we interviewed personnel belonging to 20 different companies for about 140 hours. All interviews were taped and transcribed. During this 10year period, the research focus has adapted somewhat according to the evolution of the 12
scholarly debate. Overall, however, it has remained highly consistent over time. The main unit of analysis, in fact, has remained stable. The field work campaign started in 2006 was specifically designed to address the research question we present in this paper. The interviews and data-gathering activities carried out before 2006-2007, hence, were a solid starting point for a more fine-grained and in-depth analysis in the last set of interviews and, at the same time, the baseline for a longitudinal comparison. This allowed us to trace the evolution of the OEM’s strategy, organization and competences for product development according to the evolution of its design outsourcing strategy. In what follows, we provide more details on the data gathering activities we build on in this article (see Table 2). The interviewees were chosen according to the relevance of their roles in the innovation process of the OEM and its first-tier suppliers. At the OEM, two company advisors supported the definition of the interview agenda and helped us gain access to the OEM’s top management, and to archival sources.
Table 2 – Interviews (period January 2006 - December 2007) Company name
Product/role
People interviewed VP Investor Relations, VP Product Portfolio Management, VP Human Resources, Business Development Manager, Director of Vehicle Concept and Integration Manufacturing Director, VP Design & Engineering (CTO), Vehicle line executive segment A-B, Vehicle line executive segment C, Vehicle line executive segment D-E, Vehicle line executive segment Commercial Vehicles, HR Director for Design & Engineering, Director of Engineering&Design Innovation&Pre-Program Concepts CEO, Business Development Director Technologies Division Plant General Manager, Engineering & Design Technical Director Assistant, Quality Manager Business Development Director, Product Engineering R&D Manager Brake Systems Business Strategy Development Manager, Project Manager, Technical Division Manager, Customer Manager, Project Leader
Date of interview
Total length of interviews (hours)
8_02_2006 9_05_2006 23_06_2006 14_07_2006 11_07_2007 13_12_2007
28
8_02_2006 22_03_2006
5
21_02_2006 07_06_2006
9
28_03_2006
3
23_03_2006 15_05_2006
10
OEM
Cars (European)
OEM Research Centre
Research Centre
Company A
Sealing systems/supplier
Company B
Brakes/supplier
Company C
Car design development, turnkey development projects/supplier
Company D
Chassis control (ABS – ESP, etc), power train, car multimedia/supplier
Manager Automotive Technology Product Planning and Marketing, Cross Functional Project Manager
29_03_2006
4
Company E
Car interiors, seats/supplier
CEO, Senior Program Manager OEM Account Manager
9_02_2006 23_03_2006
5
Account Director, Manager Programs & Application Engineering Inflatable Restraint Systems
9_02_2006 23_03_2006
5
Plant manager
3_02_2006
5
Sales & Marketing General Manager, OEM sales manager, R&D Thermal Systems Division Manager
3_04_2006
6
Company F
Company G Company H
Safety systems (airbags, seat belts, brakes, chassis control (ABS – traction control systems, etc.) /supplier Stamped parts in metal/supplier Thermal systems/supplier
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We deliberately involved people in charge of strategic decisions as well as personnel with more operative roles. In this way, we combined the perspectives of top management with the micro-analytical details provided by people involved in the execution of the NPD process. We interviewed the Chief Technology Officer, the Senior Vice President of Human Resources, the Vice President of Product Portfolio Management (all three members of the OEM’s toplevel steering committee), and the Director of Vehicle Concept & Integration (i.e., the manager responsible for systems integration for chassis and vehicle), four of the five vehicle line executives (i.e. the engineers responsible for the development of cars in the small (A-B), medium (C), and upper (D-E), as well as the commercial vehicle, segments), and the staff functions of the Design and Engineering division (the Human Resources Manager and the Division Controller). We thus covered most of the top managers leading the product development process. This set of interviews provided us with a comprehensive picture of the OEM perspective. Regarding the eight suppliers involved in the 2006-2007 interviews, we interviewed ‘account managers’ (responsible for the commercial relationship with the OEM from the pre-offer phase till the end of the project) and ‘project managers’ (responsible for component or system development). In some cases we also interviewed the supplier’s CEO (Table 1). The people we interviewed at the OEM and at the suppliers frequently dealt with each other on a daily or weekly basis. In these cases, there was a solid possibility for data triangulation, strengthening our interpretation. Triangulation is particularly recommended in qualitative research in order to reinforce data validity (Patton, 1987). Patton discusses four types of triangulation in doing evaluations, i.e. the triangulation of data sources (data triangulation), among different evaluators (investigator triangulation), of perspectives on the same data set (theory triangulation) and of methods (methodological triangulation). In this research we employed the first type of triangulation, i.e. data triangulation. Following Yin’s advice (1994) we took care to make sure that the multiple sources aimed at corroborating the same fact or phenomenon. The usual strategy we undertook was to triangulate data sources in two dimensions: First we used archival data to reconcile diverse views we obtained through the interviews. In this respect, we extensively used the rich documentation that the OEM provided us concerning its NPD process. In the NPD process handbook, for example, we found both technical norms (e.g. how a component should be engineered, what competences and knowledge bases were the OEM’s priority, etc.) and organizational procedures (e.g. company structure, processes milestones, supplier segmentations, type of contracts and responsibilities of suppliers, etc.). We constantly verified the consistency of information gathered from these two types of sources (company documents and interviews). Second, we 14
triangulated data, systematically comparing the information gathered from staff belonging to different organizations. The baseline for comparison was asking the same questions on the same unit of analysis. Given the type of research question, confronting the suppliers’ and OEM’s views on the allocation of component specific knowledge, architectural knowledge and their development over time has been fundamental to building a comprehensive and articulated representation of reality. In many cases, in fact, if we had confined our analysis to the OEM side we would have had a fairly distorted representation of reality (for example, the OEM pretending to have a high level of knowledge on issues where it did not, in fact, possess such knowledge. The same applies to the opposite case, with suppliers exaggerating their contributions to the OEM’s innovation processes.) In this respect, the possibility of gathering data from eight different suppliers was of paramount importance. This allowed us to get a more precise and articulated picture of the real strategy the OEM has implemented as far as the allocation of design activities along the supply chain is concerned. Overall, given the nature of the research questions, our investigation greatly benefited from data triangulation: many of the insights concerning the competences of the OEM and its suppliers in performing design and engineering tasks, the complexity of system integration tasks, the interorganizational routines for product development, and the overall complexity of involving external sources of innovation in product development would not have emerged if we had not relied on the combination and constant comparison of multiple data sources (interviews and archival data concerning both the OEM’s and suppliers’ perspectives) 8.
Our method is subject to limitations. Our sample could be biased by the fact that we only interviewed companies located in one country, and belonging to one industry. However, the vast majority of companies in the sample are local branches of multinational corporations. Moreover, technological heterogeneity somewhat counterbalances industry specificity. As shown in Table 1, the companies analyzed belong to completely different sectors (from pure mechanical engineering to electronics, engineering consultancy, and rubber). Exposure to multiple technological domains, product development priorities, communities of practice, 8
On a final note, we also addressed the issue of whether new conceptual development arising from interview data reflects, primarily, a sort of retrospective sense-making by image-conscious informants. Eisenhardt and Graebner (2007: 28) suggest that a key approach to mitigating this problem is to use ‘numerous and highly knowledgeable informants who view the focal phenomena from diverse perspectives’ and to ‘combine retrospective and real time cases’. As emerges from the data-gathering description, we employed both countermeasures. Our choice of the data to be presented in this article, finally, deserves a comment. Our main concern in gathering and presenting the data was to try to connect the constructs used with the conceptual argument we wanted to address (Siggelkow, 2007). Of course, we do not report all the data we gathered, being well aware of the trade-off in presenting qualitative data; given the amount of data and details, we preferred to narrow our attention in order to avoid a typical drawback of case study research, i.e. the lack of selectivity.
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technical complexity, and system, component and module integration characteristics during the research process provided a source of learning and contributed to conclusions that are well informed and empirically grounded (although they can, of course, be considered neither normative nor generally applicable). There are, of course, also the intrinsic limitations of case study research (see Miles and Huberman, 1994, for a comprehensive discussion.)
4. Empirical findings
In this section, we first describe the evolution of the OEM’s engineering and design strategy and how its implementation was organized, then turn to identifying the consequences produced by this strategy and by how it was implemented.
4.1 The evolution of the OEM’s vertical structure for innovation
Phase 1: Supply base rationalization (1987-1993)
Around the beginning of the 1990s, the OEM’s supply base was essentially limited to the domestic automotive components industry, and the OEM was still a highly vertically integrated company. Very few if any suppliers were involved in the design process: about 3450 of the 3500 technical drawings that make up the design of a car were realized by the OEM’s engineers. Moreover, the OEM dealt with more than 3000, mostly quite small, first tier suppliers. In these years, rationalisation needs were a priority and many efforts were dedicated to building a local supply base that was competitive in terms of quality and production costs9.
Phase 2: Towards extreme design outsourcing (1993-2001)
Until the mid-1990s, supplier involvement in the OEM’s new product development was still limited to the phase of industrialization and production of components and systems. With the re-engineering of the NPD process in 1996, the OEM’s outsourcing strategy took up speed, however. The OEM decided to move from outsourcing manufacturing tasks to suppliers (a 9
Especially between 1990 and 1992, the OEM experimented with so called driven growth programmes. Suppliers which demonstrated the potentiality, in terms of quality and cost of their products, to comply with the new OEM standard, were provided with continuous managerial support from the OEM together with tailored contractual agreements, such as long term contracts and steady increase of volumes purchased. In exchange, these suppliers had to respect an improvement schedule (Enrietti et al., 2002).
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practice already consolidated at that time) to outsourcing the design and engineering of components and systems. At the same time, the OEM began to frame suppliers’ contribution also in terms of strategic partnerships to develop complementary capabilities and to outsource components design. The OEM’s target for the end of 1990s was to outsource complete systems of components, and finally, complete pre-assembled modules. The aim was to deal with just two types of suppliers during the NPD phase: systems and module suppliers. The OEM did indeed reach an exceptional level of outsourcing: up to 85% of the total value of a car was engineered by suppliers at the beginning of the 1990s. In doing so, the OEM could leverage on a newly shaped tiered supplier structure and was able to find suppliers to build and pre-assemble modules. Between 1996 and 2001, the OEM became one of the firms with the highest degree of outsourcing of design engineering in the automotive industry. Most likely, it is the one which has pushed design outsourcing further than any other OEM.
Why did this happen? As other car makers did, in these years the OEM needed to cope with new exogenous10 technologies. At the same time, the group the OEM belongs to did not have sufficient resources to invest in the auto division. Moreover, at least at the beginning of the outsourcing implementation, the OEM started appreciating the benefits of increased strategic flexibility, reduction of development costs and lead time, and quality improvement yielded by the early involvement of suppliers in the new product development process. Ironically, to management this confirmed the idea that no new investments in the auto business were required, reinforcing a vicious circle whose consequences only became clear later on.
Phase 3: A new pattern towards in-sourcing (2002-2006)
When we interviewed the OEM’s manager responsible for product development in 2001, he admitted the OEM had lost its competence to design dashboards, suspensions, and occupant safety systems. In the interview, he also reported, however, that the OEM had started a process of re-building some competences in house, which would have taken an estimated 5 years. Our interviews in 2006 confirm this information:
When I arrived [in 2005] the situation was disastrous from the point of view of technical competences and from an organizational point of view. The business 10
I.e., exogenous to the automotive industry.
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units were completely out of touch. Through a very strange strategy of outsourcing, the firm had systematically destroyed the technical heart of the firm. The engineering division was just another engineering supplier that by accident was part of the firm. Nothing more, nothing less. (Chief Technology Officer, 2006)
Our interviews in 2006, moreover, allow to trace how the recovery strategy was put into action. It had two important parts. First, the OEM realized that learning from suppliers had to become an objective in itself, and a justification for involving suppliers in the product development process (i.e., the main objective was to learn, rather than to have support in designing a particular component or system). Suppliers were selected on the basis of their competence and with an explicit agreement of sharing knowledge.11 In this respect, the decreasing emphasis on cost aspects was a true novelty for the OEM’s managers. Second, the OEM started hiring staff knowledgeable in the areas in question, and to enable internal development and learning (the most important areas in which the OEM started acquiring competences that were previously lost are dashboards, suspensions, occupant safety systems and virtual development tools). At the moment, the OEM has engineers that cover all the necessary competences to design and engineer a whole new car. It currently outsources 50% of the design and engineering of new systems, down from 85%. Note that 50% is considered ‘natural’ for the auto industry by the OEM’s managers – it being standard industry practice to outsource the design and engineering of components whose technology is mature (i.e., the calliper for a brake), or not within the scope of their activities (i.e., electronics hardware).
Our interviews, however, show that not all the problems in acting as a system integrator related to the level of outsourcing. In fact, they were not solved just by increasing the amount of design tasks carried out in house. One of the main consequences of the outsourcing strategy described above, in fact, was that the OEM found itself in a very delicate situation of competence erosion. Apparently, it had pushed outsourcing too far. However, the case also shows that the organisational and strategic problems triggered by the outsourcing decision and the way they have been managed matter. In the following sub-section, we describe how systems integration was organized at the OEM. The question is: Precisely which problems were triggered by too high a degree of engineering outsourcing?
11
Most often, the purpose of knowledge sharing was knowledge acquisition on the part of the OEM.
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4.2 Organizational aspects of system integration
The scope of the knowledge base According to the managers we interviewed at the OEM, the principal reason why the OEM’s system integration strategy failed was a substantial lack of technological competence in key areas and the way the OEM interpreted system integration. This observation is echoed by a concise statement made by the Director of Vehicle Concept and Integration:
‘It is naïve to believe you can integrate a system without holding an in depth and detailed knowledge of the components that are going to affect the performance of the whole car. Managing each system performance does not, in fact, automatically result in effective system integration. The performance is the ultimate objective, not systems’ (2006).
The Chief Technology Officer also underlined that:
‘… what matters is the cost of performances, not the cost of systems’ (2006).
An illustration of the difference between integrating systems and performances and of the role of specific component knowledge is provided by the following quote from an interview at a first tier supplier supplying safety systems (airbags, seat belts, brakes, chassis control, ABS – traction control systems, etc.):
‘Before the integration of the occupant safety system was outsourced to us, despite the fact that we did not control the design of all the (sub-)systems involved. In fact, we were not responsible (or even competent) for the design of the chassis, the engine layout, and packaging, i.e. of components and systems that affect the performance of the occupant safety system. After the successful frontal crash test of a key vehicle for the OEM which obtained the maximum score on the EuroNCAP test, we met with the OEM people in order to consolidate the lessons learnt and draw some best practices to extend to future projects. In the meeting we could not point to the reasons for success because neither the OEM nor we fully dominated the whole system performance, i.e. the interactions of all the components. After this, the OEM 19
realized that they could not leave the fate of the next occupant safety system developments to serendipity. The OEM re-internalized the responsibility for managing the overall Occupant Safety System. As a consequence, we have been relieved of being responsible for the whole system performance and, now, develop only parts and components of the system (OEM Account Director at the supplier, 2006).
This example shows to what extent the OEM had outsourced system integration and, with it, full control of key vehicle performances. The OEM’s managers had to realize that acting as a system integrator without underlying component-specific knowledge was just not possible: without this underlying component-specific knowledge, systems integration competence was difficult to achieve. Precisely such knowledge, however, had been lost by focusing – a little too much it seems – exclusively on the competence of systems integration. As a consequence, this affected its ability to attain given vehicle performances in areas considered highly relevant for customers (dashboards or safety-NCAP test).
The organization of new product development One of the basic problems was that due to outsourcing of certain design and engineering tasks, there simply were no more people in-house with competences to design dashboards, suspensions, and occupant safety systems at the level that was required. To appreciate the situation, it is useful to look at the changes in the internal structure adopted by the OEM in 1996-2001. The OEM had gradually adapted it to fit the outsourcing strategy it had adopted. Functional units (where component and system technologies were developed) lost many engineers that were permanently staffed at the ‘platforms’ (in the OEM jargon, ‘platforms’ are organisational units whose task is to develop vehicles, all the way from concept to production ramp-up; this might induce some ambiguities with respect to the usual meaning of ‘product platform’). Platforms became the most important units of the company. They performed most of the design and engineering of the vehicle, heavily leveraging on suppliers’ competences, and were responsible for development projects execution. The design and engineering division accordingly became very ‘light-weight’. In the words of the Chief Technology Officer:
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‘Engineers in the company just delegated design and engineering to somebody else, usually outside the company. This was not acceptable for a technology firm’ (2006).
The assumption underlying delegation was that the role of the OEM’s engineers was to put together the systems developed by competent suppliers. The work of the OEM’s engineers – as they interpreted it – was, hence, basically to coordinate suppliers and manage the development projects. Such an interpretation did not lack a certain consistency with a ‘lightweight’ design and engineering division (although that might or might not have been intended). This task consisted mainly in assigning (and monitoring) systems/components performances to suppliers, to be achieved in a specified time schedule at given costs. In many cases, the level of specification of systems/components characteristics did not go far beyond the setting of target price and performances. There was a problem, though. As the manager responsible for system integration put it:
‘In so doing, [the OEM] was loosing the ability to set performance targets to suppliers and monitor their work. Most importantly, [the OEM] was losing the ability to manage performance trade-offs. Managing each system performance does not, in fact, automatically result in effective system integration’ (2006).
The managers we interviewed on the issue justified the lack of competences in managing performances trade-offs at the systems and components level with the direct consequences of not carrying out design activities concerning those systems and components any more. In particular, the managers we interviewed confirmed it is difficult (if not outright impossible) to integrate systems without mastering the technology underlying each system in depth.
Moreover, the growing importance of the ‘platforms’ within the organisation, together with the need of coordinating external suppliers, contributed to congest many development projects. In a recent interview (2006), a vehicle line executive told us:
‘Before [period until 2005], you had to be a “magician”. Everything was under the control of the manager responsible for the vehicle. It was just impossible to cope with all the aspects of product development, from technical to economic issues.’ (Vehicle Line Executive, 2006) 21
The problem was that platform managers were responsible both for the economic and project management aspects, and at the same time, for the all technical coordination, having the responsibility for the engineering solutions. The latter task included systems integration. That was simply too much.
From this example, it is evident that the consequences of extreme outsourcing also affected the efficiency and effectiveness of project management and the organisation. The loss of control of the important pre-development phase (Figure 2) and the OEM’s peculiar interpretation of co-design12 are both relevant consequences of the choice to implement an networked innovation strategy that deserve further attention. We now turn to analyzing them.
Time (around 5 years) Pre –development
Development
OEM:
OEM:
Defines components systems characteristics and systems performance trade offs (design archetypes and expected performances)
Designs and engineers the product for massproduction
Suppliers:
Suppliers:
Contribute to the product concept design through the proposition of new technologies and technical solutions underlying the components supplied
Design and industrialize components in detail
Freeze of the product concept and design
In the development of a new vehicle, two major phases can be distinguished: (1) the pre-development phase: the vehicle is ‘set up’, including the definition of component and system characteristics (design archetypes and expected performances), and (2) the development phase: the design and engineering of the vehicle is specified in detail. Between the two phases lies the freeze of the design, and the go-ahead for the full set of investments required in order to industrialize the vehicle with those particular design parameters.
Figure 2 – Pre-development and development phases
Due to the lack of manpower in some areas, and of the quality of engineers’ competences in designing particular systems, the OEM chose to involve suppliers in the pre-development phase in order to let them carry out large parts of it. Involving and governing such supplier involvement is not trivial, however. Because of lacking competences, it had problems for instance in setting precise component specifications (interview with manager responsible for systems integration, 14 July 2006). Suppliers were handed the responsibility for (and the task of organizing and carrying out) integrating sub-systems (defining main component targets and specifications). This process was not ‘explicit’, in the sense that the OEM pretended to set up 12
Co-design was interpreted as ‘black box’ sourcing (Lamming, 1993) and not as a form of joint development.
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targets and specifications. The point, in fact, was that the design solutions and systems performances were not fully under the OEM’s control. That is why, implicitly, suppliers gradually took over parts of the pre-development phase. Moreover, the pre-development phase was not organized as well as possible, resulting in bottlenecks in the decision process. As the manager responsible for system integration observed:
‘When system integration is carried out in the ‘development’ phase, the overall product performances are tested at the end of the process: there remains little time for fine tuning and any change is costly and may result in product quality problems’ (2006).
This is the result of black-box sourcing: suppliers in charge for component concept development (pre-development phase) hand over the component to the OEM when necessary for the physical integration in the vehicle, i.e. in the late stages of development.
It is worth noting that the loss of control occurring during the pre-development phase is particularly important: the pre-development phase decides on the ‘amount’ and difficulty of trade-offs that necessarily will occur down the line in the development phase. They are ‘programmed’ in the pre-development phase. Not dominating that phase but letting suppliers take important decisions (with a focus on their sub-systems), and not focusing attention on this phase sows the seeds for a whole string of problems in the development phase. When solicited on this issue in order to gather information on how they decided to cope with the problem, the OEM’s managers reported that they acted on two levers. Beyond the tendency described above to increase the amount of in-house design, the OEM started differentiating the involvement of suppliers in its NPD process in order to re-gain control of the predevelopment phase. In particular, the OEM increased the amount of in-house design during the pre-development phase, reversing the black-box sourcing strategy as it was carried out before. This also implied a change in the type of skills that the OEM’s engineers are requested to have. In this respect, it is important to report that one of the main concerns expressed by the manager of human resources of the division in charge for products engineering and design was a particular shortage of staff with skills in virtual simulation technology. These skills are key for performing pre-development activities with efficiency (as few prototypes as possible) and effectively (with reliable representations of the performance the vehicle will display once in production). The Chief Technology Officer confirmed that this shortage represented a 23
serious constraint for organization design: because such staff were few, it was impossible to establish decentralized virtual simulation groups in the various organization units where virtual simulation was needed. Rather, there was little choice but to have a central group where all virtual simulation was carried out complicating the re-focusing on the predevelopment phase. The following quote drawn from an interview with Director of ‘Innovation & Pre-Program Concepts’ in the Engineering & Design Division exemplifies this point:
‘We realized that technical interdependences must be tackled at the beginning of the process, not at the end. Before we integrated the vehicle at the end of the process with inevitable and costly re-design. This was a consequence of the way we outsourced design activities and of the balance within the firm of design responsibilities. At the moment my division carries out the pre-development for all the vehicles under development. This has changed our organization for NPD substantially relieving product platforms and suppliers of most pre-development activities.’
5. Discussion Our study was designed to inductively address a specific gap in the literature: What are the key micro organizational decisions for seizing the benefits of a networked innovation strategy? As illustrated in section 2, this gap originates in the research approach of the main stream literature on the issue. To address it, in our empirical work we systematically analyzed the consequences of a lean product development approach on the firm’s competences and knowledge domains, on the one hand. On the other hand, we analyzed to what extent the way in which design outsourcing was implemented in practice (organizational processes and structures) affected the sustainability of such a strategy. Our two-pronged approach was indeed able to address the gap by systematically covering it from these two angles. Our data add new insights on the choices concerning the balance between architectural and component specific knowledge and on how to maintain and develop the knowledge base necessary to leveraging external sources of innovation. These issues seem to be amongst the most important operational micro-details that require management attention. At the same time, they also seem to be the operational details that have the most important strategic consequences.
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In what follows, we discuss our findings in the light of the literature. Figure 3 provides an overview of our findings. The starting point is the assumption that complex products are not fully decomposable (Simon, 1962). Based on our empirical evidence, in this section we unfold the consequences of incomplete decomposability for the integration and coordination between design tasks. As will be clarified below, our research confirms previous studies but adds some new insights on the following two points: (1) The role of component specific knowledge in addressing the integration of overall product performance (section 5.2), and (2) the organizational implications of complex product development (section 5.3). In the remainder of this section, our objective is to show the interplay between these different aspects and discuss how it matters for guiding managerial decisions in developing complex products.
Complex products are not fully decomposable Implications for the boundary of the firm
Implications for the organization of NPD
Research gap
Research gap
What are the strategic and broader organizational implications (competence scope and knowledge domains) of lean product development practices
How to put strategy into action
An integrated framework
1. The role of component specific knowledge vs. architectural knowledge 2. The role of organizational decisions vs. architectural decisions
Figure 3: Overview of findings
As the main implications of our study are tightly connected to the fact that complex products are not fully decomposable, we start our discussion (section 5.1) by identifying the empirical implications of this fact.
5.1 Incomplete decomposability of product performance and its consequences One of the key insights that emerge clearly from the case study is the crucial importance of the difference between the integration of physical systems and the integration of performance of such systems (a process known as ‘performance management’). Simply speaking, a car is designed in order to provide a certain performance (handling, fuel consumption, certain crash 25
test parameters, and so on). This performance is generated by physical components and systems (such as the occupant safety system composed of brakes, airbags, seats, seat belts etc.). The practical problem engineers have to solve is to design a vehicle that can systematically generate a certain level of overall performance (such as, for instance, 5 stars in the NCAP crash test, handling characteristics, noise, etc). This task is accomplished by designing individual physical components and systems. What really matters, though, is the performance of the vehicle as a whole. Importantly, however, performance cannot necessarily be decomposed in the same way as the components. The reason is that some performances are generated by more than one system (Sosa et al., 2003). The occupant safety system is a good example. Brakes, seat belts, etc. are important in determining the safety characteristics of a car. In a frontal crash, however, the position, weight, and structure of the engine, such as the chassis characteristics, will also influence the impact absorbed by the vehicle and the consequences on the driver. Vehicle-level performances, thus, are not fully decomposable and different aspects of vehicle-level performance cannot always be attributed completely to particular components and systems. In our example, in order to design a car so that it has high performance values regarding occupant safety, it is not sufficient to design just a good occupant safety system. The second limit to the decomposition of performances is posed by multiple performance dimensions (e.g. speed, noise, vibration, harshness, etc.), which are interdependent in the overall vehicle-level performance. For these two reasons, there remain reciprocal interdependencies between the contribution of the individual components and systems to the overall performance (Sosa et al., 2003). As a consequence, there are limits to what extent one can fully specify the contribution of an individual component or system to overall vehicle-level performances ex ante. Extant research on search under complexity (e.g. Levinthal, 1997) shows that in such situations, finding the combination with the global performance optimum is non-trivial.
The existence of reciprocal technical interdependences between components, component specific performances and the overall performance of the product thus force managers to consider performance trade-offs. This is precisely what we have seen in the case: as the manager in charge of systems integration explained, the key challenge in system integration therefore is to manage performance tradeoffs between the various systems. The requirement to address performance trade-offs brings two questions to the attention of innovation managers: What are the organizational prerequisites for making performance trade-offs? And how to organize in order to take such trade-offs? The empirical evidence points to two 26
organizational parameters: component-specific knowledge and learning-by-doing. We now turn to explaining the role of these two parameters.
5.1.1 Component specific knowledge vs. architectural knowledge
Our empirical evidence indicates that for making performance trade-offs, a profound knowledge and understanding of the interaction between the subsystems (for example, seat belts, airbags, ABS system, engine, body etc. in a frontal crash) is indispensable. This is neither surprising nor new. It is an insight well established in the literature, both in complex product systems more generally and in new product development more specifically. Such knowledge is sometimes termed ‘architectural knowledge’ (Baldwin and Clark, 2000). Our empirical contribution is to identify the prerequisites for acquiring a profound knowledge and understanding of the interaction between the subsystems. As described in section four, one of the main causes of the OEM’s difficulties was problems in setting cross-system functional requirements. Problems in setting such requirements, in turn, were caused by insufficient knowledge of the underlying systems. As previous research has argued, knowledge of the underlying systems is required to identify the consequences of different trade-offs and make the best decision regarding overall product performances (Takeishi, 2001; Brusoni et al., 2001). That is, component-specific knowledge is a prerequisite for architectural knowledge. This is why component specific knowledge has such an important role for designing the performances of complex products. This importance has been recognized also beyond the specific context of development of complex products. In their work on knowledge recombination, for instance, Taylor and Greve (2006) reach a conclusion that is fully consistent but even stronger. One of their conclusions from an analysis of innovation in the comic book industry is that combining knowledge requires a deep understanding of knowledge, rather than information scanning or exposure (Taylor and Greve, 2006: 735). Such findings from a different context raise additional questions (pointing to matters of great interest for operational implementation). For instance, to what degree can shadow engineering, listening posts, and monitoring of technological advances fulfil the requirement to ‘keep abreast’ of the developments of component-specific knowledge? Taylor and Greve’s (2006) finding indicates that understanding, not just the possession of the information, is required. This idea is corroborated in our case, where component-specific knowledge fulfils a very precise function in solving performance trade-offs. Notably, to fulfil that function, a
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certain depth of understanding seems to be required. As it turns out, it appears best provided by learning by doing.
Our empirical evidence thus supports the argument established by previous research that component specific knowledge is a complement to the firm’s architectural knowledge (Takeishi, 2002). At the same time, component specific knowledge is also a means to strengthen architectural knowledge and to provide the possibility of maintaining it even in the face of technological change (Brusoni et al., 2001). Our empirical evidence goes beyond previous research by indicating that maintaining component-specific knowledge in important areas in-house can hold the key to successful involvement of external sources of innovation in the development of complex products. Our empirical evidence supports the idea that it will be difficult, if not impossible, to maintain systems integration capabilities – for which performance integration is key – without a mastery of the underlying component-specific knowledge. Interestingly, a mastery of such knowledge will be impossible without getting into operational details such as the organization of component-development tasks. This brings us to the second issue to be emphasized, the role of learning-by-doing.
5.1.2 The role of learning-by-doing
As emerged from our interviews, the problems with performance integration that we described did not manifest itself right from the start, i.e. when the outsourcing strategy was being implemented at the beginning of the 1990s. The reason was simply that the OEM’s engineers had only just handed over components and systems engineering to suppliers. At that point of time, their knowledge of underlying systems was still intact, and they could still easily guide the engineering work of suppliers, also during the pre-development phase. Over the next couple of years, however, these competences steadily eroded. At the end of the nineties, they were almost completely lost, at least for some systems.
The arguments for the importance of component-specific knowledge we referred to above help understand better what happened, and the implications.
First, because component design was outsourced, the OEM’s engineers did not have access to the learning opportunities any more. They were cut off from learning by doing about component design. Above, we have argued that understanding, rather than just information 28
about components and how they work is required (see 5.1.1), and that learning by doing is a powerful mechanism that can provide understanding (Levitt and March, 1988; Gavetti and Levinthal, 2000). The case supports the idea that learning by doing opportunities are important for developing understanding. Cutting engineers off from learning by doing opportunities, their understanding of component specific knowledge started to decay. Moreover, the case also provides interesting indications on the question to what extent learning by doing opportunities can be substituted. Consider the following: during the predevelopment phase, suppliers (in particular suppliers of important systems) were actually colocated at the OEM’s design and engineering division, providing the occasion for intense communication, for building trustful and personal relations, and for transferring tacit knowledge and competences. In the literature, co-location (Lamming, 1993) is seen as conducive to knowledge transfer and absorptive capacity (Cohen and Levinthal, 1990). Even despite such favourable conditions, however, regarding some systems the ability of the OEM’s engineers to dominate the pre-development phase eroded. Cutting off the OEM’s engineers from both components underlying technology and from learning by doing negatively impacted their ability to design overall vehicle performance in the predevelopment phase. The important insight is that lack of learning by doing can weaken the firm’s absorptive capacity and, subsequently, the ability to integrate external knowledge (in this case provided by the suppliers) into its own product development process. The absence of learning by doing opportunities therefore has a double negative consequence.
The example also provides a powerful indication that learning by doing seems to be very difficult to substitute. Only learning by doing seems to be able to assure the maintenance of specific design competences over time (on the effects of different learning types see Gavetti and Levinthal, 2000 and Levitt and March, 1988). Our data show that delegating all component development work to suppliers weakened the OEM’s competence to take design decisions early on in the development process.
In conclusion, our empirical evidence indicates that learning by doing seems to be the most important operational lever for acquiring and maintaining component-specific knowledge. In turn, such knowledge plays a key role for deciding performance trade-offs, which are crucial for the development of complex products. Once again, our empirical evidence points to operational details (providing guidance on how to implement in practice), which hold the answers to questions of great strategic importance. Moreover, it also seems to support the 29
argument that the strategic effects cannot be had without attending to these operational details – and why the operational details need to be decided with the strategic issues in mind (we should remember that on the operational level, there are many practical and operational matters to consider that might make strategic considerations appear far away, and perhaps more often than not, in contradiction to operational demands).
5.1.3 Implications for firm boundaries As shown in section 5.1.1, component-specific knowledge plays a crucial role for being able to make integration mechanisms work. This insight leads to new questions, however. If component-specific knowledge is crucial and learning by doing is the most important means of acquiring and maintaining it, which component-specific knowledge should be maintained in-house (by keeping component development tasks in-house)? Our empirical evidence provides an answer to this question – a new criterion for what component specific knowledge to retain in house. The analysis of our empirical evidence indicates a two-fold criterion of what type of knowledge firms that develop complex products should retain in house: develop in house all the specific component technologies that (1) have a direct impact on key product performances and (2) present a high degree of reciprocal interdependences with the key technologies contributing to the overall product performances. The first criterion refers to the relevance of the component or subsystem, the second suggests when the knowledge concerning how to design and engineer that component or subsystem has to be retained in house in order to achieve system integration efficiently and effectively. OEMs can choose which component technology to invest in according to their assessment on what are the overall performances that matter most for their customers.
An example drawn from our observations can clarify this point. In the development of a sports car, ‘handling’ is usually one of the key performance dimensions. Our first criterion would lead the OEM to develop and maintain in house component specific knowledge about ‘handling’ of sports cars. It would not be possible, in fact, to master a sports car architecture (i.e. to have the correct architectural knowledge) without a full command of the components and systems affecting the handling performances. However, these performances are determined by numerous components (e.g. tires, suspensions, steering system, etc.). Having assessed the importance of handling for the overall product performance achievement (first criterion), our second criterion would suggest the OEM acquires component specific knowledge only for the components whose performance present a high degree of 30
interdependence with the rest of the product (in the case of low interdependence it is possible to rely on black box sourcing, it being possible to specify the interface between the component and the rest of the product and manage the integration of performances either ex ante, through standard (modular) interfaces, or ex post, after minor adjustments). With reference to handling, in fact, the OEM re-acquired some component-specific knowledge about suspensions and not about tires13.
In our view, this argument adds another, more general, criterion that goes beyond the criterion indicated by Takeishi (2002). The key criterion for deciding on which components firms should develop component specific knowledge, according to Takeishi, is ‘the nature of component development project in terms of technological newness’ (Takeishi, 2002: i).14 Our criterion includes Takeishi’s notion but indicates that knowledge partitioning demands overlaps between the OEM and the supplier not only in the case of technological newness but also in all the cases in which knowledge about the component is required for managing complex technical interdependences. In this latter case, as in the case of technological newness, the outcomes of component integration within the product are uncertain and difficult to specify ex ante. This is not only due to a lack of knowledge by the supplier, as suggested by Takeishi in the case of technological newness, but also due to the intrinsic complexity of overall product performance integration. We have thus been able to indicate, based on the empirical findings, an operative criterion for where to draw the boundary of the firm’s knowledge (thus contributing to casting light on the mechanisms by which product architecture and firm boundaries influence each other, Fixson, Ro & Liker, 2005). Once more, this operative detail holds the key to unlocking (or not) important strategic consequences.
5.2 Organizational decisions vs. architectural decisions
13
Please note that for sports cars, tires are not a completely standard option as could be intuitively thought. An extreme case is the need for tight integration between the tires and the rest of the vehicle in Formula 1, an example of how important the component specific knowledge on tires could be. 14 ‘For regular projects, it is more important for automakers to have a higher level of architectural knowledge (how to coordinate various components for a vehicle) than of component-specific knowledge, which is supposed to be provided by suppliers. However, when the project involves new technology for the supplier, it is important for the automaker to have a higher level of component-specific knowledge to solve unexplored engineering problems together with the supplier. In innovative projects effective knowledge partitioning seems to demand some overlaps between an automaker and a supplier, rather than efficient and clear-cut boundaries’ (Takeishi, 2002: i).
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As argued in the previous paragraphs in section five, the empirical evidence in our case points to component-specific knowledge and learning-by-doing as the keys to the ability to integrate overall vehicle performances. So what insights and advice do we have to offer on how firms can organize in order to successfully maintain component-specific knowledge and learning opportunities?
5.2.1 Organizing for NPD is not independent from the innovation strategy chosen
As seen in section four, the OEM was forced to re-organize the NPD activities on the basis of a new criterion for allocating design responsibilities to suppliers and a different structure of the internal NPD process. This is why the case provides such strong and clear indications for our conceptual frameworks. Even after re-acquiring component specific knowledge, focusing organizational efforts on the integration of physical systems and components was not a sufficient condition for integrating overall systems performance. This forced the OEM to reorganize its NPD activities thoroughly. This re-organization revolved around the distinction between integrating physical systems vs. integrating systems performances. The assumption the OEM started with was the following: in designing performances on the level of the overall vehicle, trial-and-error and experimentation with the vehicle as a whole is indispensable.15 (Such an assumption makes sense on the basis of research such as Gavetti and Levinthal, 2000 and Pisano, 1994). We can now appreciate why experimentation and the use of virtual simulation started to play such an important role. Without such experimentation with the vehicle as a whole, there is no guarantee that reciprocal interdependences between the individual performances of systems and components are addressed completely. In such a situation, getting a tight grasp on the design of the overall product performance is difficult. (Sosa et al., 2003). This aspect links back to the incomplete decomposability of overall product performance, and the impossibility to fully identify the contribution of each individual component and system to overall performance. Because most of the vehicle performance involves reciprocal interactions between many components and systems that are usually developed by different suppliers, rich interaction and ongoing coordination with suppliers is required. Our findings thus support the literature in this respect (Takeishi and Fujimoto, 2003, Sako, 2003). Moreover, because ongoing coordination, rich interaction, and
15
In order to see why, take the example of an automobile and try to put together suspensions, chassis, engines, etc. and drive the car. The car would work, but the handling would require further rounds of trial and error and integration activities to reach the handling that is desired (handling can be defined as the dynamic behavior of a vehicle on the road and the related driving experience this behavior generates for the customer).
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component-specific knowledge is required, performance integration has to be recognized as an important organizational task in its own right. It will involve, for instance, a job position responsible for accomplishing it, an organizational unit dedicated to systems integration, important resources, or making it a dominating criterion in structuring the firm. While our findings are consistent with recent articles on systems integration (Brusoni and Prencipe, 2006 and the citations therein), they go beyond the level of detail with which the organizational implications are spelled out. A further organizational decision that has important strategic consequences is the point of time at which integration efforts take place. The reason is that interdependencies increase as the design process progresses and more specifications become more concrete, thus tightening constraints and increasing interdependencies ever more. Anticipating the design and definition of the decomposition scheme into the pre-development phase therefore enables coordination mechanisms and efforts to intervene at a stage where interdependencies are less strong. Consequently, interdependencies are dealt with at a point of time when they are less strong than later on. The simple conclusion is that it makes sense to intervene early on in the process. The earlier the OEM tackles the problem, the lesser the need for late re-design to match expected performances (Thomke 1998a, 1998; Thomke and Fujimoto, 2000). Obviously this is a matter of interest only in the presence of severe time and cost constraints. While the point seems obvious once a step back is taken, the crunch of the matter is precisely that in taking strategic decisions, one does not usually have the luxury of fully addressing the operational implications. Bridging the gap between strategic decisions and the operational details necessary to implement them, also means that those responsible for taking operational decisions need to take a step back and consider the strategic, not just operational, consequences of operational decisions. The problem is that often, operational and strategic consequences easily conflict. Fostering the capability of operations managers to include such strategic considerations (and vice versa), and providing the opportunity for them to take a step back, are important organizational challenges that our empirical research points to.
5.2.2 The limits of leveraging product architecture for achieving coordination
The argument for the importance of organizational decisions obviously redresses the balance of managerial attention away from product architecture (Baldwin and Clark, 2000). In addition to this, our empirical evidence also points to intrinsic limits of product architecture
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for achieving the coordination of external sources of innovation in the development process of complex products.
As seen in the literature review section, modularity is a central concept in the scholarly debate on organizing networked innovation. What is the role of modularity in organizing the development of complex products? As described above, from the mid-1990s onwards, the OEM attempted to pursue a system-integration strategy and was trying to outsource whole modules. The analysis of the case clearly shows that modular product design is not the most appropriate way to deal with the issue of integrating performances – even though it is appealing for physical integration. The reason is that the benefits attributed to modularity (Sanchez, 1999) are not able to address the problem of integrating performances at all. Modular product design is beneficial in solving the task of coordinating suppliers as they independently develop components and systems that need to be integrated physically (thanks to standardized interfaces). For that task, modular product design is effective, as it diminishes the coordinative efforts required to assure the systems and components the various suppliers develop will actually lead to a product with high product integrity. As seen, this is the case when it is possible to both define the interfaces between elements of the whole ex ante, and to assign the development of a specific part to a supplier. Coordination then would follow as a natural consequence. The interface definition, in fact, would embed all the necessary information for the parties. However, our case study shows that for purposes of designing vehicle-level performances, it is necessary either to reduce the reciprocal interdependencies between the performances of the different components and systems ex ante, or to specify them. There are limits to the first, and for doing the second, component-specific knowledge is required. Defining standardized physical interfaces does not mean to standardize the performance contribution of a module. It does not, therefore, diminish reciprocal interdependencies between component- and systems-performances.
This is why firms need to tackle performance trade-offs. And in tackling performance tradeoffs, standardized interfaces simply have no traction. Modular product design as an ex ante integration mechanism is not, therefore, effective for the integration of performances. This is an important addition and limit to the consequences of modular product design that is not usually mentioned in the influential literature on modular product design (e.g. Sanchez and Mahoney, 1996, Baldwin and Clark, 2000).
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In consequence, the upshot is that modular product architecture does not lower the coordination cost amongst different parties involved in developing complex products (for similar evidences see Brusoni, 2005). The reason is that modular product architecture simply cannot directly address the dimension that is important, performance. That becomes clear once performance, rather than the physical dimension that generates such performance, is in the focus of attention. The hopes in modular product architecture for easing the involvement of external sources of innovation in the development of complex products therefore seem to be largely disappointed. On a final note, one might apply a coordination cost perspective on the involvement of external sources of innovation. Such a perspective would decide on how many of such sources to involve (and which ones) based on coordination cost, driven by coordination challenges. Our argument in this section says that modular product architecture cannot lower the coordination cost in the context of performance integration at all. Moreover, the drivers of coordination cost in the context performance integration are very different ones from modular product architectures, i.e., learning by doing processes.
6. Conclusion
The starting point of this article was a gap in the literature on innovation management that left managers with little advice on how to organize the involvement of external sources of innovation in the development of complex products. In particular, we have focused on one question regarding the organization of the involvement of external sources of innovation that has remained unanswered so far: ‘What are the key micro organizational decisions for seizing the benefits of a networked innovation strategy?’ We have addressed this question by identifying organizational decisions that can contribute to successfully implementing a networked innovation strategy for complex products. The main insights we developed from the empirical evidence are two. First, decisions on how to organize the operational details hold the keys to strategic benefits of leveraging external sources of innovation in the development of complex products. These decisions can be at least as important, if not much more important than decisions on product architecture. Second, the most important such decisions are which component-specific knowledge to maintain in-house and how that can be organized. The answer to this question is to allocate learning by doing opportunities and thus, taking a decision on the knowledge boundaries of the firm. These contributions add to our knowledge of how OEMs can nurture the right organizational competences to successfully involve external sources of innovation. In so doing, they close a gap as regards advice to 35
innovation managers. They also stimulate more research aiming at a systematic connection and integration of strategic aspects of innovation management and its operational aspects. Of course, our findings are somewhat specific to the industry we examined. The most relevant specificities are that cars are not fully decomposable complex systems and that, in the automotive sector, there is a substantial lack of common industry standards or standard architectures for most of the systems involved in a car (MacDuffie, 2006). Our interviews show that in some cases, suppliers have even been induced to change the basic design of a component just because the testing protocol was different from that of the OEM for which the component was originally designed: with different testing procedures the component would not have been approved although it delivered the expected performances. This makes the issue of system integration more idiosyncratic to each company, and the strategic concern of controlling the industry architecture via a dominating platform (Jacobides et al., 2006) less relevant, at least for the time being. As a consequence, our conclusions cannot necessarily be applied to contexts where industry standards play an important role in both the development of product architectures and components (e.g. the PC or the telecommunication industry). However, our results contribute to show that much still remains to be included in current theories, particularly in an integrated theory that covers both strategic and operational aspects. It also is highly relevant for innovation management practice, as glossing over dimensions and factors that matter can have serious consequences.
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