Value creation and innovation games:

Managing R&D for Business Growth

 

 

Roger Miller

Jarislowsky Chair in Management of Technology

École Polytechnique de Montréal, Montréal,QC Canada

Roger.miller@polymtl.ca

AND

Serghei Floricel

Associate Professor of Project Management

University of Québec, Montreal

floricel.sergei@uqam.ca

 

 

With the collaboration of

Matthew Cook, Armstrong World Industries

Sal Miraglia, Timken

Larry Schwartz, Intellectual Assets Inc.

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Many believe that innovation is unmanageable given the uncertainties involved, the tendency to make unduly optimistic forecasts, and the difficulty of predicting consumers’ responses. The proposed solution is to foster many “entrepreneurial flowers” and let markets select the best products. This romantic view of innovation is sometimes inefficient, as too many resources are allocated to “hot sectors,” creating bubbles. The research that we conducted with a 125 VPs R&D and CTOs[1] around the world as part of the R.O.R. subcommittee, titled Managing R&D for Growth, is leading us to a contrary view. Indeed, innovation is manageable and is not totally a gamble.

The original purpose of our study was to identify, first, effective R&D strategies to manage for growth, and second, best practices to achieve superior performance. Our central finding is that firms achieve high levels of performance in terms of profitability and growth not so much by adopting best practices but by adapting their capabilities and practices to the requirements of value creation and capture in the innovation “game” or “games” in which they have elected to compete. The competitive and technological contexts orient and structure each “game” differently.

This paper is divided into five sections. First, we outline our research methods, data sources, and data analysis approaches. Second, we describe the eight “games” of innovation that were identified by understanding value creation. In the third section, the generic practices for managing innovation are shown to vary with value-creation activities in each “game” of innovation. The fourth section presents, for four “games” of innovation, the specific capabilities and practices that are significantly associated with high level of sales growth. To conclude, we summarize our key findings and explore future avenues for research.

 

1.         Methodological Approach

As this research began, the context created by the New Economy challenged many received practices and theories related to the management of innovation. Novel ways of managing R&D were defined as distributed cross-functional teamwork, speed in bringing products to markets, technology outsourcing, and so on (Gupta and Wilemon 1996, Quinn 2000). For our part, instead of relying on existing management literature to identify best practices, we decided to build from reality, and we interviewed 75 CTOs in the United States, Canada, and Europe, asking them what strategies and practices they had developed to face the new situation. From our extensive discussions, a theoretical model was elaborated and a survey instrument was designed. Next, the same CTOs, as well as a broader group, were invited to respond to the instrument in personal or virtual meetings. Seventy-three CTOs and VPs R&D in Europe (25), Canada (20), and the United States (28) agreed to provide data. Ratings were obtained on 105 practices. The industries covered are both capital- and knowledge-intensive. Only 20% of our sample is from IRI membership. Data on the financial performance of firms were gathered independently from public databanks and corporate Web sites.

The wealth of information that we gathered made it possible to undertake statistical analyses. First, factor analyses were conducted to identify the underlying vectors that characterize the responses of CTOs to their use of management practices. Second, cluster analyses of the different ways that firms create value were made. Finally, stepwise multi-factorial regressions were used to link innovation management practices to sales growth globally or within games of innovation.

2. Games of Innovation and Value Creation

Value creation is often presented as the development of new products and services that increase the utility that customers obtain from them (Kim and Mauborgne 2000). Innovation is seen as combining scientific knowledge with marketing to identify radically superior solutions, thus making market rivalry irrelevant (Prahalad and Hamel 1998; Hamel 2000). By breaking away from conventional wisdom, companies are said to be able to discover fundamentally new sources of value that were not apparent before (Kim and Mauborgne 2000).

In terms of innovation, the strategic intentions of the firms that were part of our study could be summarized along three axes: first, advancing the frontier of science and technology through R&D investments that are riskier but could lead to the development of new markets and build a reputation of innovative leadership; second, capturing value from existing product lines by adding new features and matching competitors’ offers and capabilities; and third, adding new businesses even at the risk of cannibalizing existing product lines.

CTOs saw that to fulfill these intentions, value creation would have to be geared toward meeting the expectations of industrial or individual buyers in specific contexts. For instance, innovating in airplane design consists not so much in introducing novelties to satisfy consumers as in focusing strategically on the needs of airlines to increase safety, achieve higher operating efficiency and control costs. Similarly, creating value in software products not only means offering innovative solutions but also reducing uncertainty for users by promoting stable architectures. When safety concerns predominate, as they do in drugs, airplanes, and cars, value is created by combining forefront knowledge and testing to gain regulatory approval.

Our results “on games of innovation” will be presented in five subsections: (1) the logic of value creation activities and its components (2) the identification and description of eight “games” of innovation (3) the configuration of stakeholders in each “game” (4) the allocation of efforts toward innovation in each “game”; and (5) the performance of each “game” in terms of sales growth and profitability.

 

2.1       The Logic of Value Creation

Through our conversations with CTOs, we have identified ten basic activities by which R&D creates value for buyers: (1) transform scientific knowledge into products (2) accelerate regulatory approval (3) engineer safety and reliability (4) make one’s products into de facto standards (5) align products and services with emerging architectures (6) reduce costs and improve quality (7) produce new features and generations of products (8) stimulate modular and architectural innovations (9) anticipate and meet the needs of lead users and (10) customize mass production for each client. Firms do not pursue all of these activities simultaneously and with the same intensity. Rather, they focus on the activities that can produce more value given the economic, technological, regulatory, and competitive context of their sector. Figure 1 displays the basic value-creation activities for firms in “games” characterized by high speed of scientific and technological change as opposed to the average for all firms in our sample.

Figure 1

 

 

As indicated at the bottom of Table 1, these ten sets of activities can be reduced to four vectors using factor analysis methods. These vectors are: (1) processes for productizing knowledge and intellectual property into products, (2) mechanisms to interact with clients and understand their needs, (3) processes to align and stabilize design architectures and (4) engineering processes to ensure cost reduction, safety and reliability.

2.2       Eight Distinct Games of Innovation to Create Value

Using a K-means cluster analysis procedure in (SPSS) Statistical Package for the Social Sciences), we produced eight groupings of firms according to their emphasis in value-creation activities. Cluster analysis procedures minimize intra-group multidimensional distances between cases to identify coherent sets of firms creating value in similar fashion and maximize the inter-group distances to separate them from other sets of firms creating value in a distinct manner. Firms in each group emphasize similar value-creation approaches, despite the fact that they belong to different industrial sectors. Table 1 shows how these eight groups are classified; clusters are statistically different from one another. Differences in value creation activities revealed by this grouping were the key insights that led us to the concept of “games” of innovation.

Games of innovation are patterns of value creation activities each of which can produce a steady flow of a certain type of innovation (Miller & Hobday 1995). We call these patterns games of innovation because each appears to be governed by rules that emphasize distinct ways of competing and collaborating, sharing knowledge and risks, coordinating efforts, and capturing value. The notion of a game is used here as a metaphor to stress the fact that firms find themselves in structured contexts that constrain and orient their approaches to innovation. Yet, within the given rules, games offer ample strategic freedom. Our focus is not the economic field known as game theory, which involves interactive decisions in which players’ preferences are stable, payoffs predetermined, and strategies limited in view of the requirements of mathematical modeling.

For the purpose of presenting the eight games, we will distinguish between high- and low-velocity games. We built an index from respondent’s evaluations of scientific pace and market dynamism. High-paced scientific output and high-growth markets characterize high velocity games, while the reverse applies to low velocity games.

2.2.1    High-velocity games of innovation

The game of Battles for Architectures is common in industries such as mass software products, telecommunications products, and Internet services. The context of such industries is characterized by high pace of change, low degree of regulation, individual clients with little information, and expert corporate clients. Value is created mostly by aligning solutions and modular components with emerging architectures in an attempt to make products become de facto standards ensure connectivity and provide engineering reliability, thus reducing uncertainty for clients.

Because increasing returns to adoptions lead to large shares for the architecture selected by market forces, strategies for identifying architectures – aligning products and pushing them through marketing, partnerships, and diplomatic activities – are the keys to success. Battles for Architectures is not a game of scientific prowess, but involves keeping abreast of new concepts and of competitors’ moves in order to surf ever-shifting architectures and seek ways to stay on the winning side so as to capture increasing returns. For instance, Sun Microsystems saw the development of JAVA as a new way to compete with Microsoft. The UNIX experience had taught Sun’s senior management that attempting to push one’s architecture may lead to competitive polarization in which one family of products eliminates another. To create a market for JAVA and Sun workstations, Sun Microsystems engaged in coalition building and shuttle diplomacy with Oracle, IBM, and 190 other firms. Sun Microsystems positioned itself as a party promoting an architectural standard that created value for customers while increasing demand for its own workstations.

Races to the Patent and Regulatory Offices. The highest scientific pace as well as the presence of institutions for regulatory safety approval and for intellectual property protection characterizes the context of this game. Competitors want to create intellectual property, working prototypes and “process knowledge” fast so as to start new businesses. Value creation is based largely on the ability to productize university-research or intellectual property through projects and management of the regulatory process.

Firms in this game are mostly entrepreneurial start-ups in biotechnology, fuel cells, or other domains that exploit the latest scientific discoveries, such as genomics and bioinformatics. The most influential stakeholders are the scientific communities, regulators, and financial analysts. The main sources of ideas are universities and other start-ups. The protection afforded to intellectual property enables the allocation of different activities among smaller specialized firms coordinated by an entrepreneurial sponsor. For instance, Altarex, a Boston-based biotechnology firm, organized a core team of four executives in the areas of research, finance, regulatory approval, and contracting. The core team relies on an external network to concurrently secure venture-capital financing and perform the scientific program by contracting with independent scientists; the aim is to deliver and obtain approval for a drug at half the price and 60% of the time of large pharmaceutical firms.

Delivering Safe Science-based Products. Moderate scientific opportunities, highly structured regulatory frameworks, and high unpredictability, due largely to challenges from pressure groups and regulators, characterize the context of this game. Competitors tend to be established firms in pharmaceutical, agro-biotech, or veterinary products. Producing value depends on productizing intellectual property and, to the largest extent of all the games, delivering in a cost-effective manner absolutely reliable and safe products. With the increasing presence of government health services and HMOs, pressures to reduce costs are high.

Aventis Pasteur, a producer of vaccines to meet the needs of large clients such as health ministries and private health groups, is involved in this game. Regulatory issues drive R&D activities and force a clear focus on both the effectiveness and the side-effects of vaccines. Intellectual property from which vaccines are developed is generally secured from university-based research groups. Projects tend to run to hundreds of millions of dollars and involve clinical testing: pre-clinical tests; proof of concept for humans; large clinical trials, lasting many years, with 10,000 to 50,000 individuals in treatment and control groups; and post-marketing surveillance. The major downside risk is the inability to gain regulatory approval, as adverse effects counter beneficial ones.

Information Systems Design and Consulting Services. Firms in this game face a context characterized by moderate speed of scientific and technological change and very demanding expert clients, but little regulatory structure. Competitors offer systems consulting for power, banking, manufacturing, communications, and other sectors. To create value, firms propose systemic architectures aligned with the dominant or emerging standards, and with existing hardware, software tools, and communication protocols. Firms are thus knowledge clearinghouses between clients, vendors, and software suppliers to design systemic solutions and align them with dominant standards.

Cambridge Technology Partners, Powertech of Vancouver, and CGI in Montreal use R&D to understand the evolution of IT systems by interacting with hardware, software, and logistics systems builders in order to develop systemic ”points of views” to guide clients’ that must make large investments in IT systems. They also help clients build competencies to implement solutions. R&D is not a distinct department but an activity funded at the corporate level, conducted by consultants, and involving wide networks of university professors, gurus, and vendors.

Research, Development, and Engineering Services. Firms in this game face contexts characterized by very rapid scientific and technological change, short product life cycles, and few large and few large demanding and expert customers. In fact, customers are chip producers, aircraft assemblers, or pharmaceutical firms that use tools to enhance engineering or scientific productivity. Competitors in this game offer advanced engineering, research tools, and sometimes services. They create value by transforming forefront university research into products and services, as well as by understanding, anticipating, and serving the complex needs of their clients.

Synopsis, a firm in Mountain View, California, builds software tools for designing integrated circuits such as Pentium chips. The key drivers of innovation are technical developments, the need for continuous new releases, and coordination with buyers. Synopsis competes with the internal R&D groups of clients such as Intel and attempts to develop superior product architectures that will form the basis for families of products with many versions. Markets are small, with 25,000 copies being a large volume. Products are licensed to large customers using multiple copies to form engineering networks. Synopsis faces a limited number of very strong clients, such as Intel and Boeing, who set rules for innovative products.

2.2.2    Low velocity games of innovation

Using the same index as above, we determined that Delivering Workable Solutions in Packs, Customized High-tech Craft, and Asset-specific Problem Solving are low-velocity games

            Delivering Workable Solutions in Packs. Competitors in this game aim at developing complete solutions to large customers’ problems in order to create new markets so as to stimulate the sales of oxygen, aluminum, packaging materials, and so on. The context in which competitors operate is characterized neither by a high pace of scientific and technological change nor by he presence of regulators. For instance, a firm producing aluminum has, over time, designed innovative solutions for product packaging in the food industry. Other firms have found new uses for industrial gases and successively entered growing markets, such as semi-conductors, petrochemicals, health, and biotechnology, while continuing to serve older industries such as steel production or metallic fabrication. Firms cooperate with clients and partners to deliver large-scale and problem-free solutions to industrial customers.

For example, Pechiney Packaging creates value by linking suppliers, equipment builders, and plant engineers to solve customers’ problems. R&D projects are large inter-organizational ventures to build solutions for customers in one industry after another. Similarly, Air Products and Chemicals builds oxygen factories within the production plants of its clients as a creative way to deliver its product (and generate sales).

Asset-specific Problem Solving. The context of this game is characterized by high capital intensity but low scientific or technological opportunities. Creating value in capital intensive sectors, such as energy, pulp and paper, cement, mining and water purification, concerns mainly productivity, quality, and customer service. Existing technologies, rather than new knowledge, are the basis for creating value by using assets more efficiently. The central mission of R&D is to identify and frame the problems to be solved. Examples are quality control in paper-making, optimal electricity-trading procedures, and continuous cost reduction in petrochemical installations. Once the problem has been well framed, R&D projects can usually be organized with internal staff but often involve outside contract research organizations or suppliers to transfer technology. The most important stakeholders are partners, environmentalists and environmental regulators.

As an example, R&D at Syncrude Canada Ltd. has the goal of continuously reducing the cost of mining and extraction of oil from tar sands. Unit costs have been reduced by close to 60% over the last ten years as a result of systematic improvements in mining methods, material handling, equipment wear, and extraction processes. Problems were defined jointly by R&D and operations. Ideas for improvement usually were found externally but applied internally through alliances with equipment suppliers and research consortia.

Customized High-tech Craft. This game of innovation takes place in sectors such as aerospace or flight simulation, in which innovation depends on the synchronization of moves between highly inter-dependent players. The context is characterized by low speed of technical change, moderate institutionalization, and highly demanding clients. The central way of creating value is understanding the needs of expert clients (to the highest extent of all games) and delivering customized solutions, while at the same time aligning such solutions with the existing solutions adopted by the client. Increasing the reliability of systems and reducing costs reveals the role of engineering expertise.

CAE, a builder of flight-simulation devices, understood many decades ago that simulators have value for customers not because they are innovative but because they are adapted to the specific aircraft and pilot-training programs of each airline, certified by regulators, and approved by aircraft builders and pilots’ associations. Hence, they not only understand user needs but participate actively in shaping the certification standards for simulators and pilot-training programs..

 

2.3       Configurations of Stakeholders in Each Game

Competitors in each game face stakeholders with different expectations, as well as different abilities and readiness to share risks. Value creation is rarely limited to internal R&D alone, but is achieved jointly within networks of organizations, each of which solves some of the uncertainties involved. For instance, university research leads to new knowledge about pathologies or therapies, thus creating intellectual property. Then, pharmaceutical or bio-technology firms apply their skills at productizing concepts, clinical testing, and interacting with regulators, with the assistance of firms that create research tools or specialized information databases. In the end, regulatory approval is the official creator of value but commercialization rests with pharmaceutical firms. Table 2 displays how stakeholders differ (with statistical significance) for each game. The differences between games are statistically significant for most stakeholders.

For instance, in Races to the Patent and Regulatory Offices, significant stakeholders are regulators, because of the role that patents and certifications play; the scientific community, for access to forefront ideas and legitimacy; and financial analysts, whose evaluations are necessary to secure access to public funds. By contrast, in Customized High-tech Craft, expert customers are dominant stakeholders, while public regulators are the dominant stakeholders in the game of Delivering Safe Science-based Products.

           CTOs also recognize that the process of creating value relies on many sources of ideas. Overall, internal R&D represents about 30% of these ideas, lead-users 25%, universities 25%, complementary start-ups 10%, and partners 15%. However, as table 2 indicates, variations across games are significant. For instance, universities represent 42% of idea sources in Races to the Patent and Regulatory Offices, while internal R&D is the predominant source of ideas in Delivering Safe Science-based Products.

2.4       The Allocation of Efforts in Each Game of Innovation

To create value, R&D expenditures as a function of sales average 15.9% for all firms in our sample for the year 2000. However, statistically significant variations can be observed across games (at the 0.05 level), as value-creation activities entail highly different levels of efforts. As table 2, shows R&D expenditures on sales range from 0.84% for firms in the game of Asset-specific Problem Solving to 39.4% for firms in Research, Development and Engineering Services. Expenditures are also quite high (22.4% of sales) for firms in the game of Delivering Solutions in Packs. Firms engaged in Races to the Patent and Regulatory Offices spend 18.0% of sales on R&D, while those in the game of Delivering Safe Science-based Products allocate 14.5% of sales to R&D. It is interesting to note that firms in Battles for Architectures spend 11% of sales on R&D.

The allocation of total R&D efforts between renewal of scientific competencies versus roadmap R&D also varies, as indicated in table 2. Roadmap R&D – directed research oriented toward current businesses to develop new products, technologies, and applications within articulated trajectories – accounted for over 80% of efforts in games such as Customized High-tech Craft, Asset-specific Problem Solving, and Battles for Architectures. By contrast, renewal research, to seek new technologies or identify new market opportunities, was significantly higher in Races to the Patent and Regulatory Offices and Information Systems Design and Consulting Services.

2.5       Variation in Performance across Games

The games in which firms compete have an important impact on performance. Competing in a game in which rewards are rich tends to increase the probability of achieving high performance. By contrast, competing in a game in which results tend to be lower will probably affect performance downwards. A range of dimensions were used to asses performance: (1) sales growth over the last five years, (2) average return on invested capital, (3) returns on assets, (4) market capitalization in 2000, (5) and growth of market capitalization over the last five years. Subjective evaluations by the CTOs of their firm’s innovativeness, competitiveness, and new product introductions were also taken into account. Only three dimensions turned out to be statistically significant across games: (1) sales growth over the last five years, (2) average returns on investment, and (3) innovativeness as compared to industry average. As the number of firms in each game is small, caution in generalizing results is encouraged.

The ability to sustain sales growth varies significantly across games. For instance, the average annual growth in sales over the last five years is 20%. As table 3 indicates, games experiencing above-average growth are Races to the Patent and Regulatory Offices (57% per year), Battles for Architecture (29% per year), Research, Development, and Engineering Services (49% per year), and Customized High-tech Craft (21% per year). By contrast, games experiencing below-average growth are Asset-specific Problem Solving (8% per year), Information Systems Design and Consulting Services (15% per year), Delivering Workable Solutions in Packs (8% per year), and Delivering Safe Science-based Products (12%).

Returns on investment also vary significantly across games. Contrary to the hypothesis that differences in returns should disappear as competitors and new entrants pursue rewarding opportunities, we have observed that differences in returns on invested capital exist and subsist. For instance, in games in which knowledge is the major factor of production, many firms achieve very high levels of returns on invested capital (32% to 51%). On average, returns on invested capital are 12.1% with a 95% confidence interval ranging from 7.6% to 17.5%.

Figure 2 plots all firms as a function of sales growth over the last five years and average returns on investment. Except for one outlier firm that grew 1200% over the last five years, performance results are distributed normally. Many firms achieve low results even if they belong to games that are characterized by high performance. The most striking fact is that while a good portion of firms in low velocity games appear to cluster in the northwest corner, where returns on investments are above average but sales growth is below average, the majority of firms in different games achieve highly scattered performance from very bad to exceptional.

Games also differ on the subjective assessments by CTOs. Innovativeness is an indicator that summarizes the frequency of new product introductions, the percentage of revenues attributable to the renewal of product lines, and the presence of technical breakthroughs. In games such as Races to the Patent and Regulatory Offices, Research, Development, and Engineering Services, and Battles for Architectures, the degree of innovativeness is judged to be significantly higher than in other games.


Figure 2 –Distribution of firms in terms of profitability and sales growth

LV: Firm in a low-velocity innovation game

HV: Firm in a high-velocity innovation game

3.         Best Practices for Managing Innovation

The goal of identifying the best practices that make organizations smart, innovative, and high-performing is promoted by many researchers (Matheson and Matheson 1998). Managers are invited to coordinate strategic plans with R&D, focus on end-customers, use formal project management, and, above all, align R&D with corporate strategy (Metz 1996). Many propose to broaden the mission of R&D to empower it to play a strategic function. (Miller 1995). Consultants and conferences convey the suggestion that a range of best practices apply across industries (Meyer & Rowan 1977; Abrahamson, 1991).

Many practices for managing R&D have been identified in our sample of firms; paradoxically not one is statistically (and significantly) related to growth in sales. In other words, practices such as planning innovation processes, interfacing with customers, managing product development, cooperating with partners, and assigning strategic roles to R&D are used to varying degrees by all firms but are not statistically related to growth in sales. Before we try to resolve this paradox, let us outline the generic practices we have identified.

3.1       Generic Practices for Managing R&D in the New Context

CTOs and VPs R&D rated their actual use of 105 distinct practices. These practices were summarized though factor analysis into 27 generic practices, which fall into 3 categories: the corporate role of R&D, policies to govern R&D, and practices for structuring the journey of innovation from idea to market shaping (see figure 3). For instance, the development of a corporate role for R&D requires the following generic practices: (1) Assign a strategic leadership function to R&D (2) put R&D in charge of managing innovation processes (3) task R&D with interfacing with clients and stakeholders (4) allocate R&D an advisory role to SBUs. A short description of these 27 generic practices is provided in Appendix A.

 

Figure 3 – Generic Practices to manage R&D

 

 

 

Generic practices represent processes for adapting to the new competitive context. However, as we tried to find statistical linkages between generic practices and sales growth over the last five years (whether in single correlations or in stepwise regressions), it became obvious that no single practice is linked to growth in sales across our sample. Competencies, such as interfacing with customers, cooperating with partners, and assigning corporate roles to R&D, are used by many. At the same time, some practices are used by one group of firms but not by another; for instance, some firms allocate close to 60% of R&D efforts to exploration of technical and market opportunities while others spend only a few percentage points.

 

3.2       Practices are contingent to the Requirements of Each Game

Does this mean that the search for best practices is irrelevant? Our findings indicate instead that the practices that lead firms to success are not universal but contingent on the requirements of the game in which they compete. Firms may try to adopt what they consider to be best practices, but the requirements of competitive rivalry to satisfy customers demand adaptations of these practices to the realities of value creation, specificities of context, and conditions emerging over time. Playing in a game calls for the development of specific competences and capabilities but the downsizing of others. For example, a firm that has built competencies to build airplanes finds it almost impossible to engage in races to develop new market with novel products.

As a result of shaping efforts to adapt to the context, learn to meet contingencies, and accumulate knowledge, some practices become fit for the purpose at hand, while others remain less productive. There is thus no single best way to manage innovation processes; the selection of practices is contingent on environmental factors. Firms facing different environments innovate by creating and capturing value differently and thus emphasis different practices.

Table 4 illustrates practices that stand out in each game as statistically different from others. For instance, in Races to the Patent and Regulatory Offices, R&D is assigned a strategic role to set the mission, technology is sourced externally, and exploration for technology and market opportunities is achieved through probing and experiments. By contrast, in Asset-specific Problem Solving, the practices that stand out are networking to explore for technical and market opportunities, extensive roadmapping, and practices that facilitate transfer to operations.

 

4.         Excellent Organizations: Practices Linked to Growth

Yet, the question still remains as to whether some practices might be associated with growth within games of innovation. In other words, are there firms that are better than others at achieving growth in their game of innovation, and what management practices they use better than others to achieve growth?

To answer this question, we analyzed the four games for which we had reasonable numbers of firms: Asset-specific Problem Solving, Battles for Architectures, Delivering Workable Solutions in Packs, and a grouping together of Races to the Patent and Regulatory Offices and Delivery of Safe Science-based Products. For each of these games, we built stepwise multiple regressions with sales growth as the dependent variable and firms’ score on generic practices as independent variables. The SPSS procedure for multiple regressions includes or excludes each independent variable as a function of its explanatory power and significance.

Table 5 presents our results. In each game, firms use a range of generic practices for managing innovation, but the majority is not significantly associated with sales growth. In fact, most generic practices for the management of R&D are excluded as predictors in stepwise regression analyses. More specifically, no statistically significant associations exist between sales growth and the presence of capabilities such as managing processes for innovation, interfacing with markets and stakeholders, imparting a business orientation to R&D, empowering of R&D, opening of R&D to competitive outsourcing, cooperating with outside partners to grow markets, or convincing by training customers, building scientific reputation, and understanding the regulatory process.

However, in each game distinct generic capabilities stand out as statistically associated with sales growth. In other words, firms that achieve high levels of sales growth use practices that are adapted to the requirements of value creation in their game. Table 5 lists specific practices that stand out as statistically associated with sales growth.

Firms in Asset-specific Problem Solving games that achieve high level of sales growth are using networking more than are their competitors: they sit on standards bodies, participate in industry networks, and interact with equipment suppliers or producers in the value chain. R&D is realistically oriented toward discussions with suppliers of IT systems, equipment manufacturers, producers of chemicals, and so on, to glean solutions that can be applied at low cost but with high benefits given the volumes involved.

Firms in games of Battles for Architectures use four different sets of practices that are significantly related to sales growth. They impart strategic as well as interface roles to R&D. Furthermore, they transform themselves by continually replacing products and establishing teams for market entry. Finally, they facilitate new product innovations and launches by developing intrapreneurship and corporate venturing policies.

Firms in games of Delivering Workable Solutions in Packs that achieve superior growth rely on still different practices. Exploration of market and technical opportunities is achieved, as table 5 indicates, through practices such as joint exploration between marketing and R&D, exploration with customers and lead users, and probing customer needs with preliminary designs. Firms also transform themselves through the building of projects for market entries.

Firms in Racing to the Patent and Regulatory Offices and Delivery of Safe Science-based Products that achieve high sales growth also use entirely distinct practices. First, the management of intellectual property is achieved through patenting of core knowledge and licensing of technology. Second, markets are developed through visibility-enhancement practices such as participating in public debates and stimulating comparative studies.

 

Conclusion: Alignment with Value Creation

Our study has generated a tremendous array of data. Our central finding has been that value creation is not only a matter of imaginatively developing new products to reach new markets or capturing wealth for investors, but consists in a set of activities and processes by which R&D transforms scientific knowledge into superior solutions, interacts with expert customers to outline requirements, aligns with dominant or emergent solutions, and engineers reliable and safe systems. Doing R&D right calls for an understanding of integrated innovation processes by which a range of activities serves to create value.

Furthermore, firms create value differently depending on the game that they compete in. Much of the discourse on R&D management stresses that R&D activities have to align with corporate strategy. Such a view is certainly possible in games in which the rate of technical and commercial change is low. However, in some games only those who participate in the turmoil of scientific and technical change can identify and exploit opportunities. In this case, R&D sets the strategy and energizes the firm by absorbing the flow of innovative energy from the scientific communities, venture capital, and leading customers. R&D then converts these ideas into opportunities. Technology managers need to be clear about the game that their firm competes in and how value is created for buyers. Gauging the expectations of stakeholders is also important. External pressures come from competitors and from players attempting to enter from other industries. Shareholders, market analysts, venture-capital investors, and interest groups also push their respective agendas.

Finally, there are no best R&D management practices that will open paths to superior performance. All firms have access to best practices through consultants, models diffused by institutions such as IRI, or exemplars set by highly successful firms. Unsurprisingly, we observed that sales growth over the last five years was unrelated to the use of best practices. However, excellent firms build competencies to match the game they compete in. To combine the requirements of value creation and the environmental context, strategic decisions need to be made with respect to central corporate responsibilities, decentralization to business units, downsizing of internal activities in view of outsourcing, and so on. For the R&D function to contribute to performance, these elements must jointly provide the R&D with a purpose, an optimal sense of urgency, incentives, and resources.

Appendix A

The 27 generic practices were identified by a factor analysis of the 105 distinct practices used by firms. These are regrouped under three headings: (1) corporate role of R&D (2) the innovation journey and (3) basic policies to manage R&D.

1 The corporate role of R&D indicates the extent to which new knowledge drives the firm’s strategy and the extent to which ‘technical and scientific’ knowledge networks have a voice inside the firm. . The various roles that firms can assign to R&D can be regrouped under the four underlying vectors that together explain over 66.5% of the variance across roles:

-       Strategic leadership role through setting the vision for the firm, developing new business and active participation in the planning process(24.3% of variance)

-       Design and Management of corporate innovation processes by linking internal functions with outside networks(15.3% of variance)

-       External Interfacing: meeting customers or lead users, testing new products in collaboration with them or dealing with stakeholders pressures and claims.((14.8%)

-       Advising business units by commenting on their strategic plans to serve and develop markets through new or improved products (12.2% of variance).

2 The basic Policies for managing R&D to manage R&D focus on the necessity to provide power and incentives while opening R&D to competition and external sourcing of technology. The various policies for managing R&D can be regrouped under four vectors:

-Empowering R&D by appointing technology officers at the top ,by allowing R&D to build business cases and propose new ventures , by accepting that R&D challenge strategic directions and by training scientists and engineers in strategic analysis(21.5% of variance).

-Attuning R&D to business concerns by rotating scientists into operations and by funding R&D from business units as well as headquarters (17.6% of variance).

-Opening R&D to competitive pressures by outsourcing to specialized technology suppliers and by spinning unneeded R&D capabilities out (12.5% of variance).

-Investing in technology development by acquiring external firms and managing a portfolio of external ventures staff (9.5% of variance)

3 The practices to manage the Innovation Journey can be broken into five distinct but inter-related systems of activities which start by exploring for market and technological opportunities and building a portfolio of investment initiatives. R&D projects at varying stages of development then have to be conducted and results either transferred internally or used to develop new businesses .Increasingly, R&D activities comprise activities to shape markets and foster diffusion.

- Engage in exchange of ideas and knowledge through joint exercises between R&D and marketing, sitting on the technical board of suppliers, interactions with customers and lead users(20.8% of variance).

-Probing the future though practices such as mapping exercises, consulting gurus or screening of external start-ups proposed to the firm as a substitute to internal R&D.(13.7% of variance)

-Networking widely by participating in industry working groups, suppliers associations and standard bodies (13.1% of variance)

-Working with partners in pre-competitive research activities and with producers of complementary products (11.3% of variance)

 

-Aligning the portfolio of projects to the corporate strategy through formal screening methods, portfolio management or R&D boards

-Reliance on the judgment of experienced corporate and SBU managers or venture capital experts to develop strategic options thinking.

-Development of scenarios of the future to ensure that the portfolio contains innovative components

-Establishment of venture capital funds to broaden the portfolio by investing in external opportunities to diversify technology options and ensure access to pioneering products.

Š      Practices to execute and manage projects which represent about two thirds of R&D efforts can be regrouped under three vectors

-Iterative practices such as cross-functional teams, interacting with customers, collaborative product development through beta-sites with lead users and strong project managers with resources (20.5% of variance).

-Formal discipline through practices such as QFD or Voice of the Customer to support R&D/Market interactions in defining and prioritizing product features, systems of gates and phase reviews and planning using project management methodologies. (19.2% of variance)

-Outsourcing of modules of activities to sub-contractors and technology suppliers (10.5%of variance) .

-       Stimulate the use of R&D outputs by supporting transfer financially , by providing incentives to reduce the risks of adoption and by locating champions in SBU’s to ensure receptivity (19.3% of variance))

-       Develop new business development capabilities by building entrepreneurship and corporate venturing processes (19.2% of variance)

-       Radical transformation of business units by re-orientation , amputation and creation of new ones supported by renewal of product lines (15.8% of variance)

-       Management of intellectual property by patenting within and around core technologies and by licensing unused knowledge(14,6% of variance)

-       Practices for shaping external environment to trigger diffusion also form four vectors which account for 63.20% of the variance across practices,

- Cooperating to build markets with partners, complementary product producers, third party suppliers and standard bodies (20.8% of variance.

- Making products and services visible by stimulating comparative studies and participating in public debates (18.1% of variance)

- Convincing potential customers about the value of products by training customers and interfacing with regulators (13,1% of variance)

- Accustoming targeted buyers to products by temporarily selling them at low prices (11.3% of variance)

 

References

Abrahamson, E. 1991. Managerial Fads and Fashions: The Diffusion and Rejection of Innovations. Academy of Management Review 16(3): 586–612.

Gupta, A.S., and D. Wilemon. 1996. Changing Patterns in Industrial R&D Management. Journal of Product Innovation Management 13(6): 497–511.

Hamel, G. (2000) Leading the Revolution. Boston, Mass.: Harvard Business School Press, 333p.

Kim, W. Chan, and R. Mauborgne. 2000, Sept.–Oct. Knowing a Winning Idea When You See One. Harvard Business Review, 129–137.

Matheson, D., and J. Matheson. 1998. The Smart Organization. Boston: Harvard Business School Press.

Metz, P.D. 1996, May–June. Integrating Technology Planning with Business Planning. Research Technology Management, 19-22.

Meyer, J. W., and Rowan, B. 1977. Institutionalized Organizations: Formal Structure as Myth and Ceremony. American Journal of Sociology 83: 340–63.

Miller, W.L. 1995, Nov.–Dec.. A Broader Mission for R&D, Research Technology Management, 24-36.

Miller, E.R. and Hobday, M. (1995) “Innovation in Complex System Industries: the Case of Flight Simulation” , Industrial and Corporate Change, Vol.4: pp.363-400.

Prahalad, C.K., and G. Hamel. 1994. Competing for the Future. Boston: Harvard Business School Press.

Quinn, J.B. 2000. Outsourcing Innovation: The New Engine of Growth. MIT Sloan Management Review 41(4): 13–28.

Samuelson 1997

Lee Roy and Beach 1998

Menke 1997

Miller 1995

 

Table 1 Games as clusters of firm with distinct value creation activities

 

 

Innovation game

 

 

High-velocity games of innovation

Low-velocity games of innovation

Game name

Battles for Architectures

Races to the patent and regulatory offices

Delivering safe science-based products

Systems design and consulting services

Research , development

and engineering services

Delivering workable solutions in packs

Asset-specific problem solving

Customized high tech craft

Number of firms

17

5

7

5

6

11

13

9

Industries typically represented

Telecom-munications services and equipment, BtoB and mass market software, electronic test and measurem. equipment

Biotechno-logy

Pharma-ceuticals, agrobio-tech, medical devices, home appliances,

MIS consulting and design, consulting and research for power systems, telecomm research services, office equipment

Computer modelling, drug research and discovery services, specialty cosmetic ingredients research

Chemical products, industrial gas products, packaging materials, building materials, pharma-ceutical ingredients

Cement, electric utility, gas utility, pulp and paper, petro-chemicals, mining and oil extraction, water treatment

Industrial controls and equipment, engineering design tools, specialty food ingredients, specialty chemicals, electronic equipment

Value creation

factors

 

 

Productizing

0,09

1,26

1,11

-0,18

1,27

-0,1

-1,21

-0,61

Serve needs

-0,35

-1,12

-0,82

-0,44

0,71

1,41

-0,58

0,83

Stabilizing

0,75

-0,69

-0,87

1,5

0,38

-0,88

-0,74

0,68

Engineering

0,73

-0,95

1

-1,89

-0,87

-0,05

-0,2

0,35

Bold figures are significant at the 0.01 level

Table 2: Stakeholders and the direction of R&D efforts for each game

 

 

Innovation game

 

 

High-velocity games of innovation

Low-velocity games of innovation

 

 

Battles for architectures

Races to the patent and regulatory offices

Delivering safe science-based products

Systems design and consulting services

Research, development and engineering services

Delivering workable solutions in packs

Asset-specific problem solving

Customized high-tech craft

Influences (1 to 7)

Regulators**

3,12

5,6

6,57

1,6

4,67

4,27

4,92

3,83

S&T commun.*

3,71

6,2

4,29

3,8

5,83

3,55

4,23

3

Customers**

5,94

3

4,71

5,6

5,67

6,23

5,31

6,44

Competitors

5,53

5,2

4,57

4,8

4,75

5,18

4,92

4,44

Partners

4,29

4,2

4,29

4,2

5,5

4,91

5,46

4

Analysts*

3,24

4,8

2,86

1,6

5,5

3,18

2,54

3,67

Venture cap.+

2,41

2,6

2,29

1,4

3,83

1,91

1,31

2

Environment.**

1,76

2,4

3,57

1

3

3,91

4,5

2

Idea sources %

Internal

41,65

36

53,57

34

33

40,36

38,31

48,33

Start-ups*

6,18

14

6,07

4

19,17

4,55

8,69

5,56

University**

10,12

42

16,79

20

14,67

8,55

18,31

5,56

Partners

12,94

7

15

10

19,67

15,82

16,92

10,56

Customers+

23,53

1

8,57

29

13,33

23,36

13,46

30

Other

4,41

0

0

3

0

7,27

3,46

0

Allocation R&D efforts

R&D over sales

11%

18%

14,50%

15%

39,60%

25,20%

0,84%

12,80%

Road map R&D

78,53%

39,00%

75,00%

42,00%

54,17%

69,55%

84,62%

81,67%

Renewal R&D

21,47%

61,00%

25,00%

58,00%

45,83%

30,45%

15,38%

18,33%

An ANOVA procedure was performed to determine whether the inter-group differences are significant

** Bold figures are significant at the 0.01 level, * Significant at the 0.05 level.

 

Table 3 Comparison of performance indicators between games

 

 

High-velocity games of innovation

Low-velocity games of innovation

Game Name

Battles for architectures

Races to the patent and regulatory offices

Delivering safe science based products

Information systems design and consulting services

Research and development services

Delivering workable solutions in packs

Asset-specific problem solving

Customized high-tech craft

Average ROI

 

 

 

 

 

 

 

 

1996-2000

19%

13%

8.9%

8%

3.9%

16%

11.5%

9.5%

Sales growth

over last 5 years

 

 

 

 

 

 

 

 

99.1%

184%

90.7%

31.8%

155%

52.2%

22%

42.5%

Subjective

evaluation of

R&D’s

contribution to competitiveness

High

Very High

Average

Average

High

Average

Low

High

 

Table 4: Generic practices and their importance in each game

 

Innovation game

 

 

Game name

High-velocity games of innovation

Low-velocity games of innovation

Battles for architectures

Races to the patent and regulatory offices

Delivering safe science-based products

Info systems design and consulting services

Research and development services

Delivering workable solutions in packs

Asset-specific problem solving

Customized high-tech craft

 

 

R&D Roles

Strategic**

0,09

0,88

0,64

0,28

0,67

-0,37

-0,72

-0,23

Process mgmt

0,2

-0,49

-0,59

-0,62

0,85

0,25

-0,1

-0,09

Interface mgmt

-0,39

0

0,53

0,69

0,4

-0,17

-0,22

0,27

 

 

Basic Policies

Empower

0,29

-0,76

0,09

0,06

0,87

-0,26

-0,28

-0,08

Attune to business

0,16

-0,82

-0,43

0,28

-0,75

0,38

0,08

0,23

Competition

-0,17

0,72

0,19

-0,77

0,17

-0,07

0,09

0,04

Invest

0,2

0,12

-0,45

-0,41

0,47

-0,08

-0,32

0,39

 

 

%

Exploration**

11,25

24

16,43

34

15,83

16,91

12,62

15,33

Portfolio mgmt

17,81

27

17,86

23

30

21,36

24,77

21,44

Execution

70,94

49

60,71

43

47,5

61,64

58,77

63,11

 

 

Explore

Transfer

0,18

-0,73

-0,42

0,24

0,37

0,24

-0,44

0,28

Probe

0,01

0,63

0,28

-0,05

0,48

-0,38

-0,33

0,14

Network

0,3

-0,31

-0,17

0,82

-0,56

-0,26

0,29

-0,48

Create jointly

-0,38

0,11

-0,55

-0,03

0,6

0,18

0,46

-0,16

R&D Boards (1 to 7) *

3,18

6

5

2,4

4,83

5

4,54

3,56

Outsource execution (1 to 7)

2,94

4,6

3,29

2,4

3,5

3

4,19

2,78

Beta sites (1 to 7) **

5,47

1,4

2,86

5

5,17

5,27

4,54

5,11

 

Remove obstacles

Easing transfer*

0,07

-0,73

-0,6

-0,08

-0,3

-0,34

0,82

0,22

Venturing

0,05

0,49

-0,12

0,87

0

0,09

-0,62

0,03

 

An ANOVA procedure was performed to determine whether the inter-group differences are significant

** Bold figures are significant at the 0.01 level, * Significant at the 0.05 level.


Table 5 Management Practices related to Growth in Sales in four Games of Innovation

Games

 

Practices

Asset-specific problem-solving

Battles for Architecture

Delivering workable solutions in packs

Races to patent office and science-based products

Practices significantly related to

Sales

growth

-Exploring by Networking *

-R square (.344)

 

-Strategic Role for R&D *

Rsquare (.362)

-Interface management **

Rsquare (.517)

--Push aggressively *

Rsquare (.648)

-Venturing policies *

Rsquare (.729)

-Exploration of Opportunities through exchanges *

Rsuare (.504)

-Transformation practices **

Rsquare (.719)

 

-External Visibility **

Rsquare (.610)

-Probing the future **

Rsquare (.980)

-Intellectual Property Management

Rsquare (.679)

Non-significantly related to

Sales

growth

-Strategic Role for R&D

-Innovation processes

-Interface management

-Empowerment of R&D

-Business Orientation

-Competition openness

-Investment policies

-Exchange Knowledge

-Probe Future

-Transfer policies

-Venturing policies

-Push aggressively

-External Collaboration

-Eternal Visibility

-Convince to diffuse

-Innovation processes

--Empowermentof R&D

-Business Orientation

-Competition openness

-Investment policies

-Exchange Knowledge

-Probe Future

-Transfer policies

-External Collaboration

-Eternal Visibility

-Convince to diffuse

-Strategic Role for R&D

-Innovation processes

-Interface management

-Empowerment of R&D

-Business Orientation

-Competition openness

-Investment policies

-Exchange Knowledge

-Probe Future

-Venturing policies

-Strategic Role for R&D

-Innovation processes

 

-Empowerment of R&D

-Business Orientation

-Competition openness

-Investment policies

-Exchange Knowledge

-Venturing policies

 

An ANOVA procedure was performed to determine whether the inter-group differences are significant

 

Appendix A

 

Figure 3 – Generic Practices to manage R&D [2001-SIUQ1] 

The corporate role of R&D

-    Strategic leadership

-    Innovation processes

-    External interface

-    Advising SBU

 

 

 



[1] We had 75 discussions and 73 questionnaire respondents : eliminating double counting, the total is 125 executives



 [2001-SIUQ1]Cette figure est déją présentée dans le texte