Avoiding Alliance Myopia: Forging Learning Outcomes for Long-term Success Hamid Mazloomi ESC Rennes School of Business
[email protected] Maryam Nasiriyar ESC Rennes School of Business
[email protected]
Introduction The strategic alliance is one of firms’ main instruments for coping with uncertainty in the business environment. Alliances help firms to fit their internal resources and activities with their partners’ strength to deal with the complexity and dynamics of industrial changes. Firms form strategic alliances not only for the economic value of cooperation, but also for learning and for the creation of new knowledge, which is the essence of any type of innovation, whether it is a product, a process, or a business model. Despite the increasing value of strategic alliances to the successful implementation of the firm’s strategy, business managers generally underestimate the learning outcomes of alliances as competitive assets. Inkpen (1998) points to “performance myopia” when decision makers focus mainly on short-term and financial objectives for evaluation of an alliance, thereby underrating learning outcomes. Recognizing the learning outcomes of alliances and then planning to apply them to improve the firm’s knowledge resources and processes enriches the sources of creative ideas for product, process, and business model innovation. In addition, firms can integrate the consideration of learning outcomes of alliances into the management of their alliance portfolio to handle what they learn and intend to learn from a particular type of alliance or from a particular partner. Through alliances, firms can
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learn about partners, the product and process of partners’ knowledge, market characteristics, and inter-firm relationship management. In this article, we introduce a framework for understanding four generic types of learning outcome of alliances. As the type of learning outcome depends on the unique features of the alliance, the framework applies two dimensions – learning type and relative contribution – to distinguish different types of alliances and their learning outcomes. We also discuss the determinant factor of success in each type of alliance regarding the corresponding learning outcome. We first explain the two dimensions of our framework individually and then present the four types of alliances on the basis of their learning outcomes. We provide illustrative examples for each type of outcome. 1) Toward an integrative framework of learning alliances: Theoretical foundations Resource- and knowledge-based views of the firm propose that to achieve long-term survival and growth, firms should focus on the creation and accumulation of knowledge-based resources and competencies. While the knowledge-based view emphasizes the type of learning process – that is, exploration and exploitation – to describe learning outcomes (Grant and Baden-Fuller, 2004), the resource-based view of strategic alliances focuses on the relative characteristics of partners’ resources as a unique source for strategic and learning advantages. We build our framework on the two dimensions proposed by each of these theoretical perspectives. In the first dimension, we consider exploration and exploitation as the learning processes of the alliance, and in the second dimension we refer to the similarity and dissimilarity of the contributions of partners. -
Exploration or exploitation of the partner’s knowledge?
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Two forms of learning can occur in any organization: exploration and exploitation (March, 1991). Exploration refers to the learning activities that involve search, variation, risk taking, experimentation, flexibility, and discovery. On the other hand, exploitation includes refinement, choice, production, efficiency, repetition, implementation and execution. In an alliance context, if partners intend to acquire the other partner’s specific knowledge, experience, and skill, the partners will explore and analyse any novelty in each other’s knowledge. In this type of alliance, partners compete implicitly to be first in learning other part’s knowledge (Hamel, 1991). However, this type of learning race does not occur in all alliances. In many alliances, firms do not need to acquire the partner’s knowledge to improve their competitive and innovation capabilities. In exploitation alliances, acquiring and integrating the partner’s knowledge is not necessary, as the firm only needs access to the knowledge, at the right time and in the right place (Grant and Baden-Fuller, 2004). In other words, to profit from using a partner’s knowledge, the firm does not need to own and internalize it. In exploitation, the firm organizes its learning effort around specialized knowledge that is not possessed by the partner or other external sources, and the partner provides access to peripheral but complementary knowledge. This type of alliance reinforces cooperative specialization (Zeng and Hennart, 2002), where each partner extends its own unique knowledge without directing learning efforts toward peripheral knowledge. Consequently, partners do not necessarily learn from each other. Rather, they learn how to link their corresponding resources and how to coordinate application of each other’s knowledge. Table 1 summarizes the two types of learning that can result from alliance. /*** INSERT TABLE 1 ABOUT HERE ***/
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Similarity versus dissimilarity: A typology of the contribution of partners
The contribution of partners to an alliance can be similar or dissimilar. Firms may pool similar resources to deepen their knowledge and experience and enjoy the joint size effects. Usually partners bring similar resources to engage in an innovative project or increase their competitive power. The idea is to take advantage of the resource size effects in their innovative and business activities. However, firms also look to find dissimilar and complementary resources and knowledge that they do not own and cannot easily trade for. Some resources are field- and industry-specific, and their development needs significant experience and knowledge accumulation. Because such special resources are mostly tacit and unique knowledge, such as the expertise of an excellent engineering team or exceptional knowledge about particular market, the firm cannot acquire them through a transaction. Therefore, a partner’s dissimilar knowledge provides excellent opportunities to have access to new areas of knowledge about product, process, or market and it creates synergistic effects resulting from the combination of complementary resources (Czipura and Jolly, 2007). Research in alliance management confirms the importance of diversity in the partners’ knowledge as an essential determinant of learning effectiveness and innovative outcomes (Sampson, 2007). In what follows, we explain how applying the two dimensions of exploration/exploitation and similarity/dissimilarity generates a comprehensive and unique framework for recognizing learning outcome of alliances. 2) Four generic types of alliance
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The characteristics of each partner’s contribution to the as well as the kind of learning efforts are complementary dimensions that shape four types of alliances. Through the alliance, the characteristics and efforts have a joint impact on improving the efficiency of the firm’s learning efforts. We discuss the key success factors in each type of alliance and provide an illustrative example. Exploration | diversity: Explore the novelty to maximize learning. When two partners share different resources to develop a new product or to enter into a new business, they actually use their differences for creating value in an exploratory way. In this context, learning happens by knowledge acquisition, because the objective is knowledge creation and learning, either from the partner or with the partner. In this type of cooperative exploration, a partner’s knowledge and resources are sources of novelty and valuable input for innovation activities. As the focal firm has an explorative intent, the novelty contributed by the partner will be integrated into the innovation process even when the firms exit the alliance. The success of this type of alliance depends mainly on the effectiveness of the internal process of learning in the focal firm. Acquiring and applying a partner’s knowledge does not happen by default and the firm must plan to facilitate learning through the alliance. Effective learning from the partner depends on the firm’s internal capacity to perform exploration activities. If the firm does not invest internally in exploration and knowledge creation efforts, it cannot identify and evaluate interesting related resources and knowledge contributed by the partner. Systematic efforts on knowledge creation and renewal learning processes help firms to identify relevant knowledge, acquire it from external sources, and apply it in innovation process. A relevant example of this category is Galderma, a joint venture between cosmetics leader L’Oreal and Nestlé, an incumbent in the food and nutrition industry. This joint venture was 5
initiated in 1981 and is now one of biggest companies focusing on dermatology. Its growing portfolio includes treatment for major skin conditions such as acne, rosacea, fungal nail infections, psoriasis, seborrheic dermatitis, non-melanoma skin cancer and photo-damage, and pigmentary disorders. The complementarity of shared knowledge between L’Oreal’s dermatology and cosmetics and Nestlé’s knowledge of clinical testing and nutrition created a solid motive for each partner to form this alliance. The explorative nature of this alliance is evident in the 14 years of R&D before the introduction of its first home-grown product, “Differin,” the anti-acne treatment, in 1995. NUMMI, the joint venture between Toyota and GM, is another example representing this category of learning alliance. Through this alliance, GM learned about the lean manufacturing system and diffused this knowledge through other manufacturing sites of GM. Toyota also learned about the North American market and labour environment. Partners shared dissimilar resources and knowledge in this alliance and the intention of exploring novelty helped GM to not only learn but also diffuse lean manufacturing knowledge in other plants via different methods of learning and knowledge transfer (Inkpen, 2008). Explorative | similarity: Unite your power, then make deep discovery and risky initiatives Sharing similar resources and knowledge for explorative objectives leads to several outcomes for partners. First, it intensifies the size effects. In addition, as explorative activities involve experimentation and trial and error, sharing knowledge and experience provides a deep knowledge about technological areas and facilitates solving complex problems more efficiently and quickly. Sharing research efforts allows the partners to develop new technologies for which a single-investor approach is unjustifiable, not only because of the potential for failure but also because of the uncertainty of the market reaction. Finally, similarity of partners’ shared 6
knowledge or resources increases their bargaining power vis-à-vis suppliers or customers (Czipura and Jolly, 2007) and reduces the uncertainty and the risk of explorative activities. The key factor to taking advantage of intense learning and exploration efforts in this type of alliance is a carefully elaborated governance structure. Alliance governance has to facilitate cooperation through specific terms of access to the other partner’s pre-existing know-how and reduce conflict in appropriation of outcomes. Because partners invest in sharing each other’s resources, the competitive nature of the partners entails a system of protection for both pooled resources and created knowledge (Norman, 2004). Effective governance structure must discourage opportunistic behaviour in knowledge appropriation and protect partners from knowledge leakage or free-riding in the application of alliance outcomes. An illustrative example of this category is Crolles II Alliance. In April 2002, Freescale joined NXP (formerly Philips Semiconductors) and STMicroelectronics at Crolles, near Grenoble, France, to set up a joint R&D center to develop (90-32nm) CMOS technologies on 300mm silicon wafers. The aim of this partnership was to attain global leadership in nano-metric technologies on 300mm wafers. By pooling resources, the alliance created cost savings through shorter design cycles and standardized platforms. The joint development program was based at the new Crolles II R&D center. In this alliance, three large semiconductor firms shared similar knowledge and capital for developing one of the future semiconductor technologies. The competitive role of this technology requires a symmetric power and symmetric result appropriation for each of the partners. Another example of this category is the recent joint development alliance between Pioneer and Mitsubishi Electric Corporation. In May 2013, Mitsubishi formed a new alliance with Pioneer to strengthen their joint platform corresponding to future multimedia technology. 7
Mitsubishi and Pioneer both had experience and relevant technologies on vehicle audio/video technologies, but to cope with ongoing changes and consequent technological uncertainty in the car electronics industry, they decided to share their efforts (Mitsubishi Electric Corporation, 2013). Exploitation | diversity: Cooperate with complementors to be become a specialist. In this type of alliance, partners provide each other access to their specialized and different knowledge, but do not intend to learn the specialized knowledge of other partner. In other words, the objective of each firm is not to internalize and appropriate the knowledge of the partner. Rather, the firm seeks to apply the knowledge of the partner and does not need to invest in it internally for developing that knowledge, even for future applications. Zeng and Hennart (2002) refer to this type of alliance as cooperative specialization. In general, in this type of alliance the dissimilarity of pooled knowledge as well as its specificity is high, so this distance creates great ambiguity. Owing to the high level of ambiguity, analysing and exploring the partner’s knowledge and then transferring that to the focal firm is extremely difficult and cost-intensive. For these reasons, the firms in this type of alliance do not intend to learn and appropriate the partner’s knowledge. Therefore, partners design the alliance in a way that they can gain advantage from exploiting the complementarities, and concentrate their resources on their distinctive knowledge rather than on other peripheral complementary knowledge, which is costly to develop internally or even costly to learn from the partner. In other words, value created by this type of alliance comes from further concentration of resources on the firm’s strategic and distinctive knowledge and capabilities. The learning in this context does not happen by internalisation of a partner’s knowledge but by observing the interaction of the firm’s
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own knowledge base with the knowledge or product of the partner and then by analysing the feedback of this interaction. This type of learning alliance develops mainly in industries where products are complex and the technological change in every component of a product is continuous, such as with computer equipment and semiconductors. Thus, each product component requires unique and updated knowledge. A key factor in this category of alliance is learning to manage the compatibility and to design interoperability of knowledge components in the alliance. As the components have to be integrated into the final product, the complementarity of components and the interface through which they interact are of vital importance. Another example of this type of alliance is that of Mitsubishi Electric and Pioneer, who united for the development of car navigation system for future electric cars. In February 2010, Pioneer announced that the firm would begin integrating its knowledge and technologies on servers and maps with Mitsubishi’s technologies to interact with vehicle data and electronic platforms. Both partners tried to increase the compatibility of their technologies in order to integrate them into a unique platform for car navigation systems that act as the centre of information in the vehicle (Pioneer Corporation, 2010). In 2013, Pioneer formed a new alliance with NTT DOCOMO, the cellular carrier, to add a new business model to the car navigation system alliance developed with Mitsubishi. The alliance with NTT DOCOMO will result in development of a compatible and interoperable platform for cloud services. The cloud service infrastructure will integrate Pioneer’s map and servers technologies for in-vehicle equipment and DOCOMO’s services for smartphones. In addition, driving-related data such as traffic information generated by location information collectable from smartphones will be integrated
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with the vehicle-tracking data as one part of the business model innovation Pioneer seeks through this alliance (Pioneer Corporation, 2013). Exploitation | similarity: Pool the similarities and gain scale economies Efforts and knowledge of the same type are generally united for exploitation in two cases. In the first case, two competitors form an alliance to achieve a critical mass to compete with the local incumbents in an international market. In the second case, firms try to reduce their fixed costs by forming an alliance and eliminating redundant activities after unifying their efforts. Comparable to the second type of learning alliance discussed earlier, this type of alliance is also characterized by unifying similar resources to obtain advantages of scale or size. However, the alliance is exploitative in nature. In other words, in this type of alliance the focal firm does not learn from the partner because the two firms have no explorative intent toward each other. However, the absence of explorative intent does not imply the absence of any kind of learning outcome in this type of alliance. Beamish and Berdrow (2003) noted that even in alliances that were formed without an explorative purpose (learning intent), the firms reported learning “unintended” but important skills and knowledge about relationship management and about how to improve their own business. Thus in this type of alliance, the firm does not necessarily learn from the partner but learns from the process of forming an alliance with the competitor from the same sector with the same interests. The factor determining success in this category is the match between the cooperative purpose of the partners and their attention to coordination. Cooperative intent is not sufficient to secure the outcome of the alliance, and it should be accompanied by the intention of the partners to coordinate their resources. Scale effects cannot result if firms encounter conflicts in coordination of resources and scheduling the activities of alliance. Coordination is an important 10
factor for attaining scale economies quickly. Otherwise the time, energy, and attention of partners will be devoted to resolving operational and technical conflicts that can happen because of the competitive position of the partners and their respective organizational culture and managerial style. An example of this category is the international joint venture between Delta and Virgin Atlantic to compete with American Airlines and British Airways on transatlantic routes between London and New York. The alliance started with simple code sharing, and will expand as the airlines coordinate their offers and prices and establish new flights (starting March 2014) between London and New York. Via this alliance, both firms learn how they can coordinate their similar resources and knowledge to compete with British Airways and American Airlines in the market of transatlantic business flights. Another example is the alliance between French PSA and American GM on logistics of their corresponding products in Europe and Russia. This global alliance allows GM and PSA Peugeot Citroën to share selected platforms, modules, and components on a worldwide basis to achieve cost savings, gain efficiencies, and leverage volumes (Automotive Logistics, 2012). The alliance allows both partners to learn how to coordinate their activities and expertise to achieve the cost saving target they set for the alliance. 3) Conclusion Financial performance myopia can prevent business managers from profiting from learning outcomes of strategic alliances. To avoid this bias, business managers should be able to recognize and assess the strategic value of learning outcomes of strategic alliances. In this article, we provide a framework for the different types of learning outcomes that a firm can gain from its
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strategic alliances. Table 2 summarizes the framework and the four types of learning outcomes in strategic alliances. For the sake of simplicity, we consider the alliance to be a single-project partnership where the learning outcome is unique. Note that in an actual business context, an alliance may have multiple projects with a mix of the learning outcomes that we have presented individually. /*** INSERT TABLE 2 ABOUT HERE ***/
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References:
Automotive Logistics. (2012,February29), “GM stake in PSA means services for Gefco”, available at: http://www.automotivelogisticsmagazine.com/news/gm-stake-in-psa-meansservices-for-gefco (accessed 25 March 2012). Beamish, P. and Berdrow, I. (2003), “Learning From IJVs: The Unintended Outcome”, Long Range Planning, Vol. 36 No. 3, pp. 285–303. Czipura, C. and Jolly, D.R. (2007), “Global airline alliances: sparking profitability for a troubled industry”, Journal of Business Strategy, Vol. 28 No. 2, pp. 57 – 64. Grant, R.M. and Baden-Fuller, C. (2004), “A Knowledge Accessing Theory of Strategic Alliances”, Journal of Management Studies, Vol. 41 No. 1, pp. 61–84. Hamel, G. (1991), “Competition for Competence and Inter-Partner Learning Within International Strategic Alliances”, Strategic Management Journal, Vol. 12, pp. 83–103. Inkpen, A.C. (1998), “Learning and Knowledge Acquisition through International Strategic Alliances”, The Academy of Management Executive (1993-2005), Vol. 12 No. 4, pp. 69– 80. Inkpen, A.C. (2008), “Knowledge transfer and international joint ventures: the case of NUMMI and General Motors”, Strategic Management Journal, Vol. 29 No. 4, pp. 447–453. March, J.G. (1991), “Exploration and Exploitation in Organizational Learning”, Organization Science, Vol. 2 No. 1, pp. 71–87. Mitsubishi Electric Corporation. (2013,May13), “Mitsubishi Electric to Strengthen Relationship with
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Pioneer Corporation. (2010,February9), “Pioneer Announces Strengthening of Business Alliance with Mitsubishi Electric Corporation and Issuance of New Shares Through Third-Party Allotment”, available at: http://pioneer.jp/press-e/2010/pdf/0209-4.pdf (accessed 11 August 2012). Pioneer Corporation. (2013,May13), “Pioneer Announces Capital/Business Alliance with NTT DOCOMO, INC. and Issuance of New Shares Through Third-Party Allotment”, available at: http://pioneer.jp/press-e/2013/pdf/0513-5.pdf. Sampson, R.C. (2007), “R&D Alliances and Firm Performance: The Impact of Technological Diversity and Alliance Organization on Innovation”, Academy of Management Journal, Vol. 50 No. 2, pp. 364–386. Zeng, M. and Hennart, J.-F. (2002), “From Learning Races to Cooperative Specialization: Toward a New Framework for Alliance Management”, Contractor FJ, Lorange P.(Eds) Cooperative Strategies and Alliances, Pergamon, Oxford, UK, pp. 189–210.
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Table 1. Two principal types of learning according to the knowledge-based view Exploitation Partners becomes more specialized
Exploration Firm learns new knowledge and extends its knowledge base
Learning activities
Refinement, production, improvement, implementation, repetition
Source of benefit derived from partner’s knowledge
Application of partner’s knowledge in right time and right place by focal firm
Search, variation, risk taking, experimentation, flexibility, creation, discovery Learning and internalizing the partner’s knowledge
Determinant success factor
Coordination and exploiting the complementarities
Internal effort to learn and assimilate the partner’s knowledge
Outcome of learning
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Table2. Four types of alliance based on the learning outcome
• Learning together by joint efforts of knowledge creation. • Similarity of shared efforts makes exploration deeper and faster in the area of knowledge • Risk of failure and investment costs on an uncertain knowledge creation project are divided among partners. • Careful design of the governance of cooperation (e.g., by a mix in business and capital alliances) is the determinant for avoiding opportunistic behavior, knowledge leakage, and free-riding. • Example: Pioneer and Mitsubishi Electric strengthen their joint platform for facing future multimedia technology evolution.
• Learning from interfirm knowledge acquisition and knowledge combination • Dissimilarity facilitates exploration through exposure of the firm to novelty • The internal capacity of the firm for knowledge creation and learning is important, because without effective internal processes of learning, external knowledge cannot be acquired and embedded in the firm’s activities and innovation processes. • Example: Galderma: Nestlé and L’Oréal combined their dissimilar knowledge (on nutrition and cosmetics) to develop new dermatologic knowledge.
• Learning outcomes are mainly how to manage a strategic alliance with a competitor. • Partners share similar resources and knowledge to gain scale economies in their existing business. Other objectives could be achieving a critical mass for entering a new market and competing jointly with the incumbents. • The intent to cooperate by competitors should be accompanied by the intent to coordinate. Coordination of resources, activities, and decisions at different levels (individual, teams, org’l units, partner firms) is essential for scale economies and size effect. • Example: Delta and Virgin on LondonNew York business flights to compete with British Airways and American Airlines.
• The learning outcome of the alliance is increasing the firm’s specialized existing knowledge base • Cooperative specialization (let the partner provide peripheral knowledge and focus the firm’s effort on core knowledge base) • Determinant factor of success is efficiency in managing the compatibility issues of the partner’s knowledge and the firm’s own knowledge components. Interoperability is essential. • Example: Pioneer integrates its knowledge on maps and servers with the knowledge of Mitsubishi on electronic data centre of the vehicle as well as NTT DOCOMO to develop a platform of car navigation compatible with cloud service.
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Exploitation
Dissimilar Resource Contribution by Partners
Exploration
Similar Resource Contribution by Partners
