RT2C W6D1 Wald

Respond to at least two of your peers’ postings in one or more of the following ways: “See attachment for details”
APA citing
No plagiarism
See Colleague attachments
ATTACHED FILE(S)
Discussion: Outsourcing Innovation
In March of 2012, Boeing agreed to collaborate with China’s Comac, which is actually something of a rival to Boeing in the commercial aerospace market (Toh, 2012). They partnered in an effort to curb the aviation industry’s contribution to climate change. This is a classic example of a partnership formed to stimulate and manage innovation outside the boundaries of any given firm. This first partnership between Boeing and Comac aims to develop a single-aisle passenger aircraft. Boeing is partnering with a rival to challenge a market in which it already enjoys a significant advantage.
In your research, consider how organizations should exercise care when implementing alliances that produce innovation without harming the competitive standing of the alliance partners.
To prepare for this Discussion
,
Review this week’s Learning Resources, especially:
·
· Building strategic partnerships– Baloh, et al., article – See pdf
· Outsourcing a Core Competency – See pdf
· Structuring enduring strategic – See pdf
· Making Business Alliances work – See pdf
Assignment:
Post a cohesive and scholarly
response based on your readings and research this week that addresses the following:
Respond totwo colleagues’ postings in one or more of the following ways:
· Ask a probing question.
· Share an insight from having read your colleagues’ postings.
· Offer and support an opinion.
· Validate an idea with your own experience.
· Make a suggestion.
· Expand on your colleagues’ postings.
· No Plagiarism
· APA citing
1st Colleague – Natasha
Outsourcing Innovation Post
Top of Form
Week 6 Discussion
Outsourcing, despite the risks involved, continues to be a fundamental business strategy that underlies many successful companies. As Baloh et al. (2008) argue, collaborative innovation is indispensable. Therefore, it is upon companies to integrate various mechanisms to avert the risks involved and harness the benefits that outsourcing brings to companies. One of the risks that needs a strategic approach to overcome is the protection of an organization’s core competencies from opportunistic partners who may use it to gain their own competitiveness. Human resources are at the center of the development of these strategic approaches, making them the key determinants of the success of outsourcing of innovation.
How HR can Manage the Outsourcing of Innovation
Baloh et al. (2008) provide three models of outsourcing innovation, including strategic alliances, acquisitions, and open source (OS) innovation. The effectiveness of each of these models is anchored on the needs of the organization that are pushing it to outsource. For instance, outsourcing innovation through acquisitions is efficient for an organization looking for specific expertise that its employees lack, and is an approach used for services or products with a mature track record and rich history (Baloh et al., 2008). The strategic alliances outsourcing innovation model is also used to obtain new knowledge and learning, particularly by competitively strong organizations (Baloh et al., 2008). This model allows an organization to acquire critical knowledge while maintaining its core capabilities. However, the model requires the management of the partner relationship throughout the project. Lastly, the open source innovation model is mainly used for software development, where the OS developers make their products and services publicly open to adaptation or adoption, after using their own resources (Baloh et al., 2008).
Whereas each of the models has its share of benefits, there are also risks involved. Therefore, HR have the primary role of evaluating the needs of the organization that are prompting it to outsource. After that, HR analyze which of the outsourcing models is appropriate for the outsourcing situation, with a special focus on value creation and increased competitiveness. HR can then make recommendations based on findings. Simply put, HR can manage the outsourcing of innovation by conducting research and finding appropriate outsourcing partners. Segil (2008) claims that decisions concerning whether to partner and with whom, as well as the goals of the partnership, are critical to alliance success. HR are responsible for all these processes.
Methods HR can Use to Manage Outsourcing of Innovation as a Foundation of Understanding
Baloh et al. (2008) outline several models of outsourcing innovation. One method HR can use to manage the outsourcing of innovation is to analyze and evaluate the benefits and risks associated with each of these models. This will provide them with in-depth understanding of which model is appropriate for what outsourcing need, leading to alliance success. Conducting background research and negotiating with prospective strategic partners is another method HR can use to manage outsourcing of innovation as a foundation of understanding. Understanding the outsourcing needs of the organization and the appropriate model to use is one thing. Getting the right partner is another and is crucial to the success of the alliance. This is because it influences each of the partnership success factors, which are collaborative innovation, value creation, and partnership quality (Gibbs & Humphries, 2009).
Role HR can Play in Maintaining the Competitive Advantage of the Organization
HR play a central role in the selection of a partner and the model of innovation outsourcing the organization chooses. From this perspective, HR influence the organization’s maintenance of a competitive advantage from the onset of the outsourcing process. HR can also maintain the competitive advantage of the organization through relationship management throughout the alliance. Gibbs & Humphries (2009) emphasize the importance of partnership quality, which involves commitment and trust as components of the quality of the alliance relationship. A good alliance relationship is likely to discourage opportunistic behavior by the strategic alliances that risk the competitive advantage of the organization. lastly, HR should push the organization to outsource innovations in non-core areas, while actively engaging in innovations in core areas internally (Baloh et al., 2008). Keeping core innovations internal while outsourcing non-core innovations increases competitiveness and protects the organization from opportunistic partners.
In conclusion, outsourcing of innovations requires strategy to help organizations increase their competitive advantage and avert the risks involved. HR are instrumental to the achievement of these tenets because they form a fundamental part of strategic management and the processes involved in effective innovation outsourcing fall within their domain.
Baloh, P., Jha, S., & Awazu, Y. (2008). Building strategic partnerships for managing innovation outsourcing.Strategic Outsourcing: An International Journal.
Gibbs, R., & Humphries, A. (2009).Strategic alliances and marketing partnerships: Gaining competitive advantage through collaboration and partnering. London, NI: Kogan Page Limited.
Segil, L. D. (2008). Making business allianceswork.Management Quarterly,49(2), 30-35.
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2nd Colleague – Sandra Patterson
Outsourcing Innovation – Wk6 D1
Top of Form
The process of selecting if to outsource HR functions includes an analysis of how outsourcing may benefit a business and includes an assessment of human resourcepreparedness to help the organization manage the outsourcing transition. It is essential to review the organization’s present HR delivery and determinegaps within HR demands and availablecapabilities. In addition, management should examine the outsourcing company and its patterns to determine how market dynamics may affect their firms.
Consideration must be given to whether the HR operations of the firm should be subcontracted. Outside counsel can aid in inquiring through data analysis, financial projections, and suggested contract clauses (Ali et al., 2020). For instance, in the case of Boeing and Comac, they shared the purpose of developing an ecologically friendly airplane. Outsourcing the position appears to be the greatest way to lower the partnership’s total human resources expenses.
Another crucial feature or consideration is reliability; it is vital to understand what reliability benefits the subcontracting vendor will give and whether the offered services will meet all of a firm’s legal requirements (Ali et al., 2020). The issue is prevalent in situations where state laws are stricter than a corresponding federal regulation. Moreover, management expectations are crucial factors to consider. If the services delivered is at a level above or below that of in-house management, confusion may ensue.
A complete understanding of the services to be delivered is required (Espino-Rodrguez & Ramrez-Fierro, 2018). In addition to knowledge, outsourcing providers frequently perform jobs that deviate from the organization’s established operating measures. The client company should have thorough awareness of the subcontractors procedures and the function of the association within them.
U.S. firms such as Boeing are discriminating when outsourcing particular tasks, such as benefits administration, recruiting, and finance. Unlike depending entirely on a single provider, specific outsourcing is prevalent since it can be personalized to meet a company’s exact needs (Espino-Rodrguez & Ramrez-Fierro, 2018). With the factors mentioned above in mind, outsourcing HR may help a business maintain its competitive edge.
Ali, S., Huang, J., Khan, S., & Li, H. (2020). A framework for modelling structural association amongst barriers to software outsourcing partnership formation: An interpretive structural modelling approach.Journal Of Software: Evolution And Process,32(6).https://doi.org/10.1002/smr.2243
Espino-Rodríguez, T., & Ramírez-Fierro, J. (2018). Outsourcing Performance in Hotels: Evaluating Partnership Quality.Sustainability,10(8), 2766.https://doi.org/10.3390/su10082766
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Strategic Outsourcing: An
International Journal
Vol. 1 No. 2, 2008
pp. 100-121
# Emerald Group Publishing Limited
1753-8297
DOI 10.1108/17538290810897138
Building strategic partnerships
for managing innovation
outsourcing
Peter Baloh
Faculty of Economics, University of Ljubljana, Ljubljana, Slovenia
Sanjeev Jha
University of Illinois at Chicago, Chicago, Illinois, USA, and
Yukika Awazu
Bentley College, Waltham, Massachusetts, USA
Abstract
Purpose – The purpose of this paper is to uncover the mechanisms of organizations managing
innovation outsourcing to business partners. In a business environment characterized by the
development of deep, niche expertise in a particular domain, business partnerships can provide a
source of innovative rejuvenation by outsourcing the innovation to business partners who have
complementary skills and expertise. This paper addresses a critical challenge which the
organizations are currently facing: how do you manage outsourcing of innovation to business
partners effectively while maintaining your strategic competitiveness?
Design/methodology/approach – Exploratory multiple case studies of over 30 innovative
European and US companies were done. It involved 50 semi-structured interviews with senior
executives from research and development, product management, information technology, and
marketing.
Findings – The paper identifies three complementary models of managing outsourcing of
innovation to business partner: acquisition, strategic alliances, and open source (OS). Based on these,
a three-dimensional ‘‘Co-Innovation Space’’ is proposed that can help in analysis and planning of
current and future innovation projects.
Research limitations/implications – Although the research is carefully designed, it is an
exploratory study and has the limitation of generalizability of the findings. Nevertheless, findings
from multiple case studies from diverse organizations shed a light to current innovation and strategic
alliance literature.
Practical implications – Partnerships can open the door to multiple knowledge sources. Accessing
and integrating information from these sources can greatly enhance knowledge base of organizations
and can help fuel sustainable innovation. The models proposed in this study provide a lens to
examine existing innovation project portfolios and/or to plan for future innovation programmes.
Originality/value – This study is probably among few to study such a large, diversified, and
geographically scattered group of organizations. Although exploratory and preliminary, this makes
the findings of the study insightful.
Keywords Innovation, Strategic alliances, Acquisitions and mergers, Partnership, Outsourcing
Paper type Conceptual paper
Introduction
Worldwide, executives agree that collaborative innovation is indispensable. When
asked about the most important sources of ideas and innovation, CEOs ranked
employees first (41 per cent of CEOs agree that they are the number one source), closely
followed by external sources such as business partners and customers (39 and 36
per cent, respectively (IBM, 2006)). Internal research and development (R&D)
departments, in contrast, ranked only eighth in importance (IBM, 2006). The nature of
innovation has undergone fundamental changes in recent times (Chesbrough, 2003).
The current issue and full text archive of this journal is available at
www.emeraldinsight.com/1753-8297.htm
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Today, it is not sufficient for an organization to simply rely on its internal knowledge
base for ideas (Carayannis, 1999; Chesbrough, 2003; Desouza et al., 2005; Dodgson,
1991; Hitt et al., 2000). Organizations have realized that they must partner with external
entities to source ideas, know-how, and capabilities.
Organizations have become highly specialized in niche areas, often focusing their
capabilities on specific expertise, services, or products. Organizations must hone in on
their core capabilities and engage with business partners to supplement, expand, and
apply knowledge. In this way, they can balance their deep expertise with partner’s
expertise in order to innovate efficiently and effectively; and this is what good
companies should do (Sull, 1999). While developing existing technology and serving
existing customers results in incremental innovations, exploration into new knowledge
or departure from existing skills leads to radical innovation serving emergent
customers or markets (March, 1991; Benner and Tushman, 2003; Herrmann et al., 2006).
Complementary assets help an organization extend the reach, scope, and impact of
their products and services to reach market faster with better and new products. This
realization has fuelled the recent surge of interest in outsourcing, both on- and off-
shore. Organizations engage in partnerships to reduce the costs of internal knowledge
creation. Moreover, when the need for knowledge in allied or foreign domains arises,
many organizations lack the capability or capacity to grow the knowledge in-house –
they need to negotiate for the ideas and know-how from external sources. Quinn (2000)
cites the example of large pharmaceutical companies outsourcing elements in their
innovation chain while specializing in their core activities. Breaking core competencies
into three broad areas of basic research, development, testing and production, and
distribution, the author argues that companies specialize in each of these three areas
while collaborating with other. Companies specializing in R&D build partnership with
firms having core competencies specializing in the other two elements in the
innovation chain: production (testing and production) and marketing, distribution, and
logistics (distribution).
Miozzo and Grimshaw (2005) argue that vertical disintegration and modularity of
innovation chain is one of the most significant phenomenons of modern organizations.
Organizations can generate faster and better products by breaking them into smaller
subsystems that can be built separately but to function together. However, to achieve
this, organizations need to have a sound strategy to manage the outsourcing of their
subsystems. We have examples of a number of organizations practicing outsourcing of
subsystems requiring their suppliers of components and services to conduct their own
innovations, while they focus on innovations in their core competency. Boeing actively
solicited business partners in the innovation process for its new 787 Jetliner (Kotha and
Nolan, 2005). Boeing created a team of 15 companies worldwide for production of the
structural sections of the plane. For example, Mitsubishi Heavy Industries (Japan) is
responsible for the wing box. Vogut and Alexia (Italy) are building the horizontal
stabilizer and the centre and aft fuselage. Product suppliers are not the only business
partners, either. Services can be outsourced, too. Most organizations today outsource
some aspect of their human resource functions (e.g. executive recruitment). In doing so,
they rely on the expertise of their providers to bring them the best-of-breed in both
product and service offerings.
The shift in the mindset towards outsourcing of innovation is driven by increased
competitive pressures. Globalization makes the need for innovating with business
partners more critical. In this age of rapid innovation, organizations cannot stay at a
static level of skills and competencies. Organizations need to ceaselessly create
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knowledge, innovate processes, and products, and learn from their predecessors’’
mistakes and services. Organizational improvisation (Cunha et al., 1999) is the mantra
to break out of this loop of the birth and death of organizations. The loop has always
been there, but globalization shortens the process. Organizations need to improvise,
experiment, and employ all their resources, especially their employees, business
partners, and customers, in a continual quest for organizational improvisation. This
demand and complexity helps to explain why opening an innovation process by
outsourcing external parties may be a challenging undertaking.
Further, innovating in isolation can be risky and costly. Out of ten R&D projects,
five flop, three are abandoned, and two go on to become successful (Rizova, 2006). A
large number of innovative ideas fail due to the lack of market orientation, such as with
misengineered products that do not fit customer needs. Consider the example of high-
definition television, a technology marvel that promised high picture quality. Philips,
Sony, and Thompson have invested millions and millions of dollars to produce consoles
since the early 1990s, but they were not in-sync with their business partners; the
product languished because the studio production equipment, signal compression
technologies, and broadcasting standards were not ready (Rizova, 2006). To maximize
profit potential, a company needs to identify its innovation fulcrum, the point at which
an additional offering destroys more value than it creates (Gottfredson and Aspinall,
2005).
If done properly, outsourcing to business partners can help organizations to achieve
sustained innovation and continuous competitive differentiation. Toyota is an excellent
example. Despite the amount of research conducted on the Toyota Production System
and the fact that Toyota even provides tours of its operations to other companies’
representatives, competitors have not been able to achieve the same level of
productivity as Toyota (Hagel and Brown, 2005). One important reason is that
knowledge resides and is owned at the network level. Participating suppliers benefit
from knowledge sharing as they themselves gain from others’ knowledge (Dyer and
Nobeoka, 2000).
In this paper, we describe three mechanisms by which organizations engage with
their business partners for outsourcing of innovation. These three modes of
collaboration are differentiated by the nature of relationships among partners, reasons
(goals) behind the decision for particular relationships, and by the scope of innovation.
In each business partnership, it is critical to identify what type of innovation is most
likely to result in successful outcomes. There is no one-size-fits-all approach.
Henderson and Clark (1990) classified innovations in two dimensions: one dimension
captures an innovation’s impact on components and the other on the linkages between
components. Through this classification, they identified multiple types of innovation:
incremental, modular, architectural, and radical innovation. Architectural innovation
illustrates how some business partnerships can lead to desired innovation effort
outcome. Henderson and Clark posit that architectural innovation is triggered by a
change in a component, which will create new interactions and new linkages in the
established product. Business partnerships often create this catalytic effect by
combining or incorporating complementary and necessary components in each
participant’s product and services. This type of innovation is very complex and risky,
and most often requires a variety of knowledge and expertise that are not located
internally in the firm. It can also be highly disruptive to organizations (Gatignon et al.,
2003). This paper focuses on such complex and disruptive innovation. We discuss
under what conditions each mechanism of outsourcing is beneficial, and the risks and
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issues related with each mode of collaboration. We also explore the critical issues related
to actually introducing new forms of collaboration in organizations. Understanding
these issues can help organizations better manage the demanding and multifaceted task
of fusing business partners into already complex innovation processes. Finally, we
introduce a three-dimensional ‘‘Co-Innovation Space’’, which is akin to various matrices
(such as Boston Consulting Group (BCG), Arthur D Little (ADL), GE/McKinsey, etc.),
known from the strategic management. Companies can use it to analyze existing
innovation portfolios and/or to plan future approaches to innovation outsourcing.
The findings presented here are based on exploratory multiple case studies of over
30 innovative European and US companies. This research design was chosen as it suits
problems where the context of action is critical (Benbasat et al., 1987), as it enabled us
to gain a rich understanding of the context of the research (Saunders et al., 2003), and
as it made possible describing in greater detail the relationships that exist in reality in
local contexts (Galliers, 1992). Data collection involved 50 semi-structured interviews
with senior representatives from R&D, product management, information technology,
and marketing. The interview data were complemented by desk research, analysis of
corporate reports, and validated in follow-up sessions with key informants.
Building strategic partnerships for innovation outsourcing
During our exploratory study, three different forms of business partner collaboration
for innovation outsourcing emerged. In this section, they are defined and managerial
issues are discussed. The first collaborative mode is innovation through acquisition,
where ideas and innovations are acquired from another independent organization in
exchange for (usually monetary) compensation (Karim and Mitchell, 2004;
Lichtenthaler, 2005). The next type of collaboration is strategic alliances, where
numerous business partners engage in a highly dynamic interplay of tapping into
external sources of knowledge, assimilating new knowledge, and transforming and
exploiting the knowledge (Doz and Hamel, 1997; Hipkin and Naude, 2006). Finally, the
OS innovation model, which is where problems and ideas are exchanged via the
network to enable more rapid innovation and access to a wide array of sources of
expertise (Grand et al., 2004).
Outsourcing of innovation through external knowledge acquisition
Consider IBM, which realized US $1,700 million (20 per cent of their total net income) in
2000 via external commercialization of their expertise. This took the form of consulting
and services related to many of their 25,000 patents (IBM, 2005; Kline, 2003;
Lichtenthaler, 2005). The number of transactions involving the trading of knowledge
assets has increased significantly from US$ 15,000 million per year at the beginning of
the 1990s to around US$ 100,000 million a year in 2002 (Kline, 2003). If the supply side
is thriving, demand must be high. Many organizations engage in outsourcing of
innovation by purchasing knowledge from external entities.
Outsourcing of innovation through external acquisition has several benefits. First,
an organization can choose to purchase the best-of-breed and incur neither the cost nor
the risk of in-house innovation. Furthermore, in an era of specialized business, many
organizations focus upon specific areas of expertise, and their employees may not have
the diversity and breadth of knowledge to develop technological or product
innovations outside the business’s dominant field or business model.
Second, the purchasing organization can act in an agile manner and acquire
knowledge that arises out of emergent needs. When a need is recognized, a company
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can search for and buy the knowledge that will answer that need immediately. That
might take the form of new technology, manufacturing procedures, or a product
component. In these instances, an organization sidesteps the costly and sometimes
lengthy R&D cycle and is able to seize solutions found to match core competencies and
supplement organizational strengths. As the competitive environment is highly
dynamic, being able to satisfy emergent needs is critical.
Third, sometimes intellectual property safeguards particular pieces of knowledge.
In these instances, an organization may work with a business partner who has the
rights to a particular patent in order to use a specific product component or piece of
technology. The patent holder may retain the right to commercialize its knowledge
with other organizations; at other times, the patent itself will be for sale and can be
acquired entirely. Sometimes, a business partnership develops out of necessity to
access or utilize information held explicitly and legally by a partner. Consider the
example of Zebra Technologies. This leading manufacturer of industrial printing
solutions (such as bar code and radio-frequency identification (RFID) smart labelling)
has acquired an extensive portfolio of RFID-related patents in 2006. With a US$ 10
million acquisition of over 200 patents from UK-based medical company BTG plc,
Zebra now holds a vast collection of patents that secure their premium position in the
lucrative and promising area of products based around RFID technology. These
patents are integrated in their products, which are used by 90 per cent of the Fortune
500 companies. In addition, Zebra’s knowledge and expertise also is a viable consulting
industry with companies’ partners who try to stay in the supply chain. As an example,
in April 2006, Zebra held a conference for over 300 suppliers of Wal-Mart, who were
facing the giant retailer’s RFID compliance mandate.
The case of the ‘‘Little Swan’’ company (Pech et al., 2005) demonstrates that
innovation can be successfully integrated into a firm after direct acquisition.
Acquisition of foreign technology propelled the company from being a pottery and
domestic appliances producer with no history of technological development to a
company with an 18 per cent yearly expansion rate in the highly competitive and low-
profit-rate world market of white-ware manufacturing. Little Swan had the reputation
of being a ‘‘me-too’’ copycat rather than an innovator. In 1989, Little Swan was in 24th
place in washing machine sales in China and made a commitment to internal R&D
around that market. The transfer of critical technology and hiring of engineers from
the Japanese manufacturer Matsushita in 1987 acted as a catalyst, enabling Little Swan
to design proprietary technology of its own. The purchased expertise was paired with
incremental innovations from in-house R&D, which resulted in over 150 patents by the
year 2002, both in innovative products and in innovative manufacturing procedures.
Huge incentive programmes have been employed, and the company continuously
expands its knowledge base with experts from all over the world who can fruitfully
engage in new knowledge creation around diverse knowledge bases (Pech et al., 2005).
The case of South Korean electronics giant Samsung provides another an analogous
example. In the late 1990s, Samsung was associated with cheap TVs and microwaves
that flooded foreign markets. During the Asian economic crisis, Samsung undertook an
innovation transformation, starting first with improving acquired patents. While those
purchases improved products dramatically, they did not merely release as new
products. Instead, the acquisitions were paired with radical strategy shifts in
managerial training, strong leadership, and a huge R&D emphasis under the
watchword of quality. Today, Samsung is the third-ranked mobile phone producer in
the world; it was rated the ‘‘Mercedes’’ of cell phones (Manecksha, 2004) and has been
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called ‘‘a killer innovator’’ (Ihlwan, 2006). For example, Samsung was the first to
introduce an MP3 player to the global market (two years before the iPod) and to
integrate MP3 players into mobile phones. It is the number two chip-maker in the
world after Intel and the top maker of LCD driver chips, with around 20 per cent of the
market; among its customers are Sony, Nokia, and Motorola.
The examples of Samsung and Little Swan emphasize that outsourcing of
innovation through acquisitions alone do not lead to sustainable innovation. In each of
these instances, key patents were acquired and then merged with new, high-quality
employees and a cultural shift towards valuing quality and innovation. The
combination of new knowledge and a cultural shift enabled both companies to develop
innovative products; the patents alone probably would not have had such a significant,
long-term impact. The process of integrating external knowledge opened the
organization up to new knowledge while simultaneously providing initial successes in
product development that further fuelled the process of change. This virtuous cycle
allowed Samsung and Little Swan to continually ramp up their innovation
programmes after each successful release of a product.
Critical considerations. Not all innovations are candidates for outsourcing through
external acquisitions. After both our literature review and our case studies, we put
forth the following hypotheses for future research. First, external acquisitions are
mainly suitable for products and services that have a rich history and a mature track
record. This is because such products and services are well understood, making it easy
to estimate their value and calculate their price. The prime example of this is in the
area of information technologies. Today, most organizations purchase their IT services,
solutions, and components from technology providers. Innovation in IT is not
conducted in-house. Rather, organizations have come to expect that the business
partners from whom they purchase these goods take responsibility for innovation.
Second, outsourcing through external acquisitions is ideal when the purchased
knowledge or ideas can be easily integrated into the current organizational fabric. By
this, we mean that the effort required to integrate innovations into the organization
should not be inordinately high enough to make it useless to purchase them off-the-
shelf. If there is need for special expertise to help the organization integrate these
innovations, the costs of the additional expertise need to be accounted for as part of the
overall project.
Third, outsourcing through external acquisitions should be used for purchasing
innovations in non-core areas of the organization. Non-core innovations, compared
with core innovations, are not critical to the operations of the business. Core
innovations can make or break a business; hence, when engaging with business
partners on core innovations it is better to use the second mechanism that we discuss,
innovation through strategic alliances.
Fourth, if a company feels that there is outstanding potential in particular
knowledge that can be bought, sometimes it engages in outsourcing knowledge
acquisition through transfer of patents from the commercializing to acquiring
company.
Outsourcing of innovation through strategic alliances
One of the main motivations for the creation of innovation-focused alliances is to
source new knowledge and learning. When two organizations are already
competitively strong, one or both parties may want to acquire critical knowledge, while
maintaining their own capabilities (Doz and Hamel, 1997; Kogut and Zander, 1992;
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Wonglimpiyarat, 2004). Alliances enable a company to intercept the technology of
another company and to close skill gaps faster than internal development would allow
(Doz and Hamel, 1997). Alliances also foster intense interaction and that collaboration
enables the transfer of tacit knowledge between members.
Strategic partners need to be sought out and a collaboration structure needs to be
formed. Relationships then need to be built and managed throughout the project
(Hipkin and Naude, 2006; Marshall, 2004). Doz and Hamel (1997) suggest that an
important antecedent for successful innovation alliances is the strategic,
organizational, and cultural compatibility of the partners. The selection and
engagement of complementary alliance members is critical for successful outsourcing
during innovation processes (Yoshingo and Rangan, 1995). The search for potential
partners must be systematic and consider contextual factors like competition, market
situation, and existing knowledge base. To facilitate the search, even web-based
evaluation tools have been devised (Humphreys et al., 2005). Strategic and cultural
issues come into play because the search for partners must also consider the roles that
the integrating company wants the partner to play in the alliance.
To find the appropriate partners for innovative alliances, several factors should be
considered. Achieving a strategic fit between the allies is vital (Rotering, 1990;
Teichert, 1994; Drejer, 2002; Lindman, 2002). Strategic fit (e.g. Rotering, 1990; Teichert,
1994) is related to the danger of opportunistic behaviour from one partner and therefore
inversely depends on the advantages both parties could gain out of the integration
(Dutta and Weiss, 1997). Appropriate partners need to be chosen considering the goals
set by the integrating company for a strategic alliance. In our study, interviewees
repeatedly stated that the complementary knowledge base of the business partner(s) is
the key selection factor. Trust and reliability is also important in selecting innovation
partners and is just as important as the complementary competences of both parties.
Unlike with external acquisitions, in strategic alliances both partners must have
knowledge to share and contribute and the benefits for both organizations must be
articulated and continually reinforced. Cultural fit is another critical consideration.
Cultural fit increases when decision processes and decision speed, tolerated risks, and
work-related values are similar. Also, the willingness to adapt to cultural differences,
which can arise both at an organizational and global level, improves the cultural fit.
Successful innovative alliances consider not only factors concerning the
organizations involved, but also the type of project being embarked upon. The results
of our study show that companies that are successful at integrating external
knowledge begin by considering the strategy for integration. They outline the goals of
the integration, roles for each company involved, and areas of integration. Our findings
principally support the findings of Wagner and Hoegl (2006), who studied the
integration of suppliers in the new product development process, and extend the data
to include technological (process) innovation. Companies distinguish between two
types of integration strategies – know-how and capacity projects.
In know-how projects, a firm’s intention is to utilize the specialized knowledge of a
business partner. For goal-oriented new product projects, which are highly innovative,
the integrating company takes on suppliers with deep knowledge in a particular area
and transfers the responsibility directly to the supplier (Wagner and Hoegl, 2006).
When embarking on strategic innovation alliances, it seems from the companies we
analyzed that such joint ventures have characteristics of the know-how projects. They
arise out of the need to adopt complementary knowledge when developing in-house
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technological knowledge. Furthermore, not only the ‘‘end product’’, but also the ‘‘means
to that end product’’, is critical.
In that sense, we saw less transfer of responsibility to the strategic alliance partner
but more joint collaborative efforts in developing new ways of doing things. A recent
example is Samsung’s partnership with Mechanical Technology Inc. (MTI) Micro Fuel
Cells of Albany, NY (MTI), a unit of Mechanical Technology, a little-known company
that had $8 million in sales in 2005. MTI Micro has extensive technological knowledge
in the area of ‘‘green’’, micro-sized electricity sources. Samsung committed $1 million to
the joint development of fuel cells, one of the largest publicly disclosed commitments to
the technology by a major manufacturer in years. Goals, knowledge security, and the
question of intellectual property were explicitly defined in advance. The joint
development deal will last about 18 months, and neither company will work with any
other companies to develop fuel cells for use in wireless phones. Samsung secured an
exclusive license to use the technology from MTI Micro, and any patents that result
from the research will be assigned to MTI Micro.
Critical considerations. From the literature, we know that opportunities for
knowledge base expansion exist mainly in combining knowledge across new domains;
this recombination view of existing physical and conceptual resources has long been
accepted as a strong source of possible innovation (Schumpeter, 1934). However, while
outsourcing external knowledge from distant domains may be novel and valuable,
firms may have difficulties in absorbing and utilizing this knowledge. In line with this,
Hipkin and Naude (2006) agree that alliances will benefit mostly from multiple
capabilities, which may lead to haphazard, nonlinear outcomes. Specializing too much
in a particular domain, however, can lock a firm into a competency trap (Cohen and
Levinthal, 1990): ‘‘exploration in domains distant from a principal partner’s existing
competencies is likely to yield a more diverse set of innovations than when the
expertise of partners is closely linked’’ (Hipkin and Naude, 2006). However, the
absorptive capacity (Cohen and Levinthal, 1990; Zahra and George, 2002) of companies
limits the assimilation of (too) distant knowledge, which will not be interpreted or
comprehensible, let alone combined with existing knowledge and acted upon (for
example, by launching a new product or improving existing technology).
An interesting word of advice to managers can be found in a study by Phene et al.
(2006), which deals both with strategic and cultural fit issues. As knowledge takes on
specific national characteristics due to various institutional factors, culture,
technological development, demand and supply conditions or scientific, technological,
and regulatory environments, the authors examined a geographical dimension –
together with an existing technological distance dimension – and its effects on chances
of breakthrough innovations. In view of strategic innovation alliances, members should
be chosen based on their geographic and technological context as follows (Phene et al.,
2006):
(1) Members with technologically distant knowledge should be coming from the
same national context; however, the effect is curvilinear, and therefore the
choice of external technologies should be made selectively and cautiously (e.g.
not too close and not too distant).
(2) When forging international alliances, breakthrough innovation is more likely to
occur when members with technologically proximate knowledge are chosen.
(3) Inviting members with technologically and geographically distant knowledge
simultaneously is unlikely to yield breakthrough innovation results, as due to
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distances on both dimensions, difficulties are likely to appear in the acquisition,
assimilation, transformation, and exploitation of knowledge.
Initially, a clear strategic direction based around existing knowledge of involved
partners is needed. Then, the alliance must shift towards the desired unknown, or the
unexplored direction, which entails the process of experimenting, discussing, and
transferring knowledge; thereby learning and changing both individuals and
organizations. These interactions result in unexpected idea development and problem
resolution, thus extending the knowledge base. Reaction to unanticipated
circumstances requires an emergent strategy (Mintzberg, 1978) in order to ‘‘take
advantage of unforeseen opportunities, or utilize radical technologies’’ (Hipkin and
Naude, 2006). Although the initial purpose of the alliance should guide action and
interaction, the relationship must be flexible enough to embrace unexpected knowledge
and technology.
It is crucial to recognize a dynamic nature of long-term relationships, in which it is
impossible to predict the result of collaboration and how innovation will affect long-
term goals. Also, imposing a static strategy in such dealings may delay or inhibit
technology advancements, as the strategy needs to adapt to and reflect newly gained
knowledge.
Knowledge-based alliances depend on the key players’ capabilities, and the
contribution of partners fluctuates as one partner’s expertise is superseded by that of
another. Lessons from a longitudinal case study involving a high-technology service
showed that the service was dependent on the behaviour and knowledge of partners,
who would create objectives on the fly; objectives would evolve through learning,
experimentation, and innovation, and a rigid and centrally led alliance targeting
innovation would only inhibit successful innovation (Hipkin and Naude, 2006).
Alliances should recognize the possibility of serendipitous outcomes and plan for such.
Consider Hipkin and Naude’s (2006) example of the South African lubrication division
of a UK-based multinational company. Because of deteriorating profit margins, they
entered an alliance to complement existing lubrication services with oil condition
monitoring. The original alliance model did not work – development was slow and
ambitions were limited. The principal partner expected other partners to be passive,
rather than instigators, of new ideas and was apprehensive about the destructive
power of new innovations. This strategy changed once principal partner recognized
the potential for added value that could be achieved through transferring skills and
knowledge between partners. Another partner, who had expertise in the field of
condition monitoring, assumed the leading role in the alliance and led the innovation
efforts. The principal partner allowed it (instead of blocking the initiative of the
‘‘smaller’’ partner, which often happens when principal partners fear loss of control in
the leadership role), supported the experimentation and free flow of information, and
finally, embedded the innovative technology into the added value service to their
customers all over the world.
These considerations suggest that outsourcing through knowledge-based alliances
require ‘‘loose–tight’’ governance, where partners are relatively autonomous in the
application and extension of their expertise, and where some sort of stable and defined
formal interaction is featured. In initial bursts of creativity and reactions to
possibilities, loose governance, with expertise leading the way, is more appropriate
than rigid structures of tight control, which may dampen creativity and innovation.
Early collaborative agreements should foster a learning culture to achieve strategic
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agility, responsiveness to promoting fresh ideas, and the ability to pursue attractive
new opportunities and technologies (Yan and Gray, 1994). After the creativity of
partners and experimentation establishes a collaborative framework and areas of
focus, the direction of the alliance is more evident. Then a new strategic centre will
emerge and earlier loose governance can be replaced by a more steady-state set of
operations. Routines can then be standardized by all partners. At this point, more
direct control (tight governance structure) adds stability, but poses the danger of
blocking new market and technological ideas.
Outsourcing of innovation through the OS model
Most recently, OS software development has become a model of innovation through
external knowledge sources. It has developed from ‘‘garage’’ software products to
big-scale software developments. For instance, in 2005 Nokia launched
opensource.nokia.com, an internet portal for all of its OS software projects. Through
the portal, Nokia hopes to mobilize actual device users and business partners to further
innovate and customize the S60 software for their smart phones and the Maemo project
(a Linux-based internet tablet).
Most of the studies on the OS model have appeared in the software development
field, as this is where the OS movement originated (Grand et al., 2004). However, extant
findings can be applied to any area where knowledge becomes publicly available, as
our study shows. What makes this model interesting and unusual is the fact that the
OS developers employ their own resources and cover their own expenses to develop
innovative products or services, which are afterwards made publicly available for
adoption and adaptation by the end users or competitors. This challenges orthodox
economic theories, as it appears OS innovation does not require a return on investment
(from the individual perspective) and does not care about free riding (looking from
collective perspective). Why would a company choose to engage in OS-type
innovation? What drives a firm to allocate valuable resources to developing products
they then provide for free to users?
The answer is that OS players gain substantially increased innovation capabilities
and can derive financial benefits from drawing upon and contributing to commonly
held goods, services, and knowledge. OS innovation lies somewhere between the two
prevalent models of innovation (von Hippel and von Krogh, 2003; Ulhøi, 2004): the
private and the collective. In private innovation, results are developed and held
privately (Liebeskind, 1996), whereas in collective innovation firms work with public
institutions, and public access to results is enabled.
Grand et al. (2004) outlined a four level model of how a company can engage in an
open, innovative community. We have uncovered very similar characteristics in other
areas in which knowledge becomes publicly available. As an example (Table I), we
present two cases. One is a common OS example, a software development company.
The other is a consulting company that provides tactical and operationalizable advice
in the areas of process innovation, focusing on improvement of everyday working
practices, focused on knowledge management concepts, and deploying contemporary
IT tools.
Each level is concerned with certain costs and benefits, risks, and rewards. The
model inherently predicts that for undertaking any open software level, active
engagement is expected in the previous ones. As knowledge investments grow,
benefits accrue to the existing firm in terms of both increased knowledge and public
awareness and acclaim.
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Reputation and internal expertise are the main gains for OS-type companies. These are
built through augmentation of developed and released-to-public products as ideas are
amended and changed. Public release of knowledge includes a built-in process of
criticism and evaluation that allows developers to refine ideas, enhance their thinking
and understand diverse points of view.
For example, while Level 1 companies use only particular OS software (e.g. Apache
web server or OpenOffice personal productivity applications), a Level 2 company needs
to gain the knowledge and capability to adapt the piece of software to suit its particular
needs, as it offers the software as a complementary asset to its existing product (e.g.
Sony recently launched the Play Station 2 with a preinstalled Linux operating system,
which had to be extensively rewritten and adapted for the new platform). Furthermore,
at Level 3 a company chooses OS to be the design of its choice for particular projects
and actively joins the open development stream by giving out the source code. In this
way, the company taps into a global community of highly skilled people and is able to
acquire and assimilate outside knowledge, which is the most important benefit. At the
highest level, OS becomes the overall business model. At this point, companies are not
selling the IT artefact but rather, services around it. For instance, consider the case of
SUSE or the RedHat operating system: the companies realize their income by selling
CDs that help in the installation process.
In the OS-type consulting company in Table I, where a longitudinal study lasting
over eight years was undertaken (Grand et al., 2004), the use of the same four levels of
OS was evident over time. In the first stage, the company was established and the
founders had previously been employed in different companies, covering the business
areas of business process reengineering, organizational design, and project
management. They used publicly available knowledge such as textbooks, white
papers, practitioner and academic journals, to gain knowledge, which helped deliver
results in their everyday working practices. Level 2 started when the founders shifted
from their full-time jobs to consultants and transferred knowledge that they had and
that was available. With experience, employees gained the skills and willingness to
take on new knowledge acquisition. They started learning and creating original pieces
of research both on the academic and at the practitioner level. By publishing in local
business publications and appearing at business conferences with innovative
Table I.
Levels of engagement of
a company in open
community
Example 1: OS software development
company (Grand et al., 2004)
Example 2: OS-type consulting company (our
study)
Level 1: Only implements and uses OS
software
Level 1: Takes existing publicly available
publications (manuals, textbooks) and uses
them in everyday operations
Level 2: Adopts OS as a complementary
asset; adapts and extends it
Level 2: Takes existing publicly available
knowledge and uses it in the company’s
existing educational-consulting programmes
Level 3: Chooses OS software as the
design choice and commits substantial
resources to OS developers
Level 3: Employs researchers that create and
publish new knowledge and make it publicly
available. Employees gain expertise while
complementing their existing knowledge
Level 4: Becomes an OS core developer
and wraps the whole business model
with the OS paradigm
Level 4: Employees who create new knowledge
and make it publicly available sell their
knowledge and capabilities through consulting
services to other companies
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presentations, the company also promoted itself and gained an image as ‘‘advanced
professionals’’ in the environment where they operated. As a final stage, employee
skills became an entry-point for high-end consulting projects, where innovative and
truly beneficial business operations improvements are necessary.
Open source companies make significant contributions to development and, at the
same time, extensively increase knowledge, development and innovation capabilities.
In effect, OS innovation requires a company to enter a period of continual
organizational and individual learning. With each iteration of publication, feedback
and modification, the core competencies are built upon, and expertise is both deepened
and extended. Extensive competencies can serve as a base for developing expert
services on OS software, which are sold mostly to Levels 1 and 2 companies. The full
potential of the OS community for knowledge creation and learning is realized in
Levels 3 and 4, as people engage in experiential learning while trying to exploit and
further explore expertise created by others. However, making that shift requires the
commitment of substantial resources as well as a deep understanding of the OS
business model and how it impacts and changes the innovation process.
The findings of Table I can be conceptualized and applied in other areas. For
example, universities, pharmaceutical companies, and other technologically driven
companies are also involved in publicly presenting their knowledge (for example,
academic publishing), thus, similar conclusions can be drawn in these arenas.
This model also seems to apply to the current changes in the music industry. With
the advent of easy-to-use and powerful personal computers, handhelds, and mobile
phones, digitization and file sharing are becoming ubiquitous. Record labels have been
struggling to retain the copyright laws in order to preserve their status and profit
margins, which lead to overpriced CD and DVD music. It seems that artists will have to
come up with a new business model; in a globally connected world where everyone can
download their music, they do not need the labels to stock millions of CD’s anymore.
Moreover, in the future, they might have to rely on harvesting the revenues solely from
performing live, while promoting their concerts with free or pay-if-you-like or pay-if-
you-earn-from-it types of access to their music. Songs themselves would thus only be a
promotion tool and a field where the artist learns, gains experience, and improves
capabilities.
A different manifestation of OS innovation has developed in scientific arenas.
Procter and Gamble (P&G) circulates science problems, throughout a network (Huston
and Sakkab, 2006), to address specific knowledge gaps. The sources of innovation in
the network are technology entrepreneurs around the world; suppliers; and open
networks (like YourEncore (retired scientists and engineers) and Yet2.com (an online
marketplace for intellectual property exchange)). The problem stories are presented to
these groups and anyone with an answer can respond. The traditional R&D
department may not have the answers, but among the myriad of scientists in the
network, someone does. P&G then integrates that knowledge into its specific problem
or context and continues to develop the product.
Similarly, Eli Lilly formed the subsidiary InnoCentive to create a business model of
external knowledge acquisition. The process is similar to bounty hunting in the Old
West: ‘‘Wanted’’ posters describing a scientific problem and a reward are posted, then
bounty hunters can compete in an online project room to answer first and best (Breen,
2002). Over 95,000 scientists from around the world now participate (Kramer, 2006).
A particular open innovation form is explored in Miles et al. (2005). The authors put
forth an idealized, futuristic example in the OpWin network, which was designed in
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accordance with the best business practices of today. The OpWin network is made up
of member companies, each of which are independent fiscal entities; a network services
hub that stores and disseminates information; and a management group that oversees
the process, states new objectives for the network and facilitates collaboration between
member firms. The OpWin network strives for continuous innovation, not just periodic
spikes of innovation.
Collaboration between OpWin members is aided by an enormous catalogue that
shares products, product improvements, innovations, market ideas, problems, and
solutions. Ongoing learning is led and facilitated by the management group, which
brings members together in functional teams (e.g. marketing) with trained facilitators
to help the group assist members in seeing new markets and strategies for those
markets. In order to enter the OpWin network, a member company must display
collaborative innovation. This is not a simple cooperation, where joint aims are met
with clear goals; members must display the hallmarks of adaptability and knowledge
transfer across companies.
How does this differ from collaboration today? Miles et al. (2005) emphasize that all
ideas and processes of member firms are open to the network. All members can use
ideas or processes generated by any member of the network, and must acknowledge
the source of their knowledge. Even in cases of disagreement, different worldviews or
other friction, some have argued that innovation emerges at the areas of conflict
because that is precisely where key issues are revealed (Hagel and Brown, 2005).
Critical considerations. A company needs to decide on the business model and
allocation of resources when choosing to engage in the OS environment, as only then
can appropriate management interventions can be applied. Our findings suggest that
two business models are prevalent in OS innovation-type companies. The first is
geared towards the new market creation. For example, while publishing white papers
and thus freely distributing knowledge, a consulting company gains an ‘‘expert’’ image,
suggesting to clients that this particular company can solve particular type of complex
business problems. The company thus creates the need for their knowledge. At the
same time, that knowledge is available through value-added solutions such as
consultancy, IT implementations, etc. The second OS business model is dual licensing
of a product or service. Here, for instance, a consulting company publicly publishes
and freely distributes a summary of a market report. If the reader wants more detail, a
complete report is available for a fee.
Open source innovation is a highly specific but open partnership requiring careful
consideration before implementation in a particular business context. Three specific
characteristics of OS development, pertinent to knowledge creation beyond firm
boundaries, can be outlined from our findings.
First, OS development represents a unique combination of public and privately held
knowledge. The artefact itself is publicly available while expertise is held privately
with developers. OS players gain substantially in increased innovation capabilities and
can derive financial benefits from drawing upon and contributing to a commonly held
good. This model is particularly appropriate when an organization can identify
modules of knowledge. Modularity is part of why software development thrives in an
OS environment; different sources can easily be integrated, and components can be
developed externally or internally and then integrated. Procter & Gamble and
InnoCentive’s approaches both emphasize modularity rather than process. By seeking
specific answers and specific types of knowledge, OS can be directed and strategically
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embarked upon. In industries or knowledge domains where segmentation of knowledge
can be undertaken easily, OS innovation becomes much easier to manage and direct.
This modularity is not the only approach to OS innovation. The OS software
movement is overcoming this approach by considering and deriving competitive
advantage from the community aspects of OS. This second consideration of using OS
innovation requires engagement with an OS community is a highly dynamic exchange
process, as the community often presents an instant review of the knowledge released.
With the OS ‘‘2.0’’ concept (as noted in Fitzgerald, 2006), not only horizontal
infrastructure is being developed sporadically by a group of relatively ad hoc developer
group. Rather, OS software developers start with a purposive strategy to gain
competitive advantage (over proprietary SW developers) by building purposive vertical
information system (IS) solutions in a less bazaar-like managed manner (Fitzgerald,
2006). With the latter, in-depth overall requirements analysis is not needed as the
software users are also developers, who indulge in improving particular modules on an
individual basis. There is no need for reconciliation of viewpoints because development
tasks improve a known software design in a modular manner. When more developers are
working jointly on an innovative software product, analysis and design becomes more
complex in vertical sense as pieces of code are highly dependent or even impossible to be
divided in modules and coupled back at the end. Developers need to act as a part of a
highly orchestrated joint effort.
Fitzgerald (2006) notes that the ‘‘mythical characterization’’ of OS software as a
collective of ‘‘supremely talented hackers’’ freely volunteering their knowledge towards
development of software that stands up against existing proprietary solutions (c.f.
Ljungberg, 2000), is an outdated one. Indeed, ‘‘the haphazard principle of individual
developers perceiving ‘‘an itch worth scratching’’ is superseded by corporate firms
considering how best to gain competitive advantage from open source’’ (Fitzgerald,
2006). Evidence from our case of a consulting company conforms to the latter, as
adoption of the OS model in the company is deliberate, with the company’s strategy
being built strictly around the OS principles. It is of crucial importance to recognize the
difference between codified knowledge (in a form of artefacts such as pieces of code or
journal articles) and the tacit knowledge inherent in cumulative experience, collective
working practices, and organizational routines. Only these can act as a true source of
competitive advantage in the OS model. Any organization must carefully consider
what knowledge should be public and what private expertise backs that knowledge up
in order to understand and increase their competitive advantage.
Third, co-creation of the public good is beyond any team, organizational, or other
boundaries. As opposed to traditional business models, ‘‘competing’’ innovators benefit
from their cooperation, as their competences grow with each project. From the
perspective of the collective, publicly available knowledge grows too and pushes the
frontiers of knowledge domains further. ‘‘The value of knowledge increases with wide
consumption’’ (Ulhøi, 2004), which marks a fundamental difference in economic
approach and the possibility for competitive advantage.
When considering OS-type innovation with external partners, companies need clear
answers to two questions. First, whether free riders, having access to the ‘‘open’’
product, can benefit substantially (and relatively more as true innovators) from gaining
reputation or competences. If they do, the OS business model is not appropriate.
Second, does making knowledge publicly available, improve possibilities of the
innovator to capitalize upon competences gained, increased reputation, and/or new
product/market created?
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Discussion
To help organizations better manage their innovation agendas, we proposed three
models of outsourcing of innovation through business partner: innovation through
acquisition, innovation through strategic alliances, and OS innovation. These models
emerged through our exploratory study of over 30 US and European companies that
had a track record of successfully innovating with external partners. Due to
exploratory nature of the research, a pragmatic selection of case studies has been
made. Additional empirical research will help reveal deeper insights into the
organizational design of the integration process based on key layout elements and
parameters. The findings presented are based on limited number of organizations. We
acknowledge and understand the issue of generalizability, and have taken necessary
steps when designing our research. To generalize our findings, future research needs to
be done. We view our study as exploratory and preliminary, yet insightful. We wish to
lay the foundation for future enquiry and therefore to contribute to the highly relevant
research stream of showing the role and potential of enabling and supporting
demanding open and distributed organizational processes.
Outsourcing of innovation through external knowledge acquisition is beneficial when
expertise exists outside, which can be purchased easily, swiftly, and immediately put to
use by integration into the organizational fabric. In these cases, organizations may not
choose to invest resources in innovating from scratch. In addition, since these pieces of
knowledge are exclusive properties of partners, competitive advantage can be gained
through knowledge acquisition. However, not every required piece of knowledge is
available in the market. Most of the time external acquisition of knowledge is available
for only mature products with rich history. For example, organizations may purchase
new IT services rather than innovating themselves if they do not have the requisite IT
expertise. Further, acquisition of knowledge should be done for the non-core areas of the
business. Core innovations provide competitive advantage, profitability, and growth and
hence organizations need to be actively engaged in innovations in core areas, while
judiciously obtaining innovations in non-core areas from the market.
Outsourcing of innovation through strategic alliances has become a popular
mechanism of innovation, given the increased level of competition with globalization
and the need for rapid innovation. Organizations cannot rely solely on their internal
skills and competencies; they need to actively work with business partners to harness
partners’ knowledge and recombine with their own to bring out new products and
services. Unlike the case of direct knowledge acquisition, in the case of innovation
through strategic alliances, the end result is not always clear. However, the modalities
of cooperation, areas of integration, and roles of each partner are well defined. Apart
from benefiting from each others’ knowledge, organizations also share the risks of
innovation by pooling resources and expertise. However, since the engagement
requires a long-term view and commitment when compared with acquisition, the risk
of a mismatch between partners is always present. Hence, for successful innovation
alliances, organizational, cultural and strategic compatibility is critical. Organizations,
therefore, need to hone the skills of finding strategic partners and understanding the
contextual factors like competition, market situation, and existing knowledge base.
Even after finding the right partner, establishing the right kind of governance for the
alliance is equally important. Knowledge-based alliances require a ‘‘loose–tight’’
governance mechanism to ensure adequate autonomy and control.
Compared to outsourcing of innovation through knowledge acquisition and
strategic alliances, outsourcing innovation through OS model is a new phenomenon.
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Although, most of the OS innovation has happened in software development field, the
concept is equally applicable in any area where experts are outside the organization.
The central concept is gaining knowledge from a community. However, organizations
need to have a proper business model in place to develop a successful OS innovation
model. Despite the simplicity of the model, organizations need to carefully plan OS
innovation model in the context of a business problem, because of the issue of engaging
people in sharing their privately held knowledge. It is also important to appreciate the
difficulty of appropriating tacit knowledge from people and organizations need to be
ready with circumventing this issue. Further, it is critical to be aware of the issue of
competitors gaining access to the knowledge and being part of the community. OS is a
potent mechanism of innovation, but organizations good business plans for success.
Our assumption that business partnerships are dynamic relationships suggested
that the success of innovation depends on correctly matching the type of business
partner innovation to an organization’s current abilities and organization’s strategy for
the future. Table II summarizes considerations for matching that have been recognized
as crucial in each of the business partner innovation models.
Table II illustrates that matching the type of business partner innovation to an
organization’s current abilities can greatly assist in success. For instance, for
organizations with a strong learning culture and a sustained base of long-term
employees innovating consistently, OS innovation can exponentially increase
knowledge and lead to highly successful consulting services.
Table II also indicates that organizations need to make conscious strategic choices that
will fit best their innovation projects. Observations from our exploratory study indicate
that the three models of business partner innovation are used in a portfolio manner.
Mature organizations with sustainable innovation programmes seem to be comfortable
and agile with each of the business partner innovation models, which are called upon as
needed to meet the needs of the innovation projects. It seems they use them at the same
time within different projects – both in a straightforward or (any other) hybrid form.
The three mechanisms of innovation outsourcing can be represented as a three-
dimensional space where companies manoeuvre to seek, manage, and achieve their
innovation. The three axes of this space are the scope of the innovation (the resources
necessary to carry it out), the impact upon existing business strategy (comparative
strength and position competitively), and the need for customization (functional
changes). The degree of customization required is the amount of effort and need to
tailor a particular innovation or the existing structures of an organization for effective
use of that innovation in a competitive context. The scope of the innovation is a way of
evaluating the likely impacts on the organization and its target consumers. The effect
on existing business strategy is a crucial factor, because innovations that have
substantial effects on business strategy will require careful communication and likely
will not be able to be acquired, as discussed above. These three factors tend to rise and
fall together. A project with a large scope often requires high customization and many
changes in business strategy. The three types of business partner innovation discussed
in this paper are also most suited for different levels of these factors. Acquiring
innovations has been discussed as most suitable for low customization, low scope of
innovation, and low impact on business strategy. On the other hand, business partner
alliances are best for mid-range projects that have some customization, a medium
scope and a not insignificant impact on business strategy. OS innovation tends to
require high customization, a broad scope, and significant business strategy changes.
Each type of innovation has different degrees of variance related to Table II. The
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Table II.
Characteristics of
business partner
innovation models
Characteristic
Innovation through
knowledge acquisition
Innovation through
strategic alliances
Open source
innovation model
Nature of
relationship with
business partner
Acquire business
partner’s privately held
knowledge
Collaborative
innovation efforts.
Relationship can be
characterized as
‘‘partnership’’ or
‘‘buyer–supplier’’,
depending on
the type of
alliance
Four levels of
integration relations,
from strict
supplier–buyer to
alliance-type of
relationship
Reason behind the
decision for
particular
relationship
Purchase already
‘‘proven-in-practice’’
knowledge, adopt it
and utilize it
Know-how projects:
transfer of tacit
technological
knowledge,
complementing an
existing knowledge
base Capacity
projects: bridge the
lack of internal
R&D resources for
less critical projects
Depends on level of
involvement. From
capitalizing
internally upon
existing, publicly
available knowledge
up to deliberate
creation of new
public knowledge
with goal to build
competences in
form of tacit
knowledge,
cumulated
experience and
collective working
practices that are
used to deliver
products
Scope of innovation Essentially less
innovative; however,
some companies, after
adopting the acquired
knowledge, advanced it.
With that, they built
innovation capability,
and started innovating
on their own
Know-how projects:
process innovation
changes the way a
company does
things, business
processes, and
technology,
resulting in
potentially very
different
(innovative)
products Capacity
projects: less
innovative,
incremental
product
changes
From none to
technological
(process) innovation
– depending on the
level of OS
involvement
Example Patents (e.g. IBM’s
patents base)
Joint collaboration
efforts, e.g. high-
definition television
OS software (e.g.
Linux), consulting
companies offering
‘‘free’’ academic
texts and
research results
to the public
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strategic goals that lead to an organization’s choosing a particular innovation strategy
can be represented along the axes, from specific, off-the-shelf product integration to
business strategy innovations. There can be some degree of variance on each axis, and
we can use this variance to locate companies’ practice in the space and then explain
how successful companies strategically choose when and how to move from one spot to
another. This approach is akin to various matrices (such as BCG, ADL, GE/McKinsey,
etc.), known from the strategic management discipline.
One example of use of such three-dimensional ‘‘Co-innovation space’’ is shown in
Figure 1, where an organization’s portfolio of innovation projects could be sketched.
Using the conceptual space represented in Figure 1, a company can analyze its
existing innovation portfolio. This awareness can increase their competitiveness with the
innovation projects. The questions that should arise in such analysis are the following:
(1) What types of innovation are our current innovation projects?
(2) What kind of innovation projects do we want in the future? An appropriate
portfolio of approaches should reflect both the current abilities and strategic plans
for the future, as we have seen that three business-partner-innovation-approaches
are to be used in different organizational and business environment settings.
(3) Moreover, by scaling the representation of projects in this figure, organizations
can answer this question: how much commitment (e.g. in terms of financial or
human resources) do our innovation projects take? Not all the innovation projects
are equally important and thus do not involve equal amount of resource
commitment.
Consider another example. Using this three-dimensional space, organizations can
analyze and discuss ‘‘where it stands today’’, ‘‘where it will stand tomorrow’’, and
‘‘where it wishes to stand in the future’’. Namely, it could be argued that companies may
take one overall innovation approach over the other two for a moment. Then, they
move from one approach to another as market (or other) conditions allow/force them to
Figure 1.
Co-innovation space
SO
1,2
118
do so. While doing that, appropriate decisions regarding future innovation orientation
need to be made. According to their strategic roadmap, organizations can visualize
their goals and approaches for business partner innovation.
Such a graphical representation can have tremendous implication in terms of
research also. Consider the aspect of degree of commitment. It could be argued that not
all the firms with innovation strategy go with equal amount of commitment or
resources. The issues that remain to be answered by further research are:
(1) Are all the organization the same in their commitment or scale with that
innovation option (i.e. strategic alliance)? Do they have only one alliance or
many? Is the alliance critical for their future? Is the alliance a long-term option?
(2) If companies differ in their commitment or strategic alliances give different
values to the partner companies, why do the companies differ?
Future research should explore the situational factors under which companies choose
to use a particular model. Perhaps firm size, market position, and other things shape
the understanding of how organizations choose their position in that particular
innovation strategy. The situational factors that could be considered include the
market environment, the competitive situation, the product specificity, the level of
technologies, partner characteristics, and the company’s in-house innovation culture to
test the impact and success of these three models of innovation. The same argument
can be applied to the other two axes as well. It would be also interesting to answer
whether companies in a certain position in three-dimensional space can survive the
market competition with their current innovation approach.
Each concentric circle represents a different approach to business partner innovation.
Projects with the smallest scope, least customization, and smallest impact on business
strategy are best suited to be acquisition type projects. On the other hand, in projects
where customization is known to be high, the scope of the innovation is very high and
the eventual impact on business strategy is expected to be high, OS-type innovation is
more suited. Business partner alliances typically fall in the middle for all factors.
This is not to say that innovation is wholly an organization-wide endeavour. Figure 1
seeks to explore the strategic needs of business partner innovation, but organizations
must also remember to balance knowledge needs. Rapid innovations make developing
both specialized and broad technological knowledge bases extremely difficult.
Complementary competencies and specialized knowledge are needed in all innovation
efforts to give the edge to an innovation. In particular, organizations need to hunt for and
retain motivated and talented individuals and teams to help them generate innovations.
Organizations must create an environment of creativity and trust in which individuals
can see their dreams to fruition.
Conclusion
Partnerships open the door to multiple knowledge sources, such as internal R&D
activities, research conducted by partner organizations, and scientific knowledge
available through public innovation. Accessing and integrating information from these
sources can greatly enhance the knowledge base of a single organization and feed into
a cycle of sustainable innovation. Strong, well-matched business partners can form the
backbone of a virtuous cycle of increasing innovation. Collaboration, paired with
differing worldviews and clear objectives, can result from business partner innovation
processes when risks are managed and success factors well considered.
Building
strategic
partnerships
119
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OUTSOURCING A CORE COMPETENCY
Pharmaceutical firms that outsource biostatistics risk losing
opportunities to improve innovation, a study shows.
Shreefal Mehta and Lois S. Peters
OVERVIEW: Data from contract research organiza-
tions (CROs) and pharmaceutical companies reveal an
increasing amount of outsourcing of biostatistics in
clinical trials. However, a surprising number of projects
involve practices Identiftedas “never outsource” and of
“key importance to grow and retain ” by the pharmaceu-
tical statistics directors. The sharing and outsourcing of
these big pharma “best practices” with the CROs is an
advantage Jor smaller competitors, particularly as
related to analysis methods and protocols that are likely
to he accepted hy the U.S. Food and Drug Administra-
tion. Over time, an accumulation of critical resources
and tacit knowledge could allow the CRO to eventually
become a new type of independent competitive player in
the drug development process.
Shreefal Mehta is clinical as.
15
34
Interviews were held with senior managers, biostatisti-
ciansand technological specialists who provided both his-
torical and current information and responses to the
research questions developed by the Rensselaer team.
Interviewees were identified by our company liaison to
ensure the breadth and depth of knowledge necessary to
address our questions and to provide a diversity of per-
spectives about the development process.
We also collected infonnation on outsourcing activities
from the web sites of the top pharmaceutical firms and
analyzed their content to help us understand cuirent activi-
ties, We also reviewed data from ParexePs Pharmaceutical
R&D Statistical Sourcehook and Bioscan to provide
insight into life science NPD practices and outsourcing as
well as changing industry dynamics and complexity.
Given the sample size of 34. we used summary statistics to
describe the responses as means, medians or percentages
of total responders to a particular survey question.
In our review of the transcripts, segments that bore on the
research questions addressed in this paper were high-
lighted and collected on summary sheets for each project.
The authors independently reviewed each transcript. The
summary sheets were then compared and aggregated, and
observations were expressed and discussed by the authors,
to identify commonalities and dissimilarities.^—S.M. and
L.S.P.
May—.lune 2007
them to clear regulatory hurdles. Statistical analysis of
the clinical data is a key point of regulatory scrutiny, sug-
gesting that biostatistics would have to be developed as a
core competence for pharmaceutical companies to be
successful. As outsourcing of drug development
functions to contract research (CRO) firms increases, we
asked these questions: Arc pharmaceutical companies
giving up their core competence to the CROs? What are
the key biostatics-related core competencies and
functions in drug development? What role, if any, can
biostatistics play in developing dynamic capabilities?
The Role of Biostatistics
Statistical analysis has always played an important role
in the pharmaceutical industry, but the drug discovery
phase has not employed heavy statistical analysis until
recently. This recent use of biostatistics in discovery is
driven by the advent of large amounts of bioinformatics
data that require fairly sophisticated statistical analysis to
interpret and validate. The focus of this study, however,
is on the key competencies of the pharmaceutieal
industry in managing and conducting drug development,
and clinical trials, and interacting with the FDA. the tra-
ditional domain of pharmaceutieals that has employed
sophisticated statistical analysis.
In the drug development process, a biostatistician is
typically involved in early planning of an experimental
study, in the preclinical (animal studies) and clinical
stages (protoeol design). The bulk of a statistician’s work
lies in analyzing data, as shown in Table 1.
The three main stages of the drug development process
are categorized as: early discovery, middle (or preclini-
cal) development and final development to commercial-
ization. The early discovery is frequently {sometimes
more than 50 percent of all projects) licensed in by big
pharma from small bioteehs and universities, and the
middle stages of late preclinical testing and early human
testing is largely process-driven by regulatory and safety
issues (21). Thus, the core competenee that is recognized
as unique to big pharma increasingly seems to be focused
toward the final stages of drug development, which
include large-scale, expensive, clinical studies to
establish efticacy, regulatory interactions for marketing
approval, manufacturing in large quantities, and
marketing, sales and distribution of the final product. In
this context, the role of biostatistics is critical to estab-
lishing success of the large-scale phase III clinicai trials,
with results of complex statistical analysis holding the
key to regulatory approval to go to market.
Trends in R&D Outsourcing
All drug companies seek to reduce costs and reduce the
tiine to market in a lengthy and expensive product devel-
opment process. In this high-risk process, where a
Table I.—Biostatistics Role in Drug Development
Drug Dcvt’lopment
Stage Biostatistician Function/Kole
Discovery stage.
Formal preclinical
data for regulatory
filings.
Chronic toxicology.
safety studies.
Clinical studies.
Clinical Phase IV—
follow-up or
extension clinic
studies.
Manufacturing—
Quality control.
Bioinformatics. data mining.
Basic analysis with
phannacological data
(rarely double blinded).
Analysis of data from toxicology
study—some study design work.
especially for complex dosages
or combination drug studies.
• Design of trial protocol with
physicians—detemiine sample
size, relevance of parameters,
data analysis methods defined.
• Make sure data are entered
correctly.
• Interim analysis as per protocol.
• End of study—reliability,
quality of data.
• Analyze—write report and check
medical report to make sure
analysis is accurate.
• Combine data across safety
studies (not efficacy data).
Analyze data, follow adverse
events, analyze, interpret,
and prepare reports for
submission to FDA,
Not specific to biostatistician—
general statistical anaiysis.
project could fail at many different steps, it is more
attractive to rent or outsource the resources needed at a
given stage. For smaller companies involved in the
clinical trials process, outsourcing is not a choice but a
need, as they cannot afford to build up internal resources
with required skills and efficiency.
In general, the global pharmaceutical R&D outsoureing
market continues to grow at over 14 percent annually,
with clinical trial management (83 percent of all CRO
revenues) dwarfing the rest of the R&D functions (21)
(Figure 1). More telling, spending on outsourced clinical
trials as a percent of total spending on clinical evaluation
studies in pharma/biotech companies increased from
16 percent in 1995 to 25 percent in 2002, with over
22 percent of all clinical studies being outsourced (2!). In
fact, a 2000 survey of pharmaceutical companies and
CROs by CenterWatch indicated that CROs now play a
major role in over 60 percent of all R&D projects,
compared to <30 percent in 1993 (2/). This increase in outsourcing (Figure 1) is particularly interesting, considering that the large phannaceutical companies view management of large clinical trials as a eore competence. Consider, for example, Glaxo Smith- Kline (GSK). GSK, a few years ago, restructured its business and R&D units, launching a hub-and-spoke Research • Technology Management model, where the R&D units were independently organized around the core hub that contained clinical Phase III management capabilities, marketing, manufac- turing, and corporate functions. In the middle stages of R&D ... GSK has created six Centres of Excellence for Dmg Discovery, or CEDDs. Each CEDD is dedicated to specific therapeutic categories; each is responsible for taking lead compounds forward to the point where the therapeutic rationale for those compounds is demonstrated sufficiently lo Jiistif}' the start of large-scale clinical trials, (from www.gsk.com). Our Study Results Reliance on CROs and increased outsourcing are also reflected in our survey results, which were obtained from a cross-section of large and small biostatistics service provider firms (see "How the Study Was Carried Out," page 29). In all, 34 responses were received and 33 were included in the analysis. The responders include not only some ofthe largest CROs but also smaller independent CROs whore the biostatistics gioup is composed of two statisticians. The CRO respondent (typically a director of biostatistics or, in a smaller fimi, the senior biostatisti- cian) summarized the clinical trials outsourced to their companies from large to mid-sized pharmaceutical companies by noting how frequently specific functions in biostatistics were included in all client projects with which they were familiar. Respondents were asked to write the approximate frequency of inclusion of various contracted fimctions in all projects and separately to indicate the same for projects that were focused only around biostatistical functions. Table 2 summarizes the responses from the CROs by noting the percent of contracts that include a pharmaceutical companies view management of iarge ciinicai triais as a core compotence. given function for different types of contracts outsourced by a large- to mid-sized pharmaceutical customer. Our data indicate that most respondents perfomied out- sourced tasks that were both mundane and technically challenging. Data compilation and collection are the more technically mundane chores (Table 2). Notably, data analysis and interpretation, which requires a higher level of engagement with the data, was also almost always included in the contracted functions at a level of 65-70 percent ofthe time in all projects, and 100 percent of the time in biostatistics-only projects. In particular, when all contracted projects were considered by CRO respondents, less challenging tasks such as data collec- tion were included at the same frequency (65-70 percent ofthe time) as higher-level analysis or interpretation in the contracted functions, possibly indicating a packaging S c a CO 80 70 60 I CRO Total •Riarma Total R&D I CRO dinfcal •Pharme Clinical R&C 4 i J 0) tt 2 O 1 O 1995 1996 1997 199 1999 ear 2000 2001 2002 Figure 1.—Increased pharma R&D budgets have clinical R&D as a significant element, and increasing CRO revenues are mainly focused on contracted clinical R&D, including data management ami statistical analysis. Mav—June 2007 Tahle 2.-—Contracted Functions in Biostatistics Outsourcing Service Function Contracted Protocol design clinical Dala collection Data compilation Data analysis Data interpretalion Project management/ decision support Presentation to FDA Broad Service Contracts % o f contracts that include the function* 32 75 65 73 68 75 10 Biostatistjcs Service-Only Contracts % o f contracts that include the function* 35 20 71 100 100 55 8 *Median of all responses of services from the CRO but also indicating an accep- tance of the CRO competence in that area by the pharma contractor. Projects that involved only CRO biostatistics groups (Table 2), always (100 percent of the projects) had data analysis and interpretation included with less than 30 percent of contracts requiring data collection activi- ties. Outsourcing of biostatistics functions alone is clearly focused on the higher-level analytical and inter- pretation work. However, interviews with pharmaceuti- cal company biostatistics directors showed that these higher-level activities are usually carried out using guidelines and templates issued by the client. A biosta- tistics director from one of the top five pharma companies indicated that the "analysis methods develop- ment is never outsourced" and that selection of the CRO sometimes depended on which one " . . . can adopt and understand our methodologies well," showing flexibility and competence. About 50 percent of the biostatistics-only contracts involved support for project decision-making, which is expected considering the intermediary role of the CRO between the data and the client. Surprisingly, a signifi- cant portion of contracts (mean of 35 percent) involved clinical trial protocol design, which is a key function of biostatisticians and clinical teams in pharmaceutical companies (Table 1). This fmding is validated in data gathered by CenterWatch in their year 2000 survey of pharma companies and CROs {21) showing that about 20 percent of polled pharma companies use protocol design services, along all phases of the clinical study process (Figure 2). Interviews with the sampled ftrms indicated that while it was not common for all protocol design to be outsourced, frequently the clinical/contract research organization had skills and expertise in the area and would collaborate with its pharmaceutical counterparts to refine the initial study protocol design. When asked to report on the role of the biostatistician in a selected recent or current large or mid-sized pharmaceutical contractor, 76 percent of all CRO respondents indicated that the contracting company had a biostatistician in-house. Further survey responses revealed that of these contracting companies with in-house biostatisticians, about 44 percent were involved in a supervisory role and 56 percent of the con- tracting biostatisticians were involved in a participatory fashion in the projects. These responses indicate that about 24 percent of the time, the (presumably mid-sized) contracting companies do not have the resources of biostatistical analysis in- house, and even when they do have in-house experts, they rely 56 percent of the time on the best practices retained by the CRO biostatistical team. In fact, in addi- tional survey questions when the CROs were asked if their responsibilities increased over time with a single client (median relationship length with specific clients was 3 years; median length for particular projects was 1 year), over 60 percent replied in the affirmative. While the survey suggested a growing tendency among pharmaceutical companies to outsource projects to CROs and rely on the CRO's statistical competence, sample comments from these companies' biostatistics directors or managers about outsourcing were as follows: . . . we would never outsource vital studies—and even if we had lo. we would never outsource anything in the critical path of drug develop- ment. On the other hand, we would completely outsource extension studies. Stability of CRO personnel [turnover] and commitments of time to the project are always an issue with large CROs. We would prefer to work with a smaller CRO that had a focus on biostatistics and much lower turnover than a big CRO. Percentage of pharm companies that use CROs "often" Rotocol design • Statislical Services 10 2 0 3 0 4 0 5 0 6 0 7 0 8 Figure 2.—A 2000 survey of pharmaceutical companies by CenterWatch showed that while most companies outsourced parts of statistical work, a significant portion of the companies (-20 percent) used CROs for protocol design services (I). Research • Technology Management This particular concern for CRO competency and personnel focus and stability was reflected by several of the pharmaceutical statistical group directors. Implications for Management Outsourcing R&D functions is a "buy versus build" decision in most companies, suggesting transaction cost logic (22). Projects will be outsourced when tasks are readily programmable, as in extension trials. When projects are long-term and arms-length monitoring is difficult, the cost of outsourcing may be too high. But for pharmaceutical companies, where the risks are high and capital costs for product development (clinical trials) are significant, outsourcing may seem like an optimum solution. However, outsourcing takes place at the risk of diluting internal competencies and increasing complexity of R&D management. The benefits and transaction costs of managing alliances have to be constantly balanced, keeping the strategic interests of the company in mind. In the knowledge management literature, it is recognized that outsourcing practices can have the short-term effect of diluting the firm's competencies and the long-tenn effect of increasing competition in the industry by diffusion of best knowledge, skills and competencies to other players in the field through the service com- panies {23). In this study, biostatistics was recognized as a core com- petence, especially in protocol development and advanced data analysis, but we found differing perspec- tives on the management styles and philosophies; one group (typieally non-bio statist ics executives) stated that biostatistics was only a process tool and technique, while another group (typically biostatistician middle managers or scientists) argued that there was significant innovation in product development that could be driven by better use of biostatistics. The increased outsourcing recorded here, particularly of the "thinking" functions of a critical com- petency such as biostatistics, would certainly reduce the potential for capturing and nurturing innovation inter- nally. This loss of innovation potential was evident in one of our case interviews. In a clinical study with a new drug for treating sleep disorders, an internal biostatistician with experience in this domain included a couple of extra measures in the study design. The original indication failed to show efficacy but the extra parameters recorded led to a realization of a new and unforeseen indication. Because the biostatistician was employed by the company, she had the capability and support to change the protocol and research design. However, the described critical insight, input to the protocol and resulting inno- vation would be much harder to capture if the study was being outsourced, in which case an external biostatisti- Outsourcing cau dilute a firm's competencies and increase competition in tiie industry. cian might be rewarded for reducing cost (minimal intro- duction of new measures or tests) or increasing speed. From the results summarized here, we note that although large pharma companies stated that they outsource only extension studies or non-critical studies, there is still an exchange with the CRO in terms of best practices, standard operating principles and analytical methods. This gives rise to the diffusion of competencies in the industry. The data from the CROs (Table 2) demonstrate the surprising number of projects that involve either trial design or have the CRO's write-ups presented to the FDA directly, both practices identified as "never outsource" and of "key importance to grow and retain" by the pharmaceutical statistics directors. The sharing and outsourcing of these big pharma best practices with the C ROs is an advantage for smal ler com- petitors, which do not have the history or resources to develop optimal processes in biostatistics, particularly as related to analysis methods and protocols that are likely to be accepted by the FDA. On the one hand, CROs can be viewed as instruments for diffusion of institutional practices and thereby a route for small firms to gain legitimacy (34.25). In this view, CROs, through their role in institutionalization of biostatistical practices in drug development, are a mechanism for bringing greater stability to drug product life-cycle dynamics. In gaining experience in areas of strategic competence for success in the industry—regulatory interactions and study protocol design—the CROs are gradually posi- tioned to take on an increased role in the drug develop- ment process. A direct recognition of their growing competence in these areas is seen in the steadily increas- ing amount of outsourced R&D from pharmaceutical companies. In fact, the capabilities of some of the larger CROs. combined with their cash positions and steady income stream from long-term contracts, will eventually lead to their emergence as risk-takers and co-investors in the drug development process, where they will appropri- ate more vaiue due to their increased competence. Mav—June 2007 A survey of 31 leading CROs by CenterWatch in 2000 showed that risk-sharing in CRO contracts was expected to increase (2/), and recent news reports verify these trends toward increased investment and risk-sharing in products by CROs {26). Thus, new business models will emerge with a sharing of jobs among industry players, hopefully leading to reduced risk for each player, and increasing pipeline productivity, which could lead to greater innovation and new products reaching the public. However, this scenario is still developing, as is the entire pharmaceutieal industry, currently under severe pricing, market and regulatory pressures. We observe in conclusion that biostatistics is a contested, immobile competency in drug development. This per- spective proposes that over time, an aeetnnulation of critical resources and tacit knowledge will allow the CRO to eventually become a new type of independent competitive player in the drug development process. Such an outcome would perhaps increase turbulence by changing industry ecosystem dynamics through increased CRO competitiveness and reduced sharing of best practices in the industry, as opposed to the potential stabilizing influence that the CRO could exert as a reliable interdependent player in the industry. 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