Creating, Growing, and Sustaining Efficient Innovation Teams

Casimer DeCusatis
IBM Corporation, Poughkeepsie, NY


Creating, Growing, and Sustaining Efficient Innovation Teams
Economic forces such as the growing service economy and commoditization of traditional value chains have led many organizations to pursue breakthrough innovations as part of their business strategy. There has been an increased interest in collaboration and teamwork as catalysts of innovation, often without a clear understanding of the different kinds of teams that can be used to foster innovation or the kinds of team building that will be most likely to yield desired results. The author describes a framework for innovation teams, ranging from highly structured to spontaneous, giving examples of how different kinds of teams relate to the characteristics of the next generation of innovators. A case study illustrates how one approach using preference profiling is more likely to yield tangible results from an innovation team.

Introduction – The Changing Nature of Innovation

The global innovation – commoditization duality has never been more pronounced than in our current economy. Many organizations are investing in efforts designed to promote innovation, without a clear idea of how these investments translate into business value.

Furthermore, organizations are also evolving from an industrial base to a service base. This is driven by several factors, including the removal of barriers to service relationships brought about by the virtualization and dissemination of information. However, value capture in the service market is based on customer perception and utility rather than more traditional metrics such as cost and quality [1]. Consequently, the value created through innovative service teams also goes largely unrecognized, making it difficult to assess the impact of teams charged with producing innovative results.

There is a great body of literature on the theory of innovation, how people collaborate and the role, structure and types of innovation ecosystems that occur [2-5]. While many companies consider themselves innovative, most lack a common lexicon for understanding how their investments in innovation translate into business value. In particular, while it is recognized that collaboration is an important element of innovation, there is a need for better approaches to forming, growing, and sustaining teams of innovators. After reviewing the changing nature of innovation and the emerging generation of innovators, we propose a framework for classifying innovation teams (note: the pronoun we is used throughout the paper to refer to the task force that carried out the internal IBM innovation study that this paper is based on). This allows us to better match the characteristics of the team with the approach to innovation, making it more likely to achieve desirable results.

It is important to first recognize that the fundamental nature of innovation has been changing in recent years. There is a growing emphasis on collaboration as part of the innovation process. There are sound economic reasons why collaborations are growing in importance, including the rising cost of technology development, shortening product life cycles, and the difficulty in sustaining closed research & development (R&D) models. An increased focus on core competencies at many businesses has provided an opportunity for interdependencies to a much greater degree than any time previously. As global information networks make knowledge increasingly widespread, social networking tools (Web 2.0 and 3.0) create more opportunities for like-minded parties to find each other and for interdisciplinary teams to form in unexpected ways. In many technology-based industries, the traditional value chain is breaking down; faced with diminishing returns on their R&D or venture capital investments, many companies have begun to emphasize collaborative tools as a catalyst for innovation. We conceptualize this view using the model illustrated in figure 1, which distinguishes between two types of innovation approaches that we call monolithic and collaborative.

The monolithic approach represents the conventional view of innovation, as driven by large organizations that hold an effective monopoly on their markets. Innovations are created by a relatively small group of discipline-specific experts, working under controlled conditions with specialized equipment. The problems they address are typically fairly well defined, and their solutions represent highly valued intellectual capital, which is protected by patents. Innovations proceed through the development process in a linear way, eventually reaching a group of passive consumers. Feedback is limited to a sampling of customer opinion in between product development cycles. This approach has held sway in the technology industry for many decades;funding for corporate research and development labs is based on the business value produced by this approach. While we can demonstrate that this approach still works well under some conditions (specifically when there is an effective monopoly), a new approach has emerged within the past decade or so, which we call collaborative innovation. In its purest form, this differs significantly from the monolithic model. Collaborative innovation delivers customer value through the creation of relationships and social networks, which involve customers early in the development process and maintain their involvement continuously. Valuable ideas can come from anywhere, at any time, and be incorporated into the product based solely on their merit. Such collaboration is interdisciplinary and cuts across organization silos. Intellectual capital is shared freely; indeed, since we may be unable to determine exactly when an idea was first conceived or by whom, the concept of patents breaks down. Some Internet-based companies, universities, and a few others have fully embraced this model. Most organizations, however, fall somewhere in between these two extremes, sharing characteristics of both approaches or changing their focus for different projects.

An example from the computer industry helps to illustrate the migration from monolithic to collaborative approaches as an innovation driver in business. Within IBM, consider the mainframe tradition spanning Systems 360, 370, 390, and Z; this began as a monoculture many years ago, and became quite successful, coming to dominate the Fortune 500 market (particularly the financial sector). Starting in the early 1960s, innovation on the mainframe was driven exclusively through corporate research and development, and consisted mainly of delivering anticipated, incremental improvements to the processor speed, memory, and other performance benchmarks on a regular basis. Over time, market demand shortened the time between product release cycles, and subsequent advances in basic performance benchmarks became less important. In the early 1990s, recognition that this platform was not leveraging industry standard component development led IBM to transform parts of this business into a more collaborative approach. For example, the input/output (I/O) subsystem, considered to be world class in the industry, was able to maintain its leadership while using industry standard rather than proprietary components (fiber optic cable and connectors, optical transceivers, etc). This led to increased interaction between development and procurement, as well as with technology suppliers outside of IBM. The operating system was another area that was opened to external developers when IBM published many of its interoperability specifications. Today, a software development community exists which can port applications to both the Z/OS and Linux operating systems, university courses teach System Z skills, and a fully functional emulator for mainframe application development is available for under $100. This has led to partnerships between hardware, firmware, and software development teams eager to optimize across traditional functional silos and exploit the full value of the server. Similarly, many companies are no longer focused exclusively on the development, manufacture and delivery of information technology, but rather on the application and integration of technology to deliver new and lasting value. The success of an innovating firm thus depends not only on its ability to meet its own innovation challenges but also on the efforts of other innovators in its environment. At the same time that partnerships have become increasingly important to IBM’s business, however, the company continues to generate the largest revenue in the industry from its patent portfolio. The lucrative market for intellectual property is more often associated with the “own and protect” mentality of a monolithic innovation model than a collaborative one.
Viewed in this way, the challenge for large companies becomes clearer. Large companies span both pillars of this model, and their business includes many examples of different combinations in between these extremes. Both pillars of this model have their own methodologies and business metrics for success. Tension is created when the conflicting approaches from either extreme overlap, such as when patent rights must be valued in a collaborative partnership. Along with these challenges come new opportunities; if a company is aware of these differences and can successfully balance its business by determining when to apply the proper approach and how to form creative teams, they can succeed where competitors might fail.

Conceptualizing Innovation Teams

We note that even within a monolithic culture, innovation cannot exist in a vacuum; research scientists must work with each other to build up the necessary insights required for true innovation to occur. In a properly designed framework, this collaboration is increased and can lead to greater innovation (of course, not all partnerships are successful or well-developed; today many are formed out of convenience, lacking recognition of how they apply in a broader scale). The impact of teamwork has been studied extensively [2-5]; it is the nature of innovation to occur with some context, as illustrated in Figure 2. While the elements supporting tools, processes, or other elements of innovation are the focus of most efforts to enhance innovation, the over-reaching context is often neglected. The context includes elements of culture, education, and business climate, all of which may vary geographically or over time and are traditionally difficult to quantify. Nevertheless, without giving attention to creating a suitable context, innovation cannot flourish.

Contextual measurements are difficult to quantify, though, and it is difficult to manage what you cannot effectively measure. For this reason, poor measurement has been a serious impediment to the effective management of innovation teams. Davila, Epstein and Shelton (4) cite a recent study in which more than half of the respondents rated their performance measurement system for innovation as poor or less than adequate. This has led to lack of visibility, poor coordination, and enormous waste of money, talent, ideas, and other resources. While this is clearly a serious problem with innovation in individual companies, it is even more of a problem in innovation teams, partnerships, and alliances, where innovation spans organizational boundaries and cultures and the management complexity is truly bewildering. Spitzer (6) discusses several keys to transforming performance measurement in teams, or in any broader organizational framework. These include a “context” of measurement that encourages people to discover and reward innovative teamwork independent of short-term value capture, rather than use measurement to support existing preconceptions.

When measuring the impact of an innovation team, it is therefore essential to legitimize qualitative measurements. It is also important to understand how the context can be improved by building up the characteristics of collaborative innovation, not simply by increasing technical or business knowledge. Our study uncovered a good deal of research into team formation, individual achievement, and group dynamics that indirectly supports these assertions. The context is sometimes referred to as the constraints applied to a problem, leading to the observation that innovation proceeds better when it is goal oriented. It has also been observed that collaboration succeeds best when it takes place between peers, with all parties feelings they have a “win-win” situation; context is essential in establishing these roles and relationships. Thus, before we introduce a framework for categorizing different types of innovation teams, we must understand the context that will appeal to the preferences of the next generation of innovators.

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