Innovating R&D Innovation

Innovation has become recognized by organizations’ executive management as a mean of creating and sustaining a competitive landscape for coping with the requirements of the new millennium. Most companies have a formal in-house process to manage both the downstream and upstream parts of the business. However in most firms, innovation management is still lacking. This reflects management’s fear of stifling what is still often perceived as a soft and intangible factor combining creativity, knowledge, learning, and culture (Ahmed and Abdalla, 1999).

Nearly two-thirds of the respondents to a recent survey of 1,414 managers and employees said that their organization does not use more than 50% of their collective brainpower (Kepner-Tregoe, 1999). The barriers to thinking cited in the survey, such as lack of a disciplined systematic thinking process, time constraints, lack of involvement in decision making, insufficient information and training, and fuzzy rules and responsibilities for decision making, provide a good set of targets for organizations seeking to liberate the thinking power of employees at every level.

Implementing an innovation program or any other change is a formidable and extremely difficult task, and in most cases change initiatives tend to fail. Out of hundreds of corporate total quality management programs studied in the United States (e.g., Arthur D. Little and McKinsey & Co.), about two-thirds grind to a halt because of their failure to produce the hoped-for results. Reengineering failure rate is estimated to be somewhere around 70%. More than 50% of 100 top-management-driven corporate transformation efforts did not survive the initial phase, few were very successful, and a few were considered complete failures (Senge et al., 1999). It is widely accepted that coming up with radical innovations—in contrast to the improve-the-widget approach that dominates R&D—is an elusive process that can span decades (Port and Carey, 1997).

The success ratio of new products is similarly very low at best. Out of 24,543 new products Ernst & Young and ACNielsen researched, only 539 were innovative and just 33 were real market successes. Based on Prime Consulting Group’s categories (i.e., product’s sales trend over an extended period of time, adjusted for the introductory period), data for all new products showed that only 1,100-1,200 products could be considered truly new. From those, only about 33% weredeemed to be successful, 42% were still in distribution but with declining sales, and 25% had failed (Adams, 1997; Hoban, 1998). The U.S. food industry is beleaguered by the widely held “myth” that of the approximately 20,000 new food products introduced annually, more than 90% fail (Connor and Schiek, 1997; Hollingsworth, 1996; Mathews, 1997). Similar failure-rate figures have been reported by others (80% in the past decade, reaching a peak of 91% in 1989; Hollingsworth, 1994). It is worth noting that there are an estimated 1 million standard stocking units (SKUs) in the U.S. alone. An average supermarket has 40,000 SKUs. Yet, an average family gets 80-85% of its needs from only 150 SKUs (Trout and Rivkin, 2000). These figures clearly highlight the pressure on new product development.

Thus, businesses do not have a very good track record in sustaining significant change. The barrage of new products, not many of which are revolutionary, has left the consumer confused and less loyal (Byrnes et al., 2000). To improve this unsatisfactory performance, Saguy and Moskowitz (1999) suggested a paradigm shift to successfully cope with the immense risk and high failure rates of food product development, and the resulting necessary but ever-increasing cost. That shift involved “higher-order” involvement of consumers in the development process: consumer data drive ongoing development and act as the yardstick for final acceptance. Hence, the paradigm shift meets consumer expectations and addresses real and perceived quality attributes; it has been defined as “total consumer compliance.”

Linnemann et al. (1998) proposed a similar approach, using consumer-oriented development. It suggests a conceptual model for translating consumer preferences and perceptions into desired technological developments based on a systems analysis. The analysis is initiated by classification of future consumers and the major technological changes facing the food industry, in relation to future consumer demand. This stepwise approach can be used as a tool to direct strategic investment in product innovation.

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However, the paradigm shift in consumer compliance is only one dimension of a much more complex and immense problem defined as innovation. “Innovate or die” (Abraham, 1999; Darlin, 1997; Drucker, 1999a) has become the rule of thumb in all aspects of all industries, particularly in the food industry. It is even more critical for corporate R&D to innovate its practices to keep up with the intensified competition in the marketplace, maintain its alignment with business strategies, and be closer to the consumer. The notion that only “old” or established brand names (e.g., Coke, Nestlé Nescafe, Cailler chocolate, Heinz ketchup, Hershey bars, Pillsbury dough, and many others) will survive is far from reality when one considers the countless new products that are carving their own territory and have inflamed the battle over shelf space. It is important to note that although incremental improvements are essential to competitiveness, only breakthroughs furnish the foundations for new markets and future growth. The next so-called “differentiate or die” stage (Trout and Rivkin, 2000) is an extension of this concept. Innovation is showing up in the way brands are valued, explaining why some of the fastest-growing brands are Internet companies (Byrnes et al., 2000).

As there are too many lingering uncertainties for “how-to” hands-on implementation formulas (e.g., Miller and Morris, 1999), this article will focus on the process required to overcome hurdles and barriers that create significant resistance, to achieve true innovation. Our approach is motivated by the realization that innovation is not about technology per se, but about how to maintain its flow from conception to the consumer (whoever that may be). Specifically, the objectives are to identify typical obstacles, stumbling blocks, barriers, and hurdles that most innovation programs must face and highlight some of the forces impeding innovation effectiveness; furnish an innovation model and suggest a new paradigm that will facilitate the flow of innovation from conception to implementation; and offer specific recommendations.

Innovation
Innovation (a term introduced in the 15th century) is the introduction of something new, a new idea, method, or device. One of its synonyms is change. According to the Merriam-Webster Dictionary, the word novelty, originating from the French word novelet (introduced in the 14th century), means something new or unusual.Innovation can be defined in many quite different ways; for instance, it could mean the creation, exchange, evolution, and application of new ideas into marketable goods and services for the success of an organization. Hence, innovation generates a new game plan (paradigm), which most often implies that some established and encrusted mechanisms are obsolete even when they still provide highly satisfying results (e.g., profit, efficiency, volume) but lack ingenuity or creativity and entrepreneurial ability to implement scientific research and technological innovation. Many other definitions for innovation are available (e.g., www.innovation.cc/articles/definition.htm).

A recent search of Amazon.com for titles containing the term innovation or related topics yielded 1,825 books. This is not surprising since Fortune magazine coined the term “innovate or die” (Darlin, 1997). However, searching the Food Science and Technology Abstracts database from January 1990 through July 2000 gave rather disappointing results: only 443 and 138 hits included the word innovation anywhere and in the title, respectively. Moreover, almost none provided an in-depth analysis or recommendations on how to maintain or build a competitive edge by applying innovation within the R&D environment. These data could be misleading and could portray an incorrect image of the food industry as lacking innovation.

The real situation is that innovation is typically treated in detail in other domains, focusing mainly on management. For instance, Amazon.com showed 2,298 hits for innovation covering a wide range of topics (management, people, process, technology, profit, consumer, new product, competitiveness, creativity, and many others), clearly indicating that innovation is a very appealing topic for many authors. It could be concluded that innovation in the food industry is considered to be in the management domain, and the scarce published data need to be sought in different domains.

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Innovation is paramount in the following cases related to the food industry: cost efficiency in production (e.g., asset base improvements, ingredients); renovation of brands; novel approaches and innovative product development; and new technology, and process development and improvement.

There are many avenues to success, and to failure, and most any one will take us to one of these two places. What makes the difference between success and failure can be concentrated into merely two fundamental and very simple but powerful ideas: a challenge that cannot be met by usual thinking; and upper management’s championship, and sponsorship, as well as a dedicated sponsor. Without the challenge, people do not perceive the need to be innovative, and without the support, people cannot allocate the appropriate resources to improve innovative outcomes. It is paramount to recognize the fact that organizations cannot make mistakes—only the people working in and with them can be held responsible for their successes as well as their failures (Nadler et al., 1999).

To begin mastering our problems, to discover and implement innovative solutions, we must shift our underlying mental assumptions about how to approach R&D topics. The fundamental thinking paradigm (a set of rules and regulations that establishes and describes boundaries and how to behave to be successful) must be reshaped. Nevertheless, because we have gotten so comfortable with using the present paradigms, resistance to change is extremely strong (Nadler et al., 1999).

The foundation of innovation is based on the following premises: solution-oriented thinking; innovation toward the value- creating outside the organization; and avoiding innovation inert, also known as “Taylorized” management, discussed below.

Solution-oriented thinking is based on an input-output-balancing mechanism, actions, and measures. It is concerned with what one gets out, under which conditions and input efforts. Problem-oriented thinking restricts itself to the details of the way (the how) to reach a result, and with segmentation into incremental (in most cases small) improvements. It is time to shift this balance toward concentrating on the solutions and then the solution-after-next (i.e., the solution that will be implemented in the future), rather than to analyze the past and be paralyzed by large bodies of data containing very little information (Nadler et al., 1999).

For R&D, improvements and changes that permit and improve innovative mechanisms have to address these main questions: What is the purpose of the innovation? What are the products and the markets in which innovation will be implemented? How will these products fulfill the needs and requirements of the consumer?

According to Nadler et al. (1999) innovation should focus on:
1. Solutions for the future, not investigations of past problems, consequently reducing “analysis paralysis.”

2. Implementing alternative and more efficient result-oriented methods.

3. Generating a larger solution space, facilitating the utilization of diverse concepts and domains.

4. Enhancing entrepreneurial, creativity, and learning experiences.

5. Providing frequent scientific and technological challenges.

6. Furnishing a continuous driving force and stimulation for improvements.

7. Encouraging personal and team involvement.

8. Enhancing and expanding imaginative and creative solution alternatives and options.

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It is widely accepted that innovation seldom starts from within a company. When it does, its two most origins are serendipity and misguided intent. Hence, most companies rely on external resources for their innovations, rather than on their own R&D organization. This could include relying heavily on consultants, analyzing competitors (“benchmarking”), monitoring consumer and market trends, acquisitions, etc. In our opinion, this perception is only partially true at best. In addition to close monitoring of the external world, innovation needs to grow and be nourished on internal seeds and contributions made by a company’s own R&D organization. It is the duty and obligation of R&D to maintain its position as part of the external domain. Excluding internal contributions could be a weighty error. For instance, it was argued recently that the firm is the principal source of innovation and growth, a device for the establishment of technological competence and its continued development over time. Markets, products, and background knowledge may change quite dramatically over time. Yet, as a result of the cumulative nature of learning in the production processes of firms, the profile of corporate technological competence will tend to persist over quite long periods, provided there is institutional continuity (Cantwell and Fai, 1999).

Management’s Role
It is very clear that management plays a crucial and paramount role in innovation (Lipman-Blumen and Leavitt, 1999). The issue is still the focus of each and every scientific debate. Suffice it to highlight that research management sets the framework to allow science to employ its strength and virtues in the process of reaching the desired goal. It is not the management of the scientific activity itself. This suggests that the origin of difficulties and misunderstandings in the management of science is that management doctrines developed in the 1950s are being employed. These doctrines used the methods of Taylor to organize the work of a knowledge worker. “Taylorism” is innovation-inert, because it is only concerned with improving the efficiency of the work flow and the functioning of the segments (Drucker, 1999b).

The role of management is also crucial in a paradigm shift proposed recently to improve the odds for launching a successful new product, calling for “higher-order” involvement of consumers in the development process required to meet consumer expectations, and the needs to address real and perceived quality attributes. The suggested paradigm shift was defined as “total consumer compliance” and is founded on four main pillars, intimate management involvement being one of them (Saguy and Moskowitz, 1999).

Management goals are changing and evolving with time. These changes are typically driven not by internal needs, but mainly by what is happening in the marketplace. Still, the paradox exists that the changes in the marketplace are not independent of the changes within companies (i.e., a typical chicken-or-egg problem). This circular inference scheme can be broken down into a useful way of thinking when recognizing that the feedback mechanisms are actually part of innovations. Moreover, it is not even necessary to have this term at hand to give the following two examples, which amplify these changes: Ford’s innovation was to make automobiles affordable for everyone through mass production. Amazon.com ’s innovation was to influence a reader’s (consumer’s) choice by critics, sales numbers, and useful information on content and impact of the book through interactive Web format and hypertext. This has led to a new approach to handling information known as “data mining.”

Several well-known pitfalls or “management traps” should be mentioned concerning R&D:
The “Smart-Talk Trap.” Many companies have fallen into the so-called “smart-talk trap,” also defined as the “knowing-doing gap.” This trap stems from the lack of understanding that there exists a gap between the comprehension of the necessity of change(s) (e.g., innovation, restructuring, etc.) and the actual realization of these changes. Management studies have reported these traps, but as yet no fundamental explanations have been provided which go beyond trivia (related to middle-management resistance).

For instance, the gap appears to depend on the management lingo prevailing in their everyday dealings with company events. The broader the scope of the activity (e.g., covering more than one department in changes), the more the lingo is general, cliché-laden, and catchword-ridden. This state is dependent not on the intentions of managers to impress (“wiseguy” effect) but on the highly segmented specialization of the parts in a modern company. Small companies have a lower incidence of “smart-talk trap” disease (Pfeffer and Sutton, 1999). R&D organizations need to avoid this pitfall completely. Relying on fundamental physical and scientific principles is one possible solution.

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Length of Command. This also has a determining aspect. Indeed, the number of layers is always under scrutiny, and every organization tries to reduce it. Nevertheless, this topic was neversuccessfully resolved and remains one of the key issues that each restructuring program addresses, most of them failing. The debate on the role of the dual ladder (scientific and managerial) for R&D has still not been resolved. However, there is a symbiotic relationship between the two mandates that R&D and management should, in addition to their traditional and fundamental role, communicate freely on scientific grounds. More important, they need to provide leadership in identifying future needs and outline the objectives. Unfortunately, there is no “Yellow Brick Road,” so this role is quite risky, explaining why so few begin this expedition.

The “Kublai Khan” Effect. This also fosters the “smart-talk” trap because the CEO and top management have less and less direct access to information. The filtered (“kublaikhaned”) information is used for decision making, and the result of the decision is passed down for implementation. Again, a small R&D organization with a short line of command typically has no such problems.

Research and Innovation
Scientists are taught to keep a very rigid protocol of hypotheses, experimentation, validation, and verification, followed by testing and retesting to ensure that the hypotheses were indeed correct and that the theory used adequately describes the system at hand. This approach is necessary to guarantee that treatment-caused change is inferred correctly. Experimental design, statistical analyses, and critical assessment of the data, which is based on past knowledge, is widely applied. The major purpose of science is to develop laws and theories to understand, explain, predict, and control phenomena. Observations are interpreted in the context of a priori knowledge. What one sees depends on both what one looks at and what previous visual-conceptual experience has taught one to see (Kuhn, 1970). Yet, innovative thinking requires breaking up the a priori knowledge and eliminating invisible barriers that may exist to be able to envision what is beyond the horizon. Hence, it seems that there is a paradox between these two approaches. However, every novice scientist competing for a scientific grant knows that to improve the chances for funding, the hypotheses should include a vision stretching beyond merely assembling the known information to date. It should include an innovative segment that could bridge over the known and reach into uncharted territory.

The really difficult issue is how one forgets the boundaries set by our own existing knowledge to quantum leap over the perceived barrier or hurdle. One approach is: “If you’re serious about innovation, you have to get serious and systematic about forgetting” (Peters, 1999). We strongly disagree. Innovation is a way of life at countless R&D sites, where researchers have realized that it is imperative to demolish the invisible and most often imaginary constraints they have imposed on themselves. Another way of looking at this issue is to “abandon yesterday,” or organized abandonment (Drucker, 1999b). Forgetting has nothing to do with R&D or with this process. It could, however, relate first to overcoming what has been coined as “the paralyzing fear of previous failure” (Prather and Gundry, 1995). This fear prevents one from solving problems and discovering real innovative solutions. Second, some of the most innovative discoveries happened by accident (e.g., aspartame). Nevertheless, they were discovered by scientists who, instead of forgetting what they knew, extended themselves and integrated their scientific knowledge in various domains. Hence, innovative solutions and structural research are not two contradicting poles, as long as they are allowed to compensate for, fertilize, and nourish one another. This coexistence unlocks the doors of our thinking boxes (i.e.,prison) formed by logic and unstatedassumptions (Prather and Gundry, 1995) and allows us to search for creative solutions to the right problem. The real issue is, therefore, identifying the true problem and the purpose for which we need to solve it.

Innovating R&D Innovation
When business performance is good, market strength is acceptable, and shareholder value is satisfying the analysts, some companies begin to relax their pursuit for innovation, ultimately affecting their future performance (e.g., IBM, P&G, H.J. Heinz). This is exactly the time to seek out new ideas, to scrutinize and examine the mode of operation and ways of thinking, and to reinvest in innovation. This will ensure that the company is not moving toward a hibernation phase and doomed to face stagnation, which could be devastating both intellectually and commercially.

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Driving Force for Innovation. First and foremost, one needs to ask the fundamental question, why do companies need to innovate? Is innovation an R&D role and/or responsibility? To date, there are many that accept the phrase “innovate or die” or that without a constant flow of ideas, a business is condemned to obsolescence (Hargadon and Sutton, 2000). Yet, how is one to guarantee that this is not more “smart talk” or another buzzword? To address these key issues, a wide spectrum of reasons have been offered. The common thread linking many can be portrayed as the need to optimize a profit function. Every innovation program needs to ultimately furnish an increase in a profit function that can either be tangible or take another form, such as increased market share, expanding consumer base, perceived value or image, consumer experience, etc.

The profit function should be considered in a multidimensional space; however, for ease of visualization, it can be envisioned in two dimensions—delivered cost and perceived value (Abell, 1999). While delivered cost is self-evident, consumer-perceived value depends on a wide gamut of different factors (e.g., quality, value per price, convenience, needs, satisfaction, taste, experience) and can play a very significant role. Innovation could, therefore, contribute to each of these main dimensions independently, or by some other, more complex relationship.

In this multidimensional space, each product or service can be described based on its specific distance from the origin that normally constitutes a unique characteristic. A schematic presentation (Fig. 1 on p. 180) clearly shows that to optimize the profit function, one can reduce the delivered cost (A-direction), increase its consumer perceived value (B-direction), or improve the profit function (in the vertical third dimension) by other factors, such as increasing market share, volume, etc.

Achieving profit function maximization is sometimes elusive and requires significant resources. Innovation is considered the most straightforward approach. The depicted schematic process also highlights the fact that most companies have no clear idea what path to take. Therefore, it is quite expected that many will take small steps (e.g., line extension, package modifications) until a barrier is reached, or until a preassigned objective is met. This prohibitive and exhaustive search could explain the aforementioned high failure rate of new products in the marketplace. Taking small steps (the zigzag approach depicted in Fig. 1) is normally applied in optimization and is known as the “simplex method.” This method is normally applied in cases where the model is not known, or when it contains constraints. It is also known from classical optimization that a much more efficient approach is to apply other techniques, which guide the search direction (e.g., derivatives). In our situation, this implies a clear need for a business strategy and vision of what and why to innovate, and, as important, in which direction innovation should be headed. The ability to have a clear vision of where one wants to go is not sufficient. Unfortunately, there is not a “Yellow Brick Road” to be followed or to indicate the way. Abell (1999) previously stated that “If you don’t know where you are going, any road will take you there.” Companies need to foresee their innovation target beyond the horizon, and need to devote significant resources to this quest. In other words, they need to redefine their profit function map. However, as there are no guarantees that innovation efforts will lead to an increase in the profit function, and because general management tends to perceive innovation as a threat rather than an opportunity, we quite often see failing programs, frustration, and lack of breakthroughs.

Flow Is Paramount. In a typical traditional company, people with innovative ideas must go hat in hand to the guardians of the old ideas for funding and staffing. On the other hand, in Silicon Valley or at many other high-tech companies, a slew of venture capitalists vie to attract the best new ideas, infusing relatively small amounts of capital into a portfolio of ventures. Talent is free to go to the companies offering the most exhilarating work and the greatest potential rewards. Therefore, it should actually be easier for large, traditional companies to set up similar markets for capital, ideas, and talent internally (Hamel, 1999). In practice however, this is not the case. Often, R&D is stifled by countless visible or invisible barriers, impairing its ability to achieve real innovation.

To overcome these curbing conditions, one needs to develop an innovation process which can be described according to several approaches (e.g., Banerjee, 1998; Baptista, 1999; Cohen et al., 1999; Senge et al., 1999; Yetton et al., 1999). For instance, efforts toward organizational change were recently depicted as a sigmoidal growth curve, characterized as accelerating first, followed by a gradual slowing down (Senge et al., 1999). Yet, when considering innovation, this model is too simplistic, as it focuses on the dynamics or the kinetics of the “reaction” and not on the driving forces, or the impeding barriers that need to be overcome if the process is to be sustained to fruition.

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Kinetics of many reactions can be typically described as differential equations, and some are quite simple (e.g., first-order). However, reality is much more complex, and often results in chaos. Kinetics of the change can be applied when the motion has already started, and, assuming that the energy barriers have been overcome or reduced, the question of what shape and direction the reaction will take can be asked. We need to focus on the changes required for an R&D organization to enhance its capability to innovate its innovation.

Integrating the whole process, from conception to final outcome, provides the basis for the definition of innovation-process flow (IPF). A successful and innovative R&D organization cannot afford a stochastic process. It should not resemble a boat drifting aimlessly with the wind or the stream, or moving forward by using “locks” to provide the energy required to climb above the “height gap” (i.e., overcoming one barrier at a time). It should be more like a military “beachhead” aimed at opening the way for the whole organization. Understanding, maintaining, and sustaining this flow is the core of our approach.

A well-known concept applied in Chemistry 101 concerns activation energy and reaction. The reaction path controls the speed of the response (Fig. 2). The molecules (reactants) follow the path of least resistance, but this path may still require significant energy, known as the activation energy. The ground elevation and its relative coordinates compared to the energy of activation defines the hurdle which has to be overcome for the reaction to take place. To reduce the activation barriers or hurdles, various approaches can be applied, including increasing the reactants’ internal energy by elevating temperature, kinetic energy, and the effectiveness of their collisions, increasing concentration, and others. It is also possible to reduce the barriers themselves by an activated complex, although the overall energy of activation is unaffected. The reaction barrier is defined as the Gibbs free energy of the activated complex. The higher this value is, the smaller the fraction of molecules that can gain sufficient energy from the activated state and pass the barrier. It is very clear that for the reaction to take place, overcoming the barrier is a first and foremost prerequisite. A catalyst or enzyme could change the structure of the activated complex and lower the energy barrier, therefore allowing a higher fraction of molecules to overcome the hurdle and yielding an increased reaction rate. It is worth emphasizing that the reaction rate can be described by its kinetics. The generation rate of the desired product depends on the flow and the side reactions.

This well-known theory of fundamental chemical reaction kinetics is described here, not to refresh our memory of chemistry or reaction kinetics, but to highlight a similar principle and analogy, which is very pertinent to innovation flow (Fig. 3). It should be categorically and clearly stated that no innovation exists as long as the barriers (either visible or invisible) are too high and block or stop the process. It is clear that both personnel and the enterprise, either directly or indirectly, can individually or collectively contribute to the fragile initial steps of idea generation. Personal input is of foremost importance, as are many other things that play significant roles (e.g., risk-taking, entrepreneurship, dedication, assimilation of both internal and external information, responsibility, time load and distress, fear of failure factor). The enterprise includes mainly leadership, vision, strategy, structure, risk, commitment to the process and continuity, core competencies, knowledge information, award systems, commitment to bottom-line innovation, and others. The enterprise interacts with the consumer and should therefore incorporate and assimilate this “bloodline” feedback, as well as benchmarking (Wind and Main, 1999).

Yet, even those ideas that have overcome the initial hurdles need to be championed, and the process needs to keep the floodgates open. In most organizations, these gates generate enough flow resistance to restrain or stifle most innovative ideas before they can reach their destination, where they can establish a “beachhead.” Fig. 3 also shows that both personal and enterprise input play a significant role in affecting the generation of ideas and can also minimize the effect of the hurdles and barriers.

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The essence of innovating R&D innovation is therefore focused on the flow that needs to be simultaneously maintained, sustained, and nourished. If we return to the beachhead concept, it is known from military history that this stage is the most fragile, inflicting heavy losses and casualties. Therefore, it requires significant planning and concentrated resources, as well as top management support. The beachhead is only one operation, and its value can be maintained only if it maintains its hold, allowing the organization to flow through it. People who have personally participated in such a devastating experience know that it can be traumatic.

Innovating R&D can create a similar experience. More often than not, the first wave suffers severe “casualties” and would prefer not to undergo a second experience. In some cases, the ramifications of unsuccessful R&D innovation experiences (unsuccessful beachheads) are not fully considered, and their long-term impact on the human factor is often forgotten. It is highly recommended that every innovative program take into consideration the long-range impact it could have on the participants and their willingness or commitment to undergo similar experiences in the future. As already pointed out, establishing the beachhead is necessary but not sufficient. It needs to be maintained and sustained so that it will enable others to follow until a new line (e.g., frontier and breakthrough) is achieved. If the flow process stops or dwindles to a very thin trickle and the floodgates start closing, the ramifications could be severe, like a massive coronary when the arteries are blocked.

It is worth noting the similarities between organizations and a complex biomolecule, where the forces keeping the system working have been previously described as Van der Waals managerial practices (Kossovsky and Brandegee, 1997). This approach was based on the concept that a company is built on elements which are bonded together, and that chemical models of management appeal to technically oriented people.

Managing Innovation
Innovation flow needs to be managed uniquely for each case, with a new and adaptive structure which will enable the handling of different control styles simultaneously. These are required to nourish what we have defined as IPF. To explain, let us refer again to mathematics, where in some cases it is well known that reversing the process and initially guessing the solution provides a very efficient method of handling both stiff differential equations and two-point boundary problems. Adopting this concept of process reversal furnishes several unique requirements and advantages simultaneously.

First, it means that one needs clear understanding and vision of the final target. Second, already being on the end-target furnishes an opportunity to consider the most innovative path for the process. It also opens new possibilities for assessing the “steps after next.” Obviously, this is a metaphorical exercise. However, this reasoning clearly indicates that innovating R&D innovation implies that management needs to reverse the process, to simultaneously perform two main activities: on the one hand, backtracking and visualizing where the major hurdles and barriers were, so that they do not become stumbling blocks, and on the other hand, searching for ways to bypass or eradicate them. Thus, a proactive role not only maintains the process flow and provides the necessary nourishing conditions to sustain it, but also provides opportunities to apply innovative thinking. Moreover, it highlights the need to start planning and projecting “the steps after.” This process is quite common among chess players, some of the legendary masters being able to plan more than five steps ahead.

The IPF process of innovating R&D innovation should be profoundly different from incremental development; therefore, conventional management techniques are not sufficient, highlighting the need for leadership. This calls for establishing a new curriculum and requirements for research and teaching institutes. Yet, in the interim, one needs to adopt new approaches to nurture and sustain innovation flow. It can be guided by setting soft goals, by evaluating progress with a shrewd eye toward long-range strategy and changes in the outside world, and by creating a climate that encourages bold thinking and risk taking. Management needs to recognize that they are the flow “gatekeepers” and to handle innovation uniquely for each case. This implies a new and adaptive structure, which will allow different control styles simultaneously, where the human factor and its long-term ramifications (e.g., next assignment) are considered. For instance, a multidisciplinary team (“cross-pollination”) could be efficient in some situations, while in others a one-man show could be the only plausible avenue. Far-fetched innovative ideas that call for an entrepreneurial mind can be stifled by a team, are scarce, and can be applied only at the very early stages of the conception.

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Barriers and Hurdles
In a typical R&D organization, some of the most common barriers and hurdles restricting the innovation flow are easily identified (Table 1). They can be categorized into personal, enterprise, and external.

Every hurdle listed can play a significant role in stifling innovation. The two most significant obstacles at the personal level are risk paralysis and an approach that is problem-oriented, not solution-oriented. Each company tries to implement an organization in which employees will be encouraged to value risk-taking. However, very few succeed, while most others fail entirely. Employees ask themselves to what degree it is acceptable for a well-reasoned attempt not to meet expectations when trying something new. The most common answer is that it depends (e.g., on the circumstances). In other words, this is just another of management’s mirages. Risk taking is one of the most important dimensions of the climate for innovation, yet many organizations send mixed signals such as, “Take risks but don’t fail” (Prather and Gundry, 1995). Risk taking on a personal level could mean that people are encouraged to try new ideas with the expectation that only a few will survive the initial stages. Nevertheless, the organization will benefit from these experiments by learning and acquiring knowledge. The value-added learning should be visual and an essential asset of the innovation process. However, it requires management dedication and commitment to enforcing and rewarding this risk-taking effort.

The second personal barrier is as important. We are trained to seek solutions to problems, and all of our training to date has been based on first analyzing the problem and then, only when we understand it, hopefully solving it. That may be the case, but we are closing our eyes to other solutions that are much more adequate for enhancing our capability to be elevated to a completely new dimension or place.

At the enterprise level, the most common barriers are lack of leadership, unclear business strategy and vision, and not adequately rewarding risk taking. These topics have been described previously and are also widely covered in the literature. It is also worth noting that every company knows that the consumer is in effect the most important factor to be considered. There are two main problems in staying “too” close to the consumer: the first is an obsessive focus that could cloud judgement (Brown, 1997), and the second relates to the consumers’ inability to articulate what they want and the fact that what they want is not always what they need.

Methods to link the consumer, the expert, and instrumental measures have been previously suggested to provide information which gives direct, practical guidance to the developer. Today, from the pattern of consumer responses and the product model, the developer can discover what to do (Miller, 1998; Saguy and Moskowitz, 1999). Nevertheless, this topic is far from resolved and has to be carefully considered and assessed. Close contact with the consumer is paramount for any R&D organization, so that it can decipher the collected data and transfer it to usable and valuable information. This fundamental R&D role is still overshadowed by some internal barriers, such as marketing. It is worth noting that being too close to the consumer can also stifle innovation, as indicated previously: if you worship the voice of the customer, you will get only incremental advances (Port and Carey, 1997).

Assessing Innovation
Change is inevitable, and learning from the process appears to be an opportunity for which we have little time. Assessing innovation is a task most food companies are struggling with. Every R&D organization uses a different criterion, which appeals to its culture. Several of these seem to be more widely used and include the percentage of new products developed in the past 3–5 years in the overall company portfolio, 30–50% being considered a very innovative figure. The problem with this method is that small changes, such as line extensions, are also considered. Another approach is to include the number of patents. Again, some patents are never implemented into new products or are linked to the recent activity of the company. Other, more-formal methods are needed.

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One example of innovation assessment is outlined by the Peter F. Drucker Award for Canadian Nonprofit Innovation (www.innovation-award.ca), whereby organizations are encouraged to actively engage in a process of reflective learning, i.e., to look critically and objectively at their work and examine just what it is that they have learned, how this learning is transferable to others, and what this learning tells us about the process of innovation. In a systematic look at innovation in nonprofit organizations, incredible energy and imagination could be still seen. These experiences indicate that effective and sustainable innovation goes through the following seven stages. They constitute an iterative process common among nonprofit organizations seeking to change, innovate, or respond to new circumstances, with the mindset of finding the courage and willpower to undertake some kind of change, even though this may initially be controversial, demanding, challenging, or distressing.

1. Exploring the Environment: looking at new realities, challenges, and opportunities so that the organization has a real sense of its socio-political and socio-technical environment.

2. Synthesizing the Learning: reflecting on the exploration and looking at its meaning in terms of the strengths, weaknesses, opportunities, and threats implied for the organization.

3. Integrating the Learning: developing a clear scenario for the future of the organization, which takes into account the needs of all stakeholders, the need for efficiency and viability, and the need for accountability.

4. Internalizing the Learning and Creating Ownership: going beyond a plan and moving into action in such a way that all who work in the organization feel that they own the process of change and innovation, and have a stake in the future of the organization.

5. Applying the New Learning: implementing the action plan, engaging the organization and its clients in the development of new ways of working, and creating momentum for change. 

6. Reflecting and Checking: making sure the new ways are working, and that some of the valuable practices and thinking of the past are not being lost.

7. Disseminating: sharing learning, experiences, and outcomes with other organizations, and ensuring that the learning itself is understood within the community served by the organization.

These stages are very useful, and some of the principles should be applied more widely. However, when focusing specifically on corporate R&D, they need some modifications. These could be carried out by taking into consideration how the above submissions are judged.

Six key criteria that allow focusing on the challenges and achievements can be applied to scrutinize each innovation program (www.innovation-award.ca):
1. Innovative Practices. This is the extent to which the organization has had to adopt new work practices, new methods, and new thinking to make the project or activity happen.

2. Organization-Wide Impact. This examines the extent of the impact of a project or activity on the organization. Some projects or activities relate to a small part of the work of the organization, while others have a broader impact on all of its aspects.

3. Outcome. This is the impact of the activity or project as expressed by measurable outcome measures, comparing old procedures with a new, more innovative way of working. 

4. Sustainability. This places a higher value on projects or activities which have a strong likelihood of having an impact over time and creating a continuing momentum for change than those innovative projects that have an immediate short-term impact but are not sustainable.

5. Replicability. This measures the extent to which a project or activity can be transferred to another organization. A key criterion for the Drucker award is the degree to which a project or activity conducted in one organization could be and is likely to be transferred to another—what we term “replicability” or the degree of replication possible.

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6. Partnership Building. This is the extent to which the project or activity has created and strengthened alliances and partnerships between two or more organizations in the nonprofit sector or between the nonprofit and private sectors, or between the nonprofit sector and government.

These stages and criteria are very useful, and should be considered carefully when innovation is assessed. However, every R&D organization needs to establish its own criteria to enable continuous monitoring and benchmarking. This is clearly an area that requires further development.

Innovation Techniques
There are numerous formal methods and techniques that can be applied to improving the thinking process to yield innovative ideas. Although a much more rigorous review is needed to do justice to this vast area, only a few are listed here. The main objective is to provide a stimulus that will trigger an appetite.

Lateral Thinking. This process—the generation of novel solutions to problems—is based on the knowledge that many problems require a different perspective to be solved successfully (De Bono, 1992). It identifies four critical factors: recognizing dominant ideas that polarize the perception of a problem; searching for different ways of looking at things; relaxing rigid control of thinking; and using change to encourage other ideas. To represent different types of thinking, De Bono used six colored hats: white (information available and needed facts), red(intuition, emotions and hunches), black (caution, difficulties and problems), yellow (benefits and feasibility), green (alternatives and new ideas), and blue (managing and organizing the thinking process).

TRIZ (from the Russian for “Theory of Inventive Problem Solving”). This is a set of methods and principles that help examine problems and quickly develop many solutions. It is emerging as a powerful tool for inventions and technological breakthroughs. It was developed over a 50-year period, from 1945 to 1995,under the leadership of Altshuller (1984), who worked for many years in the Russian patent office, where he began classifying patents from simple modifications to major innovations. As he studied the most innovative patents, he began to identify the principles that led to the innovation. He also began developing a series of algorithms for solving the most difficult problems. One of the key focuses of TRIZ is identifying and solving the basic contradiction at the root of the problem. This is different from the approach of trying to find a good trade-off. TRIZ is a systematic way of solving the contradiction. It is also useful in reducing unneeded functions in a product, thus reducing its cost and improving its reliability. There are numerous innovative spin-offs of TRIZ, e.g., utilization of inventive templates for new product development (Goldenberg et al., 1999a, b, c; Goldenberg and Mazursky, 1999; www.sit.co.il).

Kepner-Tregoe This solving and decision-making program provides a logical, consistent approach to every situation. It is a proven method that helps people gain control of the situation at hand. It has three major steps—identifying the problem analyzing and finding causes, and decision-making—and several minor steps.

Brainstorming This method for developing creative solutions to problems by divergent thinking works by focusing on a problem, then deliberately coming up with the broadest possible spectrum of solutions and pushing the ideas as far as is workable. During the brainstorming session, there should be no criticism or killer phrases (e.g., it won’t work, we’ve tried that before, they won’t let us, it’ll never fly, are you serious? you’re kidding, no one will go along with it, get real, it’s good but, it’ll cost too much, it’s not practical, get a clue, we don’t have enough people to do that, we’ll never find the time, we’ve always done it this way, etc.). The moderator should be experienced and well trained to avoid many visible and invisible pitfalls. Participants should come from as wide a range of disciplines with as broad a range of experience as possible.

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Ideas must not be criticized or evaluated during the brainstorming session because defensiveness and self-censorship are endemic to this approach. Furthermore, criticism introduces an element of risk for a group member in putting forward an idea. This stifles creativity and cripples the free-flowing nature of a well conducted brainstorming session. Sparking off from associations with other participants’ ideas and developing others’ ideas is critical. Typically, brainstorming will generate 1,000–2,000 new ideas, which can yield tens of quality and potentially tangible ideas when applying post-brainstorming methods.

Post-Brainstorming. There seem to be numerous methods to extend brainstorming and to break or trigger the pattern. They can be categorized into four groups: forcing associations, reversing hidden assumptions, metaphorical thinking, and the “outrageous” idea (Prather and Gundry, 1995). These methods are very useful to converge and focus on the most innovative and plausible ideas generated during the brainstorming sessions.

Cyberspace. The Internet is sparking innovation. For instance, teams (known as “GameChangers”) at the Royal Dutch/Shell Group in the Netherlands rounded up 320 ideas pitched to them by employees’ e-mails. The outcome of this approach was four out of five top business initiatives (in millions of dollars) in early 1999. This example highlights why increasing numbers of companies are using the World Wide Web to stimulate and manage innovation—and to put the brightest new ideas into the hands of the people who can turn them into products the most quickly. It is also claimed that large companies can harness the Web to build idea factories or idea markets, introducing a startup mentality (Stepanek, 1999).

This powerful global conversation has already begun. Via the Internet, people are discovering and inventing new ways to share relevant knowledge with blinding speed. As a direct result, markets are getting smarter faster than most companies (www.cluetrain.com). It seems that more and more companies are finding out that cyberspace is the most useful way not just of sharing information but also, and probably more important, of increasing its knowledge, leading to innovation that is paramount to survival in the emerging forces in the marketplace.

Recommendations
Innovation could be a threat to management as well to “established” brands (Wang, 1999). To reduce this risk and to innovate R&D innovation, the IPF model suggested here highlights some major barriers and hurdles that need to be understood and reduced. It also suggests that every company needs to be aware of the various visible or invisible barriers it is facing, and to implement a paradigm shift that searches for solutions and results that will keep the innovationflowing. Here are specific recommendations:
• Seek to become a pivotal player and a significant driving force in the quest of innovation, in spite of the associated high risk and cost.

• Implement an innovation process flow through a paradigm shift to furnish and sustain adequate conditions to overcome the resistance imposed by actual and imaginary hurdles and barriers.

• Identify, investigate, and thoroughly comprehend innovation obstacles.

• Instigate solution-oriented thinking.

• Apply an adaptive structure management allowing unique control styles simultaneously

• Adopt a “beachhead” mentality to pave the way for the whole organization. Constantly support its moving forward, ensuring that the organization sustains the innovation flow and prevents its blockage.

• Link innovation to a profit function which could be attributed to tangible and/or a perceived value.

• Thoroughly consider the human factor. Establish visible award mechanisms, supporting culture change, and develop long-term programs encouraging individual risk taking.

• Develop methods for assessing innovation and benchmarking.

Heribert J. Watzke and I. Sam Saguy
Author Watzke is Head, Dept. of Food Structure & Processing, Nestec Ltd., Nestle Research Center, Vers-Chez-Les-Blanc, P.O. Box 44, CH-1000 Lausanne 26, Switzerland. Author Saguy is Professor, The Institute of Biochemistry, Food Science and Nutrition, Faculty of Agriculture, Food and Environmental Quality Sciences, The Hebrew University of Jerusalem, P.O. Box 12, Rehovot 76100, Israel. Send reprint requests to author Saguy.

References