One of the innovations that happened in the 1990s was to make more money off of innovating upon your company’s business model that innovating further upon the company’s technology. It didn’t take long to figure out however that neither was really done in isolation. In fact the desired state was concurrent innovation on both business model and products and services. Simple model of this is shown in the “Framework for Business Model Innovation” figure.

Driving the Internet explosion in the late 1990s was the realization that business model innovation was often a method to change the productivity of mature organizations. This is shown graphically in the “The Need For How To Do Disruptive Development In Maturing Businesses” figure. Companies in traditional industry segments were looking for innovation products and services as a means to create disruptive or discontinuous change in maturing areas.

Not only was there a need in maturing business segments for new breakthroughs that would build future business, but critical conditions affecting innovation were becoming understood. The six of these critical conditions affecting innovation were: (1) acceleration of change, (2) discontinuous evolution of markets, (3) economic paradigm change, (4) appalling expectations of customers, (5) high cost of R&D., and lastly (6) failure of past R&D projects.

Change through the 1990s started coming at faster and faster rates. This was true not only technical change but also (as companies moved their businesses to the Internet) in the way they went to market. These change also affected the economic paradigm. Previously, a company’s profitability model held that it was only when the company exceeded the product’s breakeven point it started making money on the incremental sales volume. As such it was common practice to do variable pricing in tough economic conditions against the variable cost of products rather than the fixed cost of products. Sophisticated variable volume/variable cost financial models allowed companies to become ever more competitive, but they did nothing to address the underlying need for changes in the overall profitability model of an industry. With the Internet, the fixed cost of running a business dropped dramatically. There was no longer the same need for a corporate infrastructure in plant and equipment that existed in the old Bricks-and- mortar areas. This allowed profitability at much lower sales volumes. The paradigm also changed from the customer standpoint. Customers expected very high quality and most importantly immediate delivery of product. To add further stress to the innovation process, R&D had problems as well. The cost of R&D was doing nothing but going up and the probability of commercial success overall remained the same as it had for decades. Something clearly needed change.

Standing back and looking at the three stages of R&D, allowed individuals to understand what was broken. Three stages are usually considered to be (1) concept development, (2) technology development, and (3) market development. In the 1990s what was happening was that concept development usually didn’t work. The technology development for the most part did work but market development only worked sometimes. This was seen in the overall probability of commercial success. The overall metric in the 1990s for all products taken into R&D, 80% of them failed on commercialization. Many times the technology worked but the market research was insufficient to forecast consumer acceptance. This performance lead to “Fourth-Generation R&D / Innovation” with its focus on really good concept development (characterized at the time as the “fuzzy front end of innovation”). Stated is a knowledge management problem, the four critical aspects Fourth-Generation R&D / Innovation were: (1) managing knowledge assets, (2) targeting dominant designs, (3) leveraging platforms, and (4) managing the innovation process.

Managing knowledge assets for Fourth-Generation R&D / Innovation required defining the product functionality needed for new products and services with clarity. Product functionality had to be stated in the same terms that consumers would use. This deeper understanding of consumer behavior leads to uncovering new dominant designs or architectures that could deliver products or services to consumers. Only after understanding the linkage between what the consumer wanted and the way in which they needed it delivered, could the third element of Fourth-Generation R&D / Innovation really be used to leverage technology and business platforms. Initially the highest leverage was the ability to understand distribution channels and ways to satisfy unmet consumer needs. After gaining that understanding the last step in Fourth-Generation R&D / Innovation was to be able to define the processes for managing innovation as a business process. By the late 1990s this last step of managing the innovation process was fairly well understood. It was targeting the new dominant design in the second step that was the real difficulty.

In getting to the details of this Nonaka and Takeuchi when looking at a knowledge creating company talked in detail about explicit knowledge and tacit knowledge. Explicit knowledge was that which can be expressed in formal language and easily transmitted between individuals. The dominant mode of knowledge in the Western tradition is of this form. Tacit knowledge on the other hand is a personal knowledge embedded in an individual experience involving intangible factors such as personal belief, perspective, and values. The relationship between these two forms of knowledge is shown in the “Relationship between Explicit and Tacit Knowledge” figure.

This figure shows that a relationship between tacit and explicit knowledge is one of a continuous cycle. Knowledge can start in any quadrant but tends to evolve in a very specific clockwise spiral. The finding of Nonaka and Takeuchi was as it goes in a clockwise manner and not in a random pattern. They provided an example starting in the lower right-hand quadrant where people are thinking about scenarios from observations (scientific observing) and create value by making decisions. This often involves to the scientific method or problem solving process of building of prototypes to test values and scenarios. From this the processes moves to the upper left-hand quadrant where personnel engage in dialogue, testing the prototypes in field studies, and thus create user experiences. In method of scientific problem-solving is one of analyzing and observing and creating a new hypothesis which leads back to the first step in the lower right-hand quadrant. Most technical people are trained in the scientific method or problem solving, but not necessarily to think of it as a model of transferring explicit to tacit knowledge backwards and forwards. Additionally, Nonaka and Takeuchi’s understanding that market knowledge or understanding of consumer’s behavior was also best described and handled by a similar model.

Another key element of this model is the relationship between explicit knowledge and tacit knowledge with respect to both individuals and groups. For individuals it’s tacit knowledge that dominates. In fact the ratio of explicit knowledge to tacit knowledge in individuals as been estimated to be approximately 1 in 99 or 1%. This ratio can be observed in some television reality shows about adults not knowing much more than a fifth grader. Most people have a good understanding of their personal beliefs, perspectives and values and a very poor understanding of the tacit knowledge or history that exists in the world. It turns out this is a similar ratio to that found in groups. Tacit knowledge in groups that is related to culture far outweighs their explicit knowledge related to policies and procedures. A look at the behavior in organizations like the military or utility corporations which have large policies and procedures shows it is often the case that people are driven off of the culture and very rarely know what is in the handbook.

Important to managing innovation is that people typically have an intuitive feeling about the talents and knowledge required on how to do things, but very poor understanding of the explicit knowledge to do them. This is shown conceptually in the “How to Get From Knowledge to Action” figure. The wavy lines on the right-hand side of this graph talk about the performance gap between knowledge and action.

The key in the “How to Get From Knowledge to Action” figure is that most technical and market research people are trained in obtaining data and converting it through filters to information, along with combining that information with their own and group experiences and theories, to create a body of knowledge (either explicit or tacit). The trick to success in development of new products and setting of strategy is to use architectural capabilities to bridge the performance gap. These architectural capabilities are often very weak are poorly understood in most organizations. It was the elements of Fourth-Generation R&D / Innovation in planning around architectural capabilities that lead to the understanding that in addition to product development projects, there should be also be projects around understanding the overall architecture and the way in which a business system operates. Product development is tightly coupled to the architecture and capability development, which in turn is coupled very tightly to strategy development. A feedback loop of course needs to occur as well. This is shown graphically in the “Intervening Architecture And Capability Step In Strategic Plan Development” figure.

The insight of Fourth-Generation R&D / Innovation was the fact that an intervening step of architecture and capability existed between product development strategy developments. Up until that time it was just strategy driving product development and vice versa. In some ways it could be argued that the value chain analysis described previously in this book accounts for these elements. That is true, but very few individuals really realize the importance of understanding that value chain in the terms of how industries, markets, and organizations were coupled to one another. Even less so was how industries, markets, and organizations were coupled with a dominant design or method of doing business. The evolution of the dominant businesses design changes over time and people were up until the advent of Fourth-Generation R&D / Innovation were not taking such into account in strategic planning processes. Utterback put it in a graphic form shown in the “Evolution of Value Chains / Dominant Designs” figure.

Utterback was able to show that the dominant design usually starts with architectural capability. Innovation management is how a whole system of bringing a product and service to market is done. The conceptual model involves putting it into practice platform innovation, followed by specific product innovation, followed by specific process innovation. The advantages of planning and executing innovation this way will be shown further when looking at the intellectual property elements of strategic planning.

In the “Evolution of Value Chains / Dominant Designs” figure the evolution of architectural capability and platform innovation precedes product innovation. A rupture or breakthrough occurs in the dominant design when a completely new way of providing a product or service to individuals or companies occurs. Usually the rupture occurs because people are able to get to a basic core human need and satisfying it in a completely different architectural way. The reason that it may have taken until the 20th century to come up with this understanding was the fact that until the advent of the Internet the growth and the frequency of ruptures occurring in industries was not high enough for people to observe the behavior and understand what was really happening. Translating this observational capability into an organization requires such a capability within the organization. Therefore within a strategic planning group, integration of changes in consumers, technology, processes, practices and tools need to be incorporated. From a holistic strategic planning standpoint, an investment in increasing knowledge (capability) of the people within an organization has to occur. Another way to do this is of course to tap outside resources effectively. Innovation planning needs to incorporate not only new technical know-how and improvements in standard R&D practices, but also to integrate legal or intellectual property into that understanding. Processes and practices need to be understood at all three levels: global, industry segment, and company architecture. Also improved information systems and physical layout of organizations are needed.

In Fourth-Generation R&D / Innovation reassigning where the capability to identify and articulate change is developed ranges from research and development to operations. In defining such roles: (1) R&D defines the new architecture and capability overall. (2) Development defines the architecture and capability with respect to the development of specific products services and distribution platforms. (3) Operations define where new platforms can be applied to product families, products, services and distribution systems for business results. Innovation thus occurs in all three organizational roles within a corporation. The important element derived from Fourth-Generation R&D / Innovation is that one must invest much more heavily in advanced marketing intelligence than one ever has in the past. The second element in Fourth-Generation R&D / Innovation needing attention is to also incorporate the effect of intellectual property changes on technology, operations and marketing. Strategic technical planning requires thought about changes in strategy in a more integrated way. The “Forces Shaping Commercialization Strategy” figure shows some of these elements.

In this “Forces Shaping Commercialization Strategy” figure the ongoing changes in strategy need to account for changing technologies, changes in the complementary business assets, changing customers, and changing competitors. More on how to run an integrated strategic planning process taking into account all these elements will be discussed later in the book.

Up to this point the methodologies center mostly upon products in the form of physical things sold to consumers. Products also can relate to what is most traditionally called services where new service innovation is a key element. This is particularly true in computer gaming, financial services, and other virtual offerings. Robert Cooper and Ulricke de Brentani looked for similarities and differences between elements of successful strategic planning for products and services. They found the key factors separating new product winners from losers were (1) a strong understanding of users’ needs, (2) a strong focus on marketing or launch advertising promotion, (3) efficiency of development, (4) effective use of outside technology spread through internal scientific communication, and (5) seniority and authority of responsible managers.

Upon studying this further they found that there were actually eight elements that usually predicted manufactured product success in the market. These were (1) Product advantage. That is product superiority or unique benefits for users’ in product quality and value for their money. (2) Product definition. Here’s the reason for doing good strategic planning is a well-defined product and project prior to the development phase increases the chance of commercial success significantly. (3) Quality of execution of technological activities. Not surprisingly technical assessment, R&D, in-house tests and trial production done in a high-quality manner outperform projects were this was haphazard. (4) Technical synergy. There was a strong match between the needs of a project and the skill level of the personnel involved, both in technology and manufacturing environments. This has to do with the capabilities fit in the Star diagrams mentioned above. (5) Quality of execution of pre-development activities. Culinary market and technical assessments, marketing research, and business analysis all play a role in making sure the product will succeed not just out technically, but on commercial launch. (6) Marketing synergy. A strong match between the needs of the project and the firm’s sales force, distribution, advertising, promotion, and marketing skills clearly improved the probability of success. This has to do with making sure complementary business assets such as a training of the salesforce or distribution system linked to what was actually being developed. This relates to the position on the “relative cost / relative performance curve” to make sure that the new R&D product R does in fact match the capabilities of the company to market and distribute it. (7) Quality of execution of marketing activities themselves. This has to do with excellent market research, user field trial test markets, and market launch. As described above in the Fourth-Generation R&D / Innovation section, this needs to be understood with deep insight. (8) market attractiveness. Clearly large, high need, growth markets are much more attractive than ones that are not. The margin for error in growing markets is also much larger so the probability of commercial success in these environments clearly better too.

Cooper also found that the probability of success with respect to financial service products was found to be eleven in number. The comparison between the success factors as shown in the “Comparison of Success Factors for Products Versus Services” figure.

The number one factor in predicting the success of new service offerings is synergy. There needs to be a fit between the needs of the product and the resources, skills and experiences of the company. Areas were synergy must exist is between the company’s existing service delivery system, the firm’s expertise in human resource capabilities, the behind the scenes production operation’s facilities, the management skills and preferences, marketing research capabilities and resources, the company sales and promotional capabilities and resources, and the company’s financial resources. Said another way and drawing upon Knowledge Based Organization benchmarking conducted by the Industrial Research Institute showed that companies that forgot about the capabilities of a sales organization (in being able to market a new product) oftentimes lead commercial failure even though technical success was achieved. Doing strategic planning and taking into these elements is clearly important. When quantitative benchmarking was done, projects that had high levels of synergy were successful 85% of the time whereas lack of synergy resulted in failures 79% of the time. The latter statistic mimics the traditional product failure rate of only 20% of products succeed upon market introduction when the technical success was achieved.

The second factor in predicting the success of new service offerings is the degree of product and market fit. Is important that the service meets customer needs and wants. More specifically, satisfying customer needs means responding to important changes in existing customer values and operating systems. Said another way the first factor in success looks at a company’s capabilities, whereas this second factor makes sure that when one looks through the e4yes of the customer that same degree of fit is present.

The third factor in predicting the success of new service offerings is the execution quality of the commercial launch. The advent of Internet-based companies clearly shows this to be the case. Companies with poor user interfaces stumble badly. Having a quality launch means that: (1) the service has been fully tested prior to launch, (2) that there are no bugs in the product, (3) that the lunch program plan was highly detailed and well documented, (4) that service personnel have received extensive training and are ready for any questions that arise from customers. This means that in large companies a formal promotional program has been designed, implemented and tested via internal marketing, and (5) that the service has the well promoted to front-line personnel so they know the true features and benefits of the new offering.

The fourth factor in offering services versus products is how critical it is to be a unique and superior product. In some ways this is the same as what is true for a manufactured product but the degree of commercial success depends even more on having clearly unique and superior benefits to users, providing better value than previously available services, having superior service outcomes than competitors, offering higher quality, delivering faster, being more efficient to use, being more reliable and having a higher-quality image.

The fifth factor was that the quality of execution of marketing activities was also important. To some extent a strong market orientation reflects the same factor for product innovation, but there are also other ingredients. Many services require consistent definitions, user friendly website design, and similar user experience on web and mobile applications. This needs to be consistent with what was detailed in the in-depth market study and product launch documents.

These five elements were the dominant ones in making sure that a new service offering would have impact. The six secondary factors were important but not as important as the first five. These are in order: (1) Having a service expertise in the company. For example, having skilled people in both the frontlines as wells in operations and production areas. Also important were (2) market size and growth, (3) the quality of execution of the technical activities, (4) the quality and execution of pre-development activities (formal ideas screening / concept testing with customers financial analysis), and (5) market research and use of the drawing board approach. The quality of the actual service delivery was found to be important. A high-quality delivery created a new service advantage of 1.5 times as successful as those that had a so-so perceived quality of service delivery performance. The last factor is present in both service and product offerings.

More important in service offerings is that there is tangible evidence of past success. For most products, people can pick the product up, look at it, determine whether they want it or not, and understand what they are getting for their money. Services on the other hand are much harder to describe. There is no way to look before you buy. Therefore references and other tangible evidence that helps enhance or makes visible to customers the service quality tends to create more successful products.

In the Star diagram methodology described above, modifying the major axis and decision matrices with the factors important to service offerings is one way to make the decision process robust for multiple projects. Making such modifications is straightforward but critically important if the company’s future growth is dependent on services.

Research on strategic planning for technology and service offerings was also conducted and reported by Bruce Walters and Richard Priem. What these authors discovered was that organizations that were focused on being different from competitors and achieved higher performance from differentiation tended in their strategic planning to pay more attention to the external environment and less to the internal environment. In contrast those organizations that were focused on being cost leaders in their field paid more attention to the internal environment within their organization and less attention to the external environment.