- Growth Drives Innovation and Vice-Versa
- Innovation Leaders Feel Pressure to Create Growth
- The Right Quantity and Form of Innovation to Invest In For Growth Is Related Economic Value Add
- A Simple View of “When to Use What Amount and What Form Of R&D
- Growth Can Be Improved By Speeding Projects through The NPD And NBD Pipelines
- Growth Is Not Achieved By Increasing the Pass Rates At Gates In The NPD And NBD Pipelines
- Growth Is Slowed When Freedom to Operate Is Clouded By Increasing Amounts of IP
- Funding R&D without Limit Is Not the Answer
- Growth Can Be Achieved Without Spending On R&D
- Risk From Poor Decision Quality and Speed Are Obstacles to Growth
- Sources, References and Selected Bibliographic Information
It is important to understand the connection between innovation and growth. New ideas create new products and services that grow a company. This growth is necessary because companies borrow money to go into, and to stay, in business. Interest on these loans has to be paid from new revenue streams that innovation creates. Without growth in profits corporations and their management teams cease to exist. The inherent need for continuous innovation gets build right into a corporation’s fabric right at its start.
Using innovation to effectively grow a company is one of the top problems facing R&D entities. Technology Management Trends Surveys conducted by the Industrial Research Institute (IRI) from 1990 to 2007 consistently show that using R&D to effectively grow a company as one of the top problems facing R&D leaders. The “Five Drivers of R&D” figure shows the drivers that CEO’s placed on their R&D leadership.
In the chart, the early 1990’s, activities related to measuring and improving R&D by reengineering efforts was the dominant factor. They shifted to a focus on service and speed in R&D through the mid-1990’s as shown in the second row. The top row, growing business through innovation, has always been large and continues to get larger as companies compete on the basic value of the new products and services they bring to customers and consumers. This survey is based on polling the industrial research Institute’s membership of over several hundred US corporations. These corporations account for some 60 to 75% of all US industrial R&D spending. The leaders of these organizations clearly see, and feel the pressure from their CEO’s to grow the business through innovation. In no uncertain terms “growth is clear driver coming from business leaders”.
Procter & Gamble’s CTOs through the years have been quite frank in describing their role at the company. At the CEOs direction, they understand that the success of Procter & Gamble hinges largely on the productivity of the R&D organization and its ability to develop breakthrough innovations. These new products are to delight consumers around the world. Innovation provides consumers benefits that they value, and from their adoption of new products, Procter & Gamble benefits from sustainable growth in both market share and profits. Without this growth the financial underpinnings of the Corporation would crumble.
Although the need for innovation is built into a company’s strategy at its birth, the right quantity and form of innovation varies. The quantity and dominant Form of innovation required for business success can be superimposed on a market value and economic value map as shown in the “Quantity and Dominant Form of Innovation Required” figure.
Important in this graph is that new startup companies or stage one disruptors are created with very high market value added per capital. As startups they have no financial capital to work with and what they’re doing is rapidly increasing in market value. As individuals working in a garage build a business and build the ability to attract capital the move to Stage two. This is the growth phase where the active innovators are building out their business, geographically expanding it and going into additional market segments in building out their product lines. Stage three is the rebuilding phase where increasing amounts of capital have been added to the corporation to build up the distribution and manufacturing facilities, sales organizations, etc. The economic value add is relatively high on such capital but we see that the market value add is starting to drop off as growth occurs, both because the money capital is increasing as well as a rate of growth is starting to decline. The last stage for industrials is really having very little economic value added per capital and low market value add per capital. For industries in their mature phase it is very difficult to grow the businesses that has become a commodity. Both economic and market values are difficult to come by. Also the capital base here is typically large dragging their performance down. As one can see the appropriate focus and distribution of R&D funding between product and process (capital reducing) programs changes as companies move through this cycle. Far too often R&D, marketing, and IP have initiatives based on where the company was, not where it is going.
A simpler means to look at the right quantity and form of New Product Development (NPD) and New Business Development (NBD) is to follow the path of the arrow shown in the “Quantity and Dominant Form of Innovation Required” figure. Transforming the arrow from a line which is going from market value add per capital and economic value add per capital and looking at it as a time sequence in the growth of most corporations, transforms the figure into a company’s or industrial segments’ business maturity S-Curve as shown in the “Simple Business Maturity S-Curve” figure.
Matching the R&D investment to the Business S-Curve has been shown in many ways. In Strategy & Leadership, elements of NPD as a function of market type are highlighted as shown in the
“Market Characteristics” figure. Early in the product adoption lifecycle a “single market” is present. Midway through the product adoption lifecycle a “multi-market proprietary” environment is typical. Finally late in the product adoption lifecycle a “multimarket commodity” environment exists.
Thinking about this in more detail, early on the S-curve a single market situation is present. This is characterized by a few early key customers. Having solid technology and a good understanding of the product technology roadmap is critical for success. The center part of the S-curve is characterized by multi-market proprietary driven entities. Since the market is growing they’ve now attracted thousands of customers. New product development is driven by both the market and competition. Each product design and intellectual property management are critical to success during this phase. The last phase of the S-curve is in when there is a multi-market commodity environment. Thousands to tens of thousands of customers exist for companies participating in this field. Price, delivery and quality are key drivers. Product development is focused on the cost and new incremental functions that have been validated for customers.
This translates into the type of innovation that’s required for each phase of the S-curve. Early on its disruptive innovation which is really about reinventing an industry and oftentimes the innovation focuses on the business model. In the intermediate part of the S-curve it is really about next-generation innovation where reinventing the category and making large changes in the product or service offering are key. In the final stages of the S-curve it is really about incremental innovation. You’re refining the product or service and streamlining the execution of manufacturing and delivery operations is often the source of innovation that creates value for the Corporation.
Said another way, the “Innovation Types along the Business Adoption Lifecycle” figure shows the challenges and type of innovation associated with each position along the Business S-curve. Of note is that the innovation focus and amount of leverage shifts accordingly. This summarizes the basis for and logic behind funding NPD at different levels in different industries that are located along the business lifecycle.
Another way to see how NPD is leveraged differently in industries along the product adoption lifecycle curve is shown in the “Impact of Non-financial Criteria on Corporation Share Price” figure, developed by Ernst & Young. The Criteria or Points of Leverage for changing a corporation’s share price are listed along with the summary of key leverage points.
It’s important to consider such nonfinancial criteria when making good decisions about how to fund new product development. It is early market and midmarket companies that can leverage new product development the most. The form of intellectual property dominantly used in these phases of the lifecycle are copyrights and patents. Later in the product adoption lifecycle, in the mature areas, the forms of intellectual property usually found to be of most value are trade secrets and trademarks as shown in the “Use of IP along the Business S-Curve” figure.
As will be more fully discussed later note that the need for freedom to practice occurs all along the lifecycle. The ability to exclude another comes immediately with creation of intellectual property rights but this capability is best conducted only after the chasm is crossed. (For a definition and description of the dip in the S-curve see the book on “Crossing the Chasm” by Geoffrey Moore.) The ability to create additional revenues for a Corporation from out-licensing one’s technology is often found for corporations that have large acquired portfolios operating in the mature, late stages of the adoption lifecycle.
An example of a typical R&D pipeline is shown in the “Number of Ideas that Succeed at each New Product Development Gate Review” figure. Along the bottom are the stage gates through which new businesses and new product development programs pass.
In this particular model there are seven stages in the stage gate model. The vertical scale shows the number of projects or programs launches and commercial successes the company achieves in each gate in this process. This starts with several thousand ideas that thin out to produce just one commercialization. Evaluation of pass NPD success rates have been conducted in many different industries. Passing rate numbers have held up roughly the same for most studies. The numbers shown here relate to work done in the 1990s and early 2000’s. In the 1980’s early work done by Booz Allen & Hamilton showed higher passing rates. They found that for every successful product commercialized, 11 serious ideas or concepts were needed, three would move ahead and enter development, followed by 1.3 being launched into the market.
Increasing the velocity down the R&D or new product development pipeline is possible. In fact acceleration down the new product development pipeline is exactly what integrated technical, business, and intellectual property management is all about. Acceleration comes from five sources. They are generally classified as: to simplify, to eliminate delays, to eliminate steps, speed-up, and parallel processing. R&D, manufacturing, marketing, and intellectual property all have roles and activities in each of those five areas. Working together they can speed up the overall process significantly. Work in the 1990s showed that in large companies, with formal stage and gate processes, cycle times could be reduced to a third. In the open innovation chapter later in this book we talk about ways to use outside resources to speed the process even more. The “Methods To Speed New Product Development Phases” figure shows a simple matrix of how this works. It is adapted from the 1992 work of Marie Millson, Espey Roche and David Willman published in the journal of product innovation management.
Important to a discussion at this time are some of the comments that show in the research and development column. It is important to generate explicit R&D goals, to link the R&D goals to the manufacturing capabilities and marketing goals, and to protect it all with intellectual property. Generating specific R&D goals may sound easy but more often than not companies struggle with finding things that are new, that are consistent with their corporate vision, mission, and values. Many times this is because they keep a narrow view of their market and core competencies. The old story that if the railroads viewed themselves as transportation companies instead of railroads, they would have been the leaders to use trucks on the growing interstate highway system and expanded into the airborne parcel transport systems that have since evolved. Such a restatement of their vision would have allowed them to capture many new markets and growth opportunities. Covered in this book in the section around creativity we will describe many ways that a company can use to expand its vision of what it could be.
The “First Mover Advantage” figure takes us in a different direction. It points out the real advantages of being the first mover. This came to the forefront in the dot.com area in the late 1990s. In that environment it was clear that the first company to offer a product was the one that would take a significant portion of market share.
This work was done at the Iacocca Institute at Lehigh University. What is unique about their work is as they were able to show that the first mover advantage depended upon the market window of opportunity. This figure shows why it was so hard for established companies like Procter & Gamble or airframe companies like Boeing to think of their business the same way as dot.coms. There was a lot of frustration in traditional companies as they tried in vain to increase the cycle time of their new products. When they launched products sooner to the market they found that they didn’t get a corresponding first mover advantage to the same extent that was found in other industries with smaller market windows. It was frustrating to say the least. From an R&D management standpoint this chart is valuable in that it shows the pace at which you need to consider launching a new product. Putting excess resources onto a new product development in order to gain a first mover advantage were the market window is long really has limited payback. On the other hand it also shows the disadvantage that a company has when they come to market late. Clearly R&D, marketing and IP management needs to pay attention to the amount of resources that will be applied to a project to make sure that the project’s time to market is consistent with obtaining a first mover or fast follower advantage. As we will see later, funding and resourcing projects depends on two things (1) when you want to come to market and (2) when do you want to file your intellectual property. Taken together the “market window of opportunity” and the “intellectual property window of opportunity” are what drives resourcing decisions.
If it were possible to easily improve the chance of success in each of the gates of an R&D pipeline as shown in the “Number of Ideas that Succeed at each New Product Development Gate Review” figure, the issue of how to improve our product and service offerings and achieve much larger company growth rates would be pretty simple. With much work over the past decades organizations have in fact improved somewhat on this passing rate.
However after lots of effort, the overall shape remains the same. Market research, technical research, and intellectual property research is all conducted because an organization is trying to do things that have never been done before and therefore the probability of the idea having merit unfortunately diminishes as this plot shows. When companies have tried to improve the pass rates, most organizations achieve that goal, but in looking critically at what happened, those companies in retrospect understand that what they’ve sent down the pipeline were incremental projects versus the hoped-for next-generation or breakthrough programs that they were banking on. In later chapters we will talk about how to improve the success rates but clearly there is no silver bullet. The fact remains that just trying to run more projects down this pipeline with higher success rates does not allow us a simple solution to the problem of growing our company rapidly
Up until the 1990s most corporations grew by way of using internal market, technology, and business development resources. It was always a challenge to run them in a way that would make sure that the company’s growth was supported by new products and service offerings. In the 1990s however things changed. For successful Internet dot.com companies market value increased radically. Dot.com startups started building market value equivalent to Fortune 500 companies in just a few years. One of the dilemmas faced by large company CEO’s, COO’s and CTO’s was how to meet shareholder expectations in such an environment. Why should large pension funds and individual investors alike continue to invest in the Fortune 500 bricks-and-mortar companies when they can make more money quicker with dot-com’s. This environment forced large Fortune 500 companies to start promising investors growth that would at least partially match what could be achieved with risky dot-com’s. The growth had to come from somewhere however. Business development and technical groups were under extreme pressure to come up with new ways to produce new products and services faster. It turned out it was the Open Innovation methodology explained later in this book that allowed such to happen. Integrating business development, market research, technical research and intellectual property research with Open Innovation options allowed traditional companies to compete with the new entrants.
One of the factors pushing large companies to move this direction was a significant increase in intellectual property secured. The “U.S. Utility Patents per Year” figure shows the growth in US utility patents. In that graph one can see three or four very different environments.
In the first environment from the start of USA as a country in the 1700s up until the mid-1800s intellectual property rights were few and far between. From the mid-1800s up until the Great Depression in the 1930s a steady growth in intellectual property occurred as the industrial age swept the nation. The Great Depression and the World War II took its toll on intellectual property. Rebounding after World War II and the dramatic scientific advances that occurred during the war, caused a much tighter growth rate in R&D investment and securing of intellectual property as shown by patents. The oil crisis and the recession of the 1970s again took its toll. The 1980s saw growth again in R&D, and filing of intellectual property took off again at an even higher rate as laws governing university generated IP and global expansion produced new innovation avenues. As business methods were allowed as intellectual property, a huge burst in the late 1990s occurred as dot-com’s and bricks-and-mortar companies alike started securing intellectual property in this new arena. Bursting the.com bubble caused a fallback in the issuance of intellectual property but one notes that again it is on a very rapid rise once more.
Last rates shown on this graph and around 175 hundred thousand US patents issuing each year this is indeed a formidable barrier towards coming up with distinct new ideas. Companies with new ideas when they search in the patent literature will sometimes find that they have patents in force and salinity is good for 20 years, in the neighborhood of hundreds of thousands of documents. Environments like this are called “intellectual property jungles”. An example of this is in the area of inkjet printing. In the late 1990s one large US Corporation decided to enter the field, there were over 120,000 issued US patents coming out at the rate worldwide of about 3000 per month. If one thinks of the technical challenges here to be unique they were very difficult. Just about every nuance of inkjet printing had been covered. It started with the paper or polymer substrates is describing fiber structure or polymer composition. People had claimed specific coatings to paper or plastic’s to make the print on them stick better, brighter. Company said developed technology around very specific printed designs. They had patented the software algorithms that control the droplet size and shape. They develop algorithms to control the color hue and intensity. And it certainly patented the overall printer design size and shape in computer interfaces. Upon entering the field as it conscientious business development or technology manager one and a look at this prior art and determine what freedom to operate would exist.
The above illustration maybe a little discouraging at first read. But all is not lost. There are ways to operate in such heavily patented areas. Usually, upon closer scrutiny what is found in a significant number of cases there are holes left in the technology or technology has expired. This reduces the complexity down to that of what is called an IP force were there hundreds to thousands of documents to consider, but certainly not 10 thousands or more. In these environments instead of a thick jungle with vines crowding out passage anywhere, one comes across instead open meadows of business opportunity in amongst trees of the IP forest.
In fact at times this task becomes even simpler. This time the example is taken from construction drywall or sheet rock. Most consider this a very mature area. In fact if you look at the overall intellectual property landscape you find that it is indeed a very thick for forest if not becoming a jungle. Using some of the strategies that will outline later on in the book, that being a blue Ocean strategy to identify consumer needs and wants, it is possible of highlight features in drywall that had yet been explored. Looking at the corresponding intellectual property landscape for these unique features what was found is actually an IP desert. In IP desert that is landscapes with only tens of documents present one really has an opportunity to conduct internal research that has a high chance of being unique and distinctive. Capturing and protecting this strong business position is a typical outcome of integrated business technical and intellectual property processes. Does rather than shying away from growth in mature industries are giving up on the opportunity in fact solid market research technical research in intellectual property research studies on well-integrated uncovers countless opportunity.
The question naturally arises, is there a simple answer to achieving growth? One answer could be to just spend more money instead of changing the way New Product Development (NPD) and New Business Development (NBD) is done. Not surprisingly companies have tried many approaches to increasing their NPD output. None have found that simple “throw money at it” works. Instead what we see in the “Median Internal Research Expenditures as % of Sales” figure is that various industries compete most effectively when their R&D intensity falls within industry segment ranges.
Studies are mixed in their view of whether or not increased R&D spending increase is company’s stock value. Many high-level studies conducted by the industrial research Institute (IRI), CIMS, PIMS, and others, such as reported by Clive Cookson, Financial Times, 27 Sept. 2001, have found positive correlations between increased R&D spending and company stock performance. However there appears to be a limit to such investment. There are counter studies which show just the opposite. In fact decreasing shareholder returns correlate to increasing expenditures in R&D. This evidence is provided by Halvard Nystrom in Engineering Management Journal, Sept 2001. Both sets of the status supports the conclusion that appropriate R&D spending occurs within a range of values corresponding to industrial segments.
An obvious comment and appropriate question is that perhaps we really don’t need innovation to grow? We may disparage the last plateau stage in the “Simple Business Maturity S-Curve” figure as being an unattractive area of commoditization, low profits and no growth. Before dismissing this as bad business however, one has to remember that when commodities are related to scarce natural or man-made resources, they can become extremely attractive business. Take the example of oil. When oil was plentiful the oil companies continued on a slow mature rate of growth and return on investment to those people investing in them. When world consumption of oil increased with the developing countries of India and China in the mid-2000’s, the demand for oil skyrocketed. With only so much oil available in the ground and with limited refinery capacity prices rose dramatically. At same time developing countries during that period also caused a rush and an increase in value for natural resources companies producing copper, steel, and polymer materials used in the building and infrastructure markets. Part of any companies’ solid strategic plan is to look at the underlying industry growth rate and profitability of its core products and services. Only then can the “Simple Business Maturity S-Curve” figure be interpreted correctly and R&D for growth invested wisely.
Another example of how to allocate money on R&D and withhold it in some areas has to do with companies who have broad portfolios of businesses. For example, a large U.S. Corporation in the mid-1990’s had 60 different operating businesses around the world. Not all those businesses were the same value to the corporation. When one looks at the economic value in the
“Economic Value of a Large Corporation’s Individual Operating Divisions in Millions of Dollars” figure there are only a few very valuable business units. In fact just five of the 60 units produced over half the corporation’s economic value added.
As a point of clarification, note that economic value added (EVA) is used for many business decisions because it allows a close apples to apples comparison of businesses. It represents as closely as possible the underlying cash value of an ongoing business. From the financial perspective note that economic value comes from knowing the gross investment, CFIRR, growth rate assumptions, fade rate assumptions, and the underlying discount rate; CFIRR comes from the book investment, the gross cash flows, and adjustments for the asset life and the residual value. EVA values help determine how to invest R&D in different business environments.
Clearly organizations which have low EVA’s, operate below the corporation’s real cost of capital, and because of market conditions in their market segment have little chance of improving, were not targeted for R&D and new business development initiatives. See the “Percentage CFIRR of a Large Corporation’s Individual Operating Divisions” figure as an example.
From this plot is easy to see where to invest R&D. The high return businesses were ones that were well supported with next-generation and break-through activity. Those divisions earning adequate returns and were of high economic value had some next-generation activity mostly targeted at improving either their market share or their profitability. NPD and NBD efforts in these businesses were very focused initiatives. The groups labeled in the figure as having Inadequate Returns were ones that were analyzed for their business potential. If they were in operating in markets where there was a good likelihood that improved products and services would generate a return for the organization, investment was made in R&D. If the market conditions didn’t indicate good business segment potential they were slated for divestiture. Clearly the sustained negative return organizations were slated for closure or divestiture. Now that’s not to say that really good breakthrough ideas weren’t welcomed and funded for any business, it is just as a technology leader it would be inappropriate to make a business bet on underperforming business unit initiatives when there were much higher probability of success options available elsewhere in the corporation. It’s tough but resources are never unlimited and when deciding on which portions of a portfolio to invest, picking those which have the best market environment appropriately get the lion’s share of the funding.
Here a quick digression is appropriate. Growth is clearly part of most companies mission and a reason for existence. From growth comes increased profits and increased returns to shareholders. It serves all stakeholders and often provides a healthier more robust and stable work environment for employees. It is not to say however that a high growth strategy is the only appropriate strategy for a company. In the early 2000’s Patagonia, a clothing company, made a deliberate choice to limit their growth. They found that growing too quickly reduced the value to their shareholders, to their customers, and employees were not having as much fun at work. I’ve had an opportunity to work for very rapidly growing companies, ones that were slow-growing ones, from Global 1000 to small garage shop startups. Each has its benefits to the shareholders, employees and customers. It is extremely important that a company continuously look at its mission, why it’s in existence, and make sure it matches and gives maximum value for all classes of stakeholders. There are certainly times where low or no growth is the best course of action.
The boundary between modern times and the past is the mastery of risk: the notion that the future is more than a whim of the gods and that men and woman are not passive before nature. By understanding risk, measuring it, and weighing its consequences, risk-taking can be converted into one of the prime catalysts that drive modern Western society. By making high-quality decisions that reduce risk, societies have been transformed and allowed economic growth, improved quality of life, and technological progress. Thus mastery of statistics and decision theory are critical competencies to growing a company through development of new products. Utilizing the best-practices of this Compendium also improves decision quality and risk reduction.
If growth is a driver and an enabler of innovation and successful businesses, then decision quality is an obstacle. New products have to be funded in order to become commercial. The decision on how much risk to accept in moving forward is always difficult.
The right way to make decisions often violates a person’s natural inclinations. Good decision-makers have learned that what they know, even about a field in which they are recognized experts, is often wrong. As Ron van Beaumont, head of senior management training at Royal Dutch Shell put it, “our executives have to learn when to distrust their own judgments.”
The key elements of an excellent decision-making process can be broken down into four main parts. Every good decision-maker must, consciously or unconsciously, go through each of them. They are:
1. Framing: structuring the question. This means defining what must be decided. Determining in a preliminary way what criteria would cause you to prefer one option over the other. In framing, good decision-makers think about the viewpoint from which they and others will look at the issue and decide which aspects they consider important in which they do not. Framing inevitably simplifies the world which on the one hand is a good thing, but on the other this viewpoint pushes other aspects of the issue to the background. Without proper framing the likelihood of a good decision is low.
2. Gathering intelligence: Seeking both the knowable facts and reasonable estimates of the unknowable that you will need to make the decision. Good decision-makers manage intelligence gathering with deliberate effort to avoid overconfidence in what they currently believe, and the tendency to seek information that confirms their biases. As Will Rogers said, “it’s not what we don’t know that causes trouble. It’s what we know that ain’t so.”
3. Coming to conclusions: Sound framing and good intelligence don’t guarantee a wise decision. People cannot consistently make good judgments using seat-of-the-pants judgment alone, even with excellent data in front of them. The systematic approach forces you to examine many aspects and often leads to better decisions than hours of unorganized thinking would. Numerous studies have shown that novices and professionals alike make more accurate judgments when they follow systematic decision-making rules than when they rely on intuitive judgment alone.
4. Learning from feedback: Everyone needs to establish a system for learning from the results of past decisions. This usually means keeping track of what you expect would happen, systematically guarding against self-preserving explanations, and making sure you review the lessons your feedback has produced the next time a similar decision comes along. Ray Dalio, referenced elsewhere in this Compendium, has just taken this decision-making process to the extreme with excellent results.
The Golden adage “stick to your knitting” becomes an epitaph if a corporation doesn’t engage in constructive conflict that innovation brings about. This is because our fixation on “what is” obscures the necessity of worrying about “what isn’t” and “what might be”. Although organizations do need to drive themselves towards perfection, the pursuit of operational excellence is often mistaken as an end in itself. Note that of the corporations and the Fortune 500 rankings five years ago over 25% are missing today. To keep a company sustainable, conflict must be embraced.
When thinking about constructive conflict, a good place to start is by identifying the factors that drive stagnation and lack of renewal in organizations. The “Fit, Split, Content, and Transcend” figure shows four such areas. The conflicts that arise when looking at an organization through this lens need to be constructively harnessed. One way to make sure that the conflicts are put to good use is to view them through all perspectives of the 7 “S” framework as shown in the “7 S Framework” figure. When using these models it is a manager’s job to maintain a constructive level of debate that leads to identifying blind spots and working around obstacles.
1. “Technological Innovation: Why the U.S. Leads”, by Herbert Fusfeld, FGI Press, 2012.
2. “Managing on the Edge”, by Richard Tanner Pascale, Touchstone, 1990.
3. “Decision Options”, by Gill Eapen, CRC Press, 2009.
4. “Against the Gods”, by Peter Bernstein, John Wiley, 1996.
5. “Decision Traps”, by Edward Russo and Paul Schoemaker, Doubleday, 1989.
6. “Why Innovation Matters”, by Bruce Brown, Research Technology Management, Dec. 2010.
7. “Innovation in Commercial Aircraft: The 787 Dreamliner Cabin”, by Blake Emery, Research Technology Management, Dec. 2010.
8. “The Struggle to Stay Ahead in Innovation”, by Haydn Evans, Intellectual Asset Management, Dec. 2011.
9. “Quantity and Dominant Form of Innovation Required” adapted from Cambridge Technology Partners “A New Economy Series White Paper – The Innovation Lifecycle”, 2000, p. 14.
10. “A New Economy Series White Paper – The Innovation Lifecycle”, Cambridge Technology Partners,2000, p. 14.
11. “Market Characteristics”, Strategy & Leadership Jan-Feb 1998, p.23.
12. “Innovation Types along the Business Adoption Lifecycle”, adapted from Cambridge Technology Partners “A New Economy Series White Paper – Creating Value Through Innovation”, 2000, p. 6, and Strategy & Leadership, Jan-Feb 1998, p.23.
13. “Impact of Non-financial Criteria on Corporation Share Price”, Ernst & Young, Strategy & Leadership Mar-Apr 1998, p. 28.
14. “Number of Ideas that succeed at each new product-development gate review”, source Industrial Research Institute, Washington, D.C.
15. “Methods To Speed New Product Development Phases”, adapted from A Survey of Major Approaches for Accelerating New Product Development, Murray Millson, S.P.Raj and David Welemon, J. Prod. Innov. Manag. 1992;9:53-69.
16. “First Mover Advantage”, adapted from Cambridge Technology Partners “A New Economy Series White Paper – The Innovation Lifecycle”, 2000, p. 8.
17. “U.S. Utility Patents per Year”, http://www.uspto.gov/go/taf/h_counts.htm
18. “New Product Management for the 1980s”, New York, Booz Allen Hamilton, 1982
19. “The Alchemy of Growth”, by Mehroad Baghai, Stephen Coley and David White, McKinsey & Company, 1999.
20. “Living on the Fault Line”, by Geoffrey Moore, Harper Business Press, 2000.