You would think it was obvious …

When advising companies and startups about planned new products, we often find ourselves repeating the same basic advice. This motivated us to develop the diagram shown above, which shows

  • customer needs
  • the competition’s product
  • the client’s own product

as well as the various overlaps between them.

Each of the resulting seven areas has its own interpretation with regard to planned or actual product features:

  • Shared must-haves. Not implementing these features would place a supplier at a serious disadvantage, since customers will view them as necessary.
  • Our stupidity. These are the product features a company is planning to implement which are of no interest to the customer and the competition has (quite sensibly) not implemented. These are simply wasteful and should be removed from the task list.
  • Shared stupidity. These are features of both the company’s and the competition’s products which the customer is not interested in. These should also be removed from consideration.
  • Their stupidity. The competition has implemented features which the customer is not interested in and the company is (quite sensibly) not planning to implement.
  • Shared Opportunity. These are features or functions the customer is interested in but cannot currently obtain. The first company to implement them will gain a competitive advantage.
  • Their advantage. Features of the competitor’s product that the customer values and that the company is not considering. Customer segments that place a high value on these features will purchase the competitor’s product.
  • Our advantage. Features of the company’s product that the customer values and that the competition does not offer. The company should concentrate on these, as they represent a USP and can capture the appropriate market segment.

The error we find companies making is planning features in the our stupidity area. This not only diverts resources from other innovation projects but will also generate no revenues when introduced to the market. Approaches such as Customer Outcomes and Lean Startup and our own Discovery-Driven Innovation are designed precisely to prevent this error from occurring.


The Four Knowledge Paths to Innovation

knowledge path innovation

Discovery-driven innovation processes such as Lean Startup and Hypothesis-Driven Entrepreneurship are currently very much en vogue. They aim to solve the problem of reducing the uncertainty involved in developing successful new-to-the-world offers. In order to better understand the importance of discovery-driven innovation and how it compares to other types, we have developed the matrix shown above.

The matrix distinguishes between the innovation goal and the route needed to achieve that goal, each of which can be either known or unknown. The resulting 2×2 structure yields four quadrants, each of which represents a different type of innovation project.

  • Quadrant I. Here, both the innovation goal and the route to achieving it are known. Incremental innovations are usually located in this quadrant. Customer feature requests and suggestions by members of the public obtained from idea portals are of this type. For example, suggestions such as „introduce a decaffeinated iced coffee“ or „bring back coconut syrup“ at My Starbucks Idea specify the goal, and Starbucks (presumably) knows how to go about implementing them directly. The metaphor of Quadrant I is that of a cook following a recipe. The strategic risk involved is concentrating on the wrong goal, so that while it might be achieved efficiently, it leads to an innovation which is ineffective, outdated or even irrelevant. This error has been likened to „straightening deck chairs on the Titanic.“
  • Quadrant II. In this quadrant, the innovation goal is known, but the route to achieving it is not. This may occur when a customer asks for a solution that is outside the domain of expertise of the supplier. This would have been the case if the proverbial buggy whip manufacturer had been asked a hundred years ago to supply steering wheels to an automobile manufacturer. In this situation, a company might ask a university or a consultant for help. The metaphor is that of a student studying from a textbook. (The illegal practices of wilfully infringing a patent or reverse engineering a competitor’s product also belong to this category.) The strategic risk is choosing a poor source of information.
  • Quadrant III. In Quadrant III innovation, a company does not know what the end result will look like, but it does have an established procedure for developing it. This is the case, for example, when the next model of a successful automobile is to be developed; the manufacturer does not know the final product, but has a tried and trusted method for getting to it. The metaphor for this type of innovation is thus the manager running an traditional engineering project. The strategic risk involved in this case is shooting at the wrong target, i.e. setting the wrong goal at the outset of the project and developing a product that nobody wants. The Edsel, Webvan and Segway are three well-known examples of products that did not meet their marketing goals for this reason.
  • Quadrant IV.  In the last case, neither the final product nor the route to finding it are known. This is the situation in which startups usually find themselves. The metaphor in this case is the scientist searching for new knowledge using an iterative process of hypothesis and experimentation. The Lean Startup approach proposed by Steve Blank follows this method. For established companies, we call this approach Discovery-Driven Innovation. The strategic risks involved here are asking the wrong questions or misinterpreting the answers received.

The largest opportunities for growth are usually to be found in Quadrant IV, since it is here that new markets meet new types of solution. However, the Lean Startup in its current form is insufficient to meet the needs of established companies. This was our motivation for developing Discovery Driven Innovation, which follows the basic hypothesis-driven method but also takes into account the additional issues that established companies have to deal with.

The motivation for the Lean Startup as described by Steve Blank is that startups which are in Quadrant IV use methods which are appropriate for Quadrant III: they set up and execute a waterfall innovation process without either knowing the customer needs or possessing an appropriate solution for them. We believe that the model presented here helps to explain this difference a little better, while at the same time taking two further types of innovation into account.


Refining the Windermere Hierarchy

windermere hierarchy

In a post from 2008, I described the Windermere Hierarchy, a model that explains on what basis buyers make a selection when they have different offers to choose from. The model states that there are four criteria, which are ranked in the customer’s mind. These are (in descending order of priority):

  1. Functionality
  2. Reliability
  3. Convenience
  4. Cost

The Windermere model suggests that customers will make their purchasing choice based on the highest priority criterion which does not satisfy their requirements. Thus, if none or only one of the alternatives available meets all of their functional requirements, they will choose the alternative that meets the most. However, if more than one alternative satisfies their functional requirements, they will make their purchase based on reliability. Similarly, if more than one alternative satisfies both their functional and their reliability requirements, they will choose based on convenience. Finally, if more than one alternative meets criteria 1, 2 and 3, the customer will choose based on cost. In this case, in the customer’s mind at least, the product has no distinguishing features – it has become a commodity which can only be sold by price discounting.

The model can be used to identify what kind of innovation is appropriate for a given product, because knowing at which stage it is in its market, it is known on what basis customers will make their purchasing choice. This in turn implies that the criteria 1 to 4 represent a long-term dynamic of a market: products that provide a new solution will initially see improvements to their functionality. In the second phase, reliability will be improved, in the third convenience, and finally innovations will be sought that reduce costs.

I believe it is of interest to look at each of the criteria more closely. This will enable us to identify different sub-criteria, which may give better suggestions for innovation goals. In the following, I describe three variants of each criterion.


  • Range of Features. This refers to the number of features the product has. Innovation in this category means adding a feature to the product, thus increasing its functionality.
  • Intensity of Attribute. This refers to the numerical value of any given feature of the product. Innovation in this category means increasing a positive value, such as horsepower for an engine or the brightness of a lamp.
  • Appropriateness for Usage. This refers to how well the features of the product match the needs of the customer. This may include attributes such as the flexibility or modularity of the product’s functions. An example would be allowing the product’s functions to be reconfigurable according to the current mode of use.


  • Longevity of performance. This is the most common meaning of reliability and is typically what is covered by a warranty: For how long will the product perform at the required level without interruption?
  • Trust in supplier. The customer may need the supplier for the entire lifetime of the product, for example for maintenance or updates. They therefore need to trust that the supplier will be willing to provide these services in a fair and customer-friendly manner. For example, manufacturers of premium tableware often guarantee the availability of a design for ten or more years, so that customers may continue to own a complete set, even when the inevitable breakages occur in the home.
  • Availability of support. Similarly, a product may become valueless if no support ceases to be available for it. IT systems are one such example.


  • Ease of Use. Customers prefer simplicity of operation. One famous example is IDEO’s design for a radically simple-to-use heart defibrillator. The classic counterexample were home video recorders, which were so complicated to program that only a small fraction of the customer base ever managed it.
  • Accessibility of Product. How easy is it for customers to get information about the product or view the product itself? This might include travel time to the nearest stockist, in-store availability of a model for „test-driving“ or no-questions-asked refunds if a product fails to satisfy a customer’s needs.
  • Simplicity of Appropriation. How easy is it for the customer to acquire the product? Does it require complicated searches or bureaucratic procedures? Given the opportunity, customers will choose the easier route. Amazon’s patented „One-Click-Buying“ is an example of an innovation in this area.


  • Financial Costs. These are the most obvious type of costs. They include not only the purchase price, but also maintenance and repair costs.
  • Physical Costs. These are other resources that are required or consumed in order to use the product such as storage space, personnel or toner for laser printers.
  • Intangible Costs. These include psychological factors such as management attention and stress incurred by using the product, as well as factors such as the negative impact on office climate or brand image.

The Windermere hierarchy is a valuable tool for predicting the future basis of competition; by refining each of its core categories, better innovation choices can be made which in turn can prolong a product’s competitive advantage.


The Innovation Hype Cycle

hype cycle

While listening to a presentation by Gartner Inc. recently, I learned about the Gartner Hype Cycle. Gartner consults in the field of information technology, and they developed the hype cycle in the 1990s as a way to visualise the phases the media go through when reporting on a new technology. Gartner claims that, in 1999, they used this tool to predict the Internet bubble of 2000.

According to the Gartner model, media coverage of a new technology goes through five distinct phases:

  1. Trigger. The new technology is presented to the world, for example as a scientific discovery or a product launch.
  2. Inflated Expectations. In the second phase, a large amount of publicity generates over-enthusiasm and unrealistic expectations.
  3. Disillusionment. Technologies fail to meet expectations and quickly become unfashionable. Consequently, press coverage diminishes rapidly.
  4. Enlightenment. A small number of businesses or universities develop an understanding of how the technology can be used appropriately.
  5. Productivity. The technology becomes stable and evolves into second and third generations. It is applied where appropriate and does a useful job.

I immediately realised that this model can also be applied to the way new innovation methods are treated in the media and that it illustrated a thought that I have had for some time. However, I also recognised that the diagram in the form proposed by Gartner was insufficient to represent what I wanted to say.

The Gartner cycle is drawn in the space-time plane: the horizontal axis represents time and the vertical axis represents the level of hype about a technology (see here and here for some examples.) This representation only allows one relationship to be mapped: the one between hype and time. However, I also wanted to display the adoption of the technology / method, something which is only contained implicitly in Gartner’s model. I therefore switched to a phase space representation, with Level of Adoption on the horizontal axis and Level of Hype on the vertical axis. This allows me to display the behaviour of both over time. The result is shown in the following diagram:

hype cycle

Here, we can still see Gartner’s five phases, as changes in the vertical coordinate of the curve. We begin at the lower left with the Trigger, where there is no hype yet, advance along the curve where we see hype sharply increasing and then decreasing, and end up at Productivity, where the hype has converged to a level that is appropriate. At the same time, we can follow the horizontal development of the curve, where we see zero adoption at the Trigger, followed by an increase in adoption as a consequence of the hype, where many companies adopt the method, even though it is not appropriate to their needs. This is followed by a decrease in adoption as reports about the failure of the method to live up to its expectations become available. Ultimately, at the Productivity stage, the adoption converges to a level at which the method is being used by those companies for whom it is an appropriate tool.

In the title diagram, I have included a number of popular innovation methodologies, placing them where I currently see them in the „innovation“ hype cycle.

  • Stage Gate Process. The Stage Gate Process is now well established and used by many companies as a standardised framework for their innovation process. Although the stage gate process ia still being developed, most companies have found a form which suits their needs and are applying it as a productive tool.
  • Lead Users. The hype about the Lead User method seems to have died down now, as companies try to figure out when the method is appropriate to them and how best to apply it.
  • Disruptive Innovation.  Hype on disprutive innovation was still very intense last year, but seems to be yielding to newer topics as companies realise that disruptive innovation only describes one very specific type of innovation and is not the magic bullet that it once seemed to be.
  • Crowdsourcing Ideas. Commonly (but incorrectly) referred to as „Open Innovation“, Crowdsourcing Ideas was the „big thing“ in 2009 and the first part of 2010. Internet platforms for crowdsourcing ideas sprung up all over the internet and companies from BMW („Virtual Innovation Agency„) to Starbucks („My Starbucks Idea„) started portals where members of the public can submit their ideas. While this is clearly not a viable approach in most cases, the hype about this topic is still very strong, and we have yet to see the first (public) reports on the limitations of this approach.
  • Design Thinking. This seems to be the current „Big Thing“ in innovation; it gets most column inches in the various innovation blogs and discussion forums. It is still unclear (at least to me), how useful this concept is for innovation as a whole and therefore how dramatic the disappointment will be when it comes.

One nice thing about the phase space representation of the hype cycle is that it allows different variants of the cycle to be plotted. In the diagram below we see

  • the Canonical Form (blue), which corresponds to the phases already described,
  • the Flash in the Pan (red), which drops back to zero quickly as people realise that they have been fooled into following a valueless management fad.
  • the Quiet Revolution (green), where a new concept or method remains below the hype radar and slowly gains in popularity and coverage as word of its usefulness spreads.

hype cycle
Some assorted observations on the innovation hype cycle:

  • I think that Crowdsourcing Ideas is actually on the Flash-in-the-Pan curve, since I do not believe that it has any substantial value for innovation.
  • You can recognise when a concept has entered the Disappointment phase when you start to see blog articles titled „What is wrong with Crowdsourcing?“, „Beyond Crowdsourcing“, „Crowdsourcing 2.0“ and so on.
  • I have no idea what method or technique will be the next to become visible on the innovation hype cycle.
  • I would place Blue Ocean Strategy in roughly the same location as Disruptive Innovation in the cycle.

How Do You Ask a Crowd For Ideas?


Tim Kastelle writes a blog on innovation called Innovation Leadership Network. In a recent article called Filtering, Crowdsourcing and Innovation he discusses crowdsourcing for innovation. There he states that one of the conditions for success is that you must ask a question.

None of the crowdsourcing portals in the Internet that I know do this. Instead, they simply say, „Citizens of world, send us your ideas!“ I agree with Tim that this is not a promising approach, and the many failed initiatives that are out there confirm this; they receive thousands of ideas, of which only a very small number – if any – are good enough to be implemented.

Tim’s article raises an interesting question for companies using idea portals, namely: „What question should we ask?“ As anyone who facilitates ideation workshops knows, the more precise the question, the better the answers will be.

Some simple questions would be

  • How could we improve our product?
  • How could we improve your customer experience?

These are simply re-formulations of the information the company is interested in. Because they are so generic, they will not provide much better ideas than no question at all.

More interesting questions would be

  • What annoys you about our product?
  • What was the most unusual situation in which you used our product?
  • When don’t you use our product, although we might have expected you to?

These questions are still fairly standard, but should nevertheless yield some interesting leads for innovation.

Most ideation techniques use a change of perspective:

  • What could we do that would make our product the only viable alternative for you?
  • If you became CEO of our company, what would you change first?
  • How would a multi-millionaire improve our product?
  • What do you think our product will be like 10 years from now?
  • We have a top-secret innovation plan hidden in our vault which will revolutionize our product. We are offering a prize if you can guess what it is!

Questions like these should inspire the creative (and therefore most valuable) visitors to the portal. The result will be a smaller number of higher-quality ideas.

If you were a company with an Internet-based idea portal, what questions would you ask?

The Prize of Uniqueness

In yesterday’s post I wrote about uniqueness and how it improves competitive position to the point of essentially becoming a monopoly. By coincidence, on the same day I discovered a very good example of this effect.

In this video, Charlie Rose interviews Spanish chef Ferran Adrià about his philosophy and his restaurant El Bulli near Barcelona. Adrià was recently voted the best chef in the world and is renowned for his highly individual, avant-garde approach to his profession.

One result of this is that El Bulli is perceived as a unique restaurant and, as a consequence, it is extremely difficult to obtain reservations. In 2010, the restaurant will be open for less than six months of the year on an average of only five days per week. Booking for 2010 opened in January, and seats for the entire year will probably sell out before the month is over. On the same page, the restaurant points out that processing the reservations will be slow, and makes no apology for this fact.

Evidently, Adrià has created a product which delivers such unique value that he can afford luxuries (such as remaining closed for more than half the year) that would be inconceivable for the vast majority of companies. This, I believe, is a very good example of the benefits of uniqueness.