Knowledge Transformation in the Innovation Process: The Knowledge Funnel and a Logical Leap

In 2009 Roger Martin authored the seminal book The Design of Business: Why Design Thinking is the Next Competitive Advantage. He described a novel approach that organisations can utilise to foster long-term innovation. Historically, organisations believed that designers were separate from the business decision-makers. Martin argued that business people have to become designers to cater to customers who are becoming more discerning.

Martin was one of the first people to write about Design Thinking; many have adapted and applied the principles in his book in different ways in the decade or so. This article takes a look at how knowledge is transformed during innovation. I’ve written another article with a more prescriptive application of Design Thinking, Empathy Mapping and Blue Ocean Strategy if that’s what you’re looking for.

As Martin described initially, Design Thinking is much less a prescriptive tool to innovate but rather a way of thinking about the transformation of knowledge in the innovation process. Thus, Design Thinking is typically applied in forming an innovative culture in an organisation. It is not a specific tool that will undoubtedly lead to some innovation when completed.

Using Design Thinking for Innovation

There are three key aspects of Design Thinking — (1) the Knowledge Funnel, (2) a Logical Leap, and (3) understanding analytical thinking versus intuitive thinking.

Figure 1: Adapted from A Brief History of the iPod

Figure 1 shows the development of the Apple iPod in which Apple transforms their knowledge about the mystery into a heuristic and, finally, a successful algorithm. The Knowledge Funnel is an analogy Martin uses to explain this knowledge transformation.

Knowledge Funnel

An organisation's knowledge about a market problem flows from the top down the funnel through three phases.

Figure 2: From The Design of Business: Why Design Thinking is the Next Competitive Advantage

Mystery

The Knowledge Funnel starts with exploring a mystery — also, point A in Figure 1.

Exploring a mystery is the first stage of the funnel. Before releasing the iPod, Apple had very little information about what customers wanted. Designers needed to figure out what features customers wanted, how they would use the product, and what features they didn’t want. Without understanding the problem to be solved, the solution can take an almost infinite number of forms. The mystery Apple explored could be condensed to, “how can we simplify the music lovers' experience?”

Heuristic

The next stage of the funnel is developing a heuristic (a rule-of-thumb), so the explorer can make sense of the mystery. Apple iterated twice between points A and B in Figure 1; they were testing and clarifying their heuristic.

This heuristic narrows the field of inquiry to a manageable size and allows for a simplified understanding. Apple’s heuristic was something to the effect of “customers like compact and easy to use.” This is shown in the first generation of the iPod Classic for Apple. Through trial and error, Apple discovered where this heuristic is correct and where it no longer stands true. Apple tested and refined its heuristic through successful and unsuccessful iterations.

Algorithm

Through further iterations, Apple was able to refine and validate this heuristic. At point C in Figure 1, Apple had successful and unsuccessful iterations. Apple had proved what had a good market fit and what didn’t. Apple evolved its heuristic into a rule that stated what was successful and not successful — an algorithm of success.

Many organisations spend a disproportionate amount of time in the algorithm stage by cutting costs and refining the proven solution.

Analytical versus Intuitive Thinking

At point B, in Figure 1, Apple had to make a crucial decision; this decision distinguishes the difference between analytical and intuitive thinking.

Figure 3: From The Design of Business: Why Design Thinking is the Next Competitive Advantage

Design Thinking is the nexus between analytical and intuitive thinking. The point at which the organisation balances exploiting the current solution and exploring better ways to solve the problem. The former exploits the algorithm's reliability; the latter explores other valid alternatives.

Adapted from: https://rogermartin.medium.com/reliability-versus-validity-in-strategy-6df8c9dde8d2

Many businesses and business leaders suffer from a reliability bias. Decision-makers focus too much on reliability; they use algorithms and quantitative reasoning when making decisions. The problem is that these algorithmic decisions almost always ignore innovations.

Logical Leap

Using analytical thinking won’t allow for innovation. Innovation requires creativity, combining ideas in a unique or new way to make unusual associations between ideas. Innovation requires this logical leap.

Once Apple had refined the iPod Classic algorithm, they returned to the mystery stage and attempted to solve it differently, resulting in multiple iterations. Some logical leaps prove valid — for example, the iPod Nano — while others do not — for example, the iPod Photo.

The touch screen was possibly the biggest logical leap and the biggest payoff for Apple. Prior, all user inputs were via physical buttons. Apple and their competitors asked customers what they wanted — more buttons (like a Blackberry). The brilliance of Apple’s logical leap was that even customers didn’t know they wanted a touch screen until the iPhone and iPod Touch were released. Apple didn’t and couldn’t have known whether this logical leap would be successful because it required intuitive, not analytical thinking.

Limitations and Advantages of Design Thinking

Design Thinking is not a prescriptive tool is both an advantage and a disadvantage. Design Thinking might not provide this in the required time frame if an organisation were seeking a quick and sure innovative leap. A requisite of Design Thinking is that it is ingrained into the organisation’s culture to foster sustained innovation in the long term. This can be considered both an advantage and a limitation. Design Thinking is not an ‘off-the-shelf’ tool that one would use in, for example, an innovation workshop if a quick, innovative leap is required. However, the upside of Design Thinking being a more long-term approach is that it leads to sustained innovation and thus gives the organisations that adopt it a competitive advantage.

Further, Design Thinking is advantageous as innovators can use it with multiple other innovative and problem-solving tools. For example, innovators may also use customer journey mapping and crowdsourcing to empathise with the customer; lateral thinking is often required when making a Logical Leap. Assumptions are inherent in developing the heuristics of Design Thinking; these assumptions need to be criticised and validated, and innovators can use Devil’s Advocate and the Six Thinking Hats approach. However, these are still assumptions and thus limit the reliability of Design Thinking. These assumptions need to be backed by data; such data collection is costly, and the limited availability of valid and reliable information is a further limitation of this approach. If flawed data validate heuristics, this will lead to poor insights and failed iterations. Design Thinking often requires multiple iterations in a trial-and-error process before a validated Algorithm is reached. This costs a considerable amount for the organisation, considering the enormous costs of taking a product to market that does not have a product-market fit. For many, the risks associated with this are so high that they stifle innovation. Martin argues that the opportunity cost of not innovating is higher, in most cases than the cost of a few failed iterations.

Key Insight 1 — Creating a Design Thinking Organisation

As stated above, Design Thinking exists in the nexus, or balance between reliability and validity — or exploitation and exploration. Businesses' structures, processes and norms are typically skewed towards reliability for three reasons:

1. the analysis is more straightforward and more widely taught compared to intuition;
2. stakeholders are oriented towards reliability; and
3. the ease of defending reliability-based decisions compared to validity-based decisions.

Design Thinking companies must utilise different reward systems and norms that foster intuitive thinking. An example is when a new CEO at Proctor & Gamble transformed the company into an innovative organisation within only a few years and great financial success.

Key Insight 2 — Developing Yourself as a Design Thinker

Martin explores how individuals can develop skills to operate as Design Thinkers in a reliability-oriented organisation. He describes a way that individuals can gain knowledge and expertise; this knowledge system has three components:

1. Stance: to position oneself with a mindset and acquire the requisite skills to become a successful Design Thinker.
2. Tools: Take on every opportunity to develop those skills in ways that will improve creativity and thought processes.
3. Experiences: one can gain invaluable experiences by exposing oneself to different challenging situations.

By following this knowledge system, one will produce more valid outcomes by using Design Thinking.

Challenges and Obstacles a Design Thinker Will Face

The most significant challenge or roadblock a Design Thinker will face is the reliability bias and executives’ tendency to favour reliability over validity. Executives must defend their paycheques and position in the organisation. For this reason, these executives are incentivised and somewhat obliged to favour reliability when making decisions.

An organisation’s heuristics often exist only in the heads of these executives. These same executives are not incentivised to convert the heuristics into algorithms that others can follow because this will make the executives less valuable to the organisation. In the Proctor & Gamble example, the new CEO urged executives to convert these heuristics into written algorithms, allowing lower-level managers to follow them without consulting the executive. This allowed executives to focus on innovation. Allowing Proctor & Gamble to achieve a balance between reliability and validity, executives delegated analytical tasks and, in turn, had more time to focus on intuitive thinking tasks themselves.

Martin puts forward five things a Design Thinker can do to be more effective when working with colleagues at the ends of the intuitive thinking versus analytical thinking spectrum:

1. Turn others’ extreme views into creative challenges;
2. Empathise with colleagues that are at the extremes of the spectrum;
3. Learn to understand and communicate with these people at the extremes, using their language;
4. Use this language to turn unfamiliar concepts into terms that are familiar to them; and
5. It is easier to prove a heuristic if the concept is big enough to give innovation a chance.

Martin urges Design Thinkers to be a “first-class noticer” (p. 30). He means that innovative ideas come from outside of one’s day-to-day experience, and they come when the noticer sees the world for all its possibilities. When the Design Thinker notices how things work, emerge and interacts and apply these insights to problems they are trying to solve, they will only be one logical leap away from the next innovation.