We repeatedly see survey results that say that CEOs think that innovation is a top priority for their firm. And yet, these same surveys also say that most CEOs are unhappy with their innovation efforts.

Why is this so?

Here’s an example – a report from a couple years ago in McKinsey Quarterly. They surveyed over 1500 C-level executives. 15% of them said that innovation was the top priority for driving growth in their firm, and over 70% listed innovation as one of the top three priorities.

But what are firms doing about it? The report says:

But the way companies manage and govern innovation doesn’t reflect that importance. For instance, although executives say corporate performance is most likely to be affected by breakthrough innovations, they also say their companies generally focus on innovation in areas such as product or service development. Only 36 percent of top managers—and just over a quarter of other executives—say innovation is part of everything the organization does. Further, although more than a third of top managers (those at the senior vice president level and above) say innovation is part of the leadership team’s agenda, an equal number say their companies govern innovation in an ad hoc way.

There are a couple of key points there. First, note that there is a disconnect between the number of CEOs that say that innovation is part of everything their firm does, and the number of lower ranking executives that say this. Second, it appears as though for many firms innovation is on the agenda, but there is no process in place to support getting better at innovation.

Mark Cuban recently answered reader questions on the Freakanomics blog, and he had this to say to someone who asked if he should follow his dream and try to get involved in major league sports:

Never follow your dreams. Follow your effort. It’s not about what you can dream of. That’s easy. It’s about whether or not it’s important enough to you to do the work to be ready to be successful in that business.

I would say that a lot of these executives are dreaming about being more innovative. And why not? Innovation does drive growth. But they’re not putting in the effort.

This is a big part of why I worked out The Innovation Matrix:

Executives talking about the importance of innovation is one of the first steps towards increasing your innovation commitment. It’s great that CEOs want their firms to innovate more. But that’s just a dream.

To improve your innovation, don’t dream about it. Increase your innovation efforts. Get better at actually executing ideas.

I remember that when Gillette came out with their double-bladed razor, I started joking about how it wouldn’t stop until razors had five blades. At the time, that seemed absurd, but sure enough, now we can buy razors with five blades.

Now, while this may seem ridiculous, it’s actually a pretty smart response to a potentially disruptive innovation.

The introduction of the double-bladed razor was actually how Gillette responded to the introduction of disposable razors. The value proposition of disposables was: the quality of the shave is almost as good as you get with real razors, but we’re a lot cheaper.

For Gillette, this is similar to the situation that Swiss watchmakers faced with the introduction of quartz watches. The main difference is that quartz watches were both cheaper and more accurate than mechanical watches. In the case of razors, disposables were cheaper, but not better.

Gillette faced a choice. They could embrace the new technology and start making disposables themselves. Or they could double down on their existing business model.

They chose the latter. They had a quality advantage, and they have continued to invest in stretching that advantage. Instead of trying to shore up their weakness (price), Gillette put all of their energy into building their advantage.

This is what Youngme Moon recommends doing in her excellent book Different: Escaping the Competitive Herd.

Doubling down on the current strategy doesn’t always work. There are at least two conditions that need to be met:

1. You must have a clear advantage in at least one feature that customers care about.
2. You must be have a value proposition that is built around this advantage.

The Swiss watchmakers had built their value propositions around accuracy. When quartz watches were introduced, this disappeared. A huge number of watchmakers that had been around for centuries went out of business. The ones that made it through built on the advantages that they still had: prestige and craftsmanship.

Gillette had a clear advantage in performance. And they’ve been able to build on that. The result has been that even in the face of a potentially disruptive innovation, they’ve managed to keep a better than 70% market share in razors.

That’s why we’re probably not too far away from razors with 8 blades. This time, I guess I’m not joking…

Often when people have an idea for a great new product or service, they rush to be first to market with it. We keep hearing about first-mover advantage and how you need it.

The only problem with first-move advantage is that it doesn’t seem to exist. The academic research on the topic shows that there is no such thing.

The first definitive work on this was done by David Teece in 1986 (pdf version of the paper here). He found that innovators capture about 20% of the profits generated by their new ideas. Followers and imitators capture slightly more. Suppliers get some of the benefit, but the big winners are customers, who get about 40% of the benefit of new ideas.

The study was done 25 years ago, but subsequent work has consistently found similar results.

Part of this is because innovations diffuse across an S-Curve – and this usually takes longer than we expect it to.

How can innovators try to capture more of the profits generated by their great ideas? It’s not by being first to market. In his excellent new book Sidestep & Twist: How to create hit products and services that people will queue up to buy,James Gardner suggests that one way to address this problem is use network effects to accelerate the S-Curve – to be the first to scale.

He uses the five factors that Rogers identified as the key characteristics that drive adoption, and reframes them for the network economy. His thesis is that by taking advantage of networks, you can move through the slow part of the S-Curve more quickly. This increases your chance of winning.

The five factors are:

1. Observability: how easy is it for people to see how the innovation works? In networks terms, does usage increase through viral effects? Think about the social games on Facebook, like Farmville. Every time one of your friends played Farmville, you get an update about it. This continues until you either start playing Farmville yourself, or you block all updates related to it. That’s observability.
2. Trialability: how easy is it for people to try out the new idea? In a network, trials are experiments. The more people test out your idea, the more likely it is that emergent properties will show up. This is how you find unexpected new uses for your idea, which expands your number of users, moving you through the S-Curve more quickly.
3. Consistency with how we currently behave: can we fit the new idea into our existing routines? Or does it require us to do new things? The former leads to faster adoption. Within a network, this leads to herd behaviour. Gardner’s example of this is Amazon’s recommendation engine, where the more people use it, the more valuable it is, leading to more people using it.
4. Relative Advantage: is your new idea substantially better than what it’s competing against? One way to get this is to build in effects where the more people use it, the better/cheaper/faster it gets. Think about Amazon’s recommendation engine again. Or Google. Google wasn’t the first search engine (not even close), so how did it come to dominate? By being substantially better than the others, and by using an algorithm that improved search results the more people used it.
5. Complexity: is the new idea simpler to use than its competitors? In network terms, does increasing use lead to great simplicity? For this, Gardner talks about how “crowds of people, learning and sharing together, make it less difficult for others to join their crowd.” His example is Wikipedia – which is trying to catalog a huge amount of knowledge. The more people participate in Wikipedia, the easier this gets. And their value proposition improves.

I love the idea of using network effects to move through the S-Curve more quickly. This quick recap doesn’t do the idea justice – it’s worth checking out the book to learn more.

In the meantime, if you are innovating and you are early in the diffusion curve, ask yourself this: how can I take advantage of networks to increase the use of my great idea? If you think about this in terms of the five factors from Rogers, your chances of capturing the value that you create will increase.

So don’t try to be first to market. Try to be the first to scale.

The economist Rudi Dornbusch succinctly describes the way that ideas spread:

Things take longer to happen than you think they will and then they happen faster than you thought they could.

It’s the innovation S-Curve in words, this is what that looks like graphically:

And the problem is that the value for X is larger than we expect it to be – that’s the essence of Dornbusch’s quote.

I ran across the quote in a post by Andrew Hargadon discussing how sustainability in business is taking longer than expected to arrive. Hargadon explains why X is big:

Forget all the names and dates you learned in elementary school, great social and technical revolutions begin with a whisper, not a bang. They take decades to develop and then, when they do, they change everything overnight.

Take the industrial revolution. It started with a whisper: three different technologies slowly emerging in the 1700s. Coal slowly replaced wood as the dominant source of fuel; the steam engine slowly replaced animal and wind power (to pump water from coal mines); and large ironworks slowly replaced local craftsmen and blacksmiths. For decades, these technologies and the businesses and lifstyles that surrounded them grew and evolved. Then, all of the sudden, the last few decades of that century and the first few of the next saw an explosion of innovation across all industries—from textiles to shipping to railroads to iron and metalworks.

The impact didn’t come from any one of these technologies, it came from the interaction between them.

This slow diffusion causes two problems for firms. The first is that if you are a powerful incumbent, you see the slow diffusion and you think that it will continue to expand along path C – slow and steady. The consequence of this is that when the change does happen, even though there have been warning signs for ages, it still takes you by surprise.

There is a quote from the CEO of a major book store in Game-Changing Strategiesby Constantinos Markides:

We were late in implementing [the web] but not in evaluating it. And our evaluation was that this thing did not make sense. yet every time I tried to explain our reasons why we wouldn’t do it to Wall Street, my share price went down! Even in 1997 when online distribution of books went from zero to 6 percent, superstores increased their share from 10 percent to 22 percent – yet our stock price dropped by 40 percent. So in the end, we decided we had to do something.

This is exactly what path C thinking sounds like. And the problem it leads to is this (via Boing Boing):

But there are also problems for innovators in the S-Curve. The long delay in diffusion causes a lot of firms to go out of business trying to catch the new wave.

You can see this in the Kodak case. Here’s the world’s first digital camera:

It was invented by Kodak in 1975. The problem was, the rest of the economy wasn’t ready for digital cameras yet. Digital memory was still so expensive that you couldn’t actually take usable photos then. Does anyone else remember how crappy the first digital photos were in the late 90s? They were just awful. The supporting technology didn’t catch up with the camera technology for about 25 years.

That is exactly what Hargadon is talking about – it takes multiple innovations to disrupt an industry.

Kodak took this to mean that digital cameras would evolve along path C. So they kept the technology on the shelf and waited. If an independent entrepreneur had invented the digital camera, he or she would have gone bankrupt waiting for the supporting technologies. Or, if they were lucky, they might have sold the rights to a big company like Kodak.

The point is, when you’re early in the S-Curve, it usually takes a lot longer to get to the tipping point than you’d like it to.

The first step in addressing these problems is being aware of them. However, there are also some positive steps that you can take as well. I talk more about these here.

Most of you would know the Nietzsche quote “that which doesn’t kill is makes us stronger” (or it could be a Kelly Clarkson quote, depending on your age). My main point for today is that quote also applies to innovation and this has far reaching implications for anyone trying to make a firm or industry more innovative.

Last year I was talking with Narelle Kennedy, CEO of the Australian Business Foundation, who has done a great job in connecting businesses, research academics and politicians to get a sensible and informed debate on innovation and growth in Australia. With colleagues at the University of Queensland Business School we have been running a large longitudinal survey of innovation and performance in Australian firms. One of the consistent patterns in the survey is that firms are far more likely to innovate when they are in a tough competitive environments. When I explained this to Narelle her response was something along the lines of “that makes sense, you need to experience pain to innovate”.

Narelle is exactly right! The list of evidence that innovation comes out of hard times and challenges is very long. For example, this is a central message in Michael Porter’s classic work “The Competititive Advatage of Nations”. To quote Porter:

A nation’s competitiveness depends on the capacity of its industry to innovate and upgrade. Companies gain advantage against the world’s best competitors because of pressure and challenge. They benefit from having strong domestic rivals, aggressive home-based suppliers, and demanding local customers.

And this is also the reason why protecting industries from competitive pain and providing public funds for pain relief rarely makes a business more competitive. With mainly good intentions, millions of dollars have been spent supporting the Australian car industry and yet it continues to die a slow and painful death. Like a billion dollar game of Russian Roulette, each government hopes that they can provide enough support so that the big collapse will occur during the life of the next government.

A good case in point for the ‘benefits of pain’ is a pretty amazing chart from Business Insider of the efficiency gains in the airline industry. I use the airline industry as an example of cut-throat competition in my MBA strategy class and Warren Buffett’s famous quote is particularly good:

If a farsighted capitalist had been present at Kitty Hawk, he would have done his successors a huge favor by shooting Orville down.

This is the kind of environment that produces the cummulative innovations that result in chart below (taken from Alan Kohler’s Eureka Report).

While traffic has increased 45%, fuel usage has increased 3%. To stay alive in this industry, firms need to continually find ways to improve pricing power and reduce costs and fuel efficiency is a big part of that.

If you want to be more innovative, embrace pain and challenge yourself.

Imagine that 100 of us have gathered together in a room somewhere. It’s a social event, but I want you to think about a couple of numbers.

If we took the average height of all of us, it would be somewhere around 1.76 meters. What happens to this average if we’re joined by Sultan Kösen, the tallest man (2.51 meters) in the world? Our average height goes up to 1.767 meters. In other words, the average increased by about 0.4%.

Now think about our average wealth. The stats vary, but average net worth in the US is around $120,000. What happens to this average if we’re joined by Carlos Slim, the richest man ($63.3 billion) in the world? Our average net worth goes up to $745,544. In other words, the average increased by 521%! And that’s after Slim lost $11b due to the GFC.

The difference between 0.4% and 521% is the difference between normal and complex.

Height is distributed normally, and in a normal system, the average dominates the extremes. The economy is a complex system, and in a complex system, outliers matter.

That picture is from The Behavior Gap: Simple Ways to Stop Doing Dumb Things with Moneyby Carl Richards.

Here is what he says about the importance of outliers:

[O]utliers matter. In fact, they matter so much that they almost make the average meaningless. Because most of our lifetime return is determined by how many of these outliers we experience, it is time we stop ignoring them.

If we’re trying to innovate, our job is to invent the future. So the fact that the economy is a complex system is important.

First off, it’s important because returns to innovation follow the kinds of returns that we see in the wealth distribution. The average return to executing a new idea is small, but a small number are gigantic. This is why it’s important to manage innovation as a portfolio.

Secondly, this has a big impact on how to think about the future. Complex systems are impossible to predict. This is a problem, since we don’t like uncertainty.

Here is how Martin King frames the problem:

The problem with long term developments are that they are subject to exponential and combinatorial factors – chaotic things that we are not good at understanding at the best of times. To compound things change cycles themselves are becoming faster.

Instead of thinking of the future as something to predict, we should think about it as part of a pattern. Greg Fisher wrote an outstanding post (read it!) discussing the importance of pattern recognition in complex systems. Here is part of his prescription:

There is a relationship between patterns and prediction. In fact, I would note that not only do patterns exist and persist, we must rely on them in every day life. We make decisions in the present assuming the persistence of some patterns e.g. I will withdraw £50 from a cash machine today for spending over the next few days. I do not expect everyone else in the UK to switch to the Thai Baht during that period. Furthermore, it is particular patterns – many of which we might call institutions – that are responsible for our civilised society and a relatively high standard of living.

But – and this is to assert the point further – it is important to emphasise that the world will change and so too will the patterns around us. By “expect to persist” in my definition of patterns I was referring to making reasonable judgments that some patterns will remain broadly the same over a particular period.

How should we respond to this? Geoffrey Morton-Haworth has written an excellent post on Learning From Patterns. First he talks about the most common example of a complex system: the weather. And he says:

We cannot control the weather but if we recognize its patterns we can manage around them. And we can do the same in complex relationships.

He then discusses the work that Edward Tufte has done on effectively assessing complex data. Morton-Haworth includes this worksheet from Tufte:

Here is how he concludes:

Tufte argues for good method. That is “a shrewd intelligence about evidence, a clear logic of display and analysis, placing data in the appropriate context for assessing cause and effect”. In short, he talks about the need for “a coherent architecture for organizing and learning from images”.

A complex relationship outlasts its components, just as the ant colony outlives the individual ant, and in so doing develops a purpose of its own greater than the free will of its parts. While individuals may only be involved for a matter of months or just a few years, a complex relationship can learn, change, grow and adapt over five, ten, fifteen or more years. Nevertheless, because our lives take place at lower levels, we frequently don’t know the contribution we make to complex relationships. But we can help its intelligence to emerge.

This is why it’s important to think about inventing the future. Another important feature of complex systems is that the systems co-evolve with their parts. In simple terms, small changes among the parts can cause large changes within the system.

These are the small number of innovations that end up having big impacts. And how can we find these? We can’t predict which innovations will hit big – knowing this is one of the important outcomes of thinking about the economy as a complex system.

Harold Jarche does a nice job of framing some of the issues here:

When we move away from a “design it first, then build it” mindset, we can then engage everyone in critical and systems thinking. Workers in agile workplaces must be passionate, adaptive, innovative, and collaborative. Autonomy is the beginning.

Instead of innovating based on prediction (design, then build), which leads to big bets, we need to innovate based on experiments. This leads to little bets.

In a complex economy, the way to think about the future is this:

• We can’t predict the future.
• But we can learn about the patterns from which the future will emerge.
• In fact, while we can’t control the future, we can influence it.
• The best way to influence the future is by innovating through experiments.

What experiment can you try today?

I ran across an outstanding post today by John Battelle reviewing Where Good Ideas Come From: The Natural History of Innovation.by Steven Johnson.

It’s one of my favourite books from the last couple of years, and Battelle does a great job of highlighting the key points in it. He also reminded me of a table that Johnson put in towards the end of the book. It looks at the genesis of what he thought were the most significant ideas of the 19th and 20th centuries. He then assessed whether they were developed in commercial firms or non-commercial organisations, and whether they were generated by individuals or by networks of people.

Here’s the table:

This illustrates several important points:

• It’s never either/or, it’s both/and. Are individuals or networks more innovative? Networks – there’s plenty of research to back this idea up. Nevertheless, individuals still generate plenty of big ideas. It’s the same with market vs. non-market – lots of great ideas come from both. More come from non-commercial environments.

  It’s really easy to argue black and white statements (“Only small firms innovate!” “No – only big ones do!”). But they’re never true. In order to support innovation, we need to look at these dichotomies and figure out which circumstances favour one approach over the other. And then we need to support both. This is true for market vs. non-market, for individuals vs. networks, for big firms vs. small firms.

  Black and white thinking is dangerous.

• Networks are a critically important source of great ideas. The lone inventor idea is still with us. Here is what Johnson says about networks:
  

  Ideas rise in crowds, as Poincaré said. They rise in liquid networks where connection is valued more than protection. So if we want to build environments that generate good ideas—whether those environments are in schools or corporations or governments or our own personal lives—we need to keep that history in mind, and not fall back on the easy assumptions that competitive markets are the only reliable source of good ideas. Yes, the market has been a great engine of innovation. But so has the reef.

  The second part of that quote leads to the next point:

• Non-market organisations are critical components of the innovation ecosystem. Many of the ideas that led to you being able to read this blog post came from non-market networks – the computer and the internet being chief among them. But just to illustrate the first point, smart phones, which aren’t in the table, came from a market network. Nevertheless, it’s important to understand how crucial non-market organisations are to generating big ideas.
• Most big ideas get turned into innovations by the market. Here is what Battelle says:
  

  This doesn’t mean those ideas don’t become the basis for commerce – quite the opposite in fact. But this is a book about how good ideas are created, not how they might be exploited. And we’d be well advised to pay attention to that as we consider how we organize our corporations, our governments, and ourselves – we have some stubborn problems to solve, and we’ll need a lot of good ideas if we’re going to solve them.

  Effectively connecting non-market organisations with market-based firms is one of the most important roles of government. In regions that innovate well, these two sectors interact more effectively than in less innovative regions.

Invention and innovation are two different things. However, we still need to start with a great idea to innovate well. Understanding how good ideas originate is an important part of doing this.

The Shift Index 2011 is out now, and as with the previous two editions, it is a must-read.

I am always skeptical of “everything is different now” type arguments, but in this series of reports, John Hagel, John Seeley Brown and a number of other contributors have done a fantastic job of documenting exactly what is changing. It might not be everything, but it’s a fair bit.

Here are the four key points that they make in the summary of this year’s report:

• ROA (Return on Assets) performance continues its long-term decline due to deteriorating firm performance
• Layoffs and other short-term measures taken by firms are not a sustainable solution to improving long-term firm performance
• Connected individuals, not companies, are the ones harnessing flows and have more power because of it
• Firms have untapped opportunities to reverse their declining performance by embracing pull

Hagel and Seeley Brown have a number of recommendations about how to deal with this in their book The Power of Pull
(discussed here and here). It’s one of the best books of the past couple of years, and I recommend it.

Another book that deals with these issues is Futuretainment: Yesterday the World Changed, Now It’s Your Turnby Mike Walsh.

The book is interesting. Here is one of the key points that Walsh makes in it:

Sometimes the best way to win a game is to question why you are even playing it. The rules that govern industries are rarely made in advance – they evolve in periods of rapid change until eventually they themselves become restraints on innovation. But there is one thing you can be sure of: when consumer behavior changes, sooner or later business behavior must follow. The future is already here, you just need to know where to look.

The book itself is a great example of trying to invent the future. Walsh has deliberately made a book that only works as a physical thing. It has a gorgeous set of photos taken by Walsh (including the one above) as the background on each page. Then it has series of insightful chapters discussing the implications of the big shift. Here is how he describes the approach:

The first question my publisher asked me was why a book and not a blog? Three years ago when I started working on Futuretainment, that was already a tough question to answer. With eBooks now on the crest of critical mass, it hasn’t got any easier. Last week, my book hit the shelves. Although you can buy it on Amazon, you can’t read it on a Kindle. In fact, with 300 pages of illustrations, original photographs and custom designed typography – it is about as Kindle friendly as a bathtub. That was a deliberate decision on my part, but it comes at a time when the very concept of a book is changing.
…
There are two aspects to any book. First, there is the book as an informational construct. Put simply – an arrangement of words, sentences, paragraphs and chapters. However in our attention drained world of 140 characters, this construct increasingly boils down to a simple image – the long tail, the tipping point or the black swan. Despite fervent claims to the contrary, the vast majority of people don’t actually read books. They consume metaphors and debate in status updates.

Fortunately, there is also a second aspect of books – ‘thingness’. Whether a Sumerian stone tablet, an Egyptian papyrus, an illuminated Medieval manuscript or just a pulp paperback – there is a physical side of books which has its own life.
…
Because, as much as I love my Kindle, it is a marriage of convenience. My true mistress will always be books. The smell of print, and the sensual touch of high quality paper will never fail to seduce me. And I can only hope that my book might elicit the same response in you.

Unlike Jonathan Franzen, who recently discussed why books need to be physical without offering much more of a reason than “because I like them”, Walsh has made a book that demands to be instantiated physically.

eBooks are a great response to the informational side of books that Walsh discusses. Seth Godin wrote a great post yesterday about how to deal with this.

But to deal with the ‘thingness’ of books, you need a new business model. You need to create value not just in the words, but in the physical object as well. Walsh has succeeded in both aspects of his book.

What should the rest of us do? Maybe it’s time to heed Jorge Barba’s advice and get an MBA in curiousity.

There’s a big problem with innovation: ideas spread much more slowly than we expect them to.

Ideas follow an S-Curve as they spread that looks like this:

They pick up steam very slowly, until they either die off or hit a tipping point and take off. The slow build-up is the time I’ve indicated as X in the drawing.

The idea for the S-Curve is based on the great work by Everett Rogers on innovation diffusion.

Based on his research, the population of users is divided into groups he called innovators, early adopters, the early and late majorities, and the laggards. In the populations that he looked at, the percentages of people in each group look like this:

You can see these numbers in the survey that Sophos Security released last week on the reactions of Facebook users to the new timeline feature:

This is being presented as a big problem for Facebook, but if you look at the numbers, they’re actually better than the stats from Rogers would lead us to expect. The survey doesn’t include the laggards, who probably still aren’t on Facebook, but the rest of the numbers map onto Rogers’ pretty well.

All of the people that hate the new timeline want to go back to the News Feed, another feature that had even worse approval numbers when it was introduced. And now people love it and don’t want it to change.

That’s the way that ideas spread. People resist, a small number adopt, and eventually over time, the idea wins. If you’re lucky.

There was another story over the weekend about the diffusion of Edison’t incandescent lightbulbs that tells the same story.

Here is what they say about adoption of electrical lighting:

By 1910, more than 30 years after Thomas Edison invented the incandescent bulb in 1879, only about 10 percent of American homes had been wired. Even in the glittering Roaring Twenties, only about 20 percent of homes had electricity — not because of a lack of electrical contractors, but because of a lack of consumer enthusiasm.

Advertisers proclaimed that homes with electricity would be brighter, cozier and happier, but the public wasn’t buying.

And this is for a product that was demonstrably better, cheaper and safer.

Again, the value for X was much longer than expected.

This is an issue that is addressed extremely well by James Gardner in his excellent new book Sidestep & Twist: How to create hit products and services that people will queue up to buy.

The book is worth reading and Gardner does a great job of explaining the S-Curve and its implications. One of the key outcomes of this is one that makes a lot of the people that have encountered Gardner’s ideas uncomfortable: breakthroughs don’t pay.

The long X shows us why. It takes so long for new ideas to spread that whoever introduces them is not always set up to capture the value from them.

This is kind of scary, because those of us that generate ideas want to think that a great idea will win. But they don’t automatically. One point that he makes is that you work around this by building on existing ideas:

A lack of genuine originality is a feature of almost every category-defining product in the last decade. Was Facebook the first social network? Certainly not: MySpace, Friendster and a host of others preceded it. In fact, the first real social network was a site called SixDegrees.com, and it was founded a decade before Facebook’s meteoric rise began. Was it Google that created web search? Of course not: the company’s contribution was to improve what Alta Vista and the other web search engines that had pioneered the field were doing already.

I could spend pages and pages going through examples like these, and will do so later on in this book. But one thing unites all these products and services: they’re built on something that was working well somewhere else.

Gardner has more good suggestions about what to do about this, and I discuss these more here. But for today, I just wanted to take the Facebook and Edison examples to illustrate the problem that we are trying to address. If you are trying to get ideas to spread, you must develop a good understanding of the idea diffusion S-Curves and what they mean.

The fact that ideas spread slowly is crucially important to understand. It is part of what makes it difficult to win through innovation. This is why we must manage innovation as a process.

It’s dangerous to think of innovation only as generating new ideas. That’s not enough. You also have to get the great ideas to spread. They spread through S-Curves, and we have to include these when we develop our innovation strategies.

There are two popular quotes that often get used when discussing innovation that were never actually said or written by the people to whom they are attributed. Despite the fact that they are fake quotes, there are still things that we can learn from them.

The first common quote is attributed to Henry Ford:

If I had asked people what they wanted, they would have said faster horses.

This quote usually comes up when people are discussing focus groups, or design-driven innovation. However, there’s no evidence that Ford ever said or wrote it.

Even though it’s not a real quote, it raises some interesting points. You can interpret it as meaning “you should ignore customers,” or some people even seem to think it means “customers are stupid.”

But that’s not really what it’s saying at all. People do have limited vision if you ask them open-ended questions. And as innovators, our job is to invent the future. Nevertheless, there is useful information in the faster horses idea.

If people really had told Ford that they wanted faster horses, what would that mean? If you frame it in a jobs-to-be-done way, it means that the main job that they’re trying to do is to get somewhere fast. That actually is a pretty good argument in favour of automobiles.

In his HBR post on this topic, Patrick Vlaskovits sums up the issue well:

An innovator should have understanding of one’s customers and their problems via empirical, observational, anecdotal methods or even intuition. They should also feel free to ignore customers’ inputs. Because by now it should be clear that Ford’s adherence to his vision of the mass-market car and how to materialize that vision was instrumental in both his early success in growing Ford Motor Company as well as his later failure to respond in a timely and effective manner to rapid innovation in the marketplace.

The real lesson learned was not that that Ford’s failure was one of not listening to his customers, but of his refusal to continuously test his vision against reality, which led to the Ford Motor Company’s failure of continuous innovation, resulting in a catastrophic loss of market share from which it never recovered.

So the quote is useful, even if Ford never said it.

The second quote is a bit more problematic – this one is frequently attributed to Charles Darwin:

It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.

As with the Ford quote, Darwin never actually said or wrote this (he never wrote “survival of the fittest” either – that was Herbert Spencer building on Darwin). This one is a bit more problematic too, because it is actually a major misinterpretation of Darwin.

Consider the Large Ground Finch, one of the species from the Galapagos Islands described by Darwin:

In a remarkable research project that has spanned nearly 40 years now, Peter and Rosemary Grant have studied the evolution of Darwin’s Finches in the Galapagos (the work was beautifully described in The Beak of the Finch: A Story of Evolution in Our Time by Jonathan Weiner – a terrific book).

Here is their key finding. When times are good, there is wide variation in the beaks of the finches. However, the Galapagos are subject to the El Niño/La Niña weather cycles, which means that they have frequent droughts. In times of drought, the finch populations dive. In the case of the Large Ground Finch, the individuals that survive these events have the biggest beaks. Why? Because the bigger beaks enable them to crack larger seeds, which would be ignored as too hard to crack when there are plenty of seeds around.

In other words, it is precisely the strongest of the species that survives.

The fake Darwin quote is completely wrong with regard to which individuals survive. But it might tell us something about which species survive. The reason that Large Ground Finches have been around for as long as they have is that there is enough variation in the species that whenever conditions are extreme, some individuals in the population will be able to adapt to the change.

If we apply this to innovation, you might think of it this way: products are like individuals and organisations are like species. To do well, products need to be the best at getting some job done for some group of customers.

However, for an organization to do well over time, it needs to be adaptable. This means that unless its environment is unusually stable, it needs to generate variety. Even though economic evolution is directed by the choices that people make, we still don’t have much control over which ideas work and which don’t. Or over which take off, and which never really click.

To maintain variety, to improve responsiveness to change, we must experiment.

Why have these two quotes become so widespread? It’s not the internet – both incorrect attributions were made in books. Both quotes are catchy and short, and they capture ideas that seem like they reflect what Ford and Darwin thought. Even though the Darwin quote is not very Darwinian, it reflects a very common misinterpretation.

The catchiness is one thing, but also, we like to argue from authority. If we don’t want to run focus groups, it’s easier to get Henry Ford to make the argument than it is for us to do it ourselves.

I wanted to think through these quotes for a couple of reasons. One is that they do offer some useful lessons. The second is that we need to figure out how to make compelling arguments ourselves. This is the key to getting our own ideas to spread – not by arguing from authority.

(The superb Large Ground Finch photo is from flickr/Steven Bedard under a Creative Commons License)