Archive for April, 2011

Innovation Myth: Ideas Spread Quickly

Posted by Tim in complex systems, connect, evolving economic entities, innovation, innovation strategy on 26 April 2011

The future’s already here, it’s just not evenly distributed, and it doesn’t look like we expect it to

When scientists first started talking about Artificial Intelligence in the 1950s and 1960s, a lot of the discussion centred around how to best create AI that would think like people do. This view of AI has dominated our imagination ever since.

Think of HAL in 2001: A Space Odyssey, Deep Blue and other chess-playing computers, Skynet and the rise of the robots in the Terminator movies, and all the current discussion about the singularity. All of these are pictures of Artificial Intelligence doing what human intelligence does – just doing it faster, or better.

Over 50 years later, except for the chess-playing computers, we’re still waiting for this form of AI to take off.

Because we’re not seeing this type of AI, AI has been a failure, right?

Well, not really. There’s actually tons of different types of AI in practical use right now. An article in Wired UK outlines many of the current uses of AI, and it’s an impressive list: warehouse stocking robots, the google search engine, algorithmic financial trading, credit card fraud detection, and self-driving cars, just to name a few.

Even though we don’t have Skynet yet, we’re still interacting with AI throughout our day, often without even realising it.

The Long S-Curve of Innovation Diffusion

The story of AI illustrates a common innovation myth – that ideas spread quickly.

Around the time that computer scientists first started thinking seriously about AI, Everett Rogers was showing that most innovations follow an S-Curve as they diffuse through the economy. The Innovation Diffusion curve looks something like this:

Ideas are first picked up by people that Rogers referred to as Innovators, then Early Adopters. This is happening over the time period that I’ve labelled “X” in the diagram. Eventually, the new idea either dies off, or it takes off. Once the tipping point occurs, the idea then spreads rapidly throughout the market, until a saturation point is reached.

When people are innovating, or thinking about innovations, one huge mistake that they commonly make is to underestimate how long the idea will stay in the X range.

Here’s an example: email. The first email was sent around 1971, just a few years after the internet started. For a long, long time, email was only used by researchers, the military, and academics. It wasn’t until the late 1980s that universities started to make email available to students (that’s when I got my first email address).

By the early 1990s, the World Wide Web was built on top of the internet, and then email started to spread a bit more quickly. By 1993 or so, it was becoming relatively common among early adopters outside of academia. But even then, the question that you asked if you wanted to send someone an email was “do you have email?”. And in just a few years, suddenly everyone had email. By 1996 or so, the question was a simple “what’s your email address?” That was the tipping point. In another five years, it was “which email address should I use for you?, because everyone had a personal email address, one for work, and often a few more. Email had reached saturation.

If you thought that email started with the WWW in the early 1990s, X was only four or five years. But if you think of the whole story, X actually lasted about 25 years.

This is pretty common for new ideas. Xerography was patented in 1936, but the first Xerox machine didn’t hit the market until 1949. The technology didn’t take off for another seven years or so. X was about 20 years for this idea.

Even in the fast-moving internet age, X is often a lot longer than we expect it to be. Jeff Bezos had the idea for Amazon in early 1993. It took about two years to get the site up and running. In 2000, people were still calling it amazon.bomb, among other things. It didn’t take off until about 2002. X was about nine years for Amazon – and that’s one of the shortest time periods that I’m aware of.

The Reasons for the Long X

The unusually long period of X for new ideas is due to several things. Most of them have to do with uncertainty – we don’t actually know what the new idea is for yet. This happens in a few ways:

We have to figure out how to make the new idea work: the best use of a new idea is often not obvious. In fact, because we tend to think in analogies, we often get this wrong at the start. In the AI example, the technology didn’t start to really take off until people stopped asking “how can we make computers that think like people?” and they started asking “we have computers that do some things that people can’t do well – how can we make use of this?” Going through this process takes time, and it requires a lot of experimentation. Many of these experiments will fail – but one of the critical things that we have to figure out is under which circumstances the new ideas work, and under which ones they don’t work so well.
We have to fight against the hype cycle: the long X is a direct contributor to the hype cycle. The Early Adopters get excited about the new idea, and it gets oversold. Then the people that are threatened by the new idea fight back. When it doesn’t spread as quickly as expected, the excitement wanes and cynicism sets in. Eventually, though, through experimentation we figure out what the best use of the new idea will be, and at that point it is finally poised to take off.
Greg Satell explains this process very well in his post Why Trends Are For Suckers. This is what the hype cycle looks like – you can see the long X at work in it!
Most importantly, we have to figure out how to create value for people with the new idea. This is the part that the Early Adopters tend to ignore – they usually like new things simply because they’re new. For everyone, the new idea needs to solve a problem. Avinash Kaushik explains the issue perfectly in 11 Digital Marketing Crimes Against Humanity:

When I look at winners and I separate them from the losers there is one thing that stands out. Winners have a sophisticated understanding of the holistic success of their digital existence. It comes from undertaking two simple steps: 1. Identifying their Macro and Micro Conversions and 2. Quantifying Economic Value.

I tend to talk about the need to create value more broadly, not simply economic value – but in either case, without clear value creation, the new idea will never take off. Again, it takes some time to figure out where how to create this value, and often the value being created isn’t the value that was originally expected.

The Myth of Quick Adoption

Our tendency to dramatically underestimate the true value of X in innovation diffusion causes all kinds of problems. If we’re early adopters, we expect new ideas to spread quickly. And yet, they don’t. If we’re threatened by new ideas, the long X can give us a false sense of security. As it becomes clear that early predictions are exaggerated, we become complacent. But eventually, once all the experimentation has been done, and people have figured out what the new ideas are really good for, and how to create value with them, the threat begins to bite.

I’m not sure of any way to move through the innovation diffusion curve more quickly. It is by its very nature slow, experimental, unpredictable, exciting, revolutionary and wasteful. It is part of what makes innovation both exhilarating but also frustrating.

Being aware of the myth of quick adoption is the first step towards figuring out how to deal with it.

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What Does Your Innovation Globe Look Like?

Posted by John in innovation on 19 April 2011

When I was a boy I used to enjoy visiting my grandparents and one of my favorite objects in their living room was a globe where the countries would light up as different colours when I switched the globe on. After seeing all of these countries I would often go to the trusty Encyclopaedia Brittanica on the bookshelf to find out more about these places and what people actually did there. The power of maps is that they help us to think about where we are in relation to other people and places.

Last week I wrote a post about the significance of global connections for stimulating innovation and a few comments and tweets got me thinking about the importance of having a global innovation map. John Hagel tweeted that he wasn’t convinced that the global connections were more important than local, implying that both were probably important. The post resonated with Karen Fu in Singapore. If you live in Singapore the importance of international connections for creating wealth is strikingly obvious. Singapore exists because of these connections.

Ned Kumar left a comment to the effect that some places are the international hubs for certain skills and industries so therefore the value of local connections will be greater than international ones. I can’t fault the logic here, Ned. The research study I refered to in the post used a sample of Norwegian firms so the importance of international connections in most industries will be much greater in that country because of the relative size of the population.

After considering these comments, I think that we need have our own innovation globe to keep thinking about where we need to connect to in order to find the existing hubs of expertise and the emerging hotspots of new ideas and technology. It doesn’t have to be an exhaustive searching exercise but it probably does need to be done at least annually so we can at least see what we need to find out about (and Google is a whole lot more powerful and quicker than the encyclopaedia).

The Royal Society has just released a report on the global map of reseearch and development. While the geography of the core of R&D still lies in Europe and the US it shows some very surprising trends about how quickly other centres are emerging as new leaders in science and technology.

The fast moving cities are mainly based on or near the Chinese coast with Sao Paolo in Brazil also emerging rapidly as a front runner. If I was a CEO of a business based in the old centres of Europe and the USA I’d be wanting to know exactly what was going on in these regions. While companies in Europe and the US might be in the clusters of today, they need international pipelines to reach out to the clusters of tomorrow.

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You Get Better at What You Do

Posted by Tim in innovation strategy on 18 April 2011

If you want to get better at innovation, you have start innovating more.

That probably sounds obvious, but in practice, not all that many people do it.

I was reminded of this by an interesting post by John Gruber discussing Apple’s transition to cloud computing. It includes this section:

Jason Fried had a good cover story for Inc. magazine last month, on how to get good at making money. His advice in a nutshell: you get good at making money by actually making money:

“I can’t say enough about bootstrapping. Whether you’re starting your first business or your next one, my advice is to bootstrap it. Bootstrapping forces you to think about making money on Day One. …”

Eye-rollingly obvious, perhaps, but so is much of the best but most-ignored advice in life. Almost nothing worthwhile is easy, and it’s hard to just jump in and be good at something difficult right off the bat. Think, say, of Twitter, whose business plan, such that it is, has always been something along the lines of “Get big and popular, then just flip the switch and start making money when we feel like it”. There is no switch.

The only reliable way to succeed at anything is to actually do it, repeatedly, with concentrated effort. True for individuals, and true for organizations. Athletes, artists, businesses.

This is just as true of innovation as it is of anything else. We always want to be instantly good at new things (well, maybe you don’t, but I sure do, and so do a lot of people that I run across). You have to go through the experience of getting to the point where you’re skilled.

In innovation terms, that means that you get better at it when you start executing the innovation process: you generate ideas, you select the ones on which to concentrate, you figure out how to make these ideas work, and you get the ideas to spread.

There’s no way to simply jump to the point where you’re great at all of these steps. That’s part of my point with the innovation matrix – it’s the act of executing ideas that moves you up the Innovation Competence axis. Too often I’ve seen firms hope that getting the right tools is all they have to do to become more innovative.

The problem with that approach is that tools don’t make you execute ideas. They can help, but you have to execute ideas consistently, over an extended period of time to build innovation skills.

Because you can only get better at what you do, the way to get better at innovating is to start innovating.

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Global Pipelines Not Local Clusters for Innovation

Posted by John in innovation on 12 April 2011

How can we make businesses more innovative? That’s easy isn’t it? We just group them together into clusters (preferably in science park developments) and it will happen… won’t it? The trouble with this cluster theory of innovation is that it confuses cause and effect. When we see a successful cluster like Silicon Valley it’s tempting to asssume that the clustering made these firms successful. Jumping to the conclusion that clustering is a cause of innovation success has triggered a lot of government expenditure to create these ‘hot spots’, but what if clustering is an outcome of succssully innovating firms? Are clusters really an innovation ‘red herring’?

The trouble is that the evidence for cluster theory is really shakey. In a previous post I mentioned the cargo cult analogy for initiatives like clusters and the weight of evidence against clusters as a precursor to innovation. A recent study of 1600 Norwegian firms concluded that:

The results indicate that firm innovation in urban Norway is mainly driven by global pipelines, rather than local interaction. The most innovative – both in terms of basic product innovation and radical product and process innovation – firms are those with a greater diversity of international partners. Local and even national interaction seems to be irrelevant for innovation.

The full paper is definitely worth reading. It is robust research and if you don’t enjoy the stats then skip to the conclusions. The findings make sense to me. If we are thinking of innovation as an open ecosytem then why should all the significant people and firms be in one city. The world is a big place. Australia, for example, is 2% of the global economy. Why would any firm want to priortise connections in one city that is just a drop in the international knowledge pool?

The really interesting part of the study is the relationship between managerial mindsets and the deliberate formation of international linkages.

…what this study has demonstrated is that the attitudes of individual managers play an important part in the innovative capacity of their firms. Open-minded managers without excessive regional orientations are often in charge of firms which develop a greater number of international interactions of the sort that promote greater innovation.

This has implications for developing innovative industries. For most of the 20th century, Sweden was an economic backwater with low standards of living. One of the really smart things that the Swedish goverment did was to sponsor students and young professionals to work and study overseas. In developing connections through this program, they also encouraged firms to be more innovative.

I’m currently reviewing a research paper based on a sample of Canadian firms that also finds a link between innovation and internationalisation. In a survey of firms in Brisbane, Australia (the Brisbane Innovation Scorecard) we also found a close relationship between innovative firms and connection to international markets. At least one study shows that international activity can preceed innovation rather than the usual assumption that innovative firms grow to compete in international markets.

Travel broadens the mind…. and makes you more innovative too.

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Use Innovation to Disrupt Dominant Logic

Posted by John in innovation on 5 April 2011

One of the ‘quick facts’ that I like to mention in my strategy seminars is that only two of the top 100 US firms in 1900 are still around today. In Australia, the stat isn’t much improved and it points to the extreme difficulty of maintaining the performance of organizations over extended time frames.

Of course, some organizations disappear through mergers and acquisitions but a major reason for the disappearance of firms is that they fail to adapt to a changing environment. Often, the environmental threat seems to be obvious to everyone except those inside the business. The strange rationalization of old business practices seems to defy rational explanation. Tim has previously used the example of a media company trying to work out how the internet can augment the newspaper offering. To the rest of us, the newspaper is a burning platform and the question of ‘how do we use the new technology to support the core business’ is simply the wrong question.

There are many other examples of these situations where organizations get stuck in the old business. A colleague who was a Monsanto executive tells me that Monsanto went into genetically-modified crops as a way of supporting the core business of herbicide manufacturing. Under patent, Roundup (glyphosate) was a license to print mony. After in went off patent, Monsanto looked for a way to make it profitable again by making Roundup resistant crops and thus began their fateful GMO journey.

In fact, this situation is so common that business academics have developed the idea of ‘dominant logic’. I’ve been doing a bit of reading on this recently and the following model by Bettis and Prahalad summarises how a dominant logic forms and how it stops new information coming into the organinzation.

It’s a simple model that shows how organizations learn to become very good at a particular business. For example, Monsanto and herbicides, newspapers or Nokia and mobile phone products. To become leaders in the industry, firms need to have an intersection of culture, performance measurement and strategy. The trouble is that this focusses managerial attention on the information that fits with the business. If I am in the business of manufacturing gasoline-powered cars then I will focus my attention on what my competititors are doing and what my customers are wanting. Information beyond this immediate environment is of lesser concern. The creation of a dominant logic might help with maximising short-term returns but it also makes the company highly vulnrerable to disruptive innovation.

One way of avoiding the dominant logic trap is to create space inside the business where new logics can be created. Tim talks a lot about the importance of experimentation in business model innovation and the real challenge here is that these experiments will often contradict the dominant logic. If the standard business case test is applied to these experiments, the risk is that they will be knocked over by the dominant logic. Alternative logics need to be incubated and shielded from the core. This requires leadership and vision.

Having more than one logic in a business makes it more resilient and able to detect changes in the environment. The formation of a singular dominant logic will mean that significant changes in the operating environment will be ignored or misunderstood.

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