I was doing some work with a company this week, and ran across one of my pet peeves. The organisation itself was very exciting. We interviewed over 20 people about various projects that were going. To a person they were smart and engaging, with great ideas, vision and energy. It was invigorating. The number of exciting projects that they have on the go is enormous. So what’s the problem? The problem is that many of these projects will never get off the ground. Why? Because they might cannibalise existing business.

This is the worst possible excuse for killing innovation. In many ways, if you worry about cannibalisation, you are falling into exactly the same trap that makes Net Present Value project evaluation so flawed. Earlier this week, Ralph Ohr and Wim Rampen both pointed me to an article that illustrates this flaw perfectly. The article is called Innovation Killers, by Clayton Christensen, Stephen Kaufman and Willy Shih from the January 2008 edition of Harvard Business Review. They include this diagram:

This shows the problem perfectly. NPV analysis assumes that our current level of performance will remain stable and that is the probable future that is used to evaluate new innovative projects. However, the ‘do nothing’ option does not result in staying at the same level of profit and performance. If we do nothing, our performance will decline. We will be worse off because someone out there is figuring out how to destroy our market. If we try new things, and they work, we might stay ahead of them. If we don’t, they’ll knock us over. There’s no way around it.

This same flawed assumption is being made when people worry about introducing new ideas that will cannibalise their current product or service lines. Of course they will. But again, the do nothing option does not result in ‘everything stays the same’. The do nothing option results in someone else doing the cannibalising.

Halfway through the day, our host said this:

When we compare ourselves to our current competitors, we look pretty good. We’re innovative and ahead of the game. But that’s the wrong comparison. I’m not worried about the people already in our market. I’m worried about the people I’ve never heard of.

Exactly.

The simple fact of the matter is this: we must introduce innovations that take away our current market share. There’s no such thing as a cash cow – if you have a product that is dominating the market, but you’re not innovating around it, it’s not a cash cow, it’s already dead.

Cannibalise your current products. Kill your best performers, or someone else will kill them for you.

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In a recent post Tim mentioned a comment by a representative of an Australian university tech transfer office at an investor’s conference the other week. As Tim says, he was declaring the death of open innovation and a return to ’sensible’ IP strategy, where we patent everything and then try to sell it or license it out.

If you’ve been reading Tim’s thoughts on patents or my post on the evidence for the Gollum effect of IP being a barrier to innovation, you can probably guess our opinion on the ‘death of open innovation’ declaration.

We are concerned that there is a growing confusion about what open innovation is (and isn’t) so I thought I’d write about an excellent review of the topic by Linus Dahlander (Stanford) and David Gann (Imperial College, London) that’s about to be published in one of the leading academic journals on innovation.

As Linus and David point out, open innovation is far from being a new phenomenon.

In the late 19th century, Edison’s laboratory – the Invention Factory at Menlo Park, displayed characteristics that in many regards had an open approach to innovation. The commercial development of electric lighting, for instance, was the product of a team of engineers that recombined ideas from previous inventions, collaborating with scientists, engineers, financiers and people in marketing outside the laboratory.

However, what is changing in innovation is the steady increase in the use of external ideas and external paths to market. Far from being a fad, this changing face of innovation is part of a shift towards alliance capitalism where companies pursue specialization but also collaborate to access capabilities that make their specializations more valuable.

I think the highlight of the review paper is a reminder that open innovation is a continuum (not just open versus closed as the only options), and that open innovation takes on several forms. The 2×2 matrix categorizing open innovation into inbound versus outbound and pecuniary versus non-pecuniary is particularly useful.

Inbound and outbound innovation is straightforward but the pecuniary versus nob-pecuniary dimension means that a lot of innovation isn’t based on ownership and formalized transactions. There are times when firms can give away technology and ideas as part of their innovation strategy. As Tim has said previously, free can be a valid business model in the right circumstances.

But here is where the conference speaker got confused. Revealing is not the only form of open innovation. When we think about open innovation as a range of activities that firms undertake to create and capture value by externalizing the innovation process, we start to see how common open innovation really is. Linus and David’s review shows the diversity of open innovation in the following table.

So….open innovation isn’t new, it’s not just about giving away ideas and it’s not going away.

Source: Dahlander, L., Gann, D.M., How open is innovation? Res.Policy (2010), doi:10.1016/j.respol.2020.01.013

I have a confession to make. Although I have been teaching business strategy and innovation management for over ten years there is always a doubt in my mind over the value of what I bring into the classroom. If you looked at my collection of PowerPoint slides and readings, you would see a bag of tools for analysis but I have never really believed that these tools, such as industry analysis, scenario planning and value chain analysis, were really very important.

My late grandfather was a self-taught businessman who created a large construction company. He was always amused by the idea that people could study business and often asked me when I was going to get a real job. Everything that the managers of the company knew was based on ‘rules of thumb’, learned from experience rather than studying ‘tools’ in a business school. What he was actually saying is that there is no shortcut to learning ‘rules of thumb’.

These rules of thumb are otherwise known as heuristics. In a complicated world, heuristics help us to process information and simplify decision making. We use heuristics every day in all sorts of ways. For example, I never go into an empty restaurant, or a full platform means that I need to run because the next train is coming soon. Malcolm Gladwell’s book, Blink, is an excellent read if you are skeptical about the importance of intuition and heuristics in rapid decision making.

Experienced innovation managers also use heuristics. Tim and I were talking to managers the other day who had worked out that they needed to quarantine innovation projects from other business activities. Now, there are a whole bunch of research results and theories which tell us why this is a good idea, but the company had arrived at this conclusion without any of these.

Experience can allow us to develop heuristics but this can be slow and sometimes very expensive (my grandfather’s business didn’t survive to learn from the effect of borrowing to fund big projects at the top of the business cycle). Is there an alternative and can we teach heuristics?

I think the answer is yes and I was provoked into thinking about this after Tim wrote his post about analysis and interpretation. Here he was questioning the emphasis that we place on tools for analysis at the expense of more expansive exploration of possibilities for innovation.

I agree that focusing on analysis will probably make us less innovative but what if we tried to emphasize the heuristic value of analytical tools? If we actually blended the tools with people’s experience and existing heuristics then possibly we can get past the tool as a thinking constraint to a point where the tool is a catalyst for thinking about new possibilities.

We can teach heuristics, but it means that the teaching style must be different from the old models based on simple content delivery (sadly, still very prevalent is most business schools). Rather than the educator being the conveyor for information, they become a facilitator of an interaction between the ‘tools’ and the experiential knowledge of the learner.

I run an executive education course in strategy and I think that one way to get the interaction going between tools and heuristics is to use a ‘live case’ teaching method where some of the managers bring strategy problems to the course that are worked through during the week with other participants in the course. The result is that preconceptions are challenged and tools are applied and adapted for purpose, with the result being a new set of heuristics and a new way of seeing business problems and opportunities.

We have a vast mountain of tools and frameworks from authors, academics and consultants. How many of these are genuinely valuable as heuristics that change the way we see the world?

Flickr photo from Mara under creative commons license

The word “network” causes a lot of the same problems that “innovation” does – it is used in so many different ways that it is often hard to tell exactly what the user means, it’s in fashion to the point of sounding like hype, and as a consequence a lot of people are ready to stop using it altogether. So when I say that “the economy is a network” it can cause some confusion. Do I mean it is like a network? That is has network-like properties? That it’s something between a hierarchy and a market?

No. I mean that the economy is a network – and that the best way to analyse it as a network. In network analysis, a network consists of nodes (people, firms, countries and so on) and the connections between them (economic exchange, friendship, family relationships, disease vectors and so on). An economic network then is one where people are the nodes, and the economic relationships form the connections between them.

Thinking about economics in this way leads to some useful insights. I was reminded of this when I read Umair Haque’s latest post today – The Real Roots of Recovery. Here is how he sets up the problem that he’s trying to address:

What is an economy? Is it just rivers of money and stuff, flowing back and forth between consumer and producer, resting on a bed of information? That’s more or less the way we’ve conceptualized it. It’s why economists often say that banks and funds make up the “financial economy,” while industries that make stuff are the “real economy.”

When we conceptualize an economy that way, the implicit goal for both “producers” and “consumers” is merely accumulation of money and stuff. More, more, more. That’s what I call a “thin” economy. That kind of economy is thin in three ways: it’s brittle, easily broken; it’s fragile, crisis-prone; and it’s as shallow as Paris Hilton.

His suggestion is that to make a stronger economy, a “thick” economy, we need to focus on making real connections with others.

Yet even that’s just a beginning. The economy is “constructed” by us: built anew every second of every day by each of our billions of tiny decisions, emergently. The real change begins with each of us, and the choices we make.

This is a network story! The issue with networks is that ties are expensive to maintain. If we think about economic ties, the involve money, attention, time and care. My read of Haque’s argument is that we tend to only think of the ties in terms of exchange. In this view, we choose to buy a loaf of bread, we pay for it, and that’s that. That’s thin. A thick network tie will consider attention, time and trust as well.

What does this mean in practical terms? If we think of our economic relationships as network ties, then the idea that every transaction is a one-off makes no sense at all. Each time we need something, we have to figure out who is cheapest, where they are, and how to make that transaction. On the other hand, if we think of economic relationships as network ties, as something that persists – we value them differently. Now trust becomes more important, as does attention. We want ties that we don’t have to worry about because we know what we’re getting. We want a stable, persistent network. The way to get that is to build relationships with the people in our personal economy. We don’t have to recreate a whole new network each time we need something.

Viewing the economy this way also changes where we want to be in the economy. Take a look at this network diagram from Valdis Krebs:

The people that I’ve circled are those with high betweenness centrality (learn about that here). In an exchange economy, those are great positions to be in because you can take advantage of your position in between two big clusters. Any goods or information that has to pass between the two groups has to go through you, and this is profitable. However, this also leads to a brittle network. If you lose the people with high betweenness, the network breaks down as the groups become isolated.

If you take a network view of the economy, you become worried about the overall structure of the network. You build links between people so that there is redundancy in the network (network weaving!). This is the strategy that O’Reilly Media has used very successfully. In a network economy, we try to build up the structure of the network to increase resiliance.

Finally, thinking about the economy as a network helps with innovation. In an exchange economy, you just have to get your new ideas out there. If they are better, people will buy from you. Everyone that has ever tried to get a new idea to spread knows that it’s not this easy. We have to get people to disconnect from whatever ideas they’re currently using and adopt ours. If we think of the economy as a network, this process makes sense. Our innovative ideas (new products, newservices or new ways of doing things) have to build new connections. Often this means that we need people to break old connections. This is the central problem in idea diffusion.

The economy is a network. Think about it this way and suddenly we move beyond transactions. The nature of the economic ties between us becomes much more important. These ties involve money, time, attention and trust. If we pay attention to these four things as we build up our economic network, we’ll start building a thicker, more resilient economy.

In all of my longer innovation courses, I use this video by Malcolm Gladwell in the first lecture. It’s his TED talk from a few years ago, and if you haven’t seen it yet, it is well worth your time:

Gladwell recounts the story of Howard Moskowitz, who did the consulting work that led to the development of, among other things, extra chunky spaghetti sauce from Prego. The story involves how Moskowitz conducted a number of taste tests for different products. Usually, the data did not make any sense when he analysed it trying to find the perfect taste combination for Pepsi, or spaghetti sauce, or coffee. His insight came when he discovered that instead of one optimum, there were multiple optima for each of these products. This is how Prego went from making just one spaghetti sauce to making regular, robusto and extra chunky.

One of the things that I emphasise in these early lectures is that innovation involves making new connections (Schumpeter had this idea first though, not me!). To encourage people to get some practice in making novel connections, I use a number of videos like this – which are not directly about innovation, but which have something important to say about the process – and I ask them to figure out what the innovation lessons are.

Here are some of the ideas that commonly come up with this one:

• The first interesting bit is how Moskowitz saw the multiple optima idea ‘like a bolt of lightning’. The popular image is that this is the way that inspiration works. But note that Moskowitz was equipped to receive this bolt of lightning by many years of hard work and intensive study. It’s like the story from Gordon Gould, one of the people that invented the laser (quoted from The Myths of Innovation by Scott Berkun):
  

  In the middle of one Saturday night… the whole thing suddenly popped into my head and I saw how to build the laser… But that flash of insight required the 20 years of work I had done in physics and optics to put all of the bricks of that invention in there.

  It’s another version of “chance favours the prepared mind.”

• The second point is that the innovation wasn’t really the new products – it was the process that led to their introduction. It was the idea that there was no perfect spaghetti sauce, just perfect spaghetti sauces. As Hugh MacLeod says:
  

  Products are idea amplifiers. The molecules and/or bytes are secondary.

• The third point, and this one is huge, is that focus group testing never revealed the desire for extra chunky spaghetti sauce. Moskowitz discovered this opportunity by testing, watching and recording what people ate and what they liked. Their actions said that they wanted extra chunky, even though this desire was never articulated. That’s what design-driven innovation is designed to get at – unarticulated needs. And when it works well, the results are like those that Prego achieved with extra chunky – very profitable!
• Finally, it shows the process of innovation. Moskowitz had his flash of insight, and he was pretty sure that he was right. But then he had to go out and execute his idea. This took a huge amount of work. And only once he had proven that process worked through working with Prego did the idea diffuse more broadly. Those are the three steps in innovation: develop a great idea, figure out how to execute it, and get it to spread.

So there’s a lot to be learned about innovation from spaghetti sauce. What ideas strike you when you watch Gladwell’s talk?

A patent is not a business model, and we need to stop acting like it is.

One of the statements at the Australian Association of Angel Investors Annual Conference that really rubbed me the wrong way came from a person in a university technology transfer office who said something like: “Open innovation is dead. It was just a fad, but companies are now realising that they have to have protectable IP if they are going to succeed.”

This is wrong in just about every conceivable way.

Stefan Lindegaard is one person that provides an excellent set of resources concerning open innovation. In one of his recent posts, he included links to a HUGE range of resources on open innovation, including a list of firms using it (including 3M, BMW, Dell, GlaxoSmithKline, Huawei, and Unilever), and numerous open innovation intermediaries, software and conferences. The inclusion of firms like GSM and Unilever are particularly interesting, since they are both in industries that have the capability of benefiting from patent protection, yet they are still pursuing open innovation. This actually makes sense, because open innovation was originally designed as a method for getting more patented technologies into play. The idea is often caricatured by opponents as meaning ‘please take all of my ideas and use them’ – this is patently absurd.

However, my biggest problem with the statement is the contention that having protectable IP is the only way to succeed. I guess this is understandable coming from an organisation whose primary performance metric is patents generated. As John has pointed out, overall, patents are a lousy proxy measure for innovation.

The focus on patents and IP is simply another incarnation of the overemphasis on ideas. The built-in assumption here is that once you have an idea that no one can copy, then you’re set. But we know that’s not true. Ideas have to be executed, and they have to diffuse – and empirically we know that these are the parts with which most organisations have difficulty.

A great idea is a core part of any business model. However, it is simply that – one piece of the puzzle. You still need to know who benefits from your great idea, and how to get your idea embedded into the value network. You need to know how to generate revenue from your idea. Patents create scarcity, and that is one way to make money. But there are others. One of the reasons that open innovation being used more widely is that it lets you outsource idea execution and idea diffusion to partners that are better at it than you are. That is why many organisations use open innovation strategies to take advantage of ideas that have patented, but which they are poorly equipped to execute.

We have to stop thinking about patents and intellectual property as ends in themselves. They are components that can built into successful business models. They are one way of certifying that our ideas are good. But as we’ve said many times here, great ideas are not enough. Let me repeat that: great ideas are not enough. To succeed, we have to better than our competitors at executing our great ideas, and better at getting them to spread.

(picture from flickr/gurdonark under a Creative Commons License (of course!))

John’s post How Accountants Kill Innovation ended up causing a bit of a stir this week. The press release that went with it was pulled from the UQ Business School website complained about it, but the post here got a huge number of reads, and the press release got picked up by BioTechnologyNews.net, where it was popular enough to end up as that site’s story of the week on Industry-News.net. Part of the traffic on the blog here was driven by the 21 tweets that it got (including one from CPA Australia – so accountants nationally are maybe not as thin-skinned as our local faculty).

All of which is interesting from the standpoint of tracking how ideas spread. Idea diffusion is one of the key things we talk about here, but that’s not what I want to talk about today. I’m interested in the analytical aspect of John’s post. He was talking about research findings that show that in Australian Biotechnology firms, using a Real Options valuation approach leads to better innovation results than using Net Present Value to evaluate potential projects. Firms using NPV actually had a negative return to innovation in their study – so the title of the post really should have been How NPV Kills Innovation. But then the idea wouldn’t have spread nearly as well.

The thing that concerns me about the study though is the use of tools in the first place. I recently read Innovation: The Missing Dimension by Richard Lester and Michael Piore. It’s one of the most insightful books that I’ve read in a while, and I recommend it strongly. Lester and Piore are reporting on the results of a massive number of case studies that they conducted in the cell phone, blue jeans and medical devices industries.

Their key finding is that to innovate succesfully, firms need to be good at both analytical and interpretive processes. Real Options and NPV are typical analytical processes that are used to evaluate potential new products. Lester and Piore argue that in addition to these types of tools, firms also need to be able to interpret the needs of their customers (which is essential the argument of Roberto Verganti in Design-Driven Innovation as well). Here’s how they describe it:

Analytical processes work best when alternative outcomes are well understood and can be clearly defined and distinguished from one another. Interpretive processes are more appropriate when the possible outcomes are unknown – when the task is to create those outcomes and determine what their properties actually are. These two ways of proceeding involve very different kinds of skills, different ways of working together, different forms of managerial control and authority, and, ultimately, different ways of thinking about the economy. The two processes are in fundamental opposition to each other, making it difficult for people to think about both of them at the same time. Yet the ability of businesses to think about these two approaches separately and to manage them simultaneously is the central challenge of product development.

That’s the real problem – analytical tools like NPV kill innovation, but we need them (or at least something like them) to innovate. The real achievement of Lester and Piore is to document how we need both analysis and interpretation in a wide variety of industries, and they include some suggestions for doing this successfully. The main one is to be aware of the necessity of both processes and how to use them effectively.

Interpretive processes are most important at the start of developing our new ideas. Design-driven tools are very effective early in the process, and they do lead to finding new competitive spaces. Disruptive innovations are most likely to arise from interpretive processes.

Because interpretation requires ambiguity and extended conversation, the biggest thing that managers need to do is to prevent shutting down discussion too early. This is the tendency in organisations dominated by analysis – they jump to a preferred option far too early.

The time to use analysis is once you have settled on the ideas that are best. This is the time to optimise things.

Innovation is filled with difficult contradictions to manage – incremental versus radical, short-term versus longer term, open models versus closed, and analytical versus interpretive. In most cases, firms need to find a balance between each of these oppositions. It is hard to do this, but the firms that are successful at finding these balances also tend to be the most innovative. And the most profitable.

Innovation 1.0: A guy in his garage

Innovation 2.0: A team in their research lab

Innovation 3.0: People – dispersed….. everywhere!

And we’re going to skip right over Innovation 4.0 – Innovation 6.0 to introduce the best, most up-to-date, most exciting version of Innovation yet – yes, that’s right:

Innovation 7.0!!

If you’re using Innovation 3.0 right now, Innovation 7.0 is four better!!

Innovation 7.0 is innovation that’s embedded in your actual cells! It lets you crowdsource your customer-related design-driven open innovation! What could be better? Nothing! If you’re not using Innovation 7.0 right now, your competitors will crush you like a bug! You’ll be like Kevin Kline – stuck in cement, and your competitors will be like the steamroller!

OK, so maybe Innovation 7.0 is a lousy idea. As I’m writing about it, I realise that there’s not much substance to the idea – it’s mostly hype. We should probably just ignore it.

I ran across two things this morning that got me thinking about hype and innovation. The first was a post by George Siemens talking about Web 3.0 for libraries. George critiques an article by saying that the ideas in it are basically sound, but that by wrapping them into the Web 3.0 idea it gives them an unuseful air of hype. And then there was Scott Berkun’s suggestion that we stop using the word ‘innovation’ completely. He makes two main points – that innovation is defined so broadly that it’s a useless term, and that firms would be better off aiming to be competent before they even think about being innovative.

I’ve got mixed feelings about both posts. I agree with Berkun’s second point to a degree – that’s why we keep talking about the importance of executing ideas. Doing things well is where many firms fail so improving the basics of performance is an imperative for many.

And businesses in particular are certainly vulnerable to fads in thinking, so hype can in fact be dangerous. On the other hand, I’m not sure that saying ‘don’t use this phrase’ actually gets us very far.

Here’s an argument that parallels Berkun’s: a penguin and an eagle are both birds, yet they look completely different, they act differently, they live in different environments, there’s no clear connection between the two of them. If we try to use the word ‘bird’ to describe two such obviously different things, then it is a useless word, and we shouldn’t use it at all.

Innovation can be defined clearly. It does get used to signify many different things – because it describes a broad phenomenon: executing new ideas so that they have economic value. It’s a classification equivalent to ‘bird’. Of course there are different ways to do this. There are many different ways to do this. Which is why we have so many different types of innovation to discuss. Incremental and radical, open and closed, design-driven and customer-focused: penguins and eagles. They are among the many different ways that we can execute ideas with economic importance.

I love Berkun’s The Myths of Innovation – nearly every idea in the book is worthwhile. But I don’t agree with him here. Of course we must execute more effectively. And yes, don’t believe the hype. And use language as precisely as possible. But I don’t think we can afford to throw out the concept of innovation just yet. I think there are a lot of great ideas out there that we still need to execute. You can forget “Innovation 7.0″, but we still need “innovation”.

I ran across this story earlier this week about Ludwig Wittgenstein in an otherwise awful piece by Paul Monk in The Australian:

A student says to Wittgenstein, “You know, it’s really not surprising that people believed for so long that the sun revolves around the earth, because it looks like that is what happens.” To which the philosopher responded, “Really? So, what would it look like if, actually, the earth revolved around the sun, while turning on its axis?”

One of the key ideas in the business models research is that once a firm develops a successful business model, they tend to replicate it with all of their future innovations. Organisations get stuck in particular business models that become their dominant logic – and this often prevents them from innovating effectively.

Today I have some very simple questions for you: what parts of your business do you completely take for granted? What parts are so obvious that they look just like the sun revolving around the earth? What would happen if you thought of these parts using a different perspective?

If you start taking these questions seriously, you start getting into the area of design-driven innovation. I keep saying that we don’t need more ideas, we simply need better ones. This is one way to get better ideas. Take your foundational assumptions, and find a different explanation for them. This leads to new business models, and this is one of the most effective forms of innovation.

One of the key skills in innovation is seeing things differently. It’s the best way to create novel connections of ideas – and that’s the fundamental creative act in innovation.

This isn’t going to be one of those rants against ‘beancounters’. We have actually collected and analysed data which tells us that traditional accounting and valuation methods will damage innovation performance. To be fair to my accounting collegues (some of my best friends are accountants) the main conclusion from our study is that we need a different type of accounting to manage the innovation process. In particular it’s the project selection step (or the filtering step in Tim’s aggregate, filter, connect model) where planning and valuation methods can make or break innovation.

In the study we surveyed Australian biotech executives on how they used financial criteria to select innovation projects. With responses from about 100 firms, we were able to see that there were two styles of innovation planning.

The traditionalists used best estimates of market size, cash flows and chances of success to arrive at a value of the project. For those of you with a working knowledge of financial management, their style was closely aligned to net present value analysis.

The other group placed less emphasis on prediction and valuations and were prepared to stage investments in the project. As the project showed promise (or not) funding would be increased or discontinued. In finance terms, these were the ‘real options’ managers. Like a stock option, they were prepared to ride the uncertainty by taking an initial stake in the upside but also recognized that options are valuable because they limit how much will be lost if the project doesn’t perform after the early stages of development.

When we compared these financial management orientations to innovation performance (as measured by patents, which is valid in biotech) the first result was unsurprising. Real-options management was positively and significantly correlated with innovation. However, the second result was a bit unexpected.

The traditionalists using mainstream planning approaches (NPV managers) were negatively correlated with innovation performance. In other words, imposing strong traditional financial criteria for project selection made the firm less innovative than firms that had no particular financial criteria for the selection of projects!

I think this leaves us with three takeaways for managing innovation.

1. Innovation means trying things out and failing. Attempting to provide detailed plans and forecasts regarding what is going to work will mean missed opportunities.

2. Large firms with traditional planning processes and valuation tools need to create different procedures for managing innovation.

3. We need to change the way we value innovation projects and include the upside of uncertainty in our assessment. While we focus on the downside risks with innovation projects, how many of us consider that risk has an upside too. Risk reduces the value of businesses in traditional valuation tools.

This research paper was written with Mat Hayward, Andrew Caldwell and Peter Liesch. It is currently under review for a journal.

Abacus picture from Flickr by Obraka under Creative Commons license