Next time you get in a car to drive somewhere, take a minute to think about how many parts of the economy are connected to your trip. There are a whole lot. There all of the people and firms involved in building your car. They have taken ideas and designs that have evolved for over a hundred years, added some new ideas, and come up with the design for your car. And if you drive a Toyota, it’s not just people in Toyota that have done that – there are hundreds of other firms that have designed particular parts – brakes, stereos, and windshield wipers.

Then another bunch of people and firms built the actual car. For the vast majority of cars, this didn’t happen in the city or town that you live in – so yet another bunch of people and firms were involved in getting the car to your particular location so that you could buy it or lease it. This includes shipping companies, trucking firms, and dealerships.

So that’s a lot of people involved with just getting the car to you in the first place. Now you turn it on – petrol ignites (if you’re driving a hybrid it takes a while longer to get to this point, but it still happens). How did that get to your car? Another chain of research, design, production and distribution. Thousands more people and firms.

Then you start driving. On what? Roads. How did they get there? Same story, although in this case a government almost certainly had something to do with it.

Every single thing in the economy is embedded deeply into these economic networks. Design, production, distribution – no matter what we’re talking about, nothing stands alone.

When you come up with a great new idea, you need to think about this economic network in two ways. The first is: how can I connect to all of the complementary parts of the economy that are needed to get my idea to work? The second is: if I’m going to get my idea to spread, which of these existing connections need to be broken?

We’ve talked before about the importance of making new connections to get your idea embedded within the economy. But breaking connections is also important.

Ford wants to get me to break my connection with Toyota and forge a new one with them. If they are successful, the overall economic network impact is relatively small. Many of the same firms are involved in making parts for both Ford and Toyota. Many of the same shipping and trucking firms move vehicles for both. I’ll drive my new Ford on the same roads, and I’ll probably buy petrol from the same stations. So the impact of that change is small.

But what if I want to buy a Honda FCX? Then things get a bit more complicated. The FCX is a hydrogen-powered car, and it’s pretty cool. But if I want one, I have to break my connection with Australia, and rebuild the one with California, because that’s the only place they’re being sold. And because they’re only sold through fleet sales, I’d have to get a job that is affiliated with the right car fleet program. So on a personal level, the connections that I would have to break to buy an FCX are much more substantial than the ones that have to be broken if I just switch to a generic Ford. And it’s extremely disruptive.

The changes required by the FCX are pretty disruptive within the economy as a whole as well. We’ve got roads already, so that at least is covered. And some of the parts manufacturers will be the same as those involved with making regular cars – tires, seats and body parts will all be essentially the same. But a lot of new suppliers need to be added to the supply chain for hydrogen-powered cars. There are hydrogen fuel cells, which replace the petrol tank. Hydrogen requires a different ignition method, so the engines have to be completely different. In connecting to manufacturers in these new areas, Honda is breaking connections with suppliers that have gone back many years.

Many connections need to be broken outside of Honda as well. Where do we get hydrogen for our hydrogen-powered cars? Currently there’s no infrastructure for this. We need new plants to make fuel-quality hydrogen, new methods of transporting this hydrogen once it’s produced, and new places to get the hydrogen. These will actually replace oil refineries, oil pipelines and petrol stations. That is a lot of disconnecting.

Everything is embedded within the economic network. So when we have a great new idea, we need to get people to connect to it to get it to spread. As Umair Haque says, we do this by making it awesome. However, we also have to be aware of the connections that need to be broken to get our ideas to spread. This can get pretty complicated. It’s not just Toyota and Ford that don’t want me to connect up with a Honda FCX. It’s Shell and BP, and all the companies that make petrol-driven engines, and all the petrol station owners, and many more. A lot of these firms will actively fight to prevent having the connections broken.

This is why having a great idea, and even executing it really well, aren’t necessarily enough. The critical third part is to get your idea to spread. This isn’t meant to be discouraging. I’m simply saying that for our innovations to be successful, we need to think about where they fit within the economic network. A lot of these connections are relatively in obvious in the case of cars, but even if you’re introducing a simple new way of doing things, you have to get people to disconnect from the old ways too. By thinking of the economy as a network, we’ll get better at getting our ideas to spread. But to get people to connect with our new ideas, we have to getting them to disconnect first. Yesterday I said that making connections is the fundamental creative act in innovation. This is definitely true when we are generating great ideas. When we are getting them to spread, connecting our ideas to people is important, but so is getting them disconnected from other ideas. That’s the key challenge in innovation diffusion.

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In this week’s class we talked about Jeff Bezos’ TED talk. When I think about innovation, to me the central part of the process is connecting ideas. As I keep emphasising, once we’ve done this, we then have to work like crazy to execute them well, and to get them to spread. But we need to start with great ideas, and we get these by making novel connections. I like this talk because there are several great examples of the importance of connecting in innovation.

The first example of connecting works at the meta level. This is a great example of confronting an uncertain business situation (what do we do about the internet?) through the use of analogy (trying to find the most comparable set connections out of several possibilities). In this case, Bezos takes on the idea that the internet was like the gold rushes of the 19th century. This was a common idea after the dot.com bust. He argues that this comparison is not the most accurate one, and that a better analogy to use would be that the internet is like electricity.

Bezos also demonstrates the importance of connecting ideas with all of his examples of repurposing. As he says, homes weren’t wired so that they’d have electricity, they were wired so that lights could be installed. However, once the houses and businesses were wired for electricity, hackers found many uses for it that had nothing to do with lighting. That’s how electrical appliances got started. It’s yet another example of how innovators often don’t know how their new ideas will ultimately be used.

And Bezos has multiple examples of making innovative things by combining existing ideas. The toaster is a good one. Prior to electric toasters, people made toast over fires, or using a rack on a stove. Once homes were wired, someone figured out that you could use electricity to heat an element stuck in the middle of the same kind of rack. It was a creative recombination of ideas – connecting ideas – that led to the innovation.

Finally, he shows the value of trying many possible combinations of ideas. Not all of them work, and in retrospect the ones that don’t look stupid. Like the electric tie straightener, and the stupid dot.coms. But that’s the essence of innovation – experiment widely to see what works. Find has many new connections between ideas as possible, and try them out. This leads to waste – so we need to find ways to test these new combinations as quickly and cheaply as possible. But since we don’t know in advance which ideas will work, the best way to filter them out is through experimenting.

We often talk about how organisations can place too much emphasis on aggregating ideas. Instead, I think we need to focus on getting better at connecting ideas in novel ways. This is how innovative ideas arise. There are skills that help in this regard – pattern recognition, lateral thinking, and so on. If you’re trying to be more innovative, try to build these skills. Don’t try to compile more ideas, focus instead on making more novel connections, because that’s the fundamental creative act in innovation.

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We have been following a bit of a theme lately on valuation methods and selecting innovation projects. This was started with my post on some research that we have been doing on valuing innovation projects. Using surveys and quantitative analysis the study showed that traditional valuation methods such as net present value inhibited innovation. However, treating an innovation project as a real option was positively correlated with successful innovation.

Following this post, a few readers pointed us to Clay Christensen’s essay on the NPV trap, which is very supportive of the survey results. Tim subsequently wrote a blog piece on this too.

If traditional valuation methods are so flawed when selecting innovation projects, then it’s probably worth saying a bit more about real options. One reader of the blog, who runs a VC investment company specializing in high-tech ventures, said she had been using real options to make investment decisions for several years and found the outcomes to be much better than traditional methods for valuing projects (thanks Deb!).

What got me thinking about real options in the first place was a finance colleague who gave me an excellent article from the McKinsey Quarterly. It’s quite old now but I still think it’s the best introduction to real options and innovation strategy so I will use some of the ideas in this post.

The first thing to think about is how to value a financial option. I won’t go into detail on this one but some very smart people won the Nobel Prize for this and then nearly brought down the global economy when they used their equations to manage a hedge fund called Long Term Capital Management (now that really is academic impact!).

In the equation for valuing a stock option, increasing uncertainty and time to expiry increase the value of the option. The cost of exercising the option decreases its potential value, as does the revenues that we might lose by holding the option, rather than the underlying stock.

The value of a real option works in exactly the same way, as explained by this diagram from the McKinsey Quarterly overview.

The most important issue for managing innovation projects is that uncertainty and time increase the value of the project. In traditional valuation methods, these variables decrease the value of the project. Innovation always involves uncertainty and longer time frames and is therefore highly compatible with real options.

But taking a real options approach to innovation can tell us more than just valuation. It also tells us how to maximise the value of the project by constructing it as a real option where we can maximise its value by looking at the variables that make the option more attractive. For example, can we take an initial stake in the project as an option that will allow us to hold the option for a long time? Can we decrease the costs of exercising the option by finding potential partners to help us take the innovation to a bigger market?

This gets a bit abstract so I will use a recent example of an Australian oil and gas producer that is buying a ‘real option’ in producing biofuel from algae.

In this case uncertainty is high. The technology is unproven and nobody really knows what the oil or carbon price will be in five years time. Given that Beach Energy owns the tenements in the Cooper Basin where the algae farms are proposed, the potential time to expiry is very long and the exercise price is also relatively low. It’s a very good case for constructing the business case as a real option.

Beach does this by staging the investment with an alliance partner. If the initial scoping study or the pilot plant fails then all they have lost is the minimal investment in the early stage of the project. They can exercise the option by scaling up production if the industry conditions make the project economically feasible.

Again, the most important point is that there is value in embracing uncertainty and learning by trying things out.

Source: Leslie and Michaels (1997) The Real Value of Real Options. McKinsey Quarterly (3), pp. 97-108.

Here are two quick connections that I made today relating to innovation.

First – watch this:

It’s called “All Creative Work is Derivative” by Nina Paley, and here’s her description of how she made it. Brian Arthur argues in his book The Nature of Technology that all new economic ideas build on the combination of things that already exist. I think that this is an excellent way to think of creativity – that it is about making novel connections. Innovation is then about getting these creative ideas to spread.

Second – check out this picture:

It’s from an excellent blog post called “Four Dimensions of Innovation” by Ellen Di Resta (definitely check out her blog – it’s very good). It is one of the best frameworks I’ve seen for classifying some of the important subsets of innovation. She talks about the differences between innovating at the more straightforward end of the spectrum – creating innovations for optimisation and for improvement. However, creating innovations for invention and disruption are harder.

Di Resta correctly points out that these types of innovation require different managerial skills. The problem is that we need to be able manage both the more incremental ideas as well as the more game-changing ones. The small innovations keep us competitive now, but the bigger ones keep us in the game as the competitive environment changes.

Noah Raford made a similar argument in his discussion of the taxonomy of design put together by GH VanPatter and Peter Jones (check out his blog too!). He also has four levels of design, with increasing complexity as you go up the scale. He points out that at the more complex end, design “problems are far more social, far more political, and tend involve many more people with vested interests and different goals.”

This is equally true of innovation, I think. The genuinely inventive and disruptive innovations are much harder to embed within the economy, because so many more people have strong connections to the ideas that are being replaced. That’s a big part of what makes executing innovation so challenging – we have to get the new ideas to spread. In the end, though, I suppose that’s what makes it fun too!

Last week I talked about how I use Malcolm Gladwell’s TED talk in my innovation courses. Another one that I use to illustrate how the innovation process is changing is the talk by Charles Leadbeater:

The innovation lessons are a little easier to pull out of this one, since it is directly about innovation. Leadbeater talks primarily about the role that collaboration plays now in innovation. Many of the key ideas are explained in his book We-Think, which is definitely worth reading. Here are some of the key ideas that jump out at me in his talk:

• His story of the invention of the mountain bike is an excellent example of customer-led innovation. Over 60% of the bicycles sold in the US now are mountain bikes, but they were not developed by bike companies. They were developed by lead users, who combined the rugged frame of the slow, clunky one-speed bikes, the gears from racing bikes, and brakes from small motorcycles to create bikes they could take off-road. This happens in many industries now – others that we talked about in class include software, adventure sports and medicine. The last one always makes students a bit nervous – who wants to have their doctor experimenting? And yet, many times they have to invent new ways of doing things on the fly when they are faced with an urgent situation. So many medical devices actually originate in use.
• Leadbeater’s discussion of the patent system builds on that last point. He says that the purpose of many innovations is discovered in use, which does not fit well with an IP system that requires inventors to know exactly how their invention will be used in order to file a patent. Inventors often don’t know what their ideas are for! I think that this is a critical point – this is one of the reasons why “release, get feedback, improve, iterate” is a very effective innovation method. It allows you to discover what your great idea is actually good for as you interact with the people using it.
• There is a good discussion of why the organisational imperatives within large firms lead to incremental innovation rather than breakthroughs. It is much easier to get sign off on an idea that builds incrementally on an existing product or service, aimed at current customers, with a reasonably predictable return. Innovation is inherently uncertain, which often makes it difficult to get innovative ideas off the ground within large organisations.
• “The truth is that most creativity is cumulative, and collaborative.” Innovations combine things that already exist. There is no thunderbolt from the sky, but rather a great deal of hard work, discussion, and collaboration that must take place if we are to be consistently innovative.
• The last half of the talk is a great explanation of the conflicts between open and closed innovation models. Leadbeater discusses why established firms try hard to maintain their primarily closed innovation models. He also correctly points out that the most successful business models of the future will probably not be either fully open or fully closed, but rather some type of hybrid combination of the two.

Overall, it is a terrfic talk and well worth your time. Both in this and in We-Think Leadbeater makes a compelling case for the benefits of collaborative innovation, why organisations might use open innovation models, and some of the tensions involved in doing so.

Nancy and I were talking about a kind of strange newspaper article that her sister sent her discussing the upcoming release of the DSM-V (the official diagnostic manual for mental illnesses). The author of the article was a psychiatrist advocating going back to the 19th century definition of depression – melancholia. I joked that we might as well go back to using phrenology.

If you’re not familiar with it, phrenology was a diagnostic system [sic] based on the idea that the bumps on your head could tell you something about the brain structures underneath the skull. The theory goes on to suggest that the different brain structures reflect different personality traits. As a science, phrenology was discredited a long time ago – around the same time we stopped talking about “melancholia”.

But Nancy had a fascinating response to my joke about phrenology. She said (approximately):

Phrenology was actually really important because it was the first time that people started thinking about the localisation in the brain. Before that, they thought of it as a pretty undifferentiated organ – like a kidney – where each part did the same thing. So phrenology was actually one of the first steps towards modern neuroscience.

That reminded me of a great post by Randy Haykin about the Apple Navigator (which I talked about earlier here). Haykin talks about how many of the key features of the Apple iPad were first introduced in the Apple Navigator – a prototype from 1987 that never launched as a product.

The stories of phrenology and the Navigator show how both science and the economy are evolutionary processes. They both build on earlier ideas to create new ones – usually through creating new combinations. Phrenology failed as a scientific theory, and the Navigator failed as a product, but both contained ideas that could be combined with others to form new, better ideas. We learned from the failures.

That’s why a lot of people, including me, advocate developing a tolerance of failure when we’re innovating. Failure gives us a chance to learn, and it helps us execute ideas that might form building blocks of better ideas in the future. If at least some of our ideas aren’t failing, we’re not trying out enough new things.

However, failure also has consequences – something that venture capitalist Mark Suster forcefully points out in Why the ‘Fail Fast’ Mantra Needs to Fail. His key point is that when fast failure is encouraged, it can have several major drawbacks for start-ups. It can encourage poor business model development, premature abandonment of start-ups, and a cavalier attitude towards the money that others have sunk into the venture.

All of these are valid points. But I think it shows that we are using ‘fast failure’ to cover many different things. One of the key quotes in Suster’s post is this:

You want to talk about the ultimate “fail fast” – how about if you fail before you’ve spent any money building product because you validate there isn’t a big enough market or you can’t make money?

This got me thinking. I think that what we need is a taxonomy of economic failure. We can actually think of failure as a hierarchy that looks something like this:

As you go down that list, failure gets less expensive. When I talk about tolerating failure, I’m talking about trying to set up systems that encourage cheap fast failure. This is usually at the level of ideas. I agree with Suster that encouraging failure at higher levels can be irresponsible.

Innovation courts failure. Not every great new idea will work – and since it is nearly impossible to tell in advance which ones will work and which ones won’t, we have to find cheap, quick ways to test them out. This can be done through the use of experiment as in rapid prototyping combined with iteration based on feedback, through the use of modelling or other simulations, or through the use of a screening tool like the stage-gate process.

The main point is that we need to try to encourage failure before new ideas get too embedded into the economic network. At the top level of the failure hierarchy, failure causes enormous disruption and pain, because those parts of the system are so deeply interconnected. It is much better for ideas to fail than it is for products, firms or economic systems to do so.

(photo from flickr/evansville under a Creative Commons License)

We’ve talked quite a bit about the situation in which the news industry currently finds itself. It is interesting because it is an industry in the middle of massive disruption, which makes it a great case study. Consequently, lots of other people are talking about it as well.

This week I tweeted abougt two stories on this topic – Marc Andreessen’s interview in which he says that media companies have to “burn the boats” and fully commit to digital, and Hal Varian’s talk urging news organisations to “experiment, experiment, experiment”.

In another of his fine weekly reviews, Mark Coddington summarises this discussion and points to two interesting responses to Andreessen from Alan Mutter and Paul Gillin, who both think that it is a bit too early to burn the boats.

Here are some of the highlights. First off, Andreessen -

[he] was talking about print media such as newspapers and magazines, and his longstanding recommendation that they should shut down their print editions and embrace the Web wholeheartedly. “You gotta burn the boats,” he told me, “you gotta commit.” His point is that if traditional media companies don’t burn their own boats, somebody else will.

Mutter’s response:

some 93% of the industry’s $45 billion in sales were associated with the legacy print product. Even though ad revenues probably fell $10 billion in 2009, print-driven newspaper revenues sill are running at better than $30 billion a year.

It doesn’t take a certifiable Silicon Valley genius to see that no business can walk away from some 90% of its revenue base without imploding.

And then Gillin’s:

In their most recent round of earnings reports, most publishers stated that they are now deriving between 12% and 16% of their revenue from online advertising. Most of them have also not done nearly as much as they can to monetize other sources such as events, transaction fees and value-added and classified advertising. Once publishers reach the threshold of 20% online revenue, they can conceivably shutter their print operations while sustaining the business and the brand. They’re trying to get to that threshold gracefully, though. Lots of money can still be made in print if publishers can manage that asset down steadily while reducing costs in lockstep….

Burning the boats isn’t a wise strategy at the moment. But it’s a good idea to start collecting firewood.

Finally, here’s Varian:

In my view, the best thing that newspapers can do now is experiment, experiment, experiment. There are huge cost savings associated with online news. Roughly 50% of the cost of producing a physical newspaper is in printing and distribution, with only about 15% of total costs being editorial. Newspapers could save a lot of money if the primary access to news was via the internet.

New tablet computers like the Kindle, iPad, and Android devices may encourage people to read online news at home in the comfort of their easy chairs. At Google, we certainly don’t think we have all the solutions, but we are definitely keen on working with the news industry to help it attract bigger audiences and generate more ad revenue. Experiments like Fast Flip, Living Stories and Starred Stories may help pull together the at-work and at-home access to the news. Online news access on handheld device like cell phones and tablets is likely to be quite different from traditional newspapers reading, with much more multimedia content, interactivity and reader involvement. The transition to a fully online news will be difficult, but there’s a good chance that we will emerge with a significantly more compelling user experience.

My opinion is that it’s a diabolically hard problem. I agree with Mutter and Gillin that you simply can’t walk away from more than 90% of your current revenue. The print operations must continue as the news organisations follow Varian’s suggestion to promiscuously experiment – a recommendation that I strongly endorse.

The thing that bothers me about most of this discussion, however, is that the vision is still conservative. There’s no point in simply porting news online. These organisations must be experimenting with finding ways to create entirely new experiences around the news – the game must be fundamentally changed.

That’s what makes me at least partially sympathetic to Andreessen’s argument – the current news organisations have to find a way to psychologically move away from the print, and they also have to move away from the idea of recreating newspaper on a website, or a smart phone, or a tablet. That doesn’t cut it. So here is my prescription – and I think that it is generic to all large, entrenched incumbents facing major disruption:

• While maintaining your current core operations, you have to abandon them psychologically. This is what Andreessen is getting at – full commitment to the new model requires no safety net, at least in his view. I’m not sure this is entirely true. The main point is that one way or another, you have to come to grips that your core operations are on a death watch.
• The second step is that you need to follow Varian’s advice and start experimenting. Try it all – big bets small bets, and everything in between. Prototype rapidly, get your new ideas out there, get feedback, and iterate. I believe that the future of news will look nothing like a newspaper that just happens to be online. I don’t know what it will look like, and the key point is that no one else does either. That’s why the rapid prototyping approach is great – it gives you a chance to shape the new future.
• Forget focus groups or consumer feedback. In saying this, I’m certainly not saying ignore the customer. However, they don’t have any more of an idea of how they’ll use new technologies than anyone else does right now. It’s smarter to figure out what jobs they are trying to get done. That will help you figure out which experiments are the most promising to prototype.
• The last suggestion is the tough one – in all turf wars between the current way of doing things and the experiments, you must support the experiments. You have to be willing to cannibalise your current strengths. Remember, your current model is dead, even though it’s still operating. Consequently, the way we’ve always done things can not be allowed to interfere with trying to make the new way of doing things. Arguments like “we’ve always done it this way” and “but that will take away revenue from our cash cows” represent capitulation and defeat. Ignore them.

These ideas are fairly easy to type, and a whole lot harder to execute. However, if you’re facing disruption, it’s your only choice. Try everything you can think of, see what works, do more of that, and learn from what doesn’t work. That’s the algorithm for business model innovation, and implementing it gives you your best chance at surviving the disruption.

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.

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