Archive for category selection
Innovation as an Evolutionary Process
Posted by Tim in innovation strategy, replication, selection, variety on 13 June 2010
Here’s another clip from the video series that we did a couple of years ago for our Innovation Leadership course. This time it’s John talking about how innovation is an evolutionary process:
Generic evolutionary processes have three parts – generation of variety, selection, and replication. This maps on to the three steps in the innovation value chain. The Innovation Value Chain also has three steps – idea generation, idea selection and execution, and idea diffusion. The connections between the two models should be fairly apparent!
Innovation as evolution has some interesting implications, including:
- The ideas that spread are often not optimal solutions to problems, they simply happen to be the best solutions currently available. In other words, our innovations just have to be good enough, not perfect.
- Consequently, the idea that we’re not looking for a perfect execution of our new ideas is a strong argument in favour of taking a build, launch, tweak approach to getting our new ideas out there. We’re most likely to get to the best solutions to the problems we are interested in through an iterative process, rather than through pure development.
- This leads to the last point, which is that the evolution of our great ideas is built on collaborative networks. The sooner we can enlist the help of our network (customers, partners, suppliers, etc.), the more likely we are to come up with the best version of our great new idea.
The economy is an evolving system. Thinking of it in this way gives us some important insights into how to best manage innovation.
The Changing Innovation Process
Posted by Tim in innovation, selection, variety on 10 June 2010
How has the internet changed the innovation process? It has had a number of impacts, particularly on collaborative innovation, which is becoming increasingly important. Here is a short discussion on this topic from one of our previous Innovation Leadership Executive Education courses:
George Dyson has a nice metaphor for the changes involved in answer to one of the big questions from edge.org – how has the internet changed the way you think? (via Simon Bostock’s excellent blog)
KAYAKS vs CANOES
In the North Pacific ocean, there were two approaches to boatbuilding. The Aleuts (and their kayak-building relatives) lived on barren, treeless islands and built their vessels by piecing together skeletal frameworks from fragments of beach-combed wood. The Tlingit (and their dugout canoe-building relatives) built their vessels by selecting entire trees out of the rainforest and removing wood until there was nothing left but a canoe.
The Aleut and the Tlingit achieved similar results — maximum boat / minimum material — by opposite means. The flood of information unleashed by the Internet has produced a similar cultural split. We used to be kayak builders, collecting all available fragments of information to assemble the framework that kept us afloat. Now, we have to learn to become dugout-canoe builders, discarding unneccessary information to reveal the shape of knowledge hidden within.
I was a hardened kayak builder, trained to collect every available stick. I resent having to learn the new skills. But those who don’t will be left paddling logs, not canoes.
This same process drives the shift towards distributed innovation. When the raw materials (great ideas) for innovation are relatively rare, it makes sense to try to control the source (creative people) as much as possible. So you hire as many innovative people as you can, and you retain all the resources inside of your firm.
However, when the raw materials are abundant, the problem isn’t finding them, it’s figuring out which ones are good. In this environment, it makes more sense to let idea generation come from anywhere, while you focus on getting very good at selecting and executing great ideas.
All of us are building canoes now.
Finding the Best Way to Fail
Posted by Tim in filter, innovation strategy, selection on 14 March 2010
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:
- System failure (the collapse of communism)
- System component failure (stock market crashes)
- Major firm failure (Enron going out of business)
- Start-up failure (pets.com going out of business)
- Product failure (New Coke tanking)
- Idea failure (Apple Navigator prototyped but never launched)
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)
How to Fail at Innovation
Posted by Tim in evolving economic entities, filter, selection on 25 February 2010
The way to fail at innovation is to try to avoid failing.
The idea of failure has popped up quite a bit this week for some reason. Innovation is filled with tensions that we have to become comfortable with if we’re going to succeed. One of the big tensions is between success and failure – when you’re innovating, you can’t have one without the other. In a very interesting post, Arne van Oosterom suggests that this is good argument for emphasising adaptability rather than innovation for many firms, as this eliminates the discomfort caused by the tension between the two.
I am in complete agreement with van Oosterom that adaptability is a desirable trait for organisations to develop. But in doing so, I don’t think we can abandon innovation. I think that we need to develop strategies for dealing with failure.
This was the conclusion reached by both Peter Yates (ex-CEO of PBL, among other things) and Patricia Cross (Non-Executive Director of Wesfarmers and numerous other organisations) in their talks at the Leaders’ Edge Luncheon here in Brisbane on Tuesday. The topic of the talks was ‘Tales from the Corporate Battlefield’ – and it sounds like both of them have been in plenty of battles. And one of the common themes that they touched on is that if you’re doing anything worthwhile, you will experience failures. It’s not fun, it’s not something to be embraced, but it’s inevitable.
This theme was also addressed by Hutch Carpenter in a fantastic post this morning. In making the point that innovative firms will fail, he included this picture:
He includes this quote from Jeffrey Phillips – one of the best innovation bloggers around:
As Edison and countless others have demonstrated, you rarely get it right the first time, and if you are stymied by early failure, then you’ll never find and implement the best ideas. Innovation, as has been pointed out by individuals with far more to say about it than me, will create some failures. Your job isn’t to avoid the failures, since you can’t predict them in advance, but to reduce the cost and impact of the inevitable failures. In other words, keep moving.
So there’s the contradiction that we have to deal with – if we’re going to successfully innovate, we have to fail. The key is to figure out how to do it as cheaply as possible. As I’ve said before, if everything that you try works, then you’re not trying enough things. These contradictions are one of the things that makes managing hard, but it’s also one of the things that makes good managers so valuable. Failing isn’t fun, and it’s natural to try to avoid it. However, it is a necessary element of success.
In other words, the one guaranteed way to fail at innovation is to try to avoid failing.
Filtering, Crowdsourcing and Innovation
Posted by Tim in book riffs, filter, innovation strategy, selection on 1 February 2010
How can we take advantage of the ‘wisdom of crowds’ in our innovation efforts? There are some distinct challenges in trying to do this. The basic idea is this: if you get a large number of people to estimate something – the weight of an ox, or the number of jellybeans in a jar, for example – usually the average of all of the estimates is closer to the actual number than any individual’s guess. Consequently, there is a strong argument for taking advantage of this phenomenon if you are trying to get a handle on estimating a particular number. Businesses have used these techniques to improve their sales forecasting for example (Gary Hamel includes a really nice example of how Best Buy used this method in The Future of Management).
Can this work to improve innovation? It’s not as obvious that it will. I’m currently reading You Are Not a Gadget by Jaron Lanier (more on this book in a later post). Lanier has this to say about using crowds:
The reason the collective can be valuable is precisely that its peaks of intelligence and stupidity are not the same as the ones usually displayed by individuals.
What makes a market work, for instance, is the marriage of collective and individual intelligence. A marketplace can’t exist only on the basis of having prices determined by competition. It also needs entrepreneurs to come up with the products that are competing in the first place.
Since the internet makes crowds more accessible, it would be beneficial to have a wide-ranging, clear set of rules explaining when the wisdom of crowds is likely to produce meaningful results… Among other safeguards, I would add that a crowd should never be allowed to frame its own questions, and its answers should never be more complicated than a single number of multiple choice answer.
Crowds can be useful, but also dangerous. Nassim Nicholas Taleb says that crowdsourcing should be avoided in situations where the potential payoffs are very complex, and when we don’t know what the outcome probability distribution looks like. Unfortunately, this is precisely the case for most innovations.
Relying on crowds can lead to innovation problems. Stefan Lindegaard identifies this as one of the common causes of open innovation failure (the comments on that post are worth reading too):
Many companies start off with idea generation platforms hoping that external contributors will contribute with great ideas and/or technologies. Most do not deliver on the expectations as they get more trash than gold.
And in a post that addresses some of the issues with crowdsourcing really nicely, Graham Horton says:
In conclusion, customer idea portals as they are currently popularly advocated will produce limited results; they will only provide suggestions for solutions that are apparent to customers, given their level of expertise and self-knowledge.
All this might suggest that we can’t use crowds to help innovation. However, I think that these two quotes suggest a possible way that we can still take advantage of crowds in our innovation efforts. One of the issues is that we often misunderstand how crowdsourcing actually works. The Lindegaard quote suggests that people think that we can turn to our crowd (customers, stakeholders, etc.) and just wait for the good ideas to roll in. This is in line with a common understanding of crowdsourced systems – people often talk about Linux, for example, as a process where thousands of people write bug fixes for the software, and all of these fixes get put into the program, making it better. This misses a critical step.
That’s a diagram that I made last year to explain to some friends how icanhascheezburger.com works – but it explains Linux just as well as it explains lolcats. The critical step in the process is the middle one. Both systems crowdsource content – Linux crowdsources code, icanhascheezburger crowdsources cat drawings. The problem is, not all of the code works, and not all of the lolcats produce lols. In each case, there is a small group that filters the incoming content. We don’t have crowds creating stuff, and then voting on stuff. We have crowds creating stuff that answers questions posed by the group guiding the process. The answers that work are then selected by that group as well.
This leads to the answer that both Lindegaard and Horton suggest: in order to get useful answers from crowds, we have to have good internal capacity ourselves. Crowdsourcing needs to be guided. To use the crowd in innovation, we need to set the questions. And we need to know enough to be able to figure out when the crowd is giving us good answers.
A while ago I talked about using jams to select ideas. This process follows these principles. The questions being asked are set by the organisation, so the crowd is trying to address a specific problem. And the best answers are not just judged by popularity – there are several evaluation mechanisms that can be used. You can use the votes and go with the most popular. You can use the ideas that were most polarizing. You can take the ideas that are generated and plug them into whatever other system you use (stage/gate, gut feel, whatever).
Crowdsourcing then is another tool that we can use in our aggregate, filter and connect strategies. In this case, the filtering is the critical step. If we don’t filter correctly, crowdsourcing simply aggregates, which by itself doesn’t help us much. And the aggregated crowdsourced answers need to be connected to questions that we know are important. Crowdsourcing is not a panacea, but it can be a useful innovation tool if we use it correctly.
Graham Horton has written a terrific post that looks at which questions we should ask the crowd.
Using Jams to Select Ideas
Posted by Tim in innovation strategy, selection on 4 January 2010
I have talked a couple of times recently about some results from the assignments in my MBA class this year. In assessing the Innovation Value Chains within their firms, 3 out of 60 identified their organisation as ideas-poor, while the other 57 had bigger problems with idea selection and idea execution. The paradox is that when firms try to become more innovative the first thing they usually do is take steps to generate more ideas.
In part, I think that this is due to the fact that we have relatively more resources available to help with this part of the process. There are plenty of books on improving idea generation and creativity. There are plenty of consultants around with methods for doing the same. It is the area where it is the easiest to see quick results, which makes it attractive. This is deceptive though, because the data from my MBA students strongly suggests that this is the area where organisations actually need the least help.
What do we have that can help with idea selection and idea execution? One approach that is very good to use for idea selection is idea jams – a technique originally developed by IBM. I’ve been talking about this some recently with my friend Kate Morrison, who uses this approach in her firm Vulture Street Innovation Software and Services. Here is how she describes the jam process:
A jam is an online, time-limited collaboration event specific to an invited group of participants and focused on a particular organisational problem, opportunity or challenge.
Compared with traditional problem solving and group decision-making techniques, the jam approach offers significant benefits because it is:
* focused around specific themes or challenges, as defined by management – hence avoiding non-productive and open-ended solicitations (such as suggestion boxes) or community discussions;
* specific to the group invited to participate, which can include customers and suppliers as well as employees;
* scalable beyond the limits of physical get-togethers, able to accommodate hundreds of participants; and
* time-limited, allowing a concentration of attention and energy and preventing the process from fading into the background of business-as-usual.
So it is a crowd-sourcing method, but it uses a specific, hand-picked crowd. The thing that I particular like about this approach is that it doesn’t just generate ideas, it selects them. As ideas come in, people are able to comment on them, and vote on the ones that they like. Here are some results from one of Kate’s projects showing the contributions of all of the people participating in a small jam, along with the 6 most popular ideas (indicated by the stars):
These results from illustrate some interesting points:
- Contributions follow a power law (roughly). This is very normal for interactive networks of people. There are usually a small number of people with really large contributions (in this case, the top 3 idea contributers generated 38% of the total ideas!), a slightly bigger number of people with a few contributions, and a majority of people who contribute only one or two ideas (Clay Shirky explains this really well in one of my favourite TED talks). In many situations, it is difficult to solicit the ideas from this last, largest group, which is important because:
- Idea quality is unrelated to idea volume! The idea voted the best was contributed by the 14th most prolific idea generator, and the one voted second best was contributed by the least prolific idea generator. The top two idea contributors support Linus Pauling’s contention that ‘the way to get good ideas is to get lots of ideas, and throw the bads ones away.’ But in good news for us introverts, the people talking the most aren’t necessarily the ones coming up with the best contributions.
- The key point is that at the end of this process, you end up not just with a bunch of ideas, but with an idea of what the best ideas are. This is what I like about jams as innovation tools – it is actually a selection tool, which is one of the areas that firms are often weak. At the end of the process, you don’t have hundreds of new ideas, you have 3 or 4 really promising ones.
So this is one method you can use to improve your capability in selecting new innovation ideas. There are more formal processes available like Stage-Gate too. If you’re going to invest time and money in improving innovation within your organisation, I think it’s essential that you focus on getting better at selecting and executing new ideas, rather than simply generating them.
You Don’t Need Any More New Ideas!
Posted by Tim in innovation strategy, replication, selection, variety on 30 December 2009
Scott Berkun let out the secret of innovation today in an outstanding blog post. It’s a secret that Rowan Gibson tried to let out of the bag recently, and so did Braden Kelley on Blogging Innovation. I’ve tried to tell you about it too, using both analogies and statistics. The secret idea of innovation is this:
You don’t need any more new ideas.
Here is Berkun on the what we really need:
If there’s any secret to be derived from Steve Jobs, Jeff Bezos, or any of the dozens of people who often have the name innovator next to their names, is the diversity of talents they had to posses, or acquire, to overcome the wide range of challenges in converting their ideas into successful businesses.
That’s it. The problem is executing your ideas. Here’s an example – yesterday I talked about mousetraps – here are some interesting stats.
The patent for the flip-trap mousetrap design was filed in 1899. That’s a better mousetrap, right? We’re still using that design over 110 years later, so it’s probably pretty good. And yet, since 1899, the US Patent Office has granted over 4400 mousetrap patents. They receive more than 400 new mousetrap patents every year. So there’s no shortage of ideas. But fewer than 20 mousetrap designs have led to products that have actually made money. The problem in innovation is executing your new idea, and getting it to spread.
There is so much effort put into improving innovation by generating more ideas. This isn’t necessarily wasted effort, but it’s not the smartest use of resources. My MBA students evaluated innovation within their firms:
This approach is flawed, and my MBA students demonstrated why. They came from a wide range of organisations – huge multinationals, small start-ups, government departments, and educational institutions. Despite these different backgrounds, their findings were remarkably consistent – only 3 of the 60 organisations that they work in are ideas-poor. The other 57 (that’s 95%!) have problems with either selecting or diffusing ideas.
Here’s more from Berkun:
The closest thing to a real secret is this: In my years studying and teaching all things innovation, there’s one fact that’s the hardest for people to swallow and it goes as follows – To invent or create is to take a bet against the unknown. No matter what you do, you are still betting you can do well in the face of many things that are out of your control. Don’t like that? Don’t want uncertainty? Then do something else. Comfort with risk and uncertainty is the real secret. Or at least acceptance of the fact you can work your ass off for uncertain rewards.
Where does this leave us? Here are some conclusions:
- If you’re going to get some help to improve innovation at your firm, don’t focus on generating ideas. Get help on selecting ideas, or on getting them to spread. Those are the hard parts.
- Innovation is a bet – you’re betting that your new idea will work better, that it will meet needs, that it will fit into the value network. All of these things have to happen for your innovation to work. Like Berkun says, this is a leap into uncertainty.
- Most of the innovation problems that organisations face are problems with innovation diffusion – the challenge is to get your new ideas to spread.
The new idea that I’d like you to accept is that you don’t need any more new ideas. Instead of generating more ideas, let’s develop some plans for getting better at executing our ideas. That seems like a good idea heading into the new year, doesn’t it?
How to Assess Your Innovation Capability
Posted by Tim in innovation strategy, replication, selection, variety on 18 December 2009
How do you know how good you are at innovation? One of the tools that we have found very useful for assessing innovation within organisations is the Innovation Value Chain. The tool was developed by Morten Hansen and Julien Birkinshaw and published in an article called The Innovation Value Chain in Harvard Business Review in 2007.
I’ve talked about this before – There are two key points with this model. The first is that there are three stages in the process of innovation: idea generation, selecting & developing ideas, and diffusing ideas. The key part, however, is that all three parts of that process have to be working well in order to innovate.
The three step aspect of the innovation process is important. Measuring idea generation, selection and diffusion helps organisations get around the problem of simply equating innovation with ideation. Organisations that do this often find that they have plenty of ideas, but they’re still not being very innovative. This is because innovation actually doesn’t occur until you execute new ideas. To do that, you have to be good at having ideas, but more importantly you also have to be good at selecting ideas and getting them to spread.
This leads to the second key point of the Innovation Value Chain – your innovation process is only as good as your weakest link. This is not simply a linear model of how things happen, it is a description of a complex system. For example, if you are bad at selecting ideas, people will become less willing to give you their new ideas. This means that there are feedback loops between the three parts of the process. If you are going to improve your innovation, the whole system has to get better. You can use the IVC to identify your weak point and take steps to improve it. Then you can move on to whichever step is your weakest point now. If you keep doing this, you will build excellent innovation capability within your organisation.
Here is a Special Deal!
Our research has shown that while organisations usually first try to improve their idea generation, 95% of the time, this is not their weakest area. I’m curious to see how broadly this is true – so I would like you to please
In exchange for your time, I’ll give you some feedback on your results. If you’d like some information about what your organisation’s innovation strengths and weaknesses are relative to others who have taken the survey, just leave an email address when you take the survey. If you would like several people from your organisation to take the survey, I can compile the results – just have everyone indicate the name of the organisation when they fill out the survey. All results are, of course, confidential. To get the most meaningful results, please tell everyone you know that might be interested about this survey. Thanks for your help!
Innovation is about more than just coming up with new ideas. If we’re going to be innovative, we have to be able to execute new ideas. The Innovation Value Chain is one tool that can help us get better at this.
the hardest part of innovation
Posted by Tim in innovation strategy, replication, selection on 28 November 2009
I was thinking about my talk from yesterday, and one bit that I just spontaneously threw in is probably worth expanding on. I spent a lot of this week marking assignments from my MBA students (who were an exceptionally good bunch this year). For the major assignment this year, I had them analyse their own firm or organisation using the Innovation Value Chain model developed by Morten Hansen and Julian Birkinshaw.
There are two key points with this model. The first is that there are three stages in the process of innovation: idea generation, selecting & developing ideas, and diffusing ideas. The key part, however, is that all three parts of that process have to be working well in order to innovate.
Both John and I have talked about the dangers of over-focusing on idea generation at the expense of execution, so we find this to be an extremely useful model. In particular, we have frequently observed organisations decide that they have to improve their innovation, and then sinking all of their resources and effort into idea generation.
This approach is flawed, and my MBA students demonstrated why. They came from a wide range of organisations – huge multinationals, small start-ups, government departments, and educational institutions. Despite these different backgrounds, their findings were remarkably consistent – only 3 of the 60 organisations that they work in are ideas-poor. The other 57 (that’s 95%!) have problems with either selecting or diffusing ideas.
So when firms focus on improving their idea generation, it is a mistake for two reasons. The first is that this is almost certainly not where their problem lies. They’re probably worse at execution. The second is that it does not take into account the entire innovation system. I just saw this quote from Russell Ackoff (via Venessa Miemis):
Improving the performance of the parts of a system taken separately will necessarily improve the performance of the whole.
False. In fact, it can destroy an organization, as is apparent in an example I have used ad nauseum: Installing a Rolls Royce engine in a Hyundai can make it inoperable. This explains why benchmarking has almost always failed. Denial of this principle of performance improvement led me to a series of organizational designs intended to facilitatethe management of interactions: the circular organization, the internal market economy, and the multidimensional organization.
Innovation within an organisation is a system. It is much more than simply idea generation. And if you focus only on improving your ideation, there’s a pretty good chance that your overall innovation performance will actually get worse. The hardest part of innovation is idea execution, and we simply must get better at it.
What is an Innovation Culture?
Posted by Tim in innovation strategy, replication, selection, variety on 27 November 2009
Here are the slides + audio from the talk I gave this morning for the UQ Centre for Educational Innovation and Technology‘s planning day. One of the things that they were working on was thinking about what they want their innovation culture to be, so Phil asked me along to give some thoughts on that. I’m not sure how close my talk was to what he wanted, but I gave it a go. It’s too bad I didn’t record the Q&A at the end, because some really good ideas came up during that too. They’re a really bright group and I’m looking forward to seeing what they’re able to do.
Even though slideshare says that this runs for over an hour, the talk is just 18 minutes.
As usual, if I sound like Jabba the Hut, you have to upgrade your flash player – slideshare doesn’t play well with older versions.
Also, I’ve added an index page with links to all of the talks that we’ve put up. There are a couple more (with video) coming soon!
