Archive for February, 2010

How to Filter Better

Posted by Tim in aggregate, connect, filter on 8 February 2010

I was at the mall yesterday eating lunch, and I took a moment to listen to the conversations going on around me. They were, without exception, utterly banal. Consequently, I concluded that conversation is a useless tool, and the widespread use of it is nothing more than a symptom of the widespread decline of intellectual discourse, manners, and civilisation as a whole.

Stupid, right? That’s a riff on Clay Shirky’s response to people that complain about the quality of discourse within social networks.

The latest version of that complaint comes from Tom Davenport on the HBR Blog, who asks for us to tweet about something important:

Almost 50 years ago, FCC Commissioner Newton Minow suggested that the then-new medium of television was becoming a “vast wasteland.” One could argue that the same fate is befalling social media.

So here we are again: a promising new medium being used largely for vapid chattering about celebrities. Couldn’t these technologies be used for good?

Here’s an analogy: bird calls. When Nancy and I started birding one of the things that we learned was bird calls. When we’re actively birding, we’re pretty alert to everything, because we want to know where the birds are. However, when we’re working at home, we pay less attention to the calls. And since we’ve got a yard that is pretty attractive to birds, there are a lot of calls.

The vast majority of bird calls don’t contain too much information. The most common form of call is what ornithologists refer to as ‘chip calls’, which are short, brief calls that birds use to let other birds know where they are. It can help them find food (lots of chips in one area), it can keep them from straying from the flock (most of the chips moving further away), and it simply be a Horton-Hears-a-Who type ‘here I am’ call or an ‘everything’s fine’ call. When we’re working at home, we don’t pay any attention to these calls at all.

However, the birds also have a few calls that contain a whole lot of information. We’re particularly interested in the calls that say ‘predator’. That usually means there’s something pretty interesting in the yard, like a Goshawk, or this Carpet Python:

We only got to see that snake because we heard the bird calls, followed them, and found the snake.

So we’re filtering the bird calls in our heads all the time, waiting to find the interesting bits. We need to do the same thing with conversations (well, maybe not the conversations at the mall food courts…), and social networks like twitter. Most of the words used in these media are like birds’ chips. We need to find the words that contain data. How can we do this?

Howard Rheingold is in the middle of putting together of series of tutorials about Mindful Infotention that explain a few different methods that work.

These are fantastic videos that are well worth your time. In the one above, Rheingold makes several important points. He demonstrates the use of several different tools for aggregating and filtering information on a topic that is of interest to you. He has step-by-step instructions that make it pretty easy to track down specific information from streams that are on average not very useful.

Rheingold also talks about two different forms of filtering – algorithmic and personal. He correctly recommends using a combination of the two. Algorithmic filtering includes tools like PostRank, which uses a formula to determine which posts are most relevant to your search. Personal filtering takes place on sites like delicious and diigo, where you can find the pages that the highest number of people have bookmarked, or the pages that specific people have saved. There’s also using your network to help filter.

Rheingold makes an absolutely critical point at the end of the video – it’s not enough to simply aggregate information, and filter it so that you have only the most relevant information. You also have to do something with it! The information is no good unless you connect it up:

The important part, as I stressed at the beginning, is in your head. It really doesn’t do any good to multiply the amount of information flowing in, and even filtering that information so that only the best gets to you, if you don’t have a mental cognitive and social strategy for how you’re going to deploy your attention.

There is a wealth of great information being shared on a constant basis within social media and elsewhere. None of it does us any good at all if we can’t find the bits that are useful to us in solving the problems on which we’re interested in working. But if we filter well, we’ll discover that we actually are tweeting about things that are important.

(I’ll also just note that Howard is currently getting treated for cancer – the prognosis sounds encouraging, and I hope that he pulls through it in good shape.)

7 Comments

Innovation Lessons from The Checklist Manifesto

Posted by Tim in book riffs, filter, innovation on 7 February 2010

How do we deal with complexity? A while ago I suggested that one strategy that we use to handle complexity is that we outsource some of the rote memorisation of facts and routines that we need regularly. This is essentially the strategy that Atul Gawande also advocates in his outstanding book The Checklist Manifesto: How to Get Things Right. The primary theme of the book is that one of the best tools we can use to handle complex situations is a very simple one – the checklist.

The key story in the book is the World Health Organization’s development of a Safe Surgery Checklist. The checklist consists of a series of items to confirm as part of the surgery process. The are all fairly basic things, and they are put into three groups that are asked at three natural pause points in the surgery – before the anaesthetic is administered, before the first cut is made, and before the patient is taken from the operating room. They address very basic issues that you would think wouldn’t be missed, but which often are: confirm that patient’s name, confirm which side of the body the surgery will take place, confirm the procedure, ensure that all surgery team members have introduced themselves by name and role, discuss key concerns for patient recovery, and several others.

After the checklist was developed, WHO tested in eight hosptials around the world – four were in developed countries, and four were in developing countries. They ran the gamut from well-funded hospitals with all mod cons to rural hospitals that had so few resources that they had to sterilize and re-use surgical gloves until they wore out. In the test study, they gathered data from about 4,000 surgery patients across all eight hospitals for three months, then they introduced the checklists into the surgical procedures, and gathered data from another 4,000 operations.

The results are astonishing. Major post-surgical complications fell 36% with the use of the checklist, deaths were down 47%. All eight hospitals saw major reductions in both categories, and from a statistics standpoint, the relationships are statistically significant. The outcomes were published in the New England Journal of Medicine at the start of 2009.

Gawande is a terrific writer, and I recommend the book highly (his earlier books Complications and Better are also great). I think there are several things that we can learn about innovation from this story, including:

The application of these ideas to innovation is fairly obvious. When you look at innovation as an evolutionary process, it quickly becomes apparent that a number of ideas need to be selected out before we invest too much into them. Most organisations do not spend too much time thinking about the ideas that didn’t work. One of the things that we need to get better at is learning from our ideas that fail. If we do this, then we can build a checklist.

Gawande has a couple of business examples in the book. He talks about three investment firms that have developed checklists to help them evaluate investment opportunities. And he talks about a study by Geoff Smart that looked at what made Venture Capitalists most effective:

Smart specifically studies how such people made their most difficult decision in judging whether to give an entrepreneur money or not. You would think that this would be whether the entrepreneur’s idea is actually a good one. But finding a good idea is apparently not all that hard. Finding an entrepreneur who can execute a good idea is another matter entirely. One needs a person who can take an idea from proposal to reality, work the long hours, build a team, handle the pressures and the setbacks, manage technical and people problems alike, and stick with the effort for years on end without getting distracted or going insane. Such people are rare and extremely hard to spot.

Which VCs are most successful? According to Smart’s study, the ones that use a checklist. Checklists are simple tools that can help us filter ideas and opportunities. They help us outsource complexity, leaving us more mental capacity to connect up ideas in novel ways – which is the key to innovation.

10 Comments

Grit versus Intelligence in Innovation

Posted by Tim in book riffs, innovation strategy, time on 6 February 2010

When I was younger, I placed a high value on intelligence. It made sense, since I was reasonably smart. However, it wasn’t until I added some grit that I started to really get things done. Up until my university years, most things came pretty easily to me. I was fortunate in that I was able to concentrate and learn a lot about things that interested me, so almost by accident there were some things that I ended up building some skills in. But it wasn’t until university that I started having to make the conscious decision to work harder, and do things that weren’t immediately fun if I wanted to get anywhere.

The summer after my first year, I got a job as a floor hand in a feed mill. It was really hard work. For the first couple of weeks, I could barely drag myself home at the end of each day – I felt broken. At the end of those two weeks, my boss Doug called me and the other new floor hand in, and chewed us out pretty comprehensively. The basic message was that we had to work a whole lot harder, or he’d get rid of us.

My first impulse was to tell him to screw himself. I was working harder than I ever had before – I had no idea even where to begin. I went home and talked about it with my Dad. He agreed with me that it didn’t seem fair. But then I started thinking about what it would mean if I quit. What if I didn’t find another job? I had to make money over the summer as part of my scholarship arrangements. After a lot of thought, I went in the next morning and asked Doug for some specific suggestions that I could follow to get better. He gave some, and I discovered that I could indeed work harder than I had been.

That’s when I got some grit. It still took a long time for me to get better at digging in and working at things, but I’m getting there, slowly.

I bring this up because Julien Smith highlighted an excellent article yesterday by Jonah Lehrer in the Boston Globe on the issue of grit versus intelligence. Lehrer starts by discussing a stream of research from psychologists that has shown in many cases, grit accounts for success more than intelligence does. It starts by talking about the story of Isaac Newton and the falling apple:

There is something appealing about such narratives. They reduce the scientific process to a sudden epiphany: There is no sweat or toil, just a new idea, produced by a genius. Everybody knows that things fall – it took Newton to explain why.

Unfortunately, the story of the apple is almost certainly false; Voltaire probably made it up. Even if Newton started thinking about gravity in 1666, it took him years of painstaking work before he understood it. He filled entire vellum notebooks with his scribbles and spent weeks recording the exact movements of a pendulum. (It made, on average, 1,512 ticks per hour.) The discovery of gravity, in other words, wasn’t a flash of insight – it required decades of effort, which is one of the reasons Newton didn’t publish his theory until 1687, in the “Principia.”

I think that this is a critical issue for innovation. We’ve talked a lot about the gaps that are common between inventing something and the idea actually getting embedded in the economy – there are several examples here, and a discussion of Edison and the light bulb also illustrates the point. Randy Haykin talks about another great example by showing how many of the features in the new iPad from Apple originated in the Navigator – a prototype the firm made in 1987.

You have to have intelligence to come up with these great ideas, but you have to have grit to get them to spread. It’s not an either or situation – one way or another, you need both. As Lehrer says, the genius idea is attractive, because it doesn’t require nearly as much effort. But the simple fact of the matter is that to successfully innovate, we need perseverance. Execution is at least as important as ideas, probably more so.

That’s why I think that Ignore Everybody and 39 Other Keys to Creativity by Hugh MacLeod is one of the best innovation books I’ve ever read. He talks about creativity not as inspiration, but as hard work. Here’s an excerpt from one of his 39 other keys ‘Dying Young is Overrated’:

But the kid thinks it’s all about talent; he thinks it’s all about ‘potential’. He underestimates how much time, discipline and stamina also play their part. Sure, there are exceptions. But that is why we like their stories when we’re young. Because they are exceptional stories. And every kid with a guitar or a pen or a paintbrush or an idea for a new business wants to be exceptional. Every kid underestimates his competition, and overestimates his chances. Every kid is a sucker for the idea that there’s a way to make it without having to do the actual hard work.

So the bars of West Hollywood and New York are awash with people throwing their lives away in the desperate hope of finding a shortcut, any shortcut. And a lot of them aren’t even young anymore; their B-plans having been washed away by Vodka & Tonics years ago.

Meanwhile their competition is at home, working their asses off.

Innovation is not about having great ideas. It is about having great ideas, and getting them to spread. You need both grit and intelligence to do this. If you need some more grit, I can put in a good word for you with Doug at the feed mill…

(Feed mill picture (not the one I worked at!) from flickr/rverspirit under a Creative Commons license)

18 Comments

Institutional Innovation

Posted by Tim in complex systems, innovation strategy on 5 February 2010

Here’s a fairly radical idea: if the problem with economic development is that many poorly developed countries have poor institutions, maybe instead of trying to improve their institutions it makes more sense to move the people that live there to a place with better institutions. Let’s break that down a bit.

There is a line of economic research that I find pretty persuasive – it says that the biggest problem in economic development is poor institutions. One of the leading researchers in this area is Dani Rodrik – his book One Economics, Many Recipes: Globalization, Institutions and Economic Growth is the best development economics book that I’ve read. His basic idea is that economic institutions both drive and constrain economic growth, and the the correct mix will vary from country to country based on each nation’s history, culture, economic system, and so on. The research that supports this approach is solid, and to me it makes a lot more sense than the one size fits all approach followed by the IMF, among others.

The second part of the opening paragraph paraphrases some of the recent talks by Paul Romer – another outstanding international economist. His fundamental idea is to try a charter cities approach to develop – the overly simplified one sentence version of that idea is that he wants to create more Hong Kongs.

Here’s a slightly longer explanation from his piece that came out last week in Prospect Magazine:

So, two days later, I opened my own TED talk with a different photo, one of African students doing their homework at night under streetlights. I hoped the image would provoke astonishment rather than guilt or pity—for how could it be that the 100-year-old technology for lighting homes was still not available for the students? I argued that the failure could be traced to weak or wrong rules. The right rules can harness self-interest and use it to reduce poverty. The wrong rules stifle this force or channel it in ways that harm society.

The deeper problem, widely recognised but seldom addressed, is how to free people from bad rules. I floated a provocative idea. Instead of focusing on poor nations and how to change their rules, we should focus on poor people and how they can move somewhere with better rules. One way to do this is with dozens, perhaps hundreds, of new “charter cities,” where developed countries frame the rules and hundreds of millions of poor families could become residents.

It’s a pretty good example of how hard it is for ideas to spread – even good ones like electricity. We’ve already talked about how Edison’s idea for the light bulb didn’t diffuse until he built a generating station and power lines. So it clearly take a fair bit of effort to get ideas to spread. And there are still issues with electricity in some countries. The idea that is gaining momentum in development circles is that it is structural problems that are leading to a lack of development.

Romer argues that the way around this is to stop fighting to change the institutions, but to create new ones in protected regions. I’m not convinced that the idea will work, but I think it is a pretty good example of re-thinking problems that seem intractable to those that are deeply embedded within a system that needs to change (see the discussion from yesterday’s post and the day before’s).

William Easterly has looked at the same ideas about institutions, and advocates an approach quite different from Romer’s. He talks about about the need to take a more bottom-up approach. In his books (The Elusive Quest for Growth and White Man’s Burden), Easterly talks about experimenting with a lot of different development and aid ideas, find the ones that work, and scale those up. It is pretty similar to the idea of algorithmic innovation that I’ve discussed previously.

What does this have to do with you if you’re trying to make innovation work better within your particular organisation – a firm, a university, a government department or whatever? I think economic development is an important issue in and of itself, but there are also a couple of useful ideas for organisations in this. The first is that if you are in one of those organisations that seems highly resistant to innovation, the approaches that Romer and Easterly are using can be taken as blueprints. Both are trying to address the issue of how to get good new ideas to spread within systems that appear to be completely stuck. As I argued yesterday, this is actually a common problem within many organisations.

So one way to attack this problem is to completely reformulate your basic assumptions, like Romer is doing. The advantage to this is that if it works, the payoff might be huge. The risk is that the overall level of risk is also high. This is basically the Apple approach to innovation – trying to reconfigure every market they enter.

A different angle of attack is to unleash a barrage of small experiments, find the ones that work, then scale these up – the Easterly approach. The advantage to this approach is that the cost of failure for each individual experiment is small, and if you try enough, you have a good chance of stumbling across a big idea that will work. Or the cumulative effect of the small institutional innovations might lead to a bigger change. The risk is that you might come up with a number of successful small innovations that fail to change the larger system. This has been the Google approach – their 20% rule for working on your own projects is a classic bottom-up innovation system.

Risks and payoffs – both paths are hard. But both are better than sitting around doing nothing, and better than continuing to try things that demonstrably don’t work. Some ideas to think about at least…

If you’d like to learn more about the Charter Cities idea, there is a good website for it, and Romer’s TED talk is also very good:

3 Comments

New Ideas in Old Systems

Posted by Tim in business models, evolving economic entities, networks on 4 February 2010

The fundamental point that I was trying to make in yesterday’s post is that most of us are facing the same innovation problem: it is extremely difficult to get new ideas to spread within most organisations. We are a bit deceived because we hear about innovation at Google, and 3M, and Apple, and we think that all of our organisations should work like that. Unfortunately, most of them don’t. My examples yesterday came from education, and I know that a lot of people in the public sector think that innovation is unusually hard in their organisations. But nearly everyone resists change. Here are some examples.

First off, here’s ex-Pitney Bowes CEO Mike Critelli on how they faced disruptive innovations:

In 1999, two start-up companies challenged us with online postage solutions. My chief operating officer, Marc Breslawsky, and I were in a minority among the senior team in believing that these companies posed no threat to us. Many employees and high-level executives, one or two board members and many shareholders told me that the world had changed and that I was in danger of ignoring potentially disruptive innovation. The reason Marc and I turned out to be right is that we understood that disruptive technologies are successful only when they are superior to the older technology they replace and when they can be marketed profitably. Neither condition was met.

The blog post discusses how Critelli has consistently had a world view that differed from those around him, and how this made it hard for him to get his ideas across. Many of his examples are cases where he was ultimately right – and in particular, I think that his experiences in changing healthcare are admirable. However, in this case, he wasn’t visionary – he was just lucky (be sure to read Mike’s response to this in the comments!).

Those two conditions are not actually required for disruptive innovations to succeed – especially the first one. Those two conditions are what entrenched incumbents always say when they discount the threat that new challengers pose. As the many studies by Clayton Christenson, Scott Anthony and others show, disruptive innovations are usually technologically inferior when they are introduced. This is precisely why the large firms don’t react – because they correctly perceive that their technology is better. The disruptive innovations change by creating a new market based on different business models, and different value networks.

This misperception of the threat posed by new technologies is one of the reasons that it is often very difficult to introduce innovations within established firms. The fact that P-B’s stock price is now 1/3 what it was when those threats appeared in 1999 suggests that a little more innovation would have proven useful for them.

Here’s another example – Kodak. Simon Waldman has a really nice post on some of the issues that Kodak was grappling with around the same time that Pitney Bowes was thinking about online competitors. He says that they didn’t react to the threat posed by digital cameras because:

* They were distracted by a ferocious price war with Fuji in the late 90s

* They were petrified of cannibalising their film business with digital (further compounding the impact of the Fuji price war)

* They massively underestimated how quickly consumers would ditch film

* Decades of comparable success had made them fat and way, way too happy with themselves

A few months ago, I asked this question to my favourite Swedish PhD student, Christian Sandstrom who has made something of a speciality of creating fabulous Slideshare presentations on the changes in the photographic industry. He responded quickly, but I never posted it here. You can see his answer here.

Here’s the quick summary

* Over aggressive diversification left them burdened with debt and in a weak financial state for dealing with the Fuji price war.
* They put too much focus on ‘hybrid’ solutions – using digital as a way to sell print (eg the Photo CD system)

To me, this sounds a whole lot like the problem that George Siemens is describing in education – they were trapped by their underlying beliefs and ideology. Their fundamental belief was that film would retain its dominance. Digital photos were technologically inferior (especially when they were first introduced), so why would anyone switch from film? Digital cameras took the normal route for disruptive innovations – they found a niche that would value their strength – people that wanted to post pictures on the web. They didn’t care about the poor quality – pictures looked lousy on the web back then anyway. And being able to transfer a digital photo straight to your computer was much easier and much faster than taking a picture, getting it developed, and then scanning it.

Like Pitney-Bowes, Kodak didn’t provide a great environment for innovators back then. Change was being fought hard.

Here’s a third example, going on right now – news. Here’s Felix Salmon arguing that the physical system of producing newspapers is one of the things that is making their transition to digital extremely painful:

Spencer Ackerman uncovers a bit of the hidden point here: newspaper conventions have been built for physical newspapers, and can look silly in the age of the web — especially when the stories themselves appear, pretty much unchanged, on newspapers’ websites. It might make sense for the physical LA Times to run one big story about Afghanistan, but once that decision is made, no one is going to chop that one big story into three smaller ones for the website.

Once again, inertia within the existing system makes it highly resistent to change, as we’ve discussed quite a bit here.

I think that the big difference between the public and private sectors in innovation imperatives is not that the private sector has the profit motive, but rather that occasionally private firms go out of business. It’s not Schumpeter’s “carrot of spectacular reward” that motivates innovation, but the “stick of destitution”. Even with this difference, fighting the inertia within established systems is our fundamental problem – no matter which sector we’re in. It’s hard to get new ideas to spread. That’s our challenge. We’ll keep talking about ways to meet it.

11 Comments

Fighting the System

Posted by Tim in complex systems, networks, replication on 3 February 2010

Today was one of those days when a lot of related ideas just seemed to keep popping up. It started when I read today’s post by George Siemens which discusses the difficulties of changing the educational system. I recommend reading the whole post, but here is part of his argument:

I want to resist the mindset of measuring what is possible by the existing system.

Look at a few of the biggest technological “innovations” of the last decade: learning management systems, student information systems, interactive whiteboards, iclickers, and virtual classrooms. These tools integrate with existing systems, which is why they are successful. The systemic design of education, from curricular planning to delivery to evaluation, has not been recast in light of the web. Instead, the web has been recast in light of existing systems. In many instances, teaching and learning has been transferred to, instead of transformed by, the internet.

What is the impact of this mindset? When I present on alternative views of assessment and accreditation, or suggest non-course approaches to teaching, the inevitable push-back is “well that won’t work because of _____ aspect of the system”.

Perhaps it is time that we turn our attention explicitly to working on, rather than in, the system.

The thing of it is, this is problem is not restricted to the educational system. It is another example of how the embeddedness of ideas makes it difficult for innovative new ideas to spread. I think that the extent to which this is a problem varies along a spectrum. It is an acute problem in education, and in the public sector. However, as I discussed in an earlier post, we see the same thing happen with the introduction of innovative new commercial ideas. Even products that are clearly superior along all dimensions, like the 56k modems versus the 28.8k modems they were designed to replace, innovation is difficult.

John and I were discussing this idea at lunch today, when I realised that another group of people have a similar problem. We are involved with teaching a class called Developing Business From Science. Many of the students in this class are in science-based jobs, and they have an invention or a new idea, and they want to figure out how to make some money with it. Their ideas don’t have any connections to other parts of the economy, and they usually have to displace something that is already economically embedded.

Here’s what I said when discussing the 56k modems:

To get your innovation embedded into the economy, you have to unconnect the members of your value network from whatever they’re currently using (28k modems, for example), and get them to reconnect to you. The unconnecting is a critical step that we often ignore – this is a mistake.

This problem is consistent across all organisations. It’s the problem that George is talking about in education. It’s the problem that innovators in the public service face. It’s the problem that people grapple with in commercial firms, whether their idea is for a new product, a new service, a new way of doing things or a new business model. The hardest part of innovation is getting our ideas to spread.

This idea was then brought home this afternoon, when I read an article by Seymour Papert that Phil Long forwarded to me. It’s called Why School Reform is Impossible, and it is looking at exactly the same issue – how can we revolutionise education when the system swallows every new idea and assimilates it into the existing structure. He concludes with this recommendation:

Complex systems are not made. They evolve. Where I part company from Tyack and Cuban is when they turn from the book’s historical theme of showing that reform will not work to give advice to reformers about how to do it better. My own view is that education activists can be effective in fostering radical change by rejecting the concept of a planned reform and concentrating on creating the obvious conditions for Darwinian evolution: Allow rich diversity to play itself out. Of course, neither of us can prove the other is wrong. That’s what I mean by diversity.

This is very similar to my view. When we’re trying to get new ideas established, we need to experiment, see what works, and do more of that. One of the areas in which we must experiment is that of our basic assumptions. Siemens’ prescription for education will for everyone, I think:

I’m suggesting something much more subtle: that we no longer allow systems-based arguments and criticism to dampen our creative exploration for what is possible in education. A period of “no boundaries” in our thinking. Forget even arguing against those who appeal to integration with existing structures. Just ignore those discussions completely. I’d like to focus instead on creating a compelling vision of what education could be given new technologies and almost global connectivity.

So there it is from two really smart guys plus me: innovation is evolutionary. The way to enact big change is to treat it as an evolutionary process. All of our organisations are operating within complex systems, so this is the approach to use, no matter what industry we’re in. Let’s start experimenting!

16 Comments

Innovations That Last

Posted by Tim in design, innovation strategy, time on 2 February 2010

Here’s another video:

Innovations that Last from Tim Kastelle on Vimeo.

Here’s the brief summary:

Today I wore to work a shirt that I bought in 1994. I’ve worn it a whole lot in the time since I bought it. It was made by Timberland, and it’s a well-made shirt that is still in pretty good shape. Since I bought it, Timberland has become more interested in making shirts that give the appearance of ruggedness rather than providing actual ruggedness. So there are no 16 year shirts for sale from Timberland now.

The shirt contrasts with two pretty cool gadgets I’ve got on my key ring – one is a little pocket knife that folds up and looks like a key, the other is a usb stick that looks like a key. Both are pretty flashy, and it is very convenient to have with me all the time with my keys. However, both have fatal flaws – every time I use the bottle opener on the knife, I cut my fingers, and the usb stick comes with a cap that covers the contacts, which just will not stay on the stick. Now the cap is lost, and if I don’t do something, the contacts will get scraped, and the stick will become unusable.

The shirts and boots that Timberland is making now, and the knife and the usb stick are all examples of poor strategy for the 21st century. They look flashy and they seem innovative, but they’re not built to meet real needs, and they’re not built to last.

I think that we have to focus our innovation efforts on ideas that are more durable. We have to come up with products and services that are sustainable. We have to make shirts that will last 20 years – I know we have the technology for it! We have to make usb sticks that are convenient, but which don’t come with built-in features that will trash them in a short period of time.

In other words, we have to make sure that our innovations take time into account. Whether we know it or not, all innovations have a life span – the way to make them live a long time is to make sure they meet real needs sustainably.

13 Comments

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.

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