Archive for category networks

Make Little Bets for Innovation Success

Posted by Tim in book riffs, connect, experiments, networks on 22 May 2011

To succeed at innovation, you need to be making a lot of little bets. What are little bets? According to Peter Sims in his excellent book called Little Bets, they are:

A small, affordable action that anyone can take to discover and develop ideas.

Here is a more complete explanation in an interview with Andrew Keen:

When I was in Silicon Valley a couple of weeks ago, there was a huge buzz going around about the book, and I was fortunate enough to hear Peter talk about it at a TEDxBayArea event. Interestingly, two different people who had read the book used almost identical words to describe it – they both said something like: “If you’ve been reading the research there isn’t anything new here, but he pulls it together really well.”

That doesn’t sound like the highest of praise, but it actually illustrates one of the main points of the book perfectly: that ground-breaking ideas don’t always look ground-breaking when they launch, instead, they tend to build up out of a series of experiments. Sims has done a great job of connecting up a bunch of ideas that were already out there in a novel way, and building an important new idea out of them. This is the essence of innovation.

He includes a great quote from Steve Jobs that explains the importance of connecting up ideas:

Creativity is just connecting things. When you ask creative people how the did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had an synthesize new things. And the reason they were able to do that was that they’ve had more experiences or they have thought more about their experiences than other people… Unfortunately, that’s too rare a commodity. A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem.

There are several key actions that you can take based on reading this book that will make more innovative, including:

Focus on what you can afford to lose, rather than what you might gain: This is similar to my suggestion that you do as much as you can get away with. The critical point of little bets is that they are little – so if they don’t work, you don’t lose too much. Don’t try to figure out the net present value of a potential idea based on growth projections in which no one can ever have any confidence. Just find a way to test your idea as quickly and cheaply as possible. This is central to any little bets approach.
Build as much diversity into your personal network as possible: the best way to make these creative, novel connections between ideas is to have a diversity of experience, and to encounter a diversity of ideas. One great way to accomplish both is to consciously build links with people that don’t think in the same way that you do. Tom Peters sums this up perfectly: Hang out with the freaks. Peters has been making this recommendation for a long time – find the people that are outsiders, that don’t fit, and spend time talking to them. It’s the easiest way to start making novel connections between ideas.
Don’t expect to have a great big idea come to you in perfect form: the reason that Sims marshalls all of the evidence that he has is to show us that big ideas don’t spring fully-formed from peoples’ minds. Instead, they build over time. As Linus Pauling said, the best way to have a great idea is to have a lot of ideas. The belief that we have to have a great idea in order to start something is a myth, and one of the main ones that Sims is trying to dispel. If you won’t start until you have a great idea, you won’t start. Instead, it is better to execute an idea, any idea, figure out what works, and build from there (he expands on this idea in an excellent interview with Nilofer Merchant).

It’s no coincidence that John and I have used the word “experiment” in 103 different posts on this blog. We keep talking about it because it works, and anyone can do it. To innovate, you need to figure out how much you can get away with (how much can you afford to lose?), figure out how to test an idea within the scope that provides you, learn from your experiment, and build on it.

That’s a little bet.

That’s innovation.

If you want to learn more about the book, here is Sims’ talk as part of the Authors @Google series:

9 Comments

The Problem with Fitting New Ideas Into Old Business Models

Posted by Tim in connect, networks on 14 May 2011

Malcolm Gladwell retells the story of the Xerox Palo Alto Research Center in the latest issue of the New Yorker (it’s readable behind a paywall here). The story of PARC is fascinating, and Gladwell provides a nice twist to it. One of the main threads in the story concerns their invention of the laser printer.

Often when we hear about PARC, the moral of the story is that they made a series of unbelievable inventions, and then completely dropped the ball when they tried to commercialise them, failing miserably, and leaving others like Apple and Adobe to make the money from these ideas. Here I am last week with one of these great ideas – that’s the world’s first Ethernet cable – still there at PARC:

In addition to ethernet, people at PARC came up with the graphical user interface, portable document formats, and they greatly advanced the technology of the mouse, invented by Douglas Engelbart. Xerox didn’t make much money off of any of that work.

But they did make a whole heap of money from another great invention – the laser printer. Some of the key quotes in the story explain why this was different. First, Gladwell talks about Gary Starkweather, the guy that came up with the idea for the laser printer. He was highly creative, and he cranked out a lot of ideas – which led to this problem:

… someone had to turn his tap off: the interests of the innovator aren’t perfectly aligned with the interests of the corporation. Starkweather saw ideas on their own merits. Xerox was a multinational corporation, with shareholders, a huge sales force, and a vast corporate customer base, and it needed to consider every new idea within the context of what it already had.

In other words, you have to be able to embed new ideas into the network of the economy. Doing this requires you to break connections that people already have with old ideas. It’s hard for big companies to do this for the reasons Gladwell discusses in the quote. It’s hard for small companies because they don’t have the clout to get their ideas heard in the first place.

This is a big part of what makes innovation hard.

Gladwell then quotes Nathan Myhrvold to expand on this point:

“Xerox did research outside their business model, and when you do that you should be surprised that you have a hard time dealing with it – any more than if some bright guy at Pfizer wrote a word processor. Good luck to Pfizer getting into the word-processing business. Meanwhile, the thing that they invented that was similar to their own business – a really big machine that spit paper out – they made a lot of money on it.” And so they did. Gary Starkweather’s laser printer made billions for Xerox. It paid for every other single project at Xerox PARC, many times over.

This leads to a key point. PARC is still there, and they are still coming up with brilliant ideas. It has actually been an incredibly successful operation for an extended period of time. By focusing on the ideas that didn’t work so well for them, we recreate a myth of innovation – that every idea that we have must work for us to be successful.

One last quote from the story – Gladwell talks about the views of Dean Simonton, a psychologist that studies creativity, who says “Quality is a probabilistic function of quantity.” That’s a fancier way of saying what Linus Pauling said much earlier – “The best way to have a good idea is to have a lot of ideas.”

Myhrvold says that the way to judge an innovative organisation is not by the failures, and not by the ideas they had they couldn’t figure out how to bring to market. Instead, he thinks we should judge them by the ideas that they do actually execute successfully.

By that measure, PARC has been great, just on the basis of the laser printer. It’s not reasonable to expect every idea to work. Ideally, if one of your ideas eventually becomes successful, it would be good to have it happen for you rather than for someone else.

Nevertheless, successful innovation requires mistakes and misfires. If you have enough of those, and, more importantly, if you learn from them, then you’ll also hit on your share of great ideas that work. That’s the real lesson in the story of PARC.

(interestingly, PARC writes about this story today too! They stress the importance of open innovation in getting around some of these problems, which I think is a critical part in this story.)

5 Comments

There’s More to Innovation Than Novelty

Posted by Tim in connect, innovation, networks on 28 March 2011

When I went to visit Neil Kay last year, we talked a bit about novelty. He said that the way that we frame PhD research is all wrong – that it is a mistake when we tell people that they need to make a novel contribution to knowledge. Instead, we agreed that people should be looking to advance knowledge, which is a bit different than making a novel contribution.

For example, you could write an economics PhD connecting the theories of Alfred Marshall with those of Justin Bieber. That would certainly be novel (at least, I hope there aren’t too many people trying that), but would it materially advance knowledge? Probably not.

Here’s another example – what do you think this is? I’ll give you a hint – it’s a symbol.

It was on a door at the conference venue that I was in at the end of last week. Throughout the two days that we were there, we had a stream of people walk up, look at the symbol, pause, continue walking down the hall and then compare the symbol with those on two more doors. The women then shrugged and walked into the last door, while the men returned to this one.

Somehow, that’s the symbol for “Men.”

This is an example of bad innovation.

It’s a novel way to indicate which room the men should use, but it’s not a good way to do so.

There are a few innovation lessons contained in the cryptic symbol:

Novel ideas are not automatically innovative. Just because an idea is completely new, it doesn’t mean that it’s good. Like the Marshall plus Bieber PhD, novelty doesn’t tell us anything about the quality of the idea. You need more than novelty – in addition:
Innovations need to create value. The weird door sign creates negative value – it confuses people, it may lead to potentially embarrassing mixups, and it wastes time. All of these are bad outcomes. To innovate, we need to execute new ideas to create value. To create value, we must remember that:
Our innovations have to fit within the existing economic network. As Jeffrey Phillips pointed out in our discussion of flying cars, that is a technology that will only work when there are a large number of related technical and social innovations in place that are required to support flying cars.
The problem with the “Men” symbol is that it doesn’t connect to any normally accepted method for communicating that this is the room into which men should go. This lack of specificity might be find in the signage for a trendy new nightclub, where part of the mystique comes from being difficult to find. I don’t know about you, but I prefer toilets without that mystique…

When you’re thinking up ideas, it is critical to think about how executing these ideas might create value. If they don’t create clear value for people, then it might be smart to spend your limited resources executing a different idea that does.

3 Comments

Don’t Push Rocks, Roll Snowballs

Posted by Tim in book riffs, connect, networks on 9 March 2011

Innovation is the process of idea management. One of the critical steps to successful innovation is getting your idea to spread. Hugh MacLeod’s outstanding new book Evil Plans has a lot about how to get your ideas to spread more effectively. One of his tenets is that we should create random acts of traction.

There are two important parts to this idea. The first is that we need to create social objects that have traction – in other words, we are using a pull strategy. The second part is the random bit – we don’t know in advance which ideas actually will gain traction. So we need to experiment, and try out a lot of different ideas.

He starts to frame this idea by quoting Doc Searls:

Tell ya what. I’m fifty-seven years old, and I’ve been pushing large rocks for short distances up a lot of hills, for a long time. Now, with blogging, I get to roll snowballs down hills. Some don’t go very far. But some get pretty big once they start rolling.

See, each snowball grows as others link to the original idea, and add their own thoughts and ideas. By the time the snowball gets big enough to have some impact, it really isn’t my idea any more.

Anyway, at this point in my life I’d rather roll snowballs than push rocks.

Hugh has more great ideas per paragraph than nearly anyone writing these days (he’s in the same league as Charlie Stross) – here is how he follows that point up:

My friends, Dennis Howlett and James Governor, both technology consultants, certainly understand this. As they can only realistically execute on 10% of their ideas, they don’t seem to mind giving away the remaining 90% for free, via their blogs. If one of their free ideas gets “Random Acts of Traction”, it’s great PR for their businesses. It leads to conversations eventually. Conversations that eventually lead to paid gigs.

This only works, of course, if you can make your “snowballs” quickly and inexpensively enough. If you spend too much time worrying about it, you lose. If you try to control where the snowballs go after you’ve released them down the hill, you lose.

“Fail cheap. Fail fast. Fail often. Always make new mistakes.” -Esther Dyson. Words to live by. Exactly.

There are a ton of important ideas tucked in there. The bit about Howlett and Governor having too many ideas to execute themselves is important. It illustrates why we have to have a good process for selecting ideas.

The Dyson quote emphasises the importance of experimenting, and then learning from the ideas that don’t work.

But to me, the important point is that we need to send the snowballs out and see if they gain traction. This is a classic pull strategy. How do we execute this?

Here is how John Seeley Brown, John Hagel and Lang Davison describe their book about this process:

In many respects, The Power of Pull can be read as an attempt to reinstate the central role of socially embedded practice in driving knowledge creation and performance improvement relative to the recent emphasis in the management literature of process reengineering. In short, companies need to refocus technology innovation on providing tools to amplify the efforts of communities of practice to drive performance improvement

If you want to roll snowballs, here are some things to keep in mind:

Your idea has to meet genuine needs. Pull strategies are based on ideas that meet real needs for people. If you are going to spread the idea through a community, people need to talk about it. They will only do this if you have created tangible value for them.
Pull strategies rely on networks. Which strategy is best for doing this? This is still a controversial question. Many people advocate targeting people within the network that are highly influential. I prefer the “big seed” approach put forward by Duncan Watts. Greg Satell explains this idea:

As I explained in an earlier post, he calls his approach Big Seed Marketing. His reasoning is that since influence is so hard to track, it is much better simply to start with a lot of reach (i.e. a big seed) and use social media to amplify it. It seems to me to be an incredibly reasonable and sound approach.
You need to try out a lot of different ideas. Just as you seed your ideas as widely as possible, you try out as many as you can. As Hugh says, you need to roll a lot of snowballs down the hill.

Push strategies are attractive because when you are pushing your ideas, it always seems like you are active, and that you are in control of how successful the idea will be. However, this feeling of control is an illusion. Instead of betting everything on one big idea, we’re usually better off trying out a lot of smaller ones – especially if our environment is turbulent.

So I’m with Doc and Hugh – it’s better to be rolling snowballs than to be pushing rocks.

5 Comments

I Have No Idea How the New iPad Will Do!

Posted by Tim in business models, networks on 2 March 2011

With the release of the new iPad just around the corner, I want to be the first to get in with this prediction for it:

I have absolutely no idea how the new iPad will perform.

I made exactly the same prediction at the release of the original iPad last year. Since people tend to bury their predictions on tech unless they were right, I thought it would be interesting to go back and revisit what I wrote at the time. Now that the iPad has been around for a year, we actually have a reasonably good idea about how the value network is forming around it, so prediction might be a little easier now.

But I’m still sticking with having no idea…

Here’s last year’s post (there are some really good comments on the original post too, which are worth checking out):

With all the feverish discussion and prognostication about Apple’s preview of the iPad, I want to be the first person online to make this prediction:

I have absolutely no idea how the iPad will perform.

I’ll go one step further – neither does anyone else. The benefit of making predictions right now is that if you happen to end up being right, you can link back to your post in a few years. If you’re wrong, well, who reads blog posts that are a few years old?

One line of argument that I find really interesting, though, is being taken by people who are arguing that the iPad will revolutionise… something. The argument is by analogy – and what a lot of people are saying in response to critics of the iPad is that people hated the iPod and the iPhone when they were released as well. In particular, the initial response to the iPod introduction was pretty universally tepid.

Garry Tan from Posterous has collected a few of these, and this one pretty well sums them up:

I still can’t believe this! All this hype for something so ridiculous! Who cares about an MP3 player? I want something new! I want them to think differently! Why oh why would they do this?! It’s so wrong! It’s so stupid!

Haha! It wasn’t Apple that was stupid – they were stupid! Right?

Well, maybe. It’s easy now to look at the iPod’s 70%+ market share and wonder how anyone could have missed that it was a game-changing innovation. I’ll tell you how. The fact of the matter is that all the people that were skeptical about the iPod as a product innovation when it was introduced were actually completely correct. There wasn’t much there. Take a look at the iPod sales figures from wikipedia:

The first iPod was introduced at the end of 2001, and you can see that sales figures for the first three years were not good at all. By the middle of 2004, the iPod’s market share had been sitting in the 20-30% range for a while. By the end of 2005, that had shot up to over 70%. What happened?

iTunes happened.

Because the iPod and iTunes are so closely interconnected now, it is easy to forget that iTunes didn’t exist for the first years of the iPod. At the time, the iPod was just another mp3 player. The innovation with the iPod was not in the product – it was the innovation in the product’s value network. It was a similar story with the iPhone. And that is why nearly everyone that is yapping about iPad right now is completely missing the point. Because we don’t know what it’s value network is going to look like yet, and this is what will actually determine whether the iPad will take off quickly like the iPhone did, or slowly like the iPod.

Even when you make great products like Apple, your innovations never stand alone. They work within the context of their economic network. The better you understand this, and the more innovative you are in constructing your value networks, the more successful you’re likely to be.

So the next time someone talks to about all the great new features something has, ignore them. Instead, think about the business model and the value network that will support the great new thing.

No Comments

Network Economy Problems: How to Get People to Give Up Old Ideas

Posted by Tim in complex systems, connect, networks on 28 February 2011

One core innovation challenge is this: it’s often not enough to simply have a great idea yourself – to get it adopted you also have to get people to give up their old ideas. Here is how John Maynard Keynes talked about the problem:

The difficulty lies, not in the new ideas, but in escaping from the old ones, which ramify, for those brought up as most of us have been, into every corner of our minds.

In her book The Watchman’s Rattle, Rebecca Costa explains this problem in terms of memes and supermemes. Meme is the concept that Richard Dawkins originated to explain culture evolution (there’s a good, short explanation of the idea here). The brief wikipedia definition is that “meme” “identifies ideas or beliefs that are transmitted from one person or group of people to another. The concept comes from an analogy: as genes transmit biological information, memes can be said to transmit idea and belief information.”

Costa identifies supermemes as an integrated set of ideas that become deeply embedded within a society. In fact, she says that they become so deeply embedded that they crowd out new ideas – which stifles innovation:

This brings us to the second reason supermemes spread like viruses: It is much easier to conform than to make a decision about every issue, regardless of whether it’s deciding the color of our roofs to the est car to drive or the most efficient way to educate our children. The more complex life becomes, the more difficult it is to acquire the knowledge we need to make a correct decision. Not only are the decisions we face more complex, we also have to make many more of them and make them faster. From this standpoint, it’s no wonder that group behavior and group think are so seductive. The alternative is to become paralyzed by too much information, too many choices, and too much difficulty.
…
Over time, supermemes become so widespread that they begin acting as filters through which other memes must pass, and only thoughts, behaviors, and beliefs compatible with the supermeme survive. This explains why so many insightful ideas and curative solutions have difficulty coming to fruition. It has nothing to do with the idea itself. As Dean Kamen pointed out, the real obstacles are our “attitudes”- the supermemes that drive how we think and act.

How do we fight this? I’m only halfway through the book, so I’m not sure what Costa’s suggestions are yet.

But one idea that we’ve talked about here is the importance of thinking of innovation as a multi-stage process. As she explains in that quote, it isn’t enough to have a great idea. It’s not even sufficient to prove that it works. To be effective innovators, we have to do both of those things, and then we have to get the idea to spread.

If you are not thinking about idea diffusion right from the start, you are likely to run into trouble. Here are some ideas for improving diffusion:

Get ready for a fight: as Keynes points out, we have to get people to give up their old ideas before they will pick up our new ones. This requires dedication and perseverance.
Better yet, duck the fight by getting people to help you develop the great ideas in the first place. Here is how Graham Hill explains the approach to co-creation:

Co-create value together with customers – A company creates the most advantage by bringing itself, the right partners and customers together in the co-creation of value. Enough value must be co-created to satisfy all involved. Customer co-creation should not be played out as a zero-sum game.
Co-creation requires effective management of value networks. This is the main message in Verna Allee’s work (see her latest book on the topic here). If you are clear about where the value is being created, it will enable more effective co-creation, and consequently better idea diffusion.

Costa explains how complexity encourages us to follow the herd – it’s less taxing cognitively to do so. This is great for us individuals, but not so great for us as innovators.

In these circumstances, having great ideas isn’t enough. We have to be able to get them to spread. Thinking about how to do this more effectively will make us more successful at innovation.

5 Comments

Without People You’re Nothing – Joe Strummer

Posted by Tim in connect, networks on 22 February 2011

I watched The Future is Unwritten again this weekend, the documentary about Joe Strummer by Julien Temple. The Clash were my absolute favourite band for a long time, and I’ve always thought highly of Strummer. The movie gives a pretty balanced view of his life, exploring his faults as well as his strengths. But the point that comes through strongly is how inspirational he was to a lot of people. His final quote in the movie captures some of that:

Throughout his career, Strummer was interested in connecting with people. He seemed a lot more at home giving out flyers on the boardwalk trying to get people to come see his last band, The Mescaleros, than he did being a rock star playing Shea Stadium. In his later years he started organising campfires – the idea being that there was something primal in the kind of connections people make when they share stories and songs around a bonfire.

In this last spiel, he talks about how important it is to connect with people – stop running down your own “little mouse trails…. without people, you’re nothing.”

I keep talking about how we need to ideas to ideas, and ideas to people – but ultimately, all of this is only worthwhile if we’re connecting people with people. Ideas and innovations are simply the vehicles that enable this.

2 Comments

Where Do Bad Ideas Come From?

Posted by Tim in complex systems, networks on 9 February 2011

There’s been a lot of buzz about Steven Johnson’s book Where Good Ideas Come From. An article in Foreign Policy by Stephen Walt addresses the opposite question: Where Do Bad Ideas Come From?

He is talking about bad ideas in foreign policy, such as the domino effect, which have been used to justify policy but which have failed to be supported by actual facts or events.

In part, Walt thinks that bad ideas result from an inability to learn from error:

All countries have obvious incentives to learn from past mistakes, but those that have successfully risen to the status of great powers may be less inclined to adapt quickly in the future. When it comes to learning the right lessons, paradoxically, nothing fails like prior success.

This wouldn’t seem to make sense. After all, strong and wealthy states can afford to devote a lot of resources to analyzing important foreign-policy problems. But then again, when states are really powerful, the negative consequences of foolish behavior rarely prove fatal. Just as America’s “Big Three” automakers were so large and dominant they could resist reform and innovation despite ample signs that foreign competition was rapidly overtaking them, strong and wealthy states can keep misguided policies in place and still manage to limp along for many years.

If you think about this, it sounds a whole lot like the Innovator’s Dilemma, doesn’t it?

The basic premise is that success reduces the incentive to innovate, which results in the propagation of bad ideas.

Bill Easterly wrote a very interesting post today called How Ignorance Dooms Autocracy, which explains in part how this happens. He includes this table:

Tier	Type of knowledge	Recommended actions	System	Compatible with autocracy?
(1)	Certainty (known knowns)	Just do it	Administration	Yes
(2)	Probability (known unknowns)	Hypothesis testing	Academic freedom	Temporarily Yes, eventually No
(3)	Ignorance (unknown unknowns)	Decentralized feedback and accountability	Individual liberty	No

Here is how Easterly describes the three tiers:

Autocrats defend themselves by claiming they live in a word of certainty, where they can solve problems with known solutions (Tier 1 in the above table) through sheer administrative effort.

If the world is really more in Tier 2, where academic freedom is necessary to test and reject hypotheses, then autocrats sometimes try to carve out the space for it, while restricting other kinds of freedom. This can sometimes succeed for a while, but a House Divided against itself cannot stand forever — it will eventually revert to no freedoms or all freedoms.

Much of the development problem is really in Tier 3, where you don’t even know the probabilities of solutions to problems working. Then you need entrepreneurs for business, inventers for technology, and political reformers for institutions, all using a trial and error method where they are accountable to positive and negative feedback. In other words, you need unhindered democracy and markets to support continuing innovation for development to keep proceeding to the highest levels.

Like the powerful countries discussed by Walt and the Autocrats discussed by Easterly, successful firms act like they exist in Tier 1, with no uncertainty at all. When you are in Tier 1, everything is simply an engineering problem, and you don’t have to worry about innovation at all.

The problem is that except for a handful of extremely stable markets, most firms actually operate in Tier 3, with plenty of genuine uncertainty. And Easterly’s prescription for economic development holds for businesses as well – when you face uncertainty the best thing to do is to experiment.

In another excellent post from earlier today, Dave Gray explains one way to address this issue. He starts by discussing data from John Hagel and John Seely Brown that shows that the average lifespan of firms in the S&P 500 has dropped from 75 years in 1937 to 15 years more recently. In other words, the corporate world is getting less stable – they are facing more uncertainty. Gray’s recommendation is to combat this by developing a Connected Company – one that functions more like an ecosystem than a machine.

A connected company is a lot like one built on Jon Husband’s idea of wirearchy, and Steve Denning’s concept of dynamic linking. Here is Gray’s recommendation:

To design the connected company we must focus on the company as a complex ecosystem, a set of connections and potential connections, a decentralized organism that has eyes and ears everywhere that people touch the company, whether they are employees, partners, customers or suppliers.

Social Business Design is a new discipline, but some basic rules are already emerging. These emerging rules have less in common with traditional business design, and more in common with urban design and city planning. It’s not about design for control so much as design for emergence. You can’t control a complex system, but you can manage its growth, and there are a lot of things you can do that will position it for success.

He then goes on to outline a number of practices that support building a connected company – I definitely recommend that you read the whole post.

Here are the key points:

Large systems tend to stagnate over time: this is true of powerful countries, and of established firms. Stagnation is dangerous, because it eventually leads to decline.
These organisations stop innovating because they act like they exist in a world with no uncertainty: if there is no uncertainty, everything is an engineering problem. You don’t need good new ideas. This allows bad ideas to take hold.
One way around this problem is to manage connections rather than hierarchies. Whether we believe or not, we are operating in an uncertain, complex world. One of the best ways to do this is to manage connections. This leads to the development of new ideas, which can lead to the renewal of even large, old organisations.

Bad ideas come from bad structures. One of the best ways to eliminate bad ideas is to build new, better structures. Managing connectivity is a great tool for doing so.

7 Comments

Can Your Friends Make You More Innovative?

Posted by Tim in connect, networks on 27 January 2011

Social influence is important to innovation. One of the critical steps in innovating is getting our great new ideas to spread – and this is often an issue of social influence. Here is an excellent short talk from network researcher Sinan Aral about how to measure social influence:

Sinan Aral: Social Contagion from PopTech on Vimeo.

Here are some of the key ideas that arise from the talk:

The economy is a network: in order to understand how innovations diffuse, and how ideas spread, we have to think about the economy as a network. We don’t make decisions in a vacuum – decisions are a social action (see the collected work of Mark Earls on this topic).
Your network is also important for idea generation: Jorge Barba recently asked whether innovation is primarily an individual or a group activity. It’s a group effort – just as decisions are social actions, so is idea generation.
If your friends are making you fat, are they also making you innovative?: this is the key issue – if idea generation is a social act, and you want to be more innovative, then you need to spend more time with people and groups that are more innovative.

If we want to innovate more effectively, we have to gain a better understanding of how social influence works.

In the meantime, it’s probably a good idea to start hanging out with people that seem to have a lot of ideas.

Let me know what you think.

Or even better, tell your friends to come and let me know what they think!

5 Comments

Is Your ‘Small World’ Network Too Small?

Posted by John in innovation, networks on 20 January 2011

If you are new to this blog, you may not know that Tim and I are business school academics with a particular research interest in networks (person to person) and innovation. We have a few other research interests but this is where we spend most of our time with our doctoral students and industry collaborators. In 2008 we were awarded a substantial research grant from the Australian Research Council on how social network structures affect innovation performance in firms.

Over the past few years we have collected data from a global mining company, engineering companies, high-tech services and local government and we have made some conclusions about a class of network called a ‘small world’. This phrase has entered popular culture and I am sure you have had several small world experience when a new work colleague from another town turns out be a married to a friend from school (or something like that).

As we have said before on this blog, this ‘small world’ experience has also been called ‘six degrees of separation’ and it has been puzzled social scientists for decades. Many years ago, a US sociologist by the name of Stanley Milgram popularized the six-degrees idea by getting people to send a letter to someone they had never met in another US city. The senders had to do this by sending the letter to people they knew who might know the final receiver. The amazing finding was that the average number of steps was a little over 6- hence the six degrees of separation.

The Milgram experiment has been repeated internationally with similar findings and the Kevin Bacon game works on the same principle. The fact that small worlds ‘work’ is a bit harder to explain. We don’t have that many contacts and we mostly prefer to be with people who are culturally or professionally similar to ourselves. This would suggest that the world is organized into distinct clusters of people and yet we have this idea that we are six network steps from anyone on the planet. Surely both clustering and few steps through the network can’t work together? Or can it….

One of the really interesting breakthroughs in network science over the past 10 years is an understanding of why small worlds work – and this has some pretty big implications for managing innovation (which I’ll explain later). Most of what follows here is taken from Six Degrees: The Science of a Connected Age by Duncan Watts. This is a really interesting account of networks and the six degrees problem and it’s very readable.

Watts introduces small world networks as being in between highly structured networks with organized clusters and networks with completely random links

The ‘regular’ sample network is highly structured with everyone connected to their immediate neighbors but count how many steps it takes to get from one side of the network to the other. On the other hand, the random network has few steps between anyone in the network but has no organization to it. The small world trick is that a few random connections across clusters in the network creates shortcuts and turns an organized (silo) structure into a small world. It turns out that this structure is very common in many social networks and this is a real map of a small world network of project engineers within a large multinational business. I have indicated a person who acts as a ‘connector’ by putting a red circle around them.

Collaboration Network of Engineers

Now, I suspect that many of you are thinking about the possibility of having organization structures together with an efficient way of transferring ideas and expertise. The small world network shows us that this is possible and there is a lot of good evidence that it can support innovation. I won’t go into great detail (and you can read a more technical review from Tim and me here) but my favorite evidence comes from the Broadway Musical industry. Using collaboration networks of score-writers, choreographers and librettists, this study showed that block-buster musicals were more likely to occur in the small-world environment.

So far, so good but can your world become too small and too connected? Another really interesting finding from the Broadway study was that too much small worldedness (e.g more clustered and less connected overall) correlated with decreased musical success. This is interesting and we think that there are two things going on here.

A highly connected cluster of people is like a goldfish bowl. Everyone knows everybody else and knows the same thing. Like a goldfish, talking around the network just makes us see the same things and hearing the same information. There is a very strong chance that group think and rigidity will set in when this network structure occurs. Another way of looking at it is that there is nowhere that different ideas can emerge.

The brokers in ‘hyper’ small worlds can get overloaded. When the clusters get too big and overall connectivity relies on a handfull of people they get overloaded or even use their position to selectively filter information for their own benefit. One study that Tim and I have done shows and engineering collaboration network that looks like a small world but the role of the connectors in that instance was to filter rather than pass on information. This small world network resulted in decreased collaboration performance on the project.

Small worlds can help innovation but look out for signs that groups are getting too inwardly focussed on their own work and watch for the overloading of connectors.

Thanks to Sam Macaulay for help with the network data.

10 Comments