Archive for category networks
Using Networks to Find Knowledge
Posted by John in innovation, networks on 1 September 2010
Last week Ralph Ohr left me with a challenge to think about how to use experts to get the best outcomes on making decisions under conditions of uncertainty. We constantly miss disruptive changes in the operating environment and I suppose if I really knew the answer, I wouldn’t be posting it on a blog.
Sometimes predictions are genuinely impossible because of true uncertainty. The future is the future and nothing in the past can help us predict some events. Rather than making predicitons, operational flexibility is probably the best response to this type of uncertaintly.
On the other hand, sometimes the emerging disruptions are right under our noses and the problem is getting over myopia. Experts can suffer from myopia as well as the rest of us so perhaps the issue is finding the right expert with the right interpretation of what is happening.
This means that an organization’s networks can be crucial in determining the successful search for the right person with the required knowledge. Tim and I have been doing some work for a large organization that is trialling new ways of doing business. It seems that one of the issues that is faced by this organization is building the expertise networks acrosss the business to find the right person to give their opinion and expertise at critical decision making points. However, in large organizations, this is difficult. A colleague from a large multinational mining company sums up the issue in the following diagram.
As you can see, effectively using the knowledge of the business means trying to get better connections to reduce the size of the “I don’t know who to ask” space.
So how can we do this? One possibility is that we direct our questions to people in the organization that we know are very highly connected. However, one simulaiton study of search in a real organizational network has found that this might result in more steps needed to find the right person. In this simulation, a slightly more efficient search could be conducted by going to the manager who is responsible for the subject area that is being investigated or by starting the search in the right department.
The simulation study needs more investigation and we have a PhD student looking at the problems of search in large organizations. However, if formal lines of enquiry can be shown to be associated with efficient search networks then this suggests that organizations may be able to connect pockets of knowledge by identifiying subject matter experts and linking them to critical projects.
Manage Knowledge Flow not Knowledge Stocks for Innovation Success
Posted by Tim in book riffs, innovation strategy, networks on 6 June 2010
I am always skeptical of ‘everything is different now’ style arguments. If we think about the history of business, we have been trying to manage in a state of turmoil going back at least to the start of the industrial revolution, possibly longer. The introduction of railways, the telegraph, electricity and the automobile were all disruptive to lifestyle and business to a degree that is at least equal to and probably greater than we are seeing with the introduction of computers and the internet.
The real issue isn’t that ‘everything is different now’ – the real issue is that people are profoundly uncomfortable with uncertainty. Authors, consultants and others seeking to push an idea take advantage of this discomfort by making sweeping ‘everything is different now’ style arguments to justify whatever it is they’re pitching. It works, but it’s not a very good way to do business.
That is not the approach taken by John Hagel III, John Seeley Brown and Lang Davison in The Power of Pull, which may well be the best business book of 2010. Hagel described some of the key points from the book at the recent Social Business Edge event organised by Stowe Boyd. The video of Hagel’s talk is worth watching (as are those by Venessa Miemis and Baratunde Thurston, among others – it looks like it was a great day!):
Hagel’s talk emphasises two points that I haven’t seen discussed much in reviews of the book. The first is the statistical review that they use to identify just what it is that has been changing in the business world. This is based on the work published in The Shift Index, a report that the authors put together for Deloitte’s Center for the Edge. They assembled statistics on all of the publicly listed firms in the US from 1965 to now. One alarming thing that they discovered is that Return on Assets has steadily declined over that time – it is now about 25% of what it was in 1965 (the figure below is taken from the report).
This is pretty good evidence that things are in fact changing, and the report also provides some evidence of how things are changing. The second point that Hagel brings out is that their belief, based on the evidence, is that this change in ROA is due in large part to a shift in emphasis from knowledge stocks to knowledge flows:
The Flow Index focuses on the key drivers of performance in a world increasingly shaped by digital infrastructure. This includes both physical and virtual flows of knowledge, capital and talent enabled by the foundational advances as well as the amplifiers of these flows. Such amplifiers include the increased use of social media and the degree of passion with which employees are engaged in their jobs.
…Improving performance starts with recognizing that knowledge flows can help a company gain a competitive advantage in an age of near-constant disruption. The number and quality of knowledge flows at a firm — both within the organization and especially across institutions — will be a key indicator of any company’s ability to master the Big Shift.
This shift from knowledge stocks to knowledge flows has several critical implications for managing innovation, including:
- As Hagel says, tapping into knowledge flows is not really about engaging in conversation – it is about using these flows to create new ideas. As we have discussed many times here, a fundamental error that many organisations make when they try to become more innovative is to focus on stockpiling ideas – this is a knowledge stock approach. It is much better to focus on making novel connections between ideas – this is the knowledge flow approach.
- In other words, we need to get better ideas, not more. How? By tapping into knowledge flow through our networks. This is how Hagel and Brown describe this in an excellent paper on creation networks (.pdf), which tries to frame a rigorous approach to managing open innovation:
Creation nets represent a particularly powerful form of open innovation
designed to harness the potential of distributed innovation activity
pursued by hundreds or thousands of participants. Creation nets
implement a set of institutional mechanisms designed to mobilize
independent entities in the pursuit of distributed, collaborative and
cumulative innovation. These institutional mechanisms are critical to
understanding how creation nets coordinate innovation efforts and how
these creation nets will re-shape the role and structure of the firm.These networks are assembled by a network organizer who serves as
gate-keeper, deciding who will be able to participate in the network. The
network organizer also defines fundamental governance processes to
coordinate the activities of the network, for example, determining how
disputes will be resolved and how performance will be measured. These
participation protocols are generally simple and informal, especially in
the early stages of network formation. Participation in the network is
rarely established through formal contractual documents, although
specific initiatives within the network may be governed by such contracts.Network management is an essential business skill these days. And we need our networks not just as a source of information, but as a resource for generating novel connections between ideas. We can do this by co-ordinating idea exchange within networks of people that share our interests and/or objectives.
We need to stop trying to stockpile ideas. It is much more important to use the ideas we have to create innovative connections. In managing innovation, this means looking at our process for managing ideas. We need to generate great ideas (better ideas, not more!), we need a system for selecting the best ones and trying them out to see if they’ll work, and we need to get the ideas to spread.
Our networks are particularly important in all of these steps. The creation nets that Hagel and Brown discuss are using networks to generate better ideas. Our networks also help us use empathy to help select the best ideas to pursue. And networks are obviously essential for getting our ideas to spread.
Network thinking is at the centre of managing knowledge flows. And as The Power of Pull demonstrates, if we are going to be successful these days, we need to be managing knowledge flows, not knowledge stocks. I’m still not sure if ‘everything is different now’ – but I’m reasonably confident that this is a worthwhile change to make.
Grassroots Innovation
Veronica Vera pointed me to a great talk by Anil Gupta from TEDIndia. He talks about grassroots innovation, and methods for getting ideas to spread in poorer regions. It’s a fascinating talk:
Innovation in developing countries is a wildly unappreciated phenomenon – there are incredibly interesting things going on in places like India, China and Brazil. Some of them are built around finding innovative ways to provide goods and services to poorer people at much lower costs. Aravind Eye Care and the Tata Nano car are just two good examples of how this works.
Gupta is talking about something different though. He is not approaching poor people as consumers, but as inventors. This is reflected in one of the slogans of the Honey Bee Network – minds on the margin are not marginal minds.
The Honey Bee Network has done some great work in cataloging thousands of inventive ideas that people have developed. Most of them are things that make their own lives better, but many of them also have much wider potential applications. There are several important things that we can learn from this.
- Innovations diffuse through networks – inventions inventoried by the Honey Bee Network have gone through two steps of the innovation process. Someone had a great idea, and they figured out how to make it work. The next step is to get the idea to spread. The HNB takes a network approach to getting people to share ideas. Their objective is the creation of technology commons – ideas are free for people to people use, but a license is required for firms. By cataloging the ideas in one central registry, it is much easier to help people connect up with the ideas. To get the ideas to spread they are creating a network.
- Use a portfolio approach to take advantage of the long tail of innovation – one of the big issues in diffusing these ideas is that many of them are of use to a relatively small number of people. Guptil argues that this should not discourage attempts to get the ideas to spread. By developing a broad network of people interested in grassroots innovation, it is easier to locate the people in the long tail. The central registry of ideas makes it relatively easy to sort through them and find ones that are appropriate to use in particular circumstances.
- Not all good ideas come from where we are – Guptil says this when trying to encourage Indians to be more willing to adopt ideas from China and Brazil. The idea applies more broadly too. It doesn’t matter where you are – there are plenty of great ideas that come from someplace else. It benefits us to be humble enough to realise this and to learn from others.
This is actually a great example of an aggregate, filter and connect value creation strategy. The Honey Bee Network does all three very effectively. They have aggregated over 10,000 great inventive ideas from around the world. By assessing and describing each one, they enable potential adopters to filter through this huge database to find the ideas that will be most useful. And they have created an extensive, strong network that they can leverage to connect ideas to ideas, and ideas to people. This is how they get the great ideas to spread.
There are great ideas everywhere – the key to innovation is developing systems that allow us to test these ideas and get them to spread. The Honey Bee Network is a great example of how to build a platform that enables the process of innovation to take place – even in locations that many people don’t often think of as innovative. There’s a lot we can learn from this.
Here is a full slide show from Anil Gupta that has more detail on a lot of the examples that he uses in his TED talk:
Network Math
Posted by Tim in innovation strategy, networks on 6 May 2010
Metcalfe’s law explains why networks are so valuable – it says that the value of a network is proportional to the square of the number of users. When Kevin Kelly explains this, he illustrates it by saying that the first person with a fax machine was an idiot. What can you do with the only fax machine in the world? Once there are two, you can communicate with each other. And as the network grows, according to Metcalfe’s law, the value created by the network grows even faster than the number of people in it.
This is true of fax machines, of telephones, of internet users, and of social networks. Once we get to very large networks, the number of potential connections available to us is staggeringly large. This high level of potential connectivity is important. It’s one of the reasons that people are willing to stick with Facebook despite each new abuse of their private information – everyone is on Facebook. You can switch to a different social network with better privacy policies, but because currently all of the competing networks are much smaller, the potential value to people is much lower as well.
While the potential connectivity creates the value in these networks, there is a potential downside to large networks. We want to have the ability to reach a large number of people, but we can’t maintain connections with everyone. These large networks tend to be pretty sparsely connected, because it is expensive to build and maintain connections. Think about how much time you’d spend if you were friends with everyone on Facebook – your newsfeed would be impossible to keep track of, and you wouldn’t be able to separate out the news from people you actually care about. At a more basic level, while it’s pretty cool that when you have a telephone, you can call everyone in the world, but what if everyone in the world suddenly decided to call you? High levels of connectivity in large networks are overwhelming.
This is why network structure is important. Every real network consists of a set of ties that are actually a small subset of the total number of possible ties. Consequently, the structure of these ties is very important. Here are some examples from Valdis Krebs’ excellent blog The Network Thinker – a group of ten people might be organised like this:
There are 90 possible ties between 10 people (n * (n-1)) – but this network only has 9 ties. The density is 10% – which is fairly typical for an organisational network. You can see that it has a high degree of structure – it is a hierarchy. In fact, it is an org chart. That’s one way that we can visualise how the group is organised and interacts.
However, if you look at who actually works together within this group, you get a very different picture:
That network is still sparsely connected, but you can see that the structure is quite different. Why is this important? Valdis’ original post makes the point beautifully. We need to understand our actual work-flow and information-sharing network structures in order to get the results that we want within our groups.
Org charts rarely reflect the true network structure of a team. Our actual networks are never fully connected. Metcalfe’s law suggests that the value in large networks is in the potential ability to reach everyone. But in practice, you can’t be connected to everyone. Consequently, the actual structure of connections within a network becomes important. It can be highly structured, like a hierarchy. It can be completely chaotic, with nothing more than random connections between members. Or it can look more like the work-flow network above. In any case, we need to understand the actual structure of our networks if we want them to perform well.
Innovation: Concentrate on People and Process, not Tools
Posted by Tim in innovation strategy, networks on 15 April 2010
Imagine that you are a unit manager in an organisation, and your CEO comes to you and says: “We need to be more innovative – you’re in charge of making that happen.” What’s the first thing you should start thinking about?
In many cases, people in this situation go out to find tools that will help their organisation improve innovation. They set up communities of practice, or they buy a big software package designed to capture ideas, or they investigate technologies that support the innovation process. In other words, they try to figure out which tools they need to do the job.
This is wrong.
I was reminded of this when reading a post by Valeria Maltoni – Why Starting from the Tool is the Wrong Approach – which looks at the issue from a marketing perspective. She talks about a new twitter analytical tool which is designed to measure interactivity, and makes a couple of good points:
You should never start from the tool when you think about your marketing strategy using emerging technologies.
However the tool works, I can tell you one thing — don’t ever rely on data without understanding the context in which it lives. As you can see in this case, there are many more variables at work than meet the eye. Some data is qualitative and will not be captured in an easy to boil down metric, it has to be experienced to be real.
The point that she’s making is that if you’re trying to figure out how to use twitter, you need to develop a strategy and execute, rather than starting with a tool or some set of metrics and working backwards from these to figure out what your strategy will be.
It’s exactly the same with innovation. Tools are precisely that – tools, not a strategy, and not drivers of strategy. Innovations come through making new connections between ideas. These are frequently the result of interactions between people. These interactions can reveal a problem that needs to be solved, they can create a synergy that drives novel thoughts, they can lead to the innovative combination of ideas.
When you’re trying to improve innovation, the first thing to consider is people. Who should be involved in our innovation processes? Do we want to include ideas from outside our organisation? Who is connected to whom? How can we improve the connective structure of our networks? How is information flowing through our organisation?
Once you’ve thought about people, then you need to think about innovation process. Innovation is not simply coming up with novel connections between ideas – that’s just the first step in a three-stage process. In addition to generating ideas, you need a system for selecting and developing the most promising ones, and once you have them working, you need to be able to get the ideas to spread so that people adopt your innovations. The questions to ask here include: how will we generate new ideas? Will we use some kind of open innovation strategy? Can we use crowd-sourcing or innovation jams? How we will select the ideas to develop? What processes do we need to experiment cheaply to test the ideas that seem most promising? How will we develop innovative business models to help spread our new innovations? Where are we in the value network? How can effectively embed our innovation within this network?
In answering these questions, consider the overall strategy of your organisation – you’re trying to integrate innovation into this strategy. Once you’ve done this, then you can start thinking about what tools might help you achieve these strategies. There are many technologies that make innovation more effective – communities of practice, idea jams and various software and communication tools for idea development; tools like stage-gate for idea selection; simulation, rapid prototyping with computers and 3d printing for idea testing; and business model development techniques to help your ideas to spread.
But if you are going to successfully fulfill your CEO’s request, you need to think about people and processes first. Only then can you start thinking about tools.
Can networks make your world small?
Posted by John in connect, innovation, networks on 14 April 2010
I realized the other day that we haven’t said anything on the blog about small worlds and how they help innovation. This is odd because it is a major research project for us so today I’ll summarize some of the current thinking and evidence in this space.
I grew up on the small island of Tasmania, which has a population of around half a million people. Now half a million is actually quite a lot but I always had a sense that we were closely connected. If I didn’t know somebody then there was always a strong chance that I knew someone who knew that person. For those of you who live in bigger population centers, I’m sure that you still have the experience of meeting someone who is an unexpected friend of a friend (although this might not happen as often as it did for me in Tasmania).
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 the network creates shortcuts and turns an organized structure into a small world.
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 small-worlds can help innovation, but I also think that the network science has some serious management implications.
Try to foster a bit of randomness in the organization
-It only take a few random links to turn a structured network into a small world. Encouraging different people to talk to each other can have big payoffs, even if very few of these contacts turn into lasting collaborations.
Understand who is making the network small and look after them
-the flip side of the small number of random links creating a small world is that they can easily be accidentally removed or overloaded. Many of the firms we work with on the research are surprised to learn who these critically important links are.
We need to continue the research into small worlds and innovation but the early evidence in encouraging enough to share with business. Network analysis has a big future in the management of innovation.
What Motivates Knowledge Brokers?
Posted by John in connect, innovation, networks on 7 April 2010
I wrote a post last week about the importance of connecting different groups as a precursor for innovation and the special role that some people have as bridges between disparate knowledge communities where ‘structural holes’ exist within the network between the communities. After writing this post I went looking for more research on the psychological characteristics of these “knowledge brokers” who bridge these groups and are a major factor in both generating new ideas and also getting ideas to spread.
What I found was an excellent review article by Garry Robbins from the network group at the University of Melbourne. The leaders of this research group, Garry Robbins and Pip Pattison are both outstanding research academics and genuinely nice people who are generous with their expertise and experience in network analysis. They run a network analysis course each year in July, which I highly recommend to anyone wanting to learn about network theory and analysis.
While Garry says that we need to do a lot more to understand the connections between networks and the personalities of people within networks, he says that we already have good evidence for the traits and motivations of knowledge brokers.
Last week I wrote about ‘self-monitoring’ or the ability to be socially adaptable as a characteristic of knowledge brokers. There are several studies that support this, but knowledge broking isn’t an easy job. While knowledge brokers are entrepreneurs in the sense that they can see valuable opportunities because of their position on the bridge, occupying the bridge can also be very stressful.
Knowledge brokers aren’t insiders, they are on the edge of two or more communities. It’s a precarious position to be in and knowledge brokers need to work hard to stay involved with multiple groups with different cultures and expertise. If you have ever asked yourself why everyone isn’t a knowledge broker, then this is probably the answer. It’s both intellectually demanding and stressful.
Knowledge broking can have significant personal payoffs but also high rates of stress and failure. It’s a high-risk/high-return personal strategy. If we think about bridging this way then just being multidisciplinary and socially adaptable isn’t enough to be a broker, other psychological traits must be involved too. For those of you who believe that some people are natural brokers, there is definitely evidence to support the idea that fundamental psychological traits can support the role of a broker, as Garry explains:
Burt found that respondents with networks rich in structural holes were inclined to be independent outsiders in search of change and authority; whereas those with few structural holes tended to seek conformity, obedience, security and stability.
In other words, knowledge brokers aren’t just social chameleons, they can also be disruptive change agents and a real pain for those interested in keeping everything just as it is. They are risk-takers and iconoclasts – two very important characteristics for entrepreneurs in general. However, Garry elaborates on these characteristics by referring to some of his own research:
….people who saw themselves as vulnerable to external forces tended to inhabit closed
networks of weak connections; whereas people who sought to keep strong tie
partners apart, and so to bridge structural holes, tended to be individualists, to
believe that they controlled events, and to have higher levels of neuroticism. Finally,
people with strong network closure and “weak” structural holes tended to categorize
themselves and others in terms of group memberships, akin to the social identity
effects discussed above; and they were more extroverted and less individualistic.
So knowledge brokers tend to highly individualistic with strong self-belief. Exactly the kind of person that could be brought into the manager’s office and given counseling about not being a team player. In the psychological sense, neuroticism is the tendency to experience negative emotional states such as anxiety and depression. Not exactly what you would call an ideal work colleague. On the other hand, the team player is unlikely to make a good knowledge broker and will instead create lots of links to close colleagues.
So here’s the paradox. Brokers are essential for innovation but harder to manage and work with. We don’t need everyone in the organization to be a broker but we do need some of these idiosyncratic people to make the networks form across holes and create new opportunities for recombining knowledge.
But if these people are individualistic and need change, then how do we align their goals with the organization. I think this is a really important question for sustaining innovation and it’s come up in discussions with several managers who we are doing research projects with. What do you think?
You Have to Break Connections to Get Your Ideas to Spread
Posted by Tim in design, evolving economic entities, networks on 19 March 2010
Next time you get in a car to drive somewhere, take a minute to think about how many parts of the economy are connected to your trip. There are a whole lot. There all of the people and firms involved in building your car. They have taken ideas and designs that have evolved for over a hundred years, added some new ideas, and come up with the design for your car. And if you drive a Toyota, it’s not just people in Toyota that have done that – there are hundreds of other firms that have designed particular parts – brakes, stereos, and windshield wipers.
Then another bunch of people and firms built the actual car. For the vast majority of cars, this didn’t happen in the city or town that you live in – so yet another bunch of people and firms were involved in getting the car to your particular location so that you could buy it or lease it. This includes shipping companies, trucking firms, and dealerships.
So that’s a lot of people involved with just getting the car to you in the first place. Now you turn it on – petrol ignites (if you’re driving a hybrid it takes a while longer to get to this point, but it still happens). How did that get to your car? Another chain of research, design, production and distribution. Thousands more people and firms.
Then you start driving. On what? Roads. How did they get there? Same story, although in this case a government almost certainly had something to do with it.
Every single thing in the economy is embedded deeply into these economic networks. Design, production, distribution – no matter what we’re talking about, nothing stands alone.
When you come up with a great new idea, you need to think about this economic network in two ways. The first is: how can I connect to all of the complementary parts of the economy that are needed to get my idea to work? The second is: if I’m going to get my idea to spread, which of these existing connections need to be broken?
We’ve talked before about the importance of making new connections to get your idea embedded within the economy. But breaking connections is also important.
Ford wants to get me to break my connection with Toyota and forge a new one with them. If they are successful, the overall economic network impact is relatively small. Many of the same firms are involved in making parts for both Ford and Toyota. Many of the same shipping and trucking firms move vehicles for both. I’ll drive my new Ford on the same roads, and I’ll probably buy petrol from the same stations. So the impact of that change is small.
But what if I want to buy a Honda FCX? Then things get a bit more complicated. The FCX is a hydrogen-powered car, and it’s pretty cool. But if I want one, I have to break my connection with Australia, and rebuild the one with California, because that’s the only place they’re being sold. And because they’re only sold through fleet sales, I’d have to get a job that is affiliated with the right car fleet program. So on a personal level, the connections that I would have to break to buy an FCX are much more substantial than the ones that have to be broken if I just switch to a generic Ford. And it’s extremely disruptive.
The changes required by the FCX are pretty disruptive within the economy as a whole as well. We’ve got roads already, so that at least is covered. And some of the parts manufacturers will be the same as those involved with making regular cars – tires, seats and body parts will all be essentially the same. But a lot of new suppliers need to be added to the supply chain for hydrogen-powered cars. There are hydrogen fuel cells, which replace the petrol tank. Hydrogen requires a different ignition method, so the engines have to be completely different. In connecting to manufacturers in these new areas, Honda is breaking connections with suppliers that have gone back many years.
Many connections need to be broken outside of Honda as well. Where do we get hydrogen for our hydrogen-powered cars? Currently there’s no infrastructure for this. We need new plants to make fuel-quality hydrogen, new methods of transporting this hydrogen once it’s produced, and new places to get the hydrogen. These will actually replace oil refineries, oil pipelines and petrol stations. That is a lot of disconnecting.
Everything is embedded within the economic network. So when we have a great new idea, we need to get people to connect to it to get it to spread. As Umair Haque says, we do this by making it awesome. However, we also have to be aware of the connections that need to be broken to get our ideas to spread. This can get pretty complicated. It’s not just Toyota and Ford that don’t want me to connect up with a Honda FCX. It’s Shell and BP, and all the companies that make petrol-driven engines, and all the petrol station owners, and many more. A lot of these firms will actively fight to prevent having the connections broken.
This is why having a great idea, and even executing it really well, aren’t necessarily enough. The critical third part is to get your idea to spread. This isn’t meant to be discouraging. I’m simply saying that for our innovations to be successful, we need to think about where they fit within the economic network. A lot of these connections are relatively in obvious in the case of cars, but even if you’re introducing a simple new way of doing things, you have to get people to disconnect from the old ways too. By thinking of the economy as a network, we’ll get better at getting our ideas to spread. But to get people to connect with our new ideas, we have to getting them to disconnect first. Yesterday I said that making connections is the fundamental creative act in innovation. This is definitely true when we are generating great ideas. When we are getting them to spread, connecting our ideas to people is important, but so is getting them disconnected from other ideas. That’s the key challenge in innovation diffusion.
The Economy is a Network
Posted by Tim in complex systems, connect, networks, time on 9 March 2010
The word “network” causes a lot of the same problems that “innovation” does – it is used in so many different ways that it is often hard to tell exactly what the user means, it’s in fashion to the point of sounding like hype, and as a consequence a lot of people are ready to stop using it altogether. So when I say that “the economy is a network” it can cause some confusion. Do I mean it is like a network? That is has network-like properties? That it’s something between a hierarchy and a market?
No. I mean that the economy is a network – and that the best way to analyse it as a network. In network analysis, a network consists of nodes (people, firms, countries and so on) and the connections between them (economic exchange, friendship, family relationships, disease vectors and so on). An economic network then is one where people are the nodes, and the economic relationships form the connections between them.
Thinking about economics in this way leads to some useful insights. I was reminded of this when I read Umair Haque’s latest post today – The Real Roots of Recovery. Here is how he sets up the problem that he’s trying to address:
What is an economy? Is it just rivers of money and stuff, flowing back and forth between consumer and producer, resting on a bed of information? That’s more or less the way we’ve conceptualized it. It’s why economists often say that banks and funds make up the “financial economy,” while industries that make stuff are the “real economy.”
When we conceptualize an economy that way, the implicit goal for both “producers” and “consumers” is merely accumulation of money and stuff. More, more, more. That’s what I call a “thin” economy. That kind of economy is thin in three ways: it’s brittle, easily broken; it’s fragile, crisis-prone; and it’s as shallow as Paris Hilton.
His suggestion is that to make a stronger economy, a “thick” economy, we need to focus on making real connections with others.
Yet even that’s just a beginning. The economy is “constructed” by us: built anew every second of every day by each of our billions of tiny decisions, emergently. The real change begins with each of us, and the choices we make.
This is a network story! The issue with networks is that ties are expensive to maintain. If we think about economic ties, the involve money, attention, time and care. My read of Haque’s argument is that we tend to only think of the ties in terms of exchange. In this view, we choose to buy a loaf of bread, we pay for it, and that’s that. That’s thin. A thick network tie will consider attention, time and trust as well.
What does this mean in practical terms? If we think of our economic relationships as network ties, then the idea that every transaction is a one-off makes no sense at all. Each time we need something, we have to figure out who is cheapest, where they are, and how to make that transaction. On the other hand, if we think of economic relationships as network ties, as something that persists – we value them differently. Now trust becomes more important, as does attention. We want ties that we don’t have to worry about because we know what we’re getting. We want a stable, persistent network. The way to get that is to build relationships with the people in our personal economy. We don’t have to recreate a whole new network each time we need something.
Viewing the economy this way also changes where we want to be in the economy. Take a look at this network diagram from Valdis Krebs:
The people that I’ve circled are those with high betweenness centrality (learn about that here). In an exchange economy, those are great positions to be in because you can take advantage of your position in between two big clusters. Any goods or information that has to pass between the two groups has to go through you, and this is profitable. However, this also leads to a brittle network. If you lose the people with high betweenness, the network breaks down as the groups become isolated.
If you take a network view of the economy, you become worried about the overall structure of the network. You build links between people so that there is redundancy in the network (network weaving!). This is the strategy that O’Reilly Media has used very successfully. In a network economy, we try to build up the structure of the network to increase resiliance.
Finally, thinking about the economy as a network helps with innovation. In an exchange economy, you just have to get your new ideas out there. If they are better, people will buy from you. Everyone that has ever tried to get a new idea to spread knows that it’s not this easy. We have to get people to disconnect from whatever ideas they’re currently using and adopt ours. If we think of the economy as a network, this process makes sense. Our innovative ideas (new products, newservices or new ways of doing things) have to build new connections. Often this means that we need people to break old connections. This is the central problem in idea diffusion.
The economy is a network. Think about it this way and suddenly we move beyond transactions. The nature of the economic ties between us becomes much more important. These ties involve money, time, attention and trust. If we pay attention to these four things as we build up our economic network, we’ll start building a thicker, more resilient economy.
Information Wants to Be Free?
We often hear that “information wants to be free” – but does it really? If it does, why did my research partners and I just pay $13,000 to get a copy of this database?
Now that’s admittedly 13,000 Australian dollars, and once you take exchange rates into account it comes out to — a whole lot, in any currency. Why is it worth that? And why did we get it? Alert readers will be able to guess that the answer to both questions is aggregate, filter and connect.
This is a concrete example of creating value from information in both cases. First off the database. It is a compilation of data about strategic innovation alliances going back over 30 years. The data has been aggregated from public sources. It has also been filtered – out of all of the available news about strategic alliances, the original researchers have filtered out all of the ones that are not innovation-related. They’ve then also aggregated data about the objectives of the alliances, start and end dates, industry, and several other things. And they’ve connected all of that data together into a database. By starting with widely available information, they have used aggregating, filtering and connecting to create a valuable resource for researchers.
The people that have put the database together have already done plenty of analyses of the data, and published many papers on their findings. So why would we pay for data that has already been pretty thoroughly worked over? Because we can aggregate, filter and connect too. In this case, we’re paying them for most of the aggregating and filtering, but we have some unique connecting capabilities that makes it worthwhile for us. I have some skills in longitudinal data analysis that are fairly rare – connecting these with the data will create new information. My primary collaborator has developed some unique economic theory, which we’ll connect with the outcomes of my network analyses. By connecting our unique skills and knowledge to a database that anyone can buy, we’ll create new value.
Our objective is to provide some practical insights that will help organisations manage innovation collaborations more effectively. Studies show that somewhere between 50-80% of all innovation alliances fail to meet their objectives. If we can figure out a way to improve these outcomes it would be quite valuable.
So the next time someone tells you that “information wants to be free”, remind them of the entire quote from Stewart Brand:
On the one hand information wants to be expensive, because it’s so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.
And then remember that the way to create the expensive information is to aggregate, filter and connect.
