Archive for category complex systems
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.
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:
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!
Filtering With Your Network
Posted by Tim in complex systems, filter, innovation strategy, networks on 27 January 2010
In yesterday’s post on Personal Aggregate, Filter & Connect Strategies, I didn’t have room for one key point: one of the key filters to use is your network. When he was in Brisbane last month, George Siemans gave a talk with an example that illustrated this perfectly.
For the past couple of years, he has run a course on Connectivism with Stephen Downes. Here is the definition of connectivism from Downes:
At its heart, connectivism is the thesis that knowledge is distributed across a network of connections, and therefore that learning consists of the ability to construct and traverse those networks.
As I understand it, one of the points of the course is to present students with so much data that they can’t possibly process or understand all of it as individuals. This forces them to create networks to build data-gathering and sense-making networks in order to succeed. There are more details about networks, connectivism and the course in this excellent presentation from Downes (the presentation also discusses Downes’ framework for building knowledge within complex networks, which consists of Aggregate – Remix – Repurpose – Feed Forward).
So as individuals, our network is part of our filtering system. This also points out how the three processes – aggregating, filtering and connecting – interact with each other. In the example of my twitter feed, I discussed this as part of my aggregation strategy. But at the same time, I’m actually counting on people within my network to filter. They’re not sending every little thing that they run across into their twitter streams – they are selecting.
This same process happens as part of the aggregate, filter and connect process for organisations. We can use our networks as aggregating/filtering tools. This is what is happening in customer-led innovation, crowd-sourcing and open innovation. We use our network to increase the flow of ideas into our organisation (aggregate), and we also count on our network to decide which things they run across might be important (filter).
And just as for individuals, these processes don’t work well for firms either unless they are good at all three steps. If you only aggregate, you get overwhelmed with ideas. You need some form of selection process. Both forms of connecting are important too. You must be able to connect ideas in novel ways – this is one of the central skills in innovation. If you’re not generating and executing your own innovative ideas, you run into several problems. Open innovation won’t work, because you’re not bringing anything of value to the table – so why would anyone want to partner with you? Customer-led innovation and crowdsourcing won’t work either, because the skills need to tell which ideas are worth pursuing – your filtering is worse if you’re bad at connecting ideas.
Outbound connecting is also critical – this is how we get ideas to spread. In the case of firms, getting ideas to spread is a critical part of innovatgion diffusion. This is also a network function. Using our networks to help with filtering is essential – both for individuals and for firms.
This is one of the reasons that we are doing research on networks. Knowledge creation within firms is also a network function. John and I recently made a video to use to explain network analysis and our main research project to people that are participating in our studies. Because many of them are in remote locations, we can’t visit everyone. And we figured that showing them a video might help them feel more of a connection with us than simply sending them a document with the same information. Take a look at this, and keep in mind the value of your network in executing aggregate, filter and connect strategies:
UQBS Innovation Networks in Project-Based Firms Information Video from Tim Kastelle on Vimeo.
Personal Aggregate, Filter & Connect Strategies
A while back my PhD student Sam and I were talking, and he asked me about my RSS feed. His question was something along the lines of ‘what blogs would I have to read if I wanted to be able to make the connections that you do on your blog?’ As we talked, I realised that it didn’t matter if I gave anyone else my exact RSS feed, they wouldn’t be able to replicate my blog – and the reason for this is aggregate, filter and connect.
When I first thought about aggregate, filter and connect as a framework, it was in an attempt to explain why Amazon’s business model worked better than that of other online bookstores. The first time I talked about it in public, it was to explain how open education might work. I’ve been working on making it in to a general model of how we create something unique when we’re primarily dealing with information.
As such, it can be used to explain business models, like Amazon’s, or blogs, like mine. The more I’ve talked about the model, the more other people are picking it up, which is great. Some of these recent discusssions have gotten me thinking about how aggregate, filter and connect works at a personal level. This was really Sam’s question. I’ve talked about how Charles Darwin basically used an aggregate, filter and connect strategy, Phil Long talks about it as part of personal knowledge management, Harold Jarche has discussed it as both a general model for business and for personal knowledge management (an idea that Jack Vinson picked up, and connected to the concept of enhanced serendipity from Ross Dawson), and Glenn Wiebe used the framework to discuss both Joseph Priestly’s inventions and teaching. So we’re starting to get a bit of discussion Today I’d like to illustrate the concept by discussing how I use it.
Aggregate, filter and connect is a non-linear process, with lots of feedback loops. However, it is unavoidable to talk about it in steps. While I do that, keep in mind that it is all going on at once. Here is how I use the framework to execute ideas in my main area of interest – innovation and networks:
Aggregate: I do a lot of data scanning. The RSS feed that Sam and I were discussing includes 182 blogs. I also follow 306 people on twitter, most of whom usually tweet about things relating to my areas of interest. In addition to that, I finish a book about once every 3 days, and I’ve been doing that for a looooooong time. I also talk to a lot of people, despite being an introvert (see Sacha Chua’s great presentation The Shy Connector to see how that works) – last year had over 80 meetings with people that are practicing innovation management, plus contact with my students, who are nearly all out in the workforce as well. Then there’s the stuff I’ve learned in all the jobs I’ve had. Collectively, this adds up to a fair bit of data.
Filter: This is my weakest area – I don’t outsource nearly enough complexity. I need to get better at taking notes on things I read, in searchable media, so that I don’t do all the filtering in my head. At the moment, I don’t even filter my twitter stream. Ken Gillgren argues that we should be taking in as much data as we can possibly handle, to improve our ability to see patterns and make novel connections. So I’ll say that’s what I’m doing. In addition to my head, I’m also using Evernote, my own tweets, diigo, and my blog as filtering tools. And I’ve used fairly primitive methods like writing reading notes, though that generally hasn’t worked too well for me – I actually find blogging more effective.
Connect: Harold Jarche has been doing some fantastic thinking about this topic recently, and he made this diagram to illustrate the process:
I think this is a nice diagram, which pulls together a lot of the recent discussion on the topic. The one thing that I would like to add to it is this idea: connection works in two related but distinct ways. The first is that we connect ideas to each other. This is the innovative act – as Schumpter said, “(Economic) development in our sense is then defined by the carrying out of new combinations”. This is where I put a lot of effort when I’m coming up with blog posts, with research papers, and even with ideas for consulting jobs. Making novel connections is a skill that I work hard to build.
The second way that connection works is that we connect ideas to people. This is the outbound side of Connection. I use several strategies. When I re-tweet something, I try to make a comment that links the tweet to a broader concept (sometimes a challenge with 140 characters!). I write about the idea connections that I make in my blog – as people read it, they start connecting with the ideas. I give as many public talks as I can – from last September until now I have given more than twice as many public talks as I had in the previous three years combined. In Canberra last week I had a talk with Geoff Garrett, who said “Innovations travel on two legs.” There’s something to be said for that idea – and I have a lot of discussions about my ideas face-to-face – it’s one of the most effective methods of outbound connection.
So that’s a brief summary of how I have been trying to use the Aggregate, Filter and Connect framework over the past few months. In using it, I have learned a few things that might be useful for others too:
- It really helps to think about the three tools explicitly. As I said, I’ve always been reasonably good at making novel connections. But my ability to get my ideas to spread has increased dramatically once I started thinking in this way. Particularly with regard to outbound connections. My use of twitter, and the increase in my public speaking were both ideas that I initiated to increase my connections.
- When people feel overwhelmed by information, it usually means that they aren’t filtering effectively. Like I said, this is my weakest area. But there are some really smart people working on this. In addition to the posts I’ve linked to, check out the rest of Harold Jarche’s blog for some ideas. Venessa Miemis and Ken Gillgren have done some really good thinking in this area too. This is one of the areas in which most of us probably need to improve.
- The other area that we probably need to address is this: we need to get better at connecting ideas. This is where we create value – by making novel connections. And it’s not enough to just make the connections in our head – we have to frame them in a way that others can act upon. That means creating tangible content – a blog, tweets that connect ideas, podcasting, something. My primary recommendation here is to practice making novel connections, and then express them in a way that enables your idea to spread. One good way to do this is to expand the range of areas from which you collect information, and as you read and hear things from outside your area, consciously think about how they connect back to things that you know well. This is the strength of weak ties between ideas.
- Finally, your personal knowledge management scheme isn’t complete until you are doing all three things well. Aggregating is great, but only an initial step. If you don’t filter well, you won’t be able to make sense of the information that you collect. At the same time, even if you aggregate and filter well, you only create real value when you make novel connections between ideas. Information is the fundamental building block of idea connections. Once you make these novel idea connections, you then need outbound people connections to get your ideas to spread. The three skills reinforce each other.
So there’s the answer to Sam – you can replicate my blog by copying my incoming information streams, using the same filtering tools that I do, and then making the same connections between ideas that I do. In other words, you can’t. Aggregate, Filter and Connect is one method you can use to generate unique intellectual value.
NOTE: I’d like to thank everyone I mention in this post, and many others as well for contributing ideas that I’ve been able to use as building blocks in this argument – It’s great that we’ve been able to Connect! George Siemens and Jon Husband have also written things on these topics that have influenced my thinking.
Another NOTE: Venessa has pointed out in the comments that Howard Rheingold has written one of the definitive articles on filtering: Crap Detection 101.
Third NOTE: Follow-up post: Filtering With Your Network
Final NOTE: Here is a practical example of how the process works.
Everything’s a Network
Posted by Tim in complex systems, networks on 18 January 2010
I ran across this on Paul Kedrosky’s blog – an article discussing international shipping as a complex network. It reminds me of some of the work I did in my PhD studying international trade as a complex network. Here is the diagram of shipping lanes and ports:
It raises a few interesting points about networks:
- Networks are everywhere! And it’s useful to analyse economic networks because you often find out interesting things. In this one the big news is that a lot of the most important ports in the network are places I’ve never heard of, and I bet a lot you haven’t heard of them either. One of the great things about network analysis is that you can learn about key players in the network, which might have been hard to identify otherwise.
- The hub ports seem to serve two purposes. Some of them are places that act as shipping conduits, like the Panama and Suez Canals. Others are endpoints, like New York/New Jersey and Antwerp. These are still conduits, but they are points of transition where cargo shifts from sea to land and vice versa. It would probably be useful to sort the ports along these lines.
- Network links are often surprisingly persistent. Antwerp has been a hub port for hundreds of years – since back in the time that Belgium was a major sea power. One of the things that surprised me in my thesis research was that Belgium is still a hub in international trade, even though we don’t think of it as a significant economic player anymore. Trading ties based on colonial relationships seem to persist for long after the formal ties have been severed as well. It is often very difficult to unbreak ties once they have been formed (and this is why it is often difficult to get new innovative ideas to diffuse through an economic network).
Networks are a central part of economic life. Gaining a better understanding of the network structures in which we’re embedded is an essential part of trying to get our innovations to spread. This study of international shipping gives us some useful insights into what we can learn from network analysis. What do you think you could learn if we studied the networks in your organisation?
Networks and the Information Glut
Posted by Tim in complex systems, connect, networks on 9 January 2010
Everyone knows that we’re living in a time of unprecedented access to information, right? Personally, I’m always a bit skeptical of these grand narratives. To see why, watch this short video showing the social networks of correspondence among 18th Century scientists:
It’s great research that illustrates some important points:
- When we talk about ’social networks’ we don’t just mean facebook and twitter. People have always functioned within networks, and these have always been important in the development and spread of ideas. James Fowler makes this same point in his interview with Stephen Colbert.
- Ideas diffuse through networks. The structure of the networks through which we are trying to get our ideas to spread has a significant influence on the diffusion of our innovations. Our connections within the network can enhance or hinder our ability to get our ideas to spread. One of the reasons that Darwin gets credited with the idea of evolution through natural selection instead of Alfred Russell Wallace is that Darwin’s connections within the scientific community at the time were more numerous, more widespread, and better.
- Even though we often feel like we’re overwhelmed with information and data to be absorbed, the information glut is nothing new. Think about the volume of connections shown in the video. Or think about Charles Darwin – over the course of scientific career he sent over 15,000 letters. It’s safe to assume that he received just as many. Think about how much time he would have spent reading & writing letters, and how much new information and ideas would have been included in that – it’s probably more than we’re spending writing our blogs, updating our statuses and twittering. In fact, if you just look at the networks, you might argue that Darwin was the Chris Brogan of the 19th Century.
The fundamentals of innovative thought haven’t changed since the 18th Century – it’s always been aggregate, filter and connect. The great thinkers of earlier times corresponded extensively because it helped them aggregate information from a wide variety of disciplines and sources. Once they did this, they had to be skilled at filtering the data to figure out what was useful, and then they had to connect up the filtered data to create innovative ideas.
And, of course, once they had the great ideas, they had to execute them, and then get them to spread. Even though the media that transmits the data to us are different now, aside from that, not much has changed.
(hat tip to Mitch Joel for the video link)
Innovation and the Value Network
Posted by Tim in business models, complex systems, innovation strategy, networks on 28 December 2009
Today I will tell you why it is so hard for you to get your innovative new idea to spread quickly. Well, one of the reasons, at least. It’s because the economy is so interconnected. This is a bit counterintuitive – after all, I was just telling you how we can use networks to spread ideas. The good side of networks is that they can make it easier for ideas to spread. The problem with networks is that to get people to actually adopt your new idea, you often have to get them to break links within their existing network, and this can be very difficult. That is why it is important to understand how to build a position within the value network.
Value networks show up in most of the various business model frameworks. The idea is that when you have an innovation, you have to understand what products, services and routines are related to your new idea. Once you understand this, you can then figure out how much of the value network you need to control yourself. Anders Sundelin just wrote a terrific post on his Business Model Database blog describing how you can map the value network for your innovation, anlyse your position within it, and take steps to improve your position. He does a great job of explaining the mechanics of value network analysis. I would like to show you why it’s important.
As an illustration, here is a model of the value network for mobile phones, adapted from the book Invisible Engines by Evans, Hagiu & Schmalensee. It shows the postion within the value network that Apple has taken with the iPhone:
Apple has chosen to control everything within the circle – in other words, everything! Even the application developers don’t have full autonomy, since every new app has to be approved before it shows up on iTunes. The advantage to taking a position like this in the value network is that it is easier to coordinate the system. Because Apple controls nearly everything, every time they have a new idea, it is relatively easy to decouple the existing value network, insert the innovation, and move along. The disadvantage is that having such tight control over the value network limits the scope of the innovations that can emerge.
In contrast, look at the position within the value network that Google has taken with Android:
They have taken almost the exact opposite approach, controlling only the operating system directly. This greatly increases the the range and number of innovation opportunities within the value network. There are two big downsides though. The first is that they are at the mercy of the other players within the value network. One of the reasons that there are very few Android phones here in Australia is that all of the handsets using it so far have been lousy. The second problem is that with less control over the network, all of the innovations within this network take longer to diffuse as there is no central coordination.
Google has the market pull to take a position within the mobile phone value network that is similar to Apple’s if they choose to. So we have to assume that this is a strategic decision, and that their bet is that the increased innovation scope provided by their more open value network will outweigh both Apple’s first move advantage, and also their relatively slow increase in market share.
And this illustrates the problem that most of us face with our value network – we can usually only control a small piece of it – as Google does with Android. This means that not only do our end users have to prefer our idea, but we also have to get others within the value network to stop using our competitors. This process is slow, difficult, and frustrating – and it adds an extra delay to the spread of our great new idea. Innovations require many players within the value network to unconnect from competitors before they can reconnect with us. This unconnect-reconnect process is often independent from the process of customers adopting our innovation, and it adds another delay to the spread of our new ideas.
There are many different models of business models available for you to use. I don’t care which one you use, but you have to use one of them. They all include an element like the value network as one of the key things that you have to understand and manage when you try to get your innovative ideas to spread. The better your understanding of this network, the more effective you’ll be at innovating.
(Here is a follow-up post with an example to illustrate the issues involved.)
What I’ve Discovered About Twitter
Posted by Tim in aggregate, complex systems, connect, filter on 21 December 2009
I first started thinking about using twitter during a very loosely organised but wildly interesting talk from Phil Long (@RadHertz) nearly two years ago now. In the course of a one hour talk that wasn’t called ‘Cool Stuff I’m Excited About’ but should have been, Phil told us about TED talks – showing us the first ten minutes of the awesome talk by Hans Rosling – then he showed us twitter, and he finished by demonstrating the Livescribe Pen.
He was pretty fired up about all three of them, and I was immediately fired up about the TED talks too. I went back to my office and showed the Rosling talk to John and Martie-Louise, then found a bunch more and started using them in my innovation courses.
I was less certain about twitter. Phil said “When you start on twitter, your reaction will be ‘what the hell is this?’ But if you start using it, after a couple of weeks you’ll decide it’s ok, and after a couple more weeks it will suddenly click, and you’ll wonder how you ever got by without it.” That pretty accurately describes my experience, except that it took 18 months for me to get to the second step.
My main problem was that I couldn’t figure out a way to fight through the noise to get to signal. I subscribed to the feeds from a few of my friends and also to a couple of the twitter stars. Like me, my friends had little to say on twitter, and ultimately, I’m not very interested in famous people (even if they’re only internet-famous) – so I just let my twitter account sit there for a while. I was pretty happy just working away on my blog.
Then a little over a month ago I read Trust Agents (reviewed here) and I suddenly realised what my problem with twitter was – I didn’t have a good strategy for what I would add to the conversation. I was talking with my PhD student Sam around the same time about the blogs that I read and he asked me how someone could be like me in terms of the links that I passed on. I told him that anyone could aggregate the same set of blog feeds as me through RSS, but no one would filter them the same way because I connect things up uniquely based on what I know and have experienced (my aggregate, filter & connect web strategy). That’s not unusual – everyone connects things up uniquely – but the strategy seems to work pretty well as a way to find interesting things to say on the blog. So that was my new twitter strategy – to use it to tell people about connections I had made that were interesting, but which didn’t merit a full blog post.
The first thing that I discovered about twitter is that you can’t find the signal in the feed until you learn how to send a useful signal yourself. When I was only sending noise, all I could find in twitter was noise. As soon as I started sending signal, I was suddenly able to find the signal in twitter. It almost perfectly reflects the spirit of the internet – you don’t get anything until you learn how to give ideas of value.
I quickly compiled a list of people to follow that were talking about things that I’m interested in – innovation, complex systems and networks. Once I did that, I realised that twitter was powerful for aggregating high quality information. By itself, any one person’s feed might be interesting, but the second thing that I learned about twitter is that value in twitter is an emergent property of the network you construct (so maybe it really is a complex adaptive system!)
This makes all the talk about monetising twitter problematic. The value isn’t in individual tweets, or even individual feeds, but in the collective stream of information that you are able to put together for yourself. This also means that you can’t monetise your own particular stream very effectively, especially if that is all that you focus on. Back in my days as a quant-oriented marketing manager, that would have driven me crazy. But now that I have other avenues to generate value from my ideas, I’m ok with it. I’ll just keep tossing out ideas, and we’ll see where it takes us.
That’s the last thing I’ve discovered about twitter – you can’t think of it as a road to drive on to reach a particular destination. You’re much better off thinking about it as the wind, which will take you wherever it blows. You might be able to direct your path a little bit, but you never know for sure where you’ll end up. Enjoy the ride.
Now I just have to figure out how to use that stupid Livescribe pen!
(this is part of the #MonTwit experiment, where several people are talking about the same idea on the same day. @VenessaMiemis came up with the idea, and @ekolsky is compiling links to the posts here.)
Linking Innovation to Strategy, part 1
Posted by Tim in complex systems, innovation strategy on 13 December 2009
I just read a great post by John Borthwick which reviews the upcoming book about google by Ken Auletta. I encourage you to read the entire post, as I’m only going to focus on this part of it:
What about a corporate statement of intent like Google’s “Don’t be evil”?
“Don’t be evil” resonated with me because it suggested that Google as a company would respect its users first and foremost and that its management would set boundaries on the naturally voracious appetite of its successful businesses.
In the famous cover letter in Google’s registration statement with the SEC before its IPO, its founders said: “Our goal is to develop services that significantly improve the lives of as many people as possible. In pursuing this goal, we may do things that we believe have a positive impact on the world, even if the near term financial returns are not obvious.” The statement suggests that there are a set of things that Google would not do. Yet as Auletta outlines, “don’t be evil” lacks forward looking intent, and most important it doesn’t outline what good might mean.
That immediately made me think of Hambrick & Fredrickson’s strategy diamond, a tool that John & I find useful when we’re working with firms on innovation and strategy issues. It looks like this:
In their original article on the diamond, Hambrick and Fredrickson take issue with statements like google’s – saying that these statements of intent are insufficient as guides to strategy. They contend that a sound strategy requires all five elements, and that these need to be integrated and consistent with each other.
It is a practical model, and you can get some good results with it (we’re currently using it to help redesign our MBA recruiting strategy). I like the systems approach it takes (which, ironically, is listed as a weakness at the Proven Models website!). There are a couple of key ideas to take from the diamond model.
First, innovation must be integrated with strategy. When you work on implementing new ideas, you need to think about how it fits in with what you’re currently doing.
Second, all elements of strategy are interconnected. This is critical when you think about innovations over a longer time horizon. If you are aiming to create a different value proposition, or to move into a new customer segment, all the other parts of your strategy will likely have to change as well. This is a large part of why large firms find it difficult to react to radical innovations – everything has to change. Nevertheless, the strategy diamond can at least help you think through how to approach these more radical changes.
Finally, innovation and strategy are about choices, not planning. I read a blog post yesterday where the author said something along the lines of “if you’re not thinking about all 6 billion people in the world as your potential customers, you’re crazy.” This is stupid. No matter what idea you’re trying to spread, it can never be for everyone. If you try to make something that pleases all 6 billion people in the world, the odds are very high that you will end up pleasing something closer to none of them.
Strategy is about choosing which subset of the 6 billion you’re aiming for – choice here is critical. That’s the real weakness with “don’t be evil” – it doesn’t actually help us make any of those choices.
How to Deal with Complexity
Posted by Tim in aggregate, complex systems, connect, filter on 4 December 2009
Is google making us stupid? No. We keep hearing the argument that relying on technology makes us less smart somehow. Plato was probably the first person to make this argument. His target? Writing – his argument was:
So, too, with written words: you might think they spoke as though they made sense, but if you ask them anything about what they are saying, if you wish an explanation, they go on telling you the same thing, over and over forever. Once a thing is put in writing, it rolls about all over the place, falling into the hands of those who have no concern with it just as easily as under the notice of those who comprehend; it has no notion of whom to address or whom to avoid.
Plato’s suggestion was that we learned best through discourse, and that writing would, well, make us stupid. I’m clearly unqualified to call Plato dumb, but it’s a dumb argument. Here’s the latest version from Steven DeMaio:
Studies have shown that using our memory improves reasoning and creativity. Yet, because of our increased reliance on technology, few of us can even recall phone numbers or appointments anymore. Try using your memory more often by dialing numbers by hand or picturing your weekly calendar in your mind.
This line of argument drives me up the wall. You can see the faulty assumption here – that if we’re not remembering phone numbers, then we’re not using our memory. It’s as though we have one part of brain that is set aside only for remembering phone numbers, and if we’re not memorising phone numbers,then we’re not using that part of our brain. That’s clearly not true. The problem is not whether we’re using our memories or not, the problem is in allocating our attention and memory correctly.
DeMaio actually gets to this point in the longer version of the article – he talks about the benefits of memorising the names of all of his students. I agree that this is a very good use of memory. But there’s a lot of stuff that I’m better off leaving to my distributed memory, much of which is aided by technology. This is how we are able to deal with the rapidly increasing amount of information that we are faced with these days (beautifully documented and discussed in this post by Venessa Miemis).
The key to dealing with all of this information is to outsource as much of the aggregating as you possibly can. My phone can remember phone numbers. Wikipedia can remember when the Magna Carta was signed. My twitter network can remember all the great stuff going on at the Open Innovation Summit right now in Orlando. All I need to know is how to access the information (and how to back it up).
Doing that lets me concentrate on the things that I’m good at – filtering and connecting. We don’t get new ideas by memorising. We get new ideas by making new connections – figuring out what information is important, and synthesising it. One of the reasons that information is increasing exponentially is that we’re getting better at processing it. This is due to the extra brain time that we’re able to free up by outsourcing memorising.
By letting us focus our concentration on making new connections, technology that remembers for us makes us smarter.
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