Archive for category complex systems
Why You Need an Innovation System
Posted by Tim in complex systems, innovation strategy on 10 July 2010
I was originally going to title this post:
Vampirenomics!
This is because while we were in Italy, I went into several bookstores, just to check out what was there. A couple had superb business sections, but all of them had enormous vampire sections too. Some of them were translations of vampire books originally written in English, and quite a few appeared to be written in Italian. Whatever the language, vampire novels appear to be pretty hot right now. So are books that use the suffix -onomics, – nomics, and -ology. So I figure that a book called Vampirenomics has to be as close to a guaranteed best-seller as you could find right now.
Unfortunately, I don’t really know how to write Vampirenomics. Like I keep saying, the value in a great idea is in the execution of it, not in having it. So if you can figure out how to write Vampirenomics, be my guest. Maybe just mention me in the acknowledgements…
But you better act fast, because I think that both vampire novels and -nomics books are a fad, and their lifespans (hopefully) won’t last too much longer.
Some people say the same thing about innovation. It’s a fad, it has too many different meanings, there are many different excuses people use to discount the importance of innovation. The one that is probably most valid is that their firm has tried to be innovative, but it hasn’t worked.
One reason that innovation initiatives often fail is that people try to take “best practice” solutions from elsewhere and cram them into a particular context where they may or may not be appropriate. What you need to make innovation work is not brainstorming, or an innovation team, or idea-tracking software, or innovation consultants, or any of the other innovation ideas that are put foreward as generic cures. What you need is an innovation system – one that manages innovation as a process.
Bill Easterly wrote a great post today called “The Answer is 42! Why Development is not about solutions, it’s about problem-solving systems” which looks at a similar problem in development economics. After making a similar list of things that are supposed to create economic development, but which don’t always work, Easterly says:
Development happens thanks to problem-solving systems.
The problem-solving systems could very well use some of the same solutions that were discussed above (a transparency law, microcredit, malaria bed nets, conditional cash transfers, web-based clever thing, eliminating business red tape). This leads to much confusion, as people then try to directly imitate particular solutions in the absence of a problem-solving system, which as stated above, leads to disappointing results.
The problem-solving system is adapting solutions to local circumstances. And even more importantly, a problem-solving system coordinates the efforts of many different problem-solvers with nobody in charge (for example, in the market, prices serve as signals to coordinate the actions of many different suppliers to solve the problems of demanders).
Direct solutions to problems (say, using aid programs) still may be worthwhile as benefiting a lot of people. But a long list of many such solutions is not development; development is the gradual emergence of a problem-solving system.
Innovation systems work the same way. Organisations slowly build up capabilities in generating ideas, in selecting new ideas, in testing whether the ideas will actually work, and in getting the ideas to spread. You need to have all of these sub-systems working well to have a functional innovation system.
Don’t look for the silver bullet, one-size-fits-all solution to create innovation within your organisation. There isn’t one. Instead, work on building the multiple capabilities that are needed to make innovation work. Some of the things like brainstorming, etc. may indeed be part of the solution that works best in your particular context. But finding this out is an evolutionary process. You need to try a bunch of stuff, see what works, and do more of that.
If you do that, you will build an innovation system that can be managed, and that will work in the long run. Then innovation will be a capability, and a source of competitive advantage – not a fad.
Innovation without Intellectual Property Protection
Posted by Tim in complex systems, connect, innovation on 4 June 2010
I love the story of the development of the Graphical User Interface (GUI). It was developed by Xerox in their Palo Alto Research Center. They used it on their first commercial home PC, the Xerox Star, but that didn’t sell very well. While the history is a bit muddled, Apple definitely knew of the work, and was influenced by the Xerox GUI when they launched the Apple Lisa and then the Mac, both with nicely working GUIs. Microsoft was late to the GUI party with Windows, but we all know where the money ended up.
When I tell this story in class, I talk about how software can’t be patented, and how copyright really doesn’t do much to protect the Intellectual Property of software developers either. When I ask my students what computer firms can do to profit from innovation in this situation, they inevitably come up with a wide range of ideas.
If I just open without the GUI story and ask people how you can profit from your innovations, the first answer is always “patents”, followed by “copyright”, followed by a long silence.
The idea that legal IP is the only way to profit from innovation is pretty deeply embedded, but it’s untrue.
This excellent TED talk by Johanna Blakley uses the example of the fashion industry to show how it is possible to profit from innovation even if you don’t use legal IP protection:
So fashion does just fine without IP protection. Some of Blakley’s key points are:
- In fashion, the ability to copy leads to increased innovation due to widespread copying, which leads to many new and novel combinations of ideas. Connecting ideas is the fundamental creative act in innovation – so it makes sense that working in an IP regime that makes it easier to connect ideas will create more novel connections.
- Even if something looks like an exact copy, there are substantial differences between knock-offs and originals. Furthermore, people can tell the difference. Once in Beijing I bought a pair of xRay-Ban sunglasses, just for fun. They fell apart in less than four months. So I went back to a pretty nice pair of sunglasses that cost about 7 times as much. I’ve had them for 17 years and counting, and they’re still in great shape. High quality ends up being a pretty good method for profiting from your innovations.
- Another way to profit from your innovation is to make things that are too complex to be easily copied. That’s what Charlie Parker was trying to do with bebop. Complex design and complex value creation networks are two very good methods for protecting yourself from copiers.
You can see all of the slides from Blakley’s talk here (and there is more information about her research at ReadyToShare.org) – here is one of the key pictures (grabbed from the talk by Simon Bostock):
This makes the point that industries with low levels of legal IP protection are actually pretty important within the economy. Massively important. The chart is a bit misleading in that there are a few high IP industries that are also pretty big, like pharmaceuticals, which aren’t included. But the main point holds – you don’t need to have legal IP protection to profit from innovation.
There are many ways to win with your great ideas. Being innovative in the business model that you build to support your innovation is one of the best ways to do this. Business models are another thing that aren’t subject to copyright protection. Don’t get hung up on patents and copyright. There are other ways to win with innovations, and many of them are actually more effective. We need to be as creative in making our business models as we are in coming up with new products, new services and new ways of doing things.
Innovate It Like Beckham
Posted by Tim in complex systems, innovation strategy on 26 April 2010
Take a look at David Beckham’s goal against Greece that sent England to the 2002 World Cup Finals:
If you ask famous athletes how they do things like that, they find it difficult to explain. How can you make a ball dip a meter while curving two? Who knows? Actually, there are some researchers that know – four physicists published two articles shortly after that goal called ‘The Curve Kick of a Football’ (summarised here). According to their simulations, to get that kind of spin, you kick the ball like this:
So if the physicists can explain it, and anyone can read how to do it, why can’t we all bend it like Beckham? According to John Kay in his new book Obliquity: Why Are Goals are Best Achieved Indirectly, it’s because it’s impossible to navigate complex systems rationally. In order to succeed in complex systems (like top tier athletics, or, more importantly for our purposes here, the economy), you succeed through expertise, practice, and judgment. When Beckham kicks it like that, he’s not solving a long series of differential equations in his head on the way to the ball – he’s applying years and years of knowledge and judgment based on experimentation and practice.
This is why experimentation is an essential part of innovation. It’s also why we need to innovate. The economy is a complex system, which makes achieving our goals difficult. Kay contrasts two approaches, the rational direct approach, and the oblique experimental one:
Direct action
* Objectives are clear
* Systems are comprehensible
* We know the available options
* What happens happens because someone intended it
* Rules can define the system
* Direction provides order
* Good decisions are the product of good processesObliquely does it
* We learn about our objectives as we strive for them
* Systems are complex and depend on unpredictable reactions
* We can consider only a few possibilities
* There is no clear link between intention and outcome
* Expertise is required, tacit knowledge is essential
* Order often emerges and is achieved spontaneously
* Good decisions are the product of good judgment
One of the reasons that people are often uncomfortable with innovation is that it doesn’t fit with the rational direct approach. We can’t show a net present value calculation that demonstrates guaranteed returns, we are actively courting uncertainty, and the links between what we are trying to achieve and our actual outcomes are unclear and difficult to unravel.
This requires an oblique approach. We need to settle on our general goals, and then experiment. As we learn what works and what doesn’t we build up our tacit knowledge and our judgment. Experiment, learn, improve. That’s how to innovate like Beckham.
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)
