Archive for category aggregate
Information Wants to Be Free?
We often hear that “information wants to be free” – but does it really? If it does, why did my research partners and I just pay $13,000 to get a copy of this database?
Now that’s admittedly 13,000 Australian dollars, and once you take exchange rates into account it comes out to — a whole lot, in any currency. Why is it worth that? And why did we get it? Alert readers will be able to guess that the answer to both questions is aggregate, filter and connect.
This is a concrete example of creating value from information in both cases. First off the database. It is a compilation of data about strategic innovation alliances going back over 30 years. The data has been aggregated from public sources. It has also been filtered – out of all of the available news about strategic alliances, the original researchers have filtered out all of the ones that are not innovation-related. They’ve then also aggregated data about the objectives of the alliances, start and end dates, industry, and several other things. And they’ve connected all of that data together into a database. By starting with widely available information, they have used aggregating, filtering and connecting to create a valuable resource for researchers.
The people that have put the database together have already done plenty of analyses of the data, and published many papers on their findings. So why would we pay for data that has already been pretty thoroughly worked over? Because we can aggregate, filter and connect too. In this case, we’re paying them for most of the aggregating and filtering, but we have some unique connecting capabilities that makes it worthwhile for us. I have some skills in longitudinal data analysis that are fairly rare – connecting these with the data will create new information. My primary collaborator has developed some unique economic theory, which we’ll connect with the outcomes of my network analyses. By connecting our unique skills and knowledge to a database that anyone can buy, we’ll create new value.
Our objective is to provide some practical insights that will help organisations manage innovation collaborations more effectively. Studies show that somewhere between 50-80% of all innovation alliances fail to meet their objectives. If we can figure out a way to improve these outcomes it would be quite valuable.
So the next time someone tells you that “information wants to be free”, remind them of the entire quote from Stewart Brand:
On the one hand information wants to be expensive, because it’s so valuable. The right information in the right place just changes your life. On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.
And then remember that the way to create the expensive information is to aggregate, filter and connect.
Why Your Great Idea Will Fail
There are a few reasons why your great idea will fail. The main one is that it will fail because it isn’t executed, or it isn’t execute well. We’ve talked about the problems with focusing just on ideas many times before. Last week I read an outstanding post by Matt Perez and realised why this is a problem. Here is one of the key parts from Matt’s post:
As I’ve been saying in several posts, I think it is obvious by now that more and more the future will be dominated by companies that can keep up a consistent stream of innovation. Given the system today, patents are a necessary evil for some industries, but woe to those who focus solely on protecting their one (and only) brilliant idea. Better to spend money and effort in creating and sustaining a culture (and processes and metrics) that makes innovation possible, even disruptive innovations.
As I read this, I realised that the issues with ideas and innovation are a stock and flow problem. When we focus just on compiling ideas, we are working on increasing our stock of ideas. Often, when we do this, we think that more ideas are better.
The problem is that better ideas are better, not more ideas. In order for this to make sense, we need to think about the flow of ideas. This is why I think that Matt’s point about the importance of having an innovation culture and process is so critical. We need to be able to translate ideas into action. That is why tools like the Innovation Value Chain are so effective. It’s not that the model is perfect, or the only tool to use. But it works because it gives us a feel for the way that we process ideas – we need to generate good ones, we need to select the most promising ones to try out, and we need to get our great ideas to spread. We miss a lot of these critical steps if we only focus on building our stock of ideas.
In arguing this point, it is easy to discount idea generation too much. As Harold Jarche points out, we need both stock and flow to make things work. But the most common mistake when firms try to become more innovative is to focus entirely on building their stock of ideas, which is why I think it’s important to emphasise the importance of building a process that facilitates idea flow.
Hugh MacLeod makes this point in a different way in his post today:
Products are idea amplifiers. The molecules and/or bytes are secondary.
This gets at the importance of the last part of the Innovation Value Chain – getting ideas to spread. And it also illustrates the importance of good quality ideas – if everything that we are trying to sell is based on ideas, then quality is clearly important. But at the same time, we have to execute them, and we have to get them so spread.
So your great idea will fail if it is only part of an idea stock. If it’s your one great idea, that you hang onto no matter what, the odds of succeeding are low. On the other hand, if your great idea goes into an idea flow process, then your chances are better. We need “consistent streams of innovation” to win – and for that, we need to concentrate on improving our idea flows, not just increasing our stocks.
(Photo from The Stock Solution Photo Agency under a Creative Commons license, and the cartoon is the latest from Hugh MacLeod’s daily newsletter, which you should subscribe to)
Establish Authority by Creating Value
Posted by Tim in aggregate, book riffs, connect, filter on 22 February 2010
One of the best ways to build connections within the economic network is to be an authority – and since revenue often follows connections, this is a useful strategy to consider. How do you become an authority? I’ve run across a couple of suggestions recently.
First up – this from the JournaMarketing Blog (I’m not trying to pick on the guy, his recent posts are much better, and worth checking out):
Services like Friendfeed make it easy to pull together information from a lot of different sources. So if you’re looking for a way to become an authority in your field, find the 5-10 top sources in that field, and pull their feeds into one location — on your own website. You’ll earn the goodwill of those other sources by linking to their content. And you’ll gradually become the 1-stop shop for anyone looking for information in your field.
Compare that process to the one outlined by Chris Brogan and Julien Smith in Trust Agents:
Say that you’re asked a question by e-mail about a specialty of yours… You could just respond by e-mail, but you don’t. Instead, you write about it on your blog. You point the person who made the original inquiry to what you wrote, so taht person gets what he or she wants; but now, anyone else can see it as well. People who arrive via Google by searching for similar information can visit and post comments weeks, even months, later. Your blog post, which used to offer answers to typical questions asked by a few people, has now become a resource…
Imagine that you do this 500 times. Over time, you’ve probably been asked 500 questions about your specialty; suppose you had answered all of them on your blog. These 500 posts now make up a pretty hefty set of resources, with a lot of insider information and tips, and you’re heping a fair number of people. As you do so, you’re starting to become known for your expertise.
So, our choice: establish your authority by creating value for people, or do it by appearing to create value. Which do you think will work better? Which person are you most likely to believe? Which takes the most work?
Aggregating by itself does not create value – this is a common fallacy doing the rounds these days. To create value, you have to aggregate, filter and connect information. In the Trust Agents example, you are not just aggregating the stuff that you know. You are filtering it so that it addresses specific problems that people have, and you are connecting up ideas to help solve those problems. And you are also connecting your solutions to people, actively through e-mail and telling people about your blog, and more passively through search engine visits.
The difference, of course, is that it takes a lot more effort to create 500 good quality blog posts. It will probably take more than a year, or even longer. And even then, you’re only “starting to become known” as an expert. But that’s what it takes to establish genuine authority. You have to put in the hours – there’s just no way around it. Of course, the payoffs (both emotional and financial) to being a genuine authority are generally higher as well.
These ideas apply whether you are building a personal brand, or whether you are creating an innovative business model. You need all three skills to creat value. You have to be able to aggregate, filter and connect to establish authority by creating value.
(Photo from flickr/Wessex Archaeology under a Creative Commons License)
Aggregate, Filter & Connect for Smaller Firms
Posted by Tim in aggregate, business models, connect, filter on 15 February 2010
We know the story by now: as it becomes less and less expensive to transfer digital content, the price firms can get for information-based products and services is being driven down. This has led to chaos in the music, news and publishing industries. So everyone in these industries is doomed, right? Wrong. I believe that successful business models in information-based industries can be built if you focus on three key skills: aggregating, filtering and connecting.
I’ve talked about how this is true for people, and also for large firms like Amazon. But what about medium-sized companies? Doesn’t all the money go to the big ‘aggregators’ like Amazon and Google? Not necessarily. A great example of a smaller firm that has been very successful in the information-based industry of publishing is O’Reilly Media. Today I’d like to talk a bit about why I think they are doing well. But first, let’s hear why Tim O’Reilly thinks they’re doing well:
Tim O’Reilly makes the argument for Open Publishing @ TOC 2009 from Open Publishing Lab @ RIT on Vimeo.
Right off the bat, he characterises the firm as ‘connectors’. O’Reilly works to spread ideas (connecting ideas to people), and then uses the connections that are made to generate money. It’s a pretty good business model, and one that I think will continue to work. Here are some more examples:
- First off, O’Reilly filters by specialising – they are not a general publisher. Here is Tim O’Reilly’s broad business goal:
Here’s mine: To become the information provider of choice to the people who are shaping the future of our planet, and to enable change by capturing and transmitting the knowledge of innovators and innovative communities.
To do this, they primarily focus on publishing books on the internet and open source technologies, programming, and systems administration are probably their core areas, but they also look at other digital topics like security, digital photography and information design. When building their business models the first thing that smaller firms need to do is to find something in which they can be the absolute best.
- Once they have filtered by specialising, O’Reilly aggregates in a couple of ways. One way is through the conferences that Tim O’Reilly mentions – they draw thousands of people that are interested in the O’Reilly core topics. It’s likely that most of the people that are interested in writing on these topics show up at these conferences. They also aggregate by building a community around their work. In addition to the conferences, they do this by hosting online user groups and forums, providing training, and giving away a lot of relevant content through blogs, white papers, and free downloadable copies of many of their books. All of these activities pull in the people that are most likely to contribute great new content themselves.
- When I talk about connecting at the personal level, there are two directions of connections. People connect up ideas, and this is how they create value. They then connect their ideas to people – this is how they get their ideas to spread. It is roughly the same for firms. First, they create value by connecting up their value network. In the case of O’Reilly, part of how they do this is by taking a highly activist role in the editing process. As John Scalzi humourously points out, publishers provide a number of services that are critically important to authors. Connecting authors to the right resources is a key part of building the value network at the back end – ultimately, it is the value network that creates economic value.
- The second part of connecting for firms is getting your ideas to spread. I think that this entails much more than marketing. It is built upon meeting the needs of your customers and business partners. Again, O’Reilly takes an approach that is different from most publishers. They have been much more willing to provide free downloads of books – sometimes this hurts sales, but sometimes it has driven sales. In both cases, it has helped to build the community. They also get their ideas to spread through the conferences. As this week’s TED conference has shown, when you have limited space available for a desirable event, you can charge people a lot to attend. One of the ways that people get their money’s worth from such events is to tell everyone they know about them – which spreads the ideas.
Tim O’Reilly wrote the book (well, the article) on Web 2.0 – and he uses the principles he has outlined to build his company. There isn’t anything new in any of the individual actions that O’Reilly Media undertakes – the thing that is unique is the way that they have combined things.
This is a great example of business model innovation. They are not delivering books, they are delivering ideas. Once you make that key switch, there are many new opportunities available. The O’Reilly Media business model is based on skills in aggregating, filtering and especially connecting. These are the three critical skills that you need to build successful information-based business models – whether you’re a person, a huge firm like Amazon, or a smaller firm like O’Reilly Media.
Creating Value from Information
How do we create value when we’re busy tweeting, blogging, reading and writing? I have been arguing that to create value from information, we need to have systems in place that allow us to aggregate, filter and connect information – and that this is true for people, and for business models. These are the things that go on all the time behind the scenes when people are creating blog posts, and I thought it would be interesting to see how this actually happens.
Shortly after the unveiling of the iPad, Venessa Miemis wrote a post called ‘iPad: Overhyped Flop or a Case of Great Design Thinking?‘ Venessa has a distinctive talent for writing about complex topics in an integrative and creative manner, so I thought it would be interesting to ask her about how she put this post together.
Tim: What resources did you use to collect & keep track of all of the discussions surrounding the iPad?
Venessa:Ever since I started blogging regularly, starting in November 2009, I’ve used Twitter as my main tool for collecting resources. It’s taken months to build a network, but it’s been well worth it. I’m very satisfied with the quality of tweets that pass through my stream. For the iPad post, it wasn’t too hard to find the articles – the Twittersphere was abuzz with speculation and opinions about the iPad in the week leading up to the keynote and in the days following it.
I saved most of the articles that came from a media outlet (Wired, New York Times, engadget, PopSci), and then paid attention to the articles by individual bloggers that were getting RT’d and referenced the most. I also used the #iPad hashtag to search what people on Twitter outside my immediate network were saying. I saved all of these links into delicious.
Comment: Twitter ended up acting as both an aggregation tool and a filter. The assumption behind Venessa’s strategy here is between the tweets from own network, which is large, and through searching that she would find most of the relevant commentary on the iPad. The filtering aspect is interesting – when we choose to follow someone on twitter, we are in part relying on them to choose the best things that they encounter to tweet about. So our network is doing a lot of the work in terms of filtering.
Tim: Did you use any tools to sort out the themes, or did you just work it out in your head?
Venessa: The themes emerged from the posts themselves. As I read through them, it seemed the implications of the iPad could be framed around three main areas: business, education, and leisure.
Comment: Here’s where I’m a lousy interviewer, because this is the key part of the process and I didn’t ask very good questions here (but see Venessa’s comment for more). But the value in the post is that it did not simply aggregate all the online discussion about the iPad. After collecting all the information that she could find, Venessa selected further by picking what appeared to be the key posts about the iPad.
Then, she connected up ideas by grouping them into themes. For me, this is the entire reason that the post works so well – it is the creative connecting. It’s also interesting that Venessa covers this in one line. It’s very typical that this step is hard to describe. We often talk about themes ‘emerging’ from our collected reading. As I’ve said before, connecting ideas is the fundamental creative act – and when you read the post, you can see how Venessa did this extensively in writing it.
After we connect up ideas, then we have to connect our ideas to people to get them to spread:
Tim: How did you promote the post?
Venessa: At 2:06pm on Feb 1st, I tweeted this:
At 5:03pm on Feb 1st, Tim O’Reilly tweeted:
That day, there were 3,672 visits to the site. The next day had 5,297. The next day had 1,690, and since then there have been between 700 – 1,000 visits daily. The post has received 21 trackbacks, and 121 comments (although I answer almost every comment, so you can subtract that by half). It was one of the top 20 posts on wordpress.com on February 3rd.
At the time of this writing, bit.ly shows the link has been clicked 7,785 times.
I also just found out that the post was mentioned on Leo Laporte’s “This Week in Tech” podcast on February 7th by Baratunde Thurston.
Tim: Can you track how the idea travelled?
Venessa: With over 1.4 million followers, it’s clear that Tim O’Reilly’s influence is far-reaching. Normally when I post a new article, I’ll get around 400-700 visits. Last week I had over 14,000.
I did get a big influx of new followers on Twitter (250+) within those first 48 hours, but I don’t know what percentage of that translated into new blog followers.This has been a really interesting experience, and more a display of the power of influence than anything else. I wouldn’t say the quality of that post was particularly higher than any others I’ve written. It was just super topical and given exposure by a highly influential person within the tech community. In order to get a post go that viral again, I may just have to be patient until Steve Jobs builds hype for whatever comes after the iPad.
Oh, and another thing to mention, which I thought was interesting – though I received 10 times the amount of traffic, I only got about twice as many comments…..so maybe 14,000 visits and only 50 comments. which to me says a lot about the amazing community that has grown around the blog. Though I may not get huge daily numbers with my traffic, a lot of people comment and engage and interact, and that’s what has made the blog so interesting. The posts are primers, but the conversations that follow is where a lot of insights and tips come in. So though I saw the power of influence via traffic, the quality of traffic I already had is unmatched.
Comment: There’s obviously a lot to say about connecting up ideas and people here. First, the traffic spike from Tim O’Reilly came as a result of the quality of idea connections in the post. There were hundreds (probably thousands) of posts about the iPad that week. Venessa’s did well because of the synthesis. That’s what led to the post getting into a traffic network with so many people in it.
I think this sheds some light on the question of the value of transient traffic. Venessa’s blog regularly gets a lot of very good, thoughtful comments as she mentions. This is because of the community that has built up around the blog (connecting ideas to people!). Because that community was already there, I think it made it easier for her to capture some value from the huge spike in traffic that she got. Double the number of comments is actually pretty good – it is sure more than you’d expect if transient traffic is ‘worthless’. Same with an increase of 250 people following on twitter. I suspect that regular RSS feed readers probably took a spike too. If you’re creating good intellectual value, it increases the connective value of transient traffic.
Finally, a lot of people talk about information aggregation as something that creates value in and of itself. Because it is a relatively easy thing to do, this why a lot of people dismiss Amazon and Google as ‘merely aggregators’. But the value doesn’t come from simply aggregating. The real value comes from aggregating information, filtering it effectively, and then creatively connecting ideas.
All three parts of the process must be done well in order to create value from information. I hope that this behind the scenes peek at the making of ‘iPad: Overhyped Flop or a Case of Great Design Thinking’ provides some insight into how the process works.
How to Filter Better
I was at the mall yesterday eating lunch, and I took a moment to listen to the conversations going on around me. They were, without exception, utterly banal. Consequently, I concluded that conversation is a useless tool, and the widespread use of it is nothing more than a symptom of the widespread decline of intellectual discourse, manners, and civilisation as a whole.
Stupid, right? That’s a riff on Clay Shirky’s response to people that complain about the quality of discourse within social networks.
The latest version of that complaint comes from Tom Davenport on the HBR Blog, who asks for us to tweet about something important:
Almost 50 years ago, FCC Commissioner Newton Minow suggested that the then-new medium of television was becoming a “vast wasteland.” One could argue that the same fate is befalling social media.
So here we are again: a promising new medium being used largely for vapid chattering about celebrities. Couldn’t these technologies be used for good?
Here’s an analogy: bird calls. When Nancy and I started birding one of the things that we learned was bird calls. When we’re actively birding, we’re pretty alert to everything, because we want to know where the birds are. However, when we’re working at home, we pay less attention to the calls. And since we’ve got a yard that is pretty attractive to birds, there are a lot of calls.
The vast majority of bird calls don’t contain too much information. The most common form of call is what ornithologists refer to as ‘chip calls’, which are short, brief calls that birds use to let other birds know where they are. It can help them find food (lots of chips in one area), it can keep them from straying from the flock (most of the chips moving further away), and it simply be a Horton-Hears-a-Who type ‘hear I am’ call or an ‘everything’s fine’ call. When we’re working at home, we don’t pay any attention to these calls at all.
However, the birds also have a few calls that contain a whole lot of information. We’re particularly interested in the calls that say ‘predator’. That usually means there’s something pretty interesting in the yard, like a Goshawk, or this Carpet Python:
We only got to see that snake because we heard the bird calls, followed them, and found the snake.
So we’re filtering the bird calls in our heads all the time, waiting to find the interesting bits. We need to do the same thing with conversations (well, maybe not the conversations at the mall food courts…), and social networks like twitter. Most of the words used in these media are like birds’ chips. We need to find the words that contain data. How can we do this?
Howard Rheingold is in the middle of putting together of series of tutorials about Mindful Infotention that explain a few different methods that work.
These are fantastic videos that are well worth your time. In the one above, Rheingold makes several important points. He demonstrates the use of several different tools for aggregating and filtering information on a topic that is of interest to you. He has step-by-step instructions that make it pretty easy to track down specific information from streams that are on average not very useful.
Rheingold also talks about two different forms of filtering – algorithmic and personal. He correctly recommends using a combination of the two. Algorithmic filtering includes tools like PostRank, which uses a formula to determine which posts are most relevant to your search. Personal filtering takes place on sites like delicious and diigo, where you can find the pages that the highest number of people have bookmarked, or the pages that specific people have saved. There’s also using your network to help filter.
Rheingold makes an absolutely critical point at the end of the video – it’s not enough to simply aggregate information, and filter it so that you have only the most relevant information. You also have to do something with it! The information is no good unless you connect it up:
The important part, as I stressed at the beginning, is in your head. It really doesn’t do any good to multiply the amount of information flowing in, and even filtering that information so that only the best gets to you, if you don’t have a mental cognitive and social strategy for how you’re going to deploy your attention.
There is a wealth of great information being shared on a constant basis within social media and elsewhere. None of it does us any good at all if we can’t find the bits that are useful to us in solving the problems on which we’re interested in working. But if we filter well, we’ll discover that we actually are tweeting about things that are important.
(I’ll also just note that Howard is currently getting treated for cancer – the prognosis sounds encouraging, and I hope that he pulls through it in good shape.)
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.
What Would Google Do? by Jeff Jarvis
Posted by Tim in aggregate, book riffs, connect, filter, innovation strategy on 25 January 2010
The question of how to best adapt to the changes brought about by the internet is of key importance to all organisations that are in information-based industries. According to Jeff Jarvis in What Would Google Do?, the answer is fairly simple: do what Google would. Here is a video in which he outlines the argument in the book (this is from the same session of BRITE ‘09 as Umair Haque’s talk that I discussed yesterday):
Jeff Jarvis at BRITE ‘09 conference from Center Global Brand Leadership on Vimeo.
Jarvis, author of the blog buzzmachine.com, takes an interesting approach in this book. He infers a number of rules for acting more like Google, but he does this without having direct contact with the firm. Because he’s a very entertaining writer, this first half of the book is worth reading. However, in some ways it rehashes ground covered well by Chris Brogan and Julien Smith in Trust Agents (reviewed here), or David Weinberger in Small Pieces, Loosely Joined (reviewed here). The main ideas are that to succeed, you should join network and be a platform (both facilitated by the internet’s linking structure), give control to your customers instead of trying to retain it yourself, and build a business model based on serving niches. There are actually ten rules in the book, but those are the ones that I found most useful. Jarvis reduces these rules down to five in his tips for creating a Googlier you.
For me, it is the second half of the book that recommends it. In this section Jarvis tries to build new business models based on his Google rules in nine different industry categories, including media, retail, manufacturing and public institutions. Each section has two to three examples, and this part of the book is just fantastic. The thing that I like about it is that Jarvis really puts his ideas to the test here – tackling a number of industries that would not obviously lend themselves to following Google rules like car manufacturing, power generation, and restaurants. It is a fascinating intellectual exercise, and I think that a lot of his ideas would be worth trying out. I recommend the book based on this section.
I’ve been thinking about the ideas in What Would Google Do? while talking with an old friend from university who is currently working with a media company in the US. They are grappling with how to best deal with the challenges of online content. One of the things that they are considering is building their own branded media reader, an idea that Jarvis would almost certainly be against (I know that I am!). Valeria Maltoni wrote an interesting post on the topic of mobile news this morning. She included this graphic, which certainly makes the argument for the necessity of some kind of mobile application for media firms:
Maltoni also checks iTunes, and counts more than 3200 iPhone news apps currently available. This definitely means that my friend’s firm must be mobile-enabled – but why build their own e-reader? Why compete directly against Apple and the iPhone (and the upcoming iTablet), and Amazon and the Kindle, and, well, nearly everyone else that is already in this space? Their argument is that having their own branded e-reader will give them control. They can push out their own content to people, and reinforce the brand in that way.
There are all kinds of problems with this argument. First off, why do people need another mobile device that is tethered to one publisher’s content? Are they suggesting that people should carry their e-reader for their content, and a Kindle for books, and a smart phone for everything else? I’ve got too many gadget as it is – there’s no way I need another one. So I’m not convinced that the demand is there for another e-reader. I haven’t seen any of the financials, but I suspect that there is no way to make it pay without fairly massive volume, and I’m skeptical about achieving that too.
Maltoni’s recommendations start with creating great content, and the rest revolve around being more interactive with people – something that is probably easier to achieve with mobile apps than it is with mobile devices.
The e-reader idea also violates at least two of Jarvis’ Google rules. The first is do what you do best and link to the rest. This is very similar to Maltoni’s creat great content idea – that is what the media firm is good at, and that is what they should do. Do they have a competence in manufacturing electronic devices? Well, no. The second Google rule that this goes against is that you have to hand over control to gain peoples’ trust. The idea behind the e-reader is to enhance control, not give it up. Jarvis argues that this is exactly the wrong strategy to be following these days.
The one way to make the e-reader scheme work is to follow another of the Google rules – be a platform. The only way I can it working would be if it were structured to enable people to do a wide variety of things on it. This means having some kind of alliance that will enable book downloading, and an open software architecture so that enthusiasts can build apps for it. It means building in interactivity so that people can rate content, access the other content that they want, and mash it all together. It means directly taking on the iTablet, Kindle and smarphones. If you do all that, the scheme could work.
But I don’t think they want to do all that. So I don’t think the e-reader is the way to go. To find the best way forward, it might be useful for them to ask What Would Google Do?
Changing the Game for News
Posted by Tim in aggregate, business models, connect, evolving economic entities, filter, innovation strategy on 23 January 2010
A lot of people have been talking recently about a Harris Poll that shows that 77% of people in the US say that they won’t pay for online news. Specifically, this is the question they were asked:
How much, if anything, would you be willing to pay per month to read a daily newspaper’s online content?
And 77% chose the answer “Nothing.” These poll results are absolutely useless – primarily because the question ignores innovation. Here are some things that these results do not say:
- They do not say that information wants to be free.
- They do not say that daily newspaper content has zero value, or value approaching zero.
- They do not say that newspaper readers (or people interested in news in general) are a bunch of freeloaders.
The only thing this polls tells us is that whoever set up the poll is incompetent, and probably shouldn’t be listened to on any further matters of importance. This is fundamentally the wrong question to ask.
If you had asked people in 1980 “How much, if anything, would you be willing to pay per month to watch a television channel’s online content?”, the answer would be “Nothing.” And yet, cable television did reasonably well.
If you had asked people in 1987 “How much, if anything, would you be willing to pay per month to have another phone in addition to the one that you already have? And also, it will have a different number.”, the answer would be “Nothing.” And yet, mobile phones did reasonably well.
Of course people say they’ll pay nothing for news online! What idiot would say that they would? They get it for free already, from a number of good sources. We’ve never really paid for news. Cable TV and mobile phones worked because they offered something fundamentally different from what people already had. Cable didn’t take off until people heard about 24 hour sports on ESPN, and 24 hour news on CNN, and 24 hour music on MTV. Prior to this, you had sports on the weekend, and news at 6 pm and 11 pm, and music, well, never. Cable changed the value proposition.
Mobile phones changed the value proposition too – they allowed you to use the phone anywhere. And eventually, they allowed you to send short text messages. Even still, for me at least, this had negative value until smart phones came along and gave me a portable computer with gps.
And the big problem is that you can’t ask customers what they would want with these things in advance, because we don’t know. You can just experiment. With phones, the telcos always thought that the market was for businesspeople. Initially it was. Once they introduced texting, all of sudden there was a huge market for teens, which drove further innovation.
News has to experiment now, and they need to specifically think about how they create value with Aggregating, Filtering and Connecting. I’ve talked before about many different possible approaches to this. We can develop new funding models, like Jeff Jarvis has. We can develop new value creation models, like Dan Gillmore advocates. We can consciously develop an aggregate, filter and connect model, like politico.com’s or Dan Conover’s.
The main point is that this situation requires business model innovation. To figure out how to do that successfully, we have to ask new questions. We need a news version of cable television. Or a news version of mobile phones. The entire model has to look different. Polls that ask if you’d pay for current content online are not just worthless, they’re harmful, because they prevent us from asking the questions that can lead us to genuine innovation.
Darwin on Twitter
Last week I talked about 19th century communication networks, Charles Darwin, and how we have had more information coming at us than we’ve known what to do with for a long time. It seems like it is a problem caused by the internet, but the roots are much deeper. I’ve also been saying for some time that the way to effectively deal with information is to use an aggregate, filter and connect strategy. This works when you’re building a business model for an information-based enterprise, and it works for individuals as well. I’ve run across more evidence of the latter this weekend, reading David Quammen’s book The Kiwi’s Egg, describing Darwin’s development of the concept of natural selection.
In my earlier post I talked about Darwin’s extensive network and prolific letter writing. These were the tools that he used to aggregate information. For evidence of filtering and connecting, here is a quote from Quammen:
He was reading widely in the literature of exploration and natural history, plus a diverse selection of books on animal and plant breeding, history, and philosophy of science and he had begun putting cryptic questions to anyone who knew anything about the odd, targeted topics that interested him… Clues, clues, clues. What did they signify, how did they fit? The cuckoos of Java versus the cuckoos of Sumatra and the Philippines – species or varieties? He wanted every possible piece of relevant data, whatever the source. He went to the Regent’s Park Zoo to see its newly acquired orangutan. He became a greedy amasser of seemingly unconnected facts. He busted his brain to connect them. It was an intense program of research and cogitation.
Aggregate, filter and connect. Darwin did a lot of all three over the 20 years between his arrival back at the end of the voyage of the Beagle and publication of The Origin of Species. And his breakthrough came because of the novel combinations of ideas that he developed. No one previously had connected the success that animal breeders had with artificial selection with a theory of natural evolution. No one previously had given much thought to the amount of variety found within species, because there was no theory to connect those facts to. Combining ideas is a central part of the innovation process – and Darwin was particularly skilled at it.
Darwin’s network of correspondents was awesome – and we can still learn a great deal now from studying how he effectively used his connections to get his ideas to spread. He wasn’t on Twitter, but if he had been, some of his writing would have worked on it:
There is a grandeur in this view of life with its powers of growth, assimilation and reproduction.
From so simple a beginning, through the process of gradual selection of infinitesimal changes, endless forms most beautiful and wonderful have evolved.
True, he would have had to have found a shorter word than ‘infinitesimal’ in the second bit, but still… And of course, Twitter is not the best medium for building one long argument, as he did in Origin. Nevertheless, Darwin’s aggregate, filter and connect approach is one that we can all use now – and we all probably should. I can think of worse people to emulate.
Amazon’s Business Model Innovation
Posted by Tim in aggregate, business models, connect, filter on 15 January 2010
I thought I’d experiment with a video blog entry. I’ve got no editing software here, so everything was straight to tape. Well, straight to bits. Anyway, if it seems to work ok I’ll scale it up! It runs for five minutes.
Amazon & Business Model Design from Tim Kastelle on Vimeo.
To summarise my main point: the business model for amazon.com did not become profitable until they were doing all three functions necessary in an information-based industry: Aggregate, Filter & Connect. Yesterday I talked about the importance of filtering in scientific publishing business models – but for amazon, the key function is connecting. In particular, the killer app for amazon is their relational database – this allows them to connect related items for people. Amazon was always good at aggregating, and they’ve tried a few different filtering methods, which have all been reasonably effective. But it was only when they added connecting that their business model took off.
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.)
The Problem with Measuring Innovation
Posted by Tim in aggregate, connect, filter, innovation strategy on 7 December 2009
The problem with measuring innovation is that you can’t measure innovation. This makes it a difficult thing to manage.
Now obviously, organisations figure out ways to measure how innovative they are – but they usually doing it by finding metrics that approximate some part of the innovation process. The fact that our metrics are all proxies leads to problems when we forget that they are only substitutes for what we are really interested in measuring, not the thing itself.
I ran across an example of this split between the measure and what we care about today when I was looking at twitalyzer. It’s a really nice free twitter analytics site that measures several things: your influence, your signal to noise ratio, your generosity (how frequently you cite other people), your velocity (how frequently you tweet) and your clout (ability to spur people to action). Influence is a composite measure that includes your clout, velocity and generosity, plus how often you are retweeted, and the number of followers that you have on twitter. It’s the last part of the measure that leads to potential trouble.
Getting followers on twitter is interesting. One strategy is to post interesting stuff for an extended period of time, and letting people find you (generosity, signal/noise and velocity all help with this). The problem with this is that it takes time. A faster way is to be famous. However, that’s not so easy. The easiest way to get followers is to follow a whole lot of people, and count on the web’s tendency towards reciprocity to work in your favour.
The problem with this is that you end up following a lot of people, which for me at least creates some difficulties. For me, twitter is a great information stream – it is part of my aggregating strategy. It helps me find innovation news and viewpoints that I don’t pick up in my rss feed from blogs. The problem with following lots of people is that this makes filtering impossible. There are tools that make it easier to manage large numbers of people that you follow – but they all work on the same principle – ignore most of them. Which means that if I do that, I’m not connecting.
My twitter strategy is to use it as part of my larger aggregate, filter & connect strategy. But if I try to manage the metric – ‘influence’ – I have to collect a lot of followers, which actually makes it harder to execute my strategy. This illustrates the problem with mistaking a metric like influence with what you actually want to accomplish.
The same thing happens when we manage innovation. One of the most common measures of innovativeness is patents. But no one actually needs patents – they need the things that patents somtimes provide – a competitive edge from exclusivity, monopoly profits, or the development of unique products. If we spend too much time managing the metric, we might not achieve the outcomes (profits, market share, etc.) that we really want.
How can we fix this? There are few things we can do:
- Don’t mistake the metrics for the thing we really care about – constantly remind yourself that since we can’t measure innovation directly, the metrics that we use are approximations, not the actual thing that we care about.
- Use multiple metrics – one way around this problem is to use multiple measures for innovation. There are many possible measures – how much we’re investing in generating ideas, how many new products/services/process improvements we actually introduce, profits from new products/services, senior management time devoted to innovation, innovation porftolio balance (both distribution of innovation efforts over time scales, and across the incremental-radical spectrum), and so on. Scott Anthony has done some outstanding work in this area, which he summarises here.
- Make sure that your innovation metrics are tied to your strategy – Think about what you are trying to accomplish, and make sure that your metrics measure actions that will contribute to the outcomes that you are trying to achieve.
Measuring innovation is one of the hardest parts of managing innovation. Avoid the trap of thinking that your innovation metrics measure innovation directly to make the process a little bit easier.
(picture from flickr/aussiegall – CC licensed)
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.
news business model summary
Posted by Tim in aggregate, business models, connect, filter, innovation strategy on 30 November 2009
The purpose of this particular post is to pull together links to all of the posts that I’ve done on the topic of new business models for journalism so that they are a bit easier to find. This is an important issue for news, but it illustrates a broader point. The key to adapting to disruptive change is to change your business model. We are seeing attempts to do this play out in front of us in real time, so I think it is a very useful learning opportunity.
This is what we’ve had so far:
- Free News?: This was the first post on journalism – the main issue here is a discussion of the impact that free news on the web has had on the business model for newspapers.
- More News Business Models: looks at Steven Johnson’s diagram of the news ecosystem and talks about how to put together a unique mix of content in a news business model.
- Regulate or Innovate: talks about how Australian newspapers have tried to deal with losing advertising revenue to the internet for house sales.
- Aggregate, Filter and Connect: are three ways to generate revenue in digital knowledge-sharing markets – like news!
- Business Models Summary: does something we probably should have done earlier, which is discuss what business models actually are, and discusses possible revenue generation mechanisms for news.
- Business Models and the Three Horizons: uses a speech by John Temple – the former editor of the Rocky Mountain News to illustrate how using the three horizons framework might help to develop a new business model for news.
- The News Value Proposition: does just what the title says – it looks at how to make a new value proposition for news.
- Splitting and Lumping: How trying to find the right analogy can help you build an effective business model when you’re surrounded by chaos.
- Publishing Business Models: Book publishers are facing some of the same issues as newspaper publishers, and this post looks at the options available to them.
- Filtering When You’re Small: Rupert Murdoch trying to turn off google leads to a discussion of how to take advantage of aggregate, filter and connect if you’re a small niche player.
- Jeff Jarvis on New Business Models for News: My comments on a great 15 minute talk from Jeff Jarvis concerning how to make new business models for news.
- Three lessons for adapting to disruptions: My interpretation of the key ideas in a talk by Arianna Huffington.
- Three horizons of news innovation: Looks at the argument between Jeff Jarvis and Dan Conover about what new business models might work best.
- Changing the Game for News: We need the cable television version of news, or the mobile phone version – not just the one where we pick up a paper newspaper and recreate it online.
So that’s a good summary of where we’ve gotten on this topic. It also highlights one of the difficulties on a blog – it’s hard to build a sustained argument across time and interspersed through other topics. And I’m not entirely convinced that tagging posts really gets around the problem – hence this summary post!
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