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There’s No Such Thing as Information Overload

The size of your inbox or your RSS feed or your twitter stream might all argue otherwise, but there’s no such thing as information overload.

Or, at least, if there is, it’s not new. Check this out:

As long as the centuries continue to unfold, the number of books will grow continually, and one can predict that a time will come when it will be almost as difficult to learn anything from books as from the direct study of the whole universe. It will be almost as convenient to search for some bit of truth concealed in nature as it will be to find it hidden away in an immense multitude of bound volumes.

That was Denis Diderot in “Encyclopedie”, back in 1755. 1755!

The problems that we have with information isn’t that there’s too much of it – there has always been too much. Rather, there are two related problems with information: how do we filter out information that doesn’t help us, and how do we find information that we need.

Jorge Luis Borges touches on this in his story The Library of Babel. You should go read it here since everyone should be reading more Borges. The story is short, but packed with ideas. The library has an infinite number of rooms, all filled with books. Each book is the same length, with randomly assembled letters. The Men of the Library spend their lives wandering the shelves, reading the books. Since the library is infinite, it must contain all books ever written (and all that will be written!), but since the library is infinite, the odds of coming across even one sentence that makes sense are exceedingly small.

It is useless to observe that the best volume of the many hexagons under my administration is entitled The Combed Thunderclap and another The Plaster Cramp and another Axaxaxas mlö. These phrases, at first glance incoherent, can no doubt be justified in a cryptographical or allegorical manner; such a justification is verbal and, ex hypothesi, already figures in the Library. I cannot combine some characters

dhcmrlchtdj

which the divine Library has not foreseen and which in one of its secret tongues do not contain a terrible meaning. No one can articulate a syllable which is not filled with tenderness and fear, which is not, in one of these languages, the powerful name of a god. To speak is to fall into tautology. This wordy and useless epistle already exists in one of the thirty volumes of the five shelves of one of the innumerable hexagons — and its refutation as well. (An n number of possible languages use the same vocabulary; in some of them, the symbol library allows the correct definition a ubiquitous and lasting system of hexagonal galleries, but library is bread or pyramid or anything else, and these seven words which define it have another value. You who read me, are You sure of understanding my language?)

What do you do when you are faced with all of the information in the world? To make any sense of it, you have to find the information that is useful to you. So we filter.

As Borges suggests, each piece of information means something to someone, even if it’s gibberish to us. We need to knock out the stuff that’s gibberish. So we find ways to ignore information, by saying things like “Twitter is just 100 million people talking about what they ate for lunch, so why would I waste my time with that?” I do this by ignoring TV (unless I can find a hockey game on). Everyone makes choices about what they should be paying attention to.

The key to dealing with information is to be conscious of the choices that you’re making, and to develop a strategy or a set of routines for handling it. Howard Rheingold has created an outstanding set of resources for his classes on Mind Amplifiers and Infotention. Start with those to develop a filtering strategy.

We’ve always had too much information to handle, and we’ve always dealt with it by developing routines. The real difference now is not that there’s so much more information, it’s that we don’t have good routines to go with the new channels that the information is taking to get to us.

The danger in thinking that we have too much information is that we’ll start missing out on innovation opportunities. After all, the creative part of innovation is about making novel connections between ideas. So we actually have to seek out information that is a bit out of the ordinary (see the end of this post for some techniques for doing this).

If you think that the problem is information overload, then this will seem completely counterintuitive. That’s why it’s a dangerous idea – if you take it seriously, it makes it much harder to innovate.

That’s why I say that there’s no such thing as information overload. Even if that’s not strictly true, we’re better off acting as though that’s the case.

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Bad Filtering Kills Businesses

If your business model is based on information, and whose isn’t these days, then you need to be able to aggregate, filter and connect. While reflecting on the death of Borders Books, I thought of three stories of filtering in retail.

First Story: Tower Records

In the mid-80s, I went in to the Tower Records in Tacoma, looking for Stop Pretending, the new record by the Pandoras. I figured my odds of finding it were high, since there was a big promo display for the record up on the wall.

I went over to the “Rock – Misc P” and flicked through the records. No luck.

I went up to the counter and asked the clerk if they had it. He said no – they’d gotten one copy, and another guy that worked at Tower had bought it. I asked them why they had the display on the wall, and he told me that the guy that bought the record really liked it, so he made the display.

Then I asked if another copy was coming in. No. Why? Because for records from independent labels, the buying policy was to send one copy to each store. If they needed more than one copy, then it had to be special ordered.

There are five forms of filtering, and this is an example heuristic filtering.

Heuristic filtering is rules-based, and this is a great example of a dumb mechanical process. It’s dumb because there’s no learning (“hey, people in Tacoma seem to like the Pandoras, send them more copies of the record”).

This approach worked fine as long as Tower was still the biggest aggregator around. The boycott of Tower that I started in response to this didn’t really seem to hurt them, even though I bought a LOT of records back then.

However, as soon as a bigger aggregator came along – various internet-based options – the Tower business model was toast.

People say that the internet killed Tower Records, but I think it was killed by bad filtering.

Second Story: Borders Books

In the mid-90s, I bought Science as a Process by David Hull, which became one of my all-time favourite non-fiction books. I bought it at the Borders in Westwood, which at the time had a superb science section. Back then, buying was decentralized to each store. So the Westwood Borders, just down the road from UCLA, had a significantly different selection from the Studio City Borders, and every other Borders in LA at the time.

This was expert filtering. Each buyer knew the kind of people that were shopping in his or her store, and they stocked books appropriate to that market.

Unlike Barnes & Noble, which appeared to use heuristics to stock their stores, each Borders was unique.

When Borders came to Australia and New Zealand around 2000, they had individual store buyers then too, so each store was still unique.

After the chain got sold, the individual buyers disappeared – replaced by a central buyer. This was done in response to the threat of online booksellers. The only way to improve efficiency was to cut down on staffing costs.

So Borders went to dumb heuristic filtering.

And now they’re gone too – also killed by bad filtering.

Third Story: Pulp Fiction Bookshop

I while ago I was browsing through the shelves at Pulp Fiction Bookshop here in Brisbane. They specialize in Science Fiction, Fantasy and Mysteries. Their selection in these areas is among the best I’ve ever seen.

A guy walked into the shop and went straight up to the counter. He said “My wife really likes Iain Rankin and Donna Leone. I want to get her a birthday present – is there a similar author that you can recommend?” The owner of the shop said “Yes, there’s a South African author (whose name I didn’t catch) that’s writing really good mysteries, but no one has heard of him (or her) yet. Try that.” The guy bought two books by that author, and left, looking pretty happy.

That’s expert filtering – both in terms of stocking the store and in terms of helping customers.

Even though people can buy books on the internet, and the Australian dollar is really strong, and the parallel importing laws here making it nearly impossible to sell books successfully, Pulp Fiction seems to be doing pretty well.

They’re doing well, because they filter well.

Conclusions

Simply calling these filtering problems is probably too simplistic. And yet, bad filtering definitely played a role in the death of Tower and Borders. Both of them were pretty good at aggregating. Borders was pretty good at using expert filtering to connect people with books they might like in-store, while Tower was less consistent in this area. For a while, Borders was pretty good at filtering, and Tower was always fairly bad at it.

The problems started when the internet killed their aggregation advantages. This caused Borders to do away with the one thing that actually made them distinctive – their expert filtering. Expert filtering is something that Tower never had.

Neither store ever was able to connect people up with products in the way that Pulp Fiction does. This type of expert filtering & connecting is better even than the algorithmic filtering you get at Amazon or iTunes.

The problem is that it doesn’t scale. So it’s hard to have a Borders-sized bookshop with great expert filtering. It’s easier if you specialize in something, as Pulp Fiction does.

To succeed in an information-based business, you must be good at aggregating, filtering and connecting information. And you have to be able to do all three. The stories of Tower and Borders show you how bad filtering can kill a business.

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The Innovation Filter Bubble

Here is a must-watch video from Eli Pariser discussing some of the themes from his new book The Filter Bubble (reviewed well here by Cory Doctorow). It’s only 9 minutes, and it is well worth your time:

Pariser’s main point is that the primary filters on the internet these days are algorithmic, and that these filters have a strong tendency to only expose you to viewpoints that reinforce whatever you currently think.

This is very important for how we use the internet, but it also has huge implications for innovation as well. I think that many of us work inside of an innovation filter bubble, and that this makes it much harder for us to innovate.

What is an innovation filter bubble? It is all of the habits and routines that prevent us from being exposed to novel ideas and new points of view. Some of these include:

  • The internet filters that Pariser discusses: much of our information comes from the web these days, and as he shows in the talk, this can lead to only running across viewpoints that reinforce our own.
  • Who we spend time with: do you always eat lunch with the same people? Or alone? Spending time with people that you know well is great (and we often don’t do enough of this), but at the same time, we usually spend time with these people because they think a lot like us.
  • Silos within our organisations: is where you work organised by specialty? Most organisations are. This has benefits in that it makes it easier to find the information that is most relevant to our jobs more easily. Still, this is another form of filtering that reinforces current views.

The end result of the filtering that occurs through these routines is that the information that we are exposed to can become too restricted. As Pariser argues, these filters make it easy to find information that is relevant to the task at hand – and that is what makes them useful. But does access to information that is highly relevant to the task at hand help innovation? Probably not.

Innovation is based on connecting ideas in novel and interesting ways. To do this, we need to run across information that is more than just relevant. We also need information that is important, uncomfortable, challenging, and that reflects other points of view.

We have to make a conscious effort to break out of our innovation filter bubble.

How can we do this? Here are some ideas:

  • Actively seek out new and different viewpoints: Ethan Zuckerman has some great ideas about how to do this on the internet. But also do it in your day to day activities. Once a week have lunch or a coffee with someone with a completely different background, area of expertise, or view of life. Go out and find those challenging ideas somewhere.
  • Use filters based on expertise instead of algorithms: as I’ve discussed before, there are at least five forms of filtering. The algorithmic filters are more efficient, but they fall prey to the problems outlined by Pariser. Make better use of expertise-based filters. You can do this by accessing people with expertise in different areas, and also by building broad networks and activating them to help you generate new ideas. Algorithms are great, but you still need some people-based filtering as well.
  • Encourage enhanced serendipity: this is an idea from Ross Dawson, and it’s also discussed in The Power of Pull. It involves building your networks (both online and personal) to maximize your exposure to new ideas and novel viewpoints. One of my personal rules in this area is that on twitter I always follow people that follow me if they come from outside of Australia, North America or Europe. And I follow nearly all of the people that run into from Europe too. This is one way to run across new viewpoints.

In order to innovate we have to generate new connections between ideas. We can’t do this if all of our routines only expose us to viewpoints that are very similar to our own.

To innovate more effectively, we have to break out of the innovation filter bubble.

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Should You Only Execute Good Ideas?

The obvious answer to the question in the title is yes, right?

But I’m not so sure that this answer is correct.

I thought of this because of an experiment that Martijn Linssen tried in January – writing one blog post a day for the whole month. In the comments the idea came up that if you set volume goals like this when you blog, then your quality will inevitably suffer.

Julien Smith made the same point quite forcefully in a discussion of how to increase the impact of your blog:

If you’re anything like me, you write your posts, and your titles, with yourself as audience. This results in a majority of posts which rank 6, 7, or 8/10 with the outside world.

Last week, if I didn’t have a 10/10 post, I didn’t publish at all. This resulted in three posts instead of 5-7, and many more subscribers than I’ve gotten in previous weeks combined.

This is important because we often see the same thing when people talk innovation – a lot of the time it is assumed that every idea that we try should be successful.

There is a deep flaw in this thinking – it assumes that we know in advance which ideas will work. But it’s impossible to know in advance which ideas will work.

Sometimes I have a great idea for a post, which I just can’t execute very well. Other times I have a throwaway idea that I execute nicely. The simple fact of the matter is that I don’t know what people are going think are a 10/10 post before I publish it – and no one else does either.

If every idea that you try is successful, this is a sure sign that you’re not trying enough ideas.

Check out this video:

What is being creative? from Kristian Ulrich Larsen on Vimeo.

Once you get over how cool the phone is, pay attention to the points they make at the end:

  • Stay away from the direct path.
  • Take risks.
  • Don’t be afraid to make mistakes. Because it’s from the mistakes that really interesting things happen.

Selecting ideas is a critical part of the innovation process. However, it’s only in executing ideas that their true value is discovered.

Idea selection is important because we all have limited resources. If you write a blog, the limit is usually time. If you run an organisation, the limit can be time as well, or money, or skill.

Nevertheless, the correct answer to the question of how many ideas you should execute is not: “only the good ones.” It is “as many as you can afford to try.”

I’m looking forward to finding out if this was a good idea or not…

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The Problem of Filters and Silos

Here is a quote from Why The West Rules – For Now by Ian Morris – explaining some of the issues with the inter-disciplinary approach he has taken in writing the book:

This courts all kinds of dangers (superficiality, disciplinary bias, and just general error). I will never have the same subtle grasp of Chinese culture as someone who has spent a lifetime reading medieval manuscripts, or be as up-to-date on human evolution as a geneticist (I am told that the journal Science updates its website on average every thirteen seconds; while typing this sentence I have probably fallen behind again). But on the otehr hand, those who stay within the boundaries of their own disciplines will never see the big picture.

And therein lies the problem. Science updates every thirteen seconds – it’s impossible to keep up with that much new knowledge. Our only hope is to filter the flow somehow.

One way that we do this is by working in silos – our silo becomes the filter. Everything from outside our area of specialty gets ignored.
silo

This helps with the information overload problem, but it creates a new one. Big ideas come at the edge of specialisations, and, particularly, at the intersections. To come up with big ideas you need to be outside of the core (see this post for some ideas on how to do this).

This is another tension in innovation – the need to be both in the core and at the edge. As usual, the best answer is to change this from an either/or into a both/and.

Both/and solutions are hard to execute. You have to accommodate yourself to conflicting intellectual demands, and you have to be comfortable with a relatively high level of uncertainty. That’s what makes innovation both challenging and rewarding.

(photo from flickr/contemplative imaging under a Creative Commons License)

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Succeed by Failing

“If you want to succeed, double your failure rate.”

-Thomas Watson, IBM

That’s a pretty succinct way to say make a point that I was trying to get a couple of weeks ago.

The key point here is that you can fail at different levels. I’ve talked before about a taxonomy of economic failure. We can actually think of failure as a hierarchy that looks something like this:

  • System failure (the collapse of communism)
  • System component failure (stock market crashes)
  • Major firm failure (Enron going out of business)
  • Start-up failure (pets.com going out of business)
  • Product failure (New Coke tanking)
  • Idea failure (Apple Navigator prototyped but never launched)

As you go down that list, failure gets less expensive. When I talk about tolerating failure, I’m talking about trying to set up systems that encourage cheap fast failure. This is usually at the level of ideas.

I think that this is the point that Watson was making as well. He’s not advocating big, expensive, public failure. He was advocating quick, cheap experiments.
Electronic flashbar prototype

We need to push our failures down that list, so that we are testing ideas and finding the ones that don’t work when they are still ideas, rather than things. One of the key skills in this is prototyping – figuring out a small-scale way to test your idea.

As Diego Rodriguez says, anything can be prototyped, and you can prototype with anything.

(photo from flickr/polapix under a Creative Commons License)

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Why New Ideas Can be Bad

Innovation is about more than just having great ideas – a point we’ve made here repeatedly. To innovate, you also have to execute ideas relentlessly. For many people, this is actually the hard part. I’m currently reading Making Ideas Happen by Scott Belsky, and it has some of the most sensible advice on this topic that I’ve run across.

Here is a talk in which Belsky outlines some of the key points from the first part of the book:

Scott Belsky: How to Avoid the Idea Generation Trap from 99% on Vimeo.

The book supports a couple of points that we’ve made here before. One is that idea execution is essential. People are idea-generation machines. Belsky started the 99% Conference based on the old Edison quote – that invention is 1% inspiration and 99% perspiration. The issue is that if you look at the books, tips and consultants that address this topic, it would sure look like the equation is reversed. Given that, it’s great to see someone trying to address the 99%.

The second issue that he addresses nicely is the idea of constraints – he correctly points out that we’re more creative when we have to deal with constraints. One of the key reasons is that constraints make us focus, which is a critical step in executing ideas. Here’s how Belsky puts it:

Constraints serve as kindling for execution. When you’re not given constraints, you must seek them. You can start with the resources that are scarce – often time, money and energy (manpower). Also, by further defining the problem you are solving, you will come across certain limitations that are helpful constraints. As you find them, try to better understand them.

Brilliant creative minds become more focused and actionable when the realm of possibilities is defined and, to some extent, restricted. …

Despite your natural tendency to thrive on untethered creativity, you must recognize and harness constraints. And it is ultimately your responsibility to seek constraints when they are not given to you.

These ideas are pulled together with the graphic that shows the project plateau (which he discusses in this post from Smashing Magazine):

This shows the levels of excitement and energy that we have for ideas over time. When they are new, we have lots of both. However, once we settle into trying to make the idea real, the levels of both excitement and energy go down – it starts to feel more like work. How do we respond to this?

According to Belsky, the natural response is to look for the excitement of a new idea again – and succumbing to this temptation is deadly. If you do, you’ll end up with a lot of partially-executed ideas, which is functionally equivalent to having, well, no ideas at all.

The book (and the supporting website) has a lot of ideas for how to work through this. The main idea is to break down ideas (and the projects that result from them) down into action steps, and then focus on getting these done. It is easier to get big projects done when you are able to build momentum by achieving small steps on them on a near-constant basis.

In some ways this is similar to Dave Allen’s Get Things Done approach, but Belsky’s is more oriented to people doing creative work. Consequently, for me at least, this approach seems more useful. And since innovation is definitely creative, Making Ideas Happen will probably be useful for most people trying to improve innovation.

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I Was Wrong

When is the last time that you wrong? Hugely, spectacularly wrong?

I’m wrong a lot. I’ve learned to live with it. Here’s an example of one of my biggest mistakes – the fundamental premise in my PhD research was completely wrong!

I had an idea when I read a paper by M. Angeles Serrano and Marian Boguna called Topology of the World Trade Web. In it, they showed that if you mapped international trade as a network, with countries as the nodes and trade relations as the links, it was a complex network (see Greg Satell’s excellent discussion of networks for more information on the basics of network analysis). I saw this, and I thought that if you could map international trade as a network over time, then that would be a great way to try to measure the impact of globalisation. After all, we all knew that globalisation was changing the fundamental structure of the international economy, right?

So that’s what I did for my PhD. I found international trade data from the International Monetary Fund that went back to 1938, and I mapped the networks as they changed over time. One of the key measures in all of this is In-Degree. For any particular country, this measures the number of other countries that send a significant percentage of their exports to that country. If you are an important trading partner for many other countries, your in-degree will be high. If few countries export goods and services to you, your in-degree will be low.

One of the important measures of the overall structure of the network is the distribution of degree. This is what the distribution of in-degree looks like from one of my sample years:

This shows that most countries have a very low in-degree. The majority of countries are clustered in the 0-5 range. In other words, the majority of countries in the international trade network are important trading partners for very few other countries. At the other end of the spectrum, you can see that a handful of countries have really big in-degree values on the right side of the graph. These are the hubs in the international trade network – countries like the US, UK, Germany, and Japan.

The physicists that started this line of research usually convert these histograms into a chart that shows degree probability distribution functions. This is what the PDF for the 1938 world trade network looks like:

Here’s where I was wrong. I thought that the shape of this distribution should change over time. We hear two stories about globalisation. The first is that everyone is trading with everyone else now. If that is the case, the degree distribution of the international trade network should be changing to more closely resemble the shape of the curved line in this figure:

However, other people say that globalisation leads to the rich getting richer. If this is true, then the shape of the degree distribution line should be changing to be more like a straight line – more closely resembling one of the lines in that figure.

I was pretty certain that my study would prove that one of these assertions was correct.

Here is what I found – this is the degree distribution of the international trade network as it evolved from 1938-2003:

What that shows is the shape of the degree distribution hasn’t changed at all. The lines have shifted to the right a bit as the number of countries in the network increased from about 100 to around 200, and that’s the only real change.

I was completely, totally wrong about the impact that globalisation would have on the structure of the overall network.

I was able to get a PhD out of that because that’s actually an interesting finding in and of itself (and I did a fair bit of work investigating other aspects of the network that have actually changed). But the core hypothesis that I had at the start of the research was wrong.

I thought of this when I was reading Where Good Ideas Come From by Steven Johnson. It’s a fantastic book. He includes one chapter discussing the importance of error in innovation, which includes this quote from William Stanley Jevons:

It would be an error to suppose that the great discoverer seizes at once upon the truth, or has any unerring method of divining it. In all probability the errors of the great mind exceed in number those of the less vigorous one. Fertility of imagination and abundance of guesses at truth are among the first requisites of discovery; but the erroneous guesses must be many times as numerous as those that prove well founded. The weakest analogies, the most whimsical notions, the most apparently absurd theories, may pass through the teeming brain, and no record remain of more than the hundredth part.

In other words, to be innovative, we have to be wrong a lot. Being wrong is the first step towards being right.

Don’t hide your mistakes, learn from them. If every idea that you try works, it’s a sure sign that you’re not trying enough ideas.

When was the last time that you were massively, gloriously wrong?

Note: I’ve got a couple of papers close to publication on this topic, but if you’d like to see it all explained, you can take a look at this conference paper from a few years ago.

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Where You Are Still Matters

Yesterday I got fed up with reading about music-sharing services like Pandora and Spotify, because neither is currently available in Australia – quite frustrating. After some hunting around, I finally found deezer.com, a French music-streaming site.* I listened to the Punk Rock radio channel on the site, and discovered a fair number of French bands that I’d never heard before. It used to be pretty hard to find music from all the parts of Europe that weren’t the UK, and it was fun to start digging into a musical history that had been mostly hidden from me.

That got me started on a serendipitous path through my music collection, and throughout the day I ended up listening to music by people from France, Italy, Sweden, Latvia, Jamaica, Algeria and Mali. The music was from many different genres, including punk, reggae, rai and several that I don’t know the name for, which mostly combine regional folk music instruments, lyrics and melodies with western rock tropes. As an example of the latter, check out this song by Garmarna, a great band from Sweden:

The issue with Garmarna is that I don’t really know what genre they fit into, but that reflects my ignorance. The standard response to this kind of categorisation problem is to create a catch-all category, like “World Music”.

When we do this, it’s a mistake. Eugene Hütz, the leader of Gogol Bordello, explains why in an interview from Boing Boing:

Boing Boing: You’ve been quoted as saying you hate the phrase “world music.”

Hütz: The term itself is just kind of weak and mindless, but that’s not the problem. The problem was that it was used wrongly, and misguided listeners for decades, it blocked audiences from being able to hear worldwide rock and roll culture, because anything not in English went into a world music section, like a trash bin that only nerds and geeks bother to go into. A lot of brilliant multicultural rock and roll music, great bands, never reached rock and roll listeners worldwide. I know these bands. Incredible musicians from Brazil, Russia, Italy, France, that end up in the world music section and never found their audience because they don’t speak English. “World music” ruined a lot of musician’s careers.

Boing Boing: Has the internet helped to undo some of that damage, by helping to connect those bands to new audiences now?

Hütz: Absolutely. It didn’t resolve all the problems for us, but it does help communication. The downside is that it multiplies the volume of bad quality recordings and videos out there. There are so many more of them out there now. The sheer volume of material makes it important for people to realize that they must have their own filter, to find really good quality material out there. Filters are more important now.

The critical point in all of this is that even in the digital age, where we are still matters (perhaps a sixth uncomfortable fact for digital maniacs?). Music is interesting, because it is a genuinely global phenomenon. Yet every region has a distinct tradition, with lyrical and musical themes that are replicated within groups of composers and performers. In many cases, the genuinely innovative musicians work within one of these traditions, but they add in bits and pieces from other forms of music (from different genres or different locations, or both) to create something entirely new.

Great music is usually an example of combinatorial creativity. It results from complex interplay between tradition, location, and innovation.

There are a few general innovation lessons in all of this:

  • Diversity of thought leads to creativity and innovation: Sturgeon’s Law says that 90% of everything is crap. This is true for most musical genres too (although I sometimes wonder if his 90% number was too optimistic…). The 10% that rise above are the ones that do something more than simply being competent in their recreation of existing tropes. They find new ways to combine ideas. Digital technologies have made it easier to gain exposure to new ideas, but we still have to figure out how to develop novel connections between them.
  • We need good filters to find the right ideas to connect: As Hütz points out, the importance of filters increases as the volume of available information increases.
  • Beware of garbage can classifications like “World Music”: this is the critical lesson. These kinds of categories end up reflecting our ignorance. This is a problem because we create categories as a way to quickly communicate some basic information about the members of that category. When the category does not reflect genuine differences, its existence can do more harm than good.

    This is why terms like Reverse Innovation bother me. The general concept that is being communicated is good – innovation takes place everywhere, and people and firms in developed countries would be wise to pay attention to what’s going on in places that they’ve usually discounted as sources of innovation. This is an important idea, and one that I completely agree with. However, the phrase Reverse Innovation, while catchy, actually reinforces the attitude that it is trying to fight against.

    I support the points that Vijay Govindarajan is making when he talks about Reverse Innovation, but I think it’s a terrible category.

Both in music and in innovation, where you are from still matters. Location has a huge influence on the way that we see the world, and on what tools we think to use in dealing with the world. To innovate, we need to find ways to expand the number of ideas that we are exposed to. We also need to able to effectively filter these ideas. To do this, we need to be able to categorise them accurately.
*It’s worth noting that after listening to music on deezer for just a couple of hours, I went out and bought 3 full CDs – something that the labels would do well to remember when they’re negotiating whether or not these services can get licensing to spread more widely. The simple lesson is that people buy music that they’ve heard – something that labels used to know back when they bribed radio DJs to play their songs…

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The Value Proposition in Business Models

Anders Sundelin wrote a post earlier this week about the evolution of the business model concept. He does a great job of showing the various ways in which this idea has been operationalized – it’s still surprisingly fuzzy. For the state of the art thinking on business model innovation, a special issue of Long Range Planning has twenty articles on the topic (all free to download through September).

One element that is consistent across nearly all of the different ways of thinking about business models is that of the Value Proposition. A central part of building a successful business model is creating value for your customers. Innovation plays a role here in two ways: first, innovation is the process of executing new ideas to create value, so it is a central part of any new value proposition; second, we can innovate in the way that we create value, not just in the products, services or know-how that we offer.

In order to innovate the way we create value, it makes sense to look at how we create value from information. In general, we do this by aggregating, filtering and connecting. This works for big firms like Amazon, and smaller firms like O’Reilly Publishing.

I ran across two more examples of how this can work for smaller firms this week. The first comes from Seth Godin’s description of Gerald Roush and his Ferrari Market Newsletter. Here is the description of the newsletter:

The newsletter, it appears, was not just lucrative, it was a bargain. It chronicled the pricing, whereabouts and details of just about every Ferrari ever made. If you were a buyer or a seller, you subscribed. If you wanted to run an ad, you were required to include the car’s VIN, which added to Roush’s voluminous database.

The Roush effect involves extraordinary domain knowledge, a market small enough to understand and diligently earning the role of data middleman. The players in the market want there to be one clearinghouse, one authority who can connect the data, see the trends and publish the conventional wisdom.

Often when people talk about “aggregators”, they are referring to places like Amazon or Google, who try to catalog everything (or close to it). This is a great example of how you can effectively aggregate on a much smaller scale. The Ferrari Market Newsletter isn’t trying to aggregate everything, it’s just trying to aggregate all available information on Ferraris.

In this case, the aggregating is combined with filtering to create an comprehensive aggregation of information in a specific niche. The connections are made between people that are interested in Ferraris – most importantly, between those that want to sell one and those who wish to buy one.

Note that this is not algorithmic filtering, as we see on the comprehensive sites. It is judgment-based filtering. It often sounds as though algorithms are the only way to go these days, and as this case shows, that is not at all the case. There are still opportunities to build effective business models based on personal judgment.

Here’s another example, though it is more speculative. On Techdirt, Michael Masnick talks about the idea of building affinity-based music groups. Techdirt is a consistently interesting blog, and you should definitely check it out. Here is how he describes these groups:

… Topspin’s CEO, Ian Rogers, penned an open letter to Guy Hands, the head of (struggling) EMI, suggesting that rather than think of itself as a “record label” focused on promotion and distribution (two things that are easier and cheaper than ever before), it could instead focus on being the smart filter for music listeners today, struggling to find the music they love amidst so much musical abundance in the world. The suggestion was to take some of the key, iconic, bands under the EMI roof, and put them under affinity-based “mini-labels” with other less well known bands, that would appeal to people who liked the more well known band. It seemed like a great idea, which, of course, EMI has not done.

Here again, the value is created through filtering. And as with the Ferrari Market Newsletter, this model would then try to aggregate all of the bands that relate to each other in a specific way. This is a model that has worked very effectively for many years for Dischord Records – and like Masnick I think it has great potential.

Creating a novel value proposition is an essential part of generating an effective business model. There are great opportunities to do this in creative ways. If you focus on aggregating, filtering and connecting, you can build a good information-based value proposition.

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