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The Serendipity of Attention

In the recent post Forget Dunbar’s Number, Our Future Is in Scoble’s Number, commenter Adam Metz wrote:

H-Dog,

Maybe I’m missing something, but where’s your definition of Attention? Can you add it in to the second or third paragraph? Good idea, but a little rough around the edges.

Calling me “H-Dog” is one way to get my attention. ;-) But back to the definition of attention. Putting it simply:

Attention = time + interest

Time being a real-world constraint. There are only but so many hours in a day, so attention is bound by that dimension. If I’m tied up with work or playing with the kids, I’m not going to give anything my attention. The second aspect is interest. Say, I do have some time. If I’m viewing something on the foraging habits of the scaup bird, my interest is quite low and I’m likely not to pay attention even though I have the time. I’ll find something else.

I will observe though, that while time is a concrete and unyielding dimension, interest is fluid and dynamic. Our moods, activities, friends and life events  affect what is interesting at any given point in time. It’s not like it’s totally random – there is a baseline of things that consistently interest us. While time is rigid, interest is a flexible dimension of attention.

Next question is how we find things that are of interest to us when we do have the time.

The Reducing Bands of Attention

I think I can make this statement with certainty:

You will miss the vast majority of information which would fit both your interests and time available to read

Anyone disagree? That’s probably a frustrating aspect of our information age. Am I finding the things I should know? How do I improve that? How can I be both more efficient and systematic in finding what interests me?

Technology is making it easier to be more efficient and systematic, but we’re nowhere near perfecting that. And we can’t get too perfect, because as I mentioned before, our “interests” are fluid and I don’t think we could possibly catalog all of what interests us.

Honestly, we have to accept a certain serendipity of attention. And realize we’ve got a much better system of discovery than we did just ten years ago. I’ve thought about my own experience. What’s my personal system for attention?  It’s a mix of ways, as the graphic below shows:

bands-of-managing-reduced-attention

Let me describe the bands.

Dunbar’s Number: This is the theoretical limit on the number of individuals whom you can follow closely. The number is pegged at 150, a number of people which even Robert Scoble uses for his core basis of attention. My Dunbar’s number includes the 70 or so people I’m following each day on my Enterprise 2.0 List on FriendFeed. It then includes some other folks who fall outside Enterprise 2.0 but interest me in other ways.

With people in your Dunbar’s Number, you read what they create, share and talk about. My guess is that this is the core use case of Facebook members. Note that you expand the number of people you track via this group when they share content or talk with someone outside your core 150. The expansion is temporary though – based on what someone you follow has engaged with.

@replies: I use the Twitter @replies function as shorthand for the ways in which people reach out directly to you. This includes the @replies, the DMs, the Facebook messages, email itself,  etc. Now I’m not inundated with these, so they still get my attention. As you rise in the social media pecking order, apparently you get bombarded with these directed messages. Then they probably move to an outer band of attention for you.

Keyword tracking: This is how people, information and conversations outside my Dunbar’s Number most often get my attention. I track content that includes keywords in which I’m interested. This is the most systematic way I have for improving the efficiency and coverage of things that interest me. As I often write here, I use the Enterprise 2.0 Room on FriendFeed for this. Another good option is Filtrbox. I’m sure there are others.

Other groups: OK, you’ve got the core group of people you follow in your Dunbar’s Number. But there are others you like to keep up with as well. This is where the group functions come in to play. You can group people based on some characteristic, and check on those groups as attention allows. On FriendFeed, these are Lists. TweetDeck lets you group people.

Groups are great for when you’ve already seen your Dunbar’s List and @replies. And sometimes you just need a break from the usual topics and people on which you’ve put focus.

Random views: I do this as well. For some, it may be dipping into the public timeline of Twitter. Or FriendFeed’s everyone tab. Once you’re following a large number of people, checking out the tweets or FriendFeed entries of everyone you follow becomes a form of random views. Because you can’t possibly take in the full river of content all the time. You’d get nothing else done. But it is worth it to dip in occasionally.

Scoble’s Number Requires a System

In the graphic, I categorize all the bands outside Dunbar’s Number as the province of Scoble’s Number. To track people well outside your core 150, you need a way that aids the goals of better efficiency and more systematic coverage, while preserving the serendipity that accompanies the fluidity of our interests.

That’s where I am these days when it comes to attention. How about you?

*****

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Supply-Demand Curves for Attention

The basic ideas behind the Attention Economy are simple. Such an economy facilitates a marketplace where consumers agree to receives services in exchange for their attention.

Alex Iskold, ReadWriteWeb, The Attention Economy: An Overview

The attention economy. It’s a natural evolution of our ever-growing thirst for information, and the easier means to create it. It’s everywhere, and it’s not going anywhere. The democratization of content production, the endless array of choices for consumption.

In Alex’s post, he listed four attention services, as they relate to e-commerce: alerts, news, search, shopping.  In the world of information, I focus on three use cases for the consumption of information:

  1. Search = you have a specific need now
  2. Serendipity = you happen across useful information
  3. Notifications = you’re tracking specific areas of interest

I’ve previously talked about these three use cases. In a post over on the Connectbeam blog, I wrote a longer post about the supply demand curves for content in the Attention Economy. What are the different ways to increase share of mind for workers’ contributions, in the context of those three consumption use cases.

The chart below is from that post. It charts the content demand curves for search, serendipity and notifications.

micro-economies-of-attention-3-demand-curves-for-content

Following the blue dotted line…

  • For a given quantity of user generated content, people are willing to invest more attention on Search than on Notifications or Serendipity
  • For a given “price” of attention, people will consume more content via Search than for Notifications or Serendipity

Search has always been a primary use case. Google leveraged the power of that attention to dominate online ads.

Serendipity is relatively new entry in the world of consumption. Putting content in front of someone, content that they had not expressed any prior interest in. A lot of the e-commerce recommendation systems are built on this premise, such as Amazon.com’s recommendations. And companies like Aggregate Knowledge put related content in front of readers of media websites.

Notifications are content you have expressed a prior interest in, but don’t have an acute, immediate need for like you do with Search. I use the Enterprise 2.0 Room on FriendFeed for this purpose.

The demand curves above have two important qualities that differentiate them:

  • Where they fall in relation to each other on the X and Y axes
  • Their curves

As you can see with how I’ve drawn them, Search and Notifications are still the best way to command someone’s attention. Search = relevance + need. Notifications = relevance.

Serendipity commands less attention, but it can have the property of not requiring opt-in by a user. Which means you can put a lot of content in front of users, and some percentage of it will be useful. The risk is that a site overdoes it, and dumps too much Serendipitous-type content in front of users. That’s a good way to drive them away because they have to put too much attention on what they’re seeing. Hence the Serendipity curve. If you demand too much attention, you will greatly reduce the amount of content consumed. Aggregate Knowledge typically puts a limited number of recommendations in front of readers.

On the Connectbeam blog post, I connect these subjects to employee adoption of social software. Check it out if that’s an area of interest for you.

*****

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Defrag 2008 Notes – Picasso, Information Day Trading, Stowe “The Flow” Boyd

defrag-logo

One of the most consistently provocative conferences I attended last year — my own Money:Tech 2008 aside, of course — was Eric Norlin’s Defrag conference. Oodles of interesting people, lots of great conversation and all of it aimed at one of my favorite subjects: How we cope with the information tsunami.

Paul Kedrosky, Defrag 2008 Conference

I spent two days out in Denver earlier this week at Defrag 2008 with Connectbeam. As Kedrosky notes above, the conference is dedicated to managing the increasing amount of information we’re all exposed to. Now my conference experience is limited. I’ve been to five of them, all in 2008: Gartner Portals, BEA Participate, TechCrunch50, KMWorld, Defrag.

Defrag was my favorite by far. Both for the subject matter discussed and the attendees. The conference has an intimate feel to it, but a high wattage set of attendees.

In true information overflow style, I wanted to jot down some notes from the conference.

Professor William Duggan: He’s a professor at Columbia Business School. He gave the opening keynote: “Strategic Intuition”, which is the name of his book.  Duggan talked about how studies of the brain showed that we can over-attribute people’s actions as being left-brained or right-brained. Scientists are seeing that both sides of the brain are used in tackling problems.

He then got into the meat of his session – that people innovate by assembling unrelated data from their past experience. For example, he talked about how Picasso’s style emerged. Picasso’s original paintings were not like those for which he became famous. The spark? First, meeting with Henri Matisse, and admiring his style. In that meeting, Picasso happened to become fascinated with a piece of African sculpture. In one of those “aha!” moments, Picasso combined the styles of Matisse and African folk art to create his own distinctive style. He combined two unrelated influences to create his own style.

Duggan also described how all innovation is fundamentally someone “stealing” ideas from others. In “stealing”, he means that people assemble parts of what they’re exposed to. This is opposed to imitating, which to copy something in whole. That’s not innovation.

Re-imagining the metaphors behind collaborative tools: This session examined whether we need need ways of thinking about collaboration inside the enterprise. The premise here is that we need to come up with new metaphors that drive use cases and technology design. I’ll hold off on describing most of what was said. My favorite moment was when Jay Simons of Atlassian rebutted the whole notion of re-imagining the metaphors. He said the ones we have now are fine, e.g. “the water cooler”. What we need is to stop chasing new metaphors, and execute on the ones we have.

Rich Hoeg, Honeywell: Rich is a manager in Honeywell’s corporate IT group (and a Connectbeam customer). He talked about the adoption path of social software inside Honeywell, going from a departmental implementation to much wider implementation, and how his own career path mirrored that transition. He’s also a BarCamp guy. Cool to hear an honest-to-goodness geek making changes in the enterprise world.

Yatman Lai, Cisco: Yatman discussed Cisco’s initiatives around collaboration and tying together their various enterprise 2.0 apps. I think this is something we’ll see more of as time goes along. Companies are putting in place different social software apps, but they’re still siloed. Connecting these social computing apps will become more important in the future.

Stowe “The Flow”: Stowe Boyd apparently gave quite the interesting talk. I didn’t attend it, because Connectbeam had a presentation opposite his. But from what I gather, the most memorable claim Stowe made was that there’s no such thing as attention overload. That we all can be trained to watch a constant flow of information and activities go by, and get our work done. I think there will be a segment of the population that does indeed do this. If you can swing it, you’re going to be well-positioned to be in-the-know about the latest happenings and act on them.

But in talking with various people after the presentation, there was a sense that Stowe was overestimating the general population’s ability and desire to train their minds to handle both the work they need to do for their employers, and to take in the cascade of information flowing by (e.g. Twitter, FriendFeed). Realistically, we’ll asynchronously take in information, not in constant real-time.

We’re Becoming Day Traders in Information: I heard this quote a few times, not sure who said it (maybe someone from Sxipper or Workstreamr). It’s an intriguing idea. Each unit of information has value, and that value varies by person and circumstances. Things like Twitter are the trading platform. Of course, the problem with this analogy is that actual day traders work with stocks, cattle futures, options, etc. Someone has to actually produce something. If all we do is trade in information and conversations, who’s making stuff?

Mark Koenig: Mark is an analyst with Saugatuck Technology. He gave the closing keynote for Day 1, Social Computing and the Enterprise: Closing the Gaps. What are the gaps?

  1. Social network integration
  2. Information relevance
  3. Integration with enterprise applications
  4. The culture shift

Mark also believes in the enterprise market,  externally focused social computing will grow more than internally focused. Why? Easier ROI, more of a sales orientation.

Charlene Li: Former Forrester analyst Charlene Li led off Day 2 with her presentation, Harnessing the Implicit Valkue of the Social Graph. Now running her own strategic consulting firm, Altimeter Group, Charlene focused on how future application will weave “social” into everything they do. It will be a part of the experience, not a distinct, standalone social network thing. As she says, “social networks will be like air”. She ran the gamut of technologies in this presentation. You can see some tweets from the presentation here.

One thing she said was to “prepare for the demise of the org chart”. When I see things like that, I do laugh a bit. The org chart isn’t going anywhere. Enterprises will continue to have reporting structures for the next hundred years and beyond. What will change is the siloed way in which people only work with people within their reporting structures. Tearing down those walls will be an ongoing theme inside companies.

Neeraj Mathur, Sun Micro: Neeraj talked about Sun’s internal initiatives around social computing in his session, “Building Social Capital in an Enterprise”. Sun is pretty advanced in its internal efforts. One particular element stuck with me. It the rating that each employee receives based on their participation in the Sun social software. Called Community Equity, the personal rating is built on these elements (thanks for Lawrence Liu for tweeting them):

Contribution Q + Skills Q + Participation Q + Role Q = Personal Q

Sun’s approach is an implementation of an idea that Harvard Professor Andrew McAfee put out there, Should Knowledge Workers Have Enterprise 2.0 Ratings? It’s an interesting idea – companies can gain a lot of value from social computing, why not recognize those that do it well? Of course, it’s also got potential for unintended consequences, so it needs to be monitored.

Laura “Pistachio” Fitton: Twitter-ologist Laura Fitton led a panel called “Finding Serendipitous Content Through Context”. The session covered the value of serendipity, and the ways in which it happens. The panel included executives from Aggregate Knowledge and Zemanta, as well as Carla Thompson from Guidewire.

What interested me was the notions of what serendipity really is. For example, Zemanta does text matching on your blog post to find other blog posts that are related. So there’s an element of structured search to bring related articles.

So I asked this question: Does persistent keyword search, delivered as RSS or email, count as “serendipity”? Carla’s response was , no it doesn’t. Serendipity is based on randomness. It’s an interesting topic worth a future blog post potentially.

And of course, Laura encouraged people to tweet during the session, using the hash tag #serendip. The audience tweets are a good read.

Daniela Barbosa, Dow Jones, DataPortability.org: Daniela works for Dow Jones, with coverage of their Synaptica offering. She’s also an ardent supporter of data portability, serving as Chairperson of DataPortability.org. Her session was titled Pulling the Threads on User Data. She’s a librarian by training, but she kicks butt in leading edge thinking about data portability and organization. In her presentation, she says she’s just like you. She then pops up this picture of her computer at work:

daniela-barbosa-laptop-screen

Wow – now that’s some flow. Stowe Boyd would be proud.

Wrapping up: Those are some notes from what I heard there. I couldn’t get to everything, as I had booth duties for Connectbeam. Did plenty of demos for people. And got to meet many people in real life that I have followed and talked with online. Looking forward to Defrag 2009.

*****

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