How do we cope with the barrage of information that we face each day? Yesterday I suggested that the information glut has been with us for a long time. Stowe Boyd ended up talking about the same issue yesterday in a terrific post called The False Question of Attention Economics.

His contention is the same as mine – that we have always had too much data to contend with, and so arguments that claim that we currently face numerous problems because of an attention deficit are starting from a false premise. You should read the whole post, but here is one key section of Boyd’s argument:

In the final analysis, I am saying there is no ‘answer’ to those that say we are overloaded, that we are being driven mad by or enslaved to the tools we are experimenting with, or that there is some attention calculus that trumps all other value systems.

Instead, I suggest we continue experimenting, cooking up new ways to represent and experience the flow of information, our friends’ thoughts, recommendations, and whims, and the mess that is boiling in the huge cauldron we call the web.

I suggest we just haven’t experimented enough with ways to render information in more usable ways, and once we start to do so, it will like take 10 years (the 10,000 hour rule again) before anyone demonstrates real mastery of the techniques involved.

There is no “answer” since they are asking a false question, one that hides preconceived premises and biases. Starting out with the assumption that we have moved past our abilities to cope with the stream of information, and therefore something has to give, is a bias.

I think that this is correct. However, the issue of attention economics is still valid – the question of how we allocate limited attention to overwhelming amounts of available data is critical. And as Tom Peters suggests, there are significant advantages that accrue to those that are able to intelligently process larger amounts of data:

The biggest change that we face now is not the fact that there is too much information that we have to process, but rather the tools that are available to help us – we are much more able now to outsource aspects of data collection and processing. And fortunately, there are some very smart people thinking about how we can best take advantage of the available tools. In addition to the blog by Boyd, those of Harold Jarche and Venessa Miemis have many good ideas on this topic. So does George Siemens – who teaches a class which involves intentionally overwhelming the students with data. Their success in the course is then dependent upon how well they are able to build and use a data-gathering and -processing network.

I like the prescription to win by outreading the competition. But I’m still working out the best way to do it. If anyone has any further suggestions or tips, I’d love to hear them.

If I gave you the choice between two training courses – How to Use Twitter for Business or Principles of Social Media, which would you rather take?

Now, let’s say it is 2004, and your choices are How to Use Friendster for Business or Principles of Social Media – which of those would you rather take?

In case you don’t remember, Friendster was the first big social network. In 2004 was about where twitter was in late 2008 in terms of the number of users, and it was the dominant social media site of the day. Now it is the subject of The Onion’s Archaeological expeditions:

Internet Archaeologists Find Ruins Of ‘Friendster’ Civilization

One of the issues that I run into when I’m teaching MBA and Executive Education classes is that people want things that are practical – things they can go out and apply right away. They want things like How to Use Friendster. Well, now, they want How to Use Twitter. But if academics are doing their job well, they should be able to teach general principles that apply across similar situations. If you had taken a Friendster class in 2004, what you learned in it now wouldn’t be doing you much good. On the other hand, if you had taken a Principles of Social Media class in 2004, you should have learned things that will still be helping you on Twitter, or LinkedIn, or on whatever comes next. This is one of the fundamental tensions that we face – trying to balance the teaching of general principles with the teaching of specific useful tools.

I’ve been told a couple of times recently that I’ve been being ‘too academic’, which is part of what prompted this thinking. I think that being ‘too academic’ can mean a few different things:

• Academics tend to think in terms of general principles and theories, but people learn best from stories. A lot of academics think that telling stories is somehow inappropriate, or beneath them. So being ‘too academic’ can mean talking only in theory, with no stories.
• Closely related to that, many people in business don’t value academic ideas because the people spouting them don’t have business experience. Sometimes this is a valid criticism, but sometimes it means that the academic is telling them something they don’t want to hear. In the latter case, discounting the discussion as being too academic is a defensive posture to avoid having to do something that they don’t want to do.
• Often, academic research uses specific words to mean specific things. This usage is different from field to field, and if you are not trained in the field, it just sounds like jargon. If academics are using too much jargon, whatever they’re saying simply won’t make sense to a non-academic audience. Sometimes you need to understand the jargon to understand the concepts, so you have to do a little work to learn about the topic. Other times, the jargon is simply a smokescreen used to hide the fact that the academic doesn’t really understand the topic well enough to explain it simply. There’s an irony in this one too – academics often think that if they simplify their ideas too much, people will assume that they don’t know what they’re talking about, when in fact the opposite is nearly always the case.

So where does this leave us? The point that I’m trying to make is that sometimes the accusation of being too academic is a valid one to which professors and lecturers really need to pay attention. If we’re not telling enough stories, or if we’re using too much jargon, we’re not communicating in a way that will help our audience. On the other hand, sometimes the accusation of being too academic is being used to avoid having to think about what is being said, or to avoid having to act on it. Good research often discovers things that contradict common sense. Good researchers can explain why this is the case, and what people should do about it (Bob Sutton is an absolute master at doing this – his blog, books and talks are all good examples of excellent communication of academic results).

A good academic can tell you a story, then use it to illustrate a general point, and talk about the situations in which that general point is true and false. The last point is critical – many of the people that are popular business gurus can do the first two, but not the last, because they haven’t done any actual research. And it is the last bit that is critical. Just because Bill Gates has done something and it has worked for him, it doesn’t mean that it will work for everyone. Or, in particular, it doesn’t mean that it will work for you.

We need to stop saying that things are ‘too academic’, and get better at specifying what we really mean by it. Don’t let your desire for hearing stories lead you to learn about Friendster or other ephemeral things when you have a chance to learn something of more lasting value. And I’ll do my best to get better at saying what I’m trying to say more clearly. How does that sound?

(And, if you can figure out what the blog title is referencing, I’ll buy you a drink next time I see you)

Photo by Phil Long (still not quite sure how he managed to catch me when I wasn’t waving my hands wildly…)