Information overload! The phrase alone is enough to strike terror into the hardiest of managers; it presages the breakdown of society as we know it and the failure of management to cope with change. The media constantly dissect the forthcoming collapse brought on by TMI ("Too Much Information"), even as they themselves pile up larger and larger dossiers on the subject, and we are frequently informed that it is our own damn fault that we are drowning in data, since we simply can't discriminate between the important stuff and everything else. Hence, the info-tsunami warning signs posted all along what we once so naively called the "information superhighway".

Of course, this is arrant nonsense—human beings have been suffering from information overload in varying forms since about the time we hit the ground and found ourselves simultaneously running after the antelope and away from the lion. There's no question that the human mind has a limited capacity to process information, but after several million years we've gotten pretty good at figuring out how to handle a lot. The two basic tricks turn out to be distinguishing between short-term and long-term information storage, and "chunking"—putting things in a limited number of baskets. This isn't primarily a course in the psychology of memory—it's about information tools and systems—but in fact the same things that make our information tools and systems work are the same things that have kept us near the antelopes and away from the lions (mostly) for the last million years or so. So we're beginning this course by thinking about information tools, what makes them like and unlike other kinds of tools, how the concept of a socio-technical system (in which social and behavioral functions shape results as much as does the technology itself) helps make sense of what we're facing, and why the technology just might win after all.

Let's start with a little historical review. Amy Blair has recently done a very intriguing summary of just why information overload isn't something that we, or still less our kids, dreamed up -- people have been drowning in data for ages regardless of the tools at their disposal:

Blair, A. (2010) Information Overload, Then and Now. The Chronicle of Higher Education Review. November 28. Retrieved November 15, 2010 from

We thought we had it all nailed down when the information theorists came up with their typology distinguishing between "data" (raw stuff), "information" (cooked stuff), and "knowledge" (cooked stuff that we've eaten). This rather elegant approach did have the virtue of emphasizing that information processing is a human task, even though we might delegate part of it to machinery, and that the tests of that task are the results for humans. It helps return us to the perspective outlined in the module introduction -- that is, tools need to be judged by what they do, not just what they are. Systems thinking is a classic approach that even pre-dates computers. Here's a good brief summary of this perspective:

Bellinger, G., Castro, D., & Mills, A. (2004) Data, Information, Knowledge, and Wisdom. The Way of Systems. November 15, 2010 from

But just when we thought we had everything nailed down, the emerging technologies of networking seemed to be blurring things a bit. First, with so much stuff floating around, it's not at all clear just how much "cooking" is really involved in the data/information boundary; a lot of data turns out to be pretty self-interpreting, and no matter how much we cook some of the stuff, it's never going to be particularly nutritious. In addition, it turns out that information sometimes looks an awfully lot like property, so that the kind of disembodied knowledge management framework we thought was going to make things clear for us gets all tied up with personal self-interest, organizational and social politics, generational conflicts, and all of the other fun things that human beings have teamed up to make life difficult for one another over the years. Here is a useful introduction to this concern:

Green, P. (2010 ) Social Media Is Challenging Notions of the Data, Information, Knowledge, Wisdom (DIKW) Hierarchy. CMS Wire. August 16. Retrieved November 25, 2010 from

But now let's put this all in a bit of organizational context. As we noted in the module introduction, the language of socio-technical design can be very helpful in diagnosing where systems are going wrong, particularly when there appear to be disconnects between the capacities of the technology and the ability of the company to establish the right kind of behaviorl and procedures to take advantage of the tools. Here is a very useful shortbut classic introduction to socio-technical design and how it can be used:

Liu, X. and Errey, C. (2006) Socio-technical systems—there's more to performance than new technology. PTG Global. Retrieved February 27, 2011, from's%20more%20to%20performance%20than%20new%20technology%20v1.0.pdf

So how does all this tie together? Well, we've got all this lovely data, information, and maybe even knowledge floating around most organizations, but we don't seem to be able to make a lot of use of it. Either there's just too much, or we can't identify relevant material on a timely basis, or things fall between the organizational cracks. In any event, we experience what amounts to "information overload" on a pretty regular basis, despite having all this understanding of information and some really good tools for managing and using it. How come?

There's a lot more out there in the optional and supplemental readings as well as the wide wonderful world of the Internet to give you a feel for whether or not we’re about to be washed away by the “info-tsunami”; the more widely you can spread your own information gathering net, the more effective your analysis is likely to be.

When you believe you have a reasonable feel for how information tools do (or don't) manage an info-tsunami, you'll be in a position to write an effective short paper on the topic:

Are organizations likely to find better solutions to information overload through changes to their technical systems or their social systems -- or both? Why?