7 Time-Proven Strategies for Dealing With Information Overload

A prominent researcher writes "information overload is a problem of the times." What’s causing that overload?

"At present in the world there are about 55,000 scientific journals publishing about 1,200,000 articles a year. Also about 60,000 books and 100,000 other research reports are issued annually . The sheer physical bulk of scientific and technical publications appearing in the United States has doubled approximately every 20 years since 1800."

The researcher then counsels that "since people can’t blow a fuse…they must adjust."

A recent blog post? A new best seller? Hardly. These statements were written in 1962 by James G. Miller, the director of the Mental Health Research Institute at the University of Michigan, in a study entitled, "Information Input Overload."

Even in that age pre-dating personal computers, the Internet, and iPads, people were overloaded by information. The advent of digital information and communication technologies has just made the problem far more acute. Berkeley economists Hal Varian and Peter Lyman estimated in 2003, that it would take about 30 feet of books to contain the amount of information generated for each person on the planet in a single year.

More recently, researchers W. Russell Neuman, Yong Jin Park, and Elliot Panek estimated that the amount of information available to a typical American household has increased by an order of magnitude between 1960 and 2005. The researchers looked at the amount of information outlets available to a typical household over time, such as TV, radio, print media, telephone, and more recently the Internet. They then calculated how much time people had to consume these media. The study found that in 1960, the number of ‘media minutes available’ divided by ‘number of minutes of actual consumption’ was 82. By 2005, that number grew to 884. The study, entitled, "Tracking the Flow of Information into the Home: 1960-2005" concludes, rather dryly, that the challenge of dealing with all this new level of information overload is "in our view… not a human-scale cognitive challenge." It’s a challenge we can’t ignore, since information has become such a central part of our personal and professional lives. And because overload leads to performance degradation, stress, and depression, it is imperative we find effective ways to cope.

What can we do to deal with the information tide? Miller in his 1962 study provides some extremely effective strategies for dealing with overload; strategies that in some cases work just as well today as they did in the 1960s. Here are Miller’s seven strategies for dealing with information overload, updated for the times:

1. Omission – The concept is simple: you can’t consume everything, so just ignore some. This is a bit dangerous since some of the omitted information might be the most critical. Imagine that the email you ignored was the one where your most important client alerts you to a new opportunity.

2. Error – Respond to information without giving due consideration. While a seemingly poor strategy, this is more common than you might think; I mean, who hasn’t reacted to an email, report, or telephone call without thinking through all the consequences because of time constraints or lack of attention?

3. Queuing – Putting information aside until there is time catch up later. An example is processing email early in the morning, before the business day begins, or reading important reports late at night.

4. Filtering – This is similar to omission except filtering employs a priority scheme for processing some information while ignoring others. Automated tools are particularly well suited to help filter information. Recommendation engines, search tools, email Inbox rule engines and Tivo are all good examples of tools that can help filter and prioritize information.

5. Employing multiple/parallel channels – Doling out information processing tasks; for example, assigning the tracking of Twitter feeds to one person and blog coverage to another person on your team.

6. Approximation – Processing information with limited precision. Skimming is an example of approximation. Like omission and error, you can process more information by approximating, but you run the risk of making critical mistakes

7. Escaping from the task – Making this someone else’s problem. While it sounds irresponsible, admitting you can’t ‘do it all’ and giving an assignment to someone else is sometimes the best strategy of all.

Over the years, self-help and management guidebooks have dedicated significant attention to queuing, employing multiple channels and approximation as ways of improving information processing. More recently, filtering has received more attention. There are now a host of digital filtering technologies to make our lives easier; some examples include search tools, RSS alerts, email filters, social media analysis tools, and web analytics. Another exciting new area for dealing with information overload are tools that prioritize information through context analysis. This is a fascinating area that is in its infancy. I will come back to that in a future post.

A final note: If you didn’t get the gist of this post, you can always skim it again or come back to it later...just don’t assign it to someone else to read.

Author David Lavenda is a high-tech product strategy and marketing executive. He also does academic research on information overload in organizations and is an international scholar for the Society for the History of Technology. He tweets from @dlavenda.

[Image: Flickr user Phil Shirley]

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3 Comments

  • Marie Wallace

    David, 

    I really like what you've been writing about the activity stream recently, but I do have to call out the potential (in fact the absolute necessity) of analytics in making the activity team actionable and functional for the business. I predict -- recognizing that I am a bit of an analytics nut :-) --  that in the future few of us will ever drink directly from the firehose but will ingest (driven by context) information that is DERIVED from the stream. It may be a summary, prediction, aggregation, trend, inference, ... based on what I need, when I need it, and in context.So when I am walking into a customer meeting, it will know to share that titbit in the stream that's relevant to the customer I am meeting. Similarly if I'm on the train heading home, it might suggest something else, or if I am inside by travel app, then something else of interest pops up.The stream will be analyzed, synthesized, and contextually served up to us as needed.

    Or think of it as "content finding people" ... that's the the dream for us analytics-heads :)

  • dlavenda

    Great ideas. We are actually working on making your suggestions a reality. This will be a reality in 2014. Let me know if you want to learn more about it.

  • Marie Wallace

    For sure. I'm always keen to hear about how folks are innovating around social data. It's an under-exploited source of data for business analytics.