Taming the Information Overload Tiger
We all face an increasing flow of information, 24/7. In theory, the more information we have, the better prepared we are and the better the decisions we make. But there are two problems with that school of thought.
Quantity or quality?
Social events on Facebook or an email about office repairs are unlikely to be relevant to a technical business decision, but how do you know what information is relevant? The world is chaotic (in the technical sense) and it’s nonlinear, nobody can tell for sure what data are relevant, or even know afterward whether they had all the relevant information when they made a decision that turned out right (or wrong).
We can try to filter the information to pick what is relevant – but we don’t know what that information is, and in trying to find the relevant elements, we have to filter ever increasing quantities of data.
Technical solutions (such as filtering software) attempt to deal with the overload, but much of the information is contextual — a given piece of information may be vital or irrelevant depending on other information, the market conditions, the readiness of new processes and so on. How does a filter (that must be programmed in advance) cope with all that real-time complexity given that the mathematical tools do not exist for nonlinear, complex and chaotic systems such as real life, such as weather or earthquake predictions for example.
Humans evolved to deal with a world that was quite small. Dunbar’s number (150) [Ed. Note. Robin Dunbar, a psychologist and evolutionary biologist, maintains that meaningful human relationships are capped at 150 individuals.] is the average village size in history, the standard size of military units and the average number of friends on Facebook. Our ability to retain all the relevant details that might be useful in life can’t get much beyond those related to that approximate size, because information processing requirements shaped our brains to allow us to survive in that environment. That was fine for about 2 million years. We could understand relationships, who was allied with whom, what the best hunting technology was and where we stood in the tribal hierarchy. We could make key decisions with very sound data, related to a relatively small world, because our “human filtering” selected the key information.
We now have available enough information to know all the details that would allow us to relate to our competitors, our colleagues, the technology and our competitive position, market share and so on. But we simply cannot keep track of it all, there are too many factors about too many things for us to be able to handle it in our heads as we used to in the past.
We have developed ways to cope with too much information in a “small world.” For example, if we can’t analyze it as we want, we use various shortcuts to cut it down. That can be heuristics – “there’s too much to look at, this is likely to be the answer” – and base it on familiarity or previous experience. That works well in a hunter-gatherer environment, but sometimes not so well in the modern world. We also can ignore anything that doesn’t fit our pre-existing notions – the banks did that in 2008; the signs were there of an impending disaster, but they didn’t fit their model, so they ignored them.
That’s what “cognitive bias” is, the evolved human brain trying to apply the processes that worked to keep us alive for 2 million years to a totally different environment. It still works very well in some situations (interpersonal ones, for example), but it’s not so hot when there are masses of data that are too big for us to comprehend.
How do you deal with the overload?
By doing simple things, looking at filtering software and telling people to avoid multitasking. Filters won’t hurt, and if people do turn off their phone and focus on one thing at a time, it will increase productivity and almost certainly improve information handling (and decision quality) substantially.
The trouble is, the complexity of modern life isn’t all about data. There’s still a big element of knowing that when one person says, “This is urgent,” it means something different to somebody else. Technology can’t really get that, people can (that’s a reason why Emotional Intelligence is an important concept).
- You’ve got a team, use it. If there are useful sources of data, divide them up. Don’t all subscribe to the same feeds; information sites duplication doesn’t help;
- Actively read or listen, and don’t look for the familiar, look for the novel or controversial. It’s often stupid or misguided, but it’s something you don’t know. The tendency is to think “that’s good” because it agrees with us (just think about why you read the papers or blogs you do –because it’s comfortable having what you think you know confirmed, but, as the banks discovered, it doesn’t always give a good result);
- Read at least one thing that has nothing to do with your function. It might be another business area, or national or international news – but it will pull you into being inquisitive because you’re not the expert. If you study only things directly relevant to your role, it’s easy to be “the expert” and ignore anything new. Nobody else is likely to challenge your view (and if they do, you’ll probably ignore them), so you might miss anything new. It’s hard to be open minded about your expert area, but learning something different makes you more curious and open to ideas;
- If you’re brainstorming ideas, do it individually first. Then combine the ideas. Repeated studies show that you get more ideas, and better ones, that way as opposed to ideas;
- Try to create (get help if necessary) a culture that’s about ideas and challenges, not about personalities. If people are confident that some novel idea they read appears to link to a current business issue, they will produce ideas. The more ideas you have, from different sources that have gone through human filters, the more likely you are as a group to pick out the wheat from the chaff. If people know that they will get insulted, ridiculed or ignored for anything unusual, they won’t suggest anything but conventional ideas that everybody’s been doing for years, and you’ll basically ignore all the new data; and
- At least consider the management team (and everybody else, to be honest) learning mindfulness. There’s increasing evidence that it helps not only with stress and collaborative working, but also allows clearer thinking and analysis. DC