During BlogWalk 1.0, a few of us concentrated on how blogs could serve as an early warning system to alert organisations to developments that require a response, i.e. as a business intelligence tool. (See the picture of the poster we made at the end of this posting)
As one of the organisational attitudes I put forward as required to do this, was the notion “that every signal starts out as noise”. It sounded cool at the time. What I meant was that you cannot know in advance what is useful information until you recognize it as such. Noise in this situation more or less equals unsorted data and information, and signals are data-patterns.
Why do we call information and data coming to us noise? Because we know not all that stuff is useful, we label the unuseful stuff as noise. And because of the tilted signal to noise ratio we perceive, i.e. what little we actually use from what comes at us, we say we suffer from information overload. I say that this is rubbish.
There is no such thing as information overload. It does not exist.
When trains were first introduced passengers suffered from jet-lag like symptoms, even at speeds as low as 20 km/h. Most likely because for the first time sensory input became asynchronous. What you heard and smelled (the train, people in the car with you) did not coincide with what you saw (the landscape passing by). We adapted, we have to do so now.
Different domains, different information needs
Dave Snowden of Cynefin, when he talks about complexity, divides the world in 4 basic realms. They range from the known, the knowable, through complexity to chaos. In chaos action precedes any order, in the known and knowable order, or routes to order, precede action. In complexity there is an intricate interplay between action and perceived order. Action is based on immediate observation, and shifts and changes with the surroundings, until patterns stabilize and migrate into the knowable or known realms. Only with hindsight is the causality chain apparent, and it does not hold any predictive power for the future in the complexity domain.
(picture taken from this presentation by Dave Snowden (ppt), copyright IBM UK Ltd. 2003)
Each of these realms has its own information need, and hence a perception of what constitutes noise, i.e. unuseful information.
In the areas of the known and the knowable, where causality can be predicted, any information that forms a distraction is considered useless up front. In measurements we e.g. call them anomalies, and ignore them.
In complex surroundings there is however no way to know causality in advance, and hence there is no way to tell signal from noise. All stimuli are equal at the start. And you need as much stimuli as you can possibly get, in order to heighten the chance that you will stumble upon something that will form into patterns for you, that has meaning to you.
Knowledge Work Is Making Sense Out of Noise
Knowledge work, in my view, increasingly means shifting your activities from the known (routine practice) and the knowable (the classic approach of science), to the complex, where you have to choose your course of action by judging as much data as possible on the basis of experience, skills and attitude. It’s in the complex realm where disruptive innovation is born, where continuous (action) learning is a prerequisite. Knowledge workers, ergo, need to be exposed to as much background noise as possible, to open up as much opportunities to respond as possible.
Adapting to ‘Information Overload’
Information overload I say does not exist. It is based on the wrong assumptions, that try to apply the way we work in the known and knowable areas to the complex realm.
Those three assumptions are:
In the known and knowable areas, these assumptions make sure that you take the right decisions about causal relationships, and thus be able to control or to cope with your situation. This made perfect sense where information was limited or even scarce. There is fear hidden behind these assumptions, that culminate in the fear to make the wrong decision.
Those three fears are:
In complexity just as there is initially no distinction between signal and noise, there is initially no right or wrong decision. There is just decision, and the three assumptions don’t hold up, and no longer improve your track record.
From a complexity perspective the answers to the three fears, and the three assumptions are:
Or when put into actions:
We’ve Dealt with Information Overload Since the Dawn of Humanity
It all boils down to trusting upon the notion in Open Space of “whatever happens is the only thing that could have”. It is also basically how we humans have looked upon the earth for most of our existence. We always take in all our surroundings all the time. We focus on those things that seem most intriguing, and in the end act upon only those of the intriguing things that we think require a response. The old sense, fright, fight or flight sequence. We now have to learn to apply that to written and other new media. But 150 years of our industrial and a hundred more of our scientific paradigms (and educational methods!) stand somewhat in the way, until we learn to surpass them.
Cro Magnon, as information overloaded as we are, only media have changed
Blogs as Early Warning Systems
Let’s bring this back to where I started. When organisations reach a certain size (albeit in number of people, the different geographical locations they occupy, or the different cultural backgrounds they encompass) natural communication flows are interrupted, and connection to the general background noise is lost, and there is a need for tools to fill that gap.
Blogs create and aggregate an enormous amount of often prefiltered background noise. Being exposed to the blogosphere enables companies to reconnect to their noisy surroundings. It requires however that they accept that their organisational structures are not all that make up reality and don’t want information to flow along those structures only, and also accept that they will not know in advance what is useful information. All signals start out as noise, basically until someone decides it ‘s a signal. To disseminate blogging in an organisation some simple social network mapping might help establish who are the essential trusted people and hubs that could get blogging started. These maybe also are the people most likely to enjoy blogging, as they are already above average exposed to inputs from their surroundings. It’s what makes them hubs in the first place.