The New Book
Part 1: Chapter 2
The biological switch

Chapter 4

A biological way to think about information, systems, people and collaboration

Part 1

The need for a new mind set

There is a rapidly growing interest in the way biological systems process and deal with information. They seem to be able to handle certain types of problems that computer algorithms have difficulty with. These are in areas that involve change, uncertainty, ambiguity, bias, subjectivity, competition and human activity.

Although many observers have commented on the parallels between information technology and biological systems, very few people have made use of their very powerful techniques and strategies. Why is this?

Probably, this oversight is due to the mind set that results from applying computer technology to conventional business strategies, where emphasis is placed upon planning, procedures, categorization and control. Once this mind set is established, it seems inconceivable that a system can work in any other way.

Yet, biological systems come into being without planning. They don't use procedures or categorization. Even control is not specific because they have an innate ability to self-organize.

It's about a system of people - not information

When computer technology is applied to information storage, retrieval and management, the primary concern is with the information itself. It is sorted, categorized, cross-referenced and various means devised to search through it efficiently.

Human effort is a secondary consideration, as it has to be directed and proceduralized to conform with whatever system of organization has been imposed on the information.

A biological strategy reverses this order. The primary concern is with the human effort. The information and its organization emerge later.

Biological strategies can be used to enable people to collaborate with each other more efficiently.

Usually, collaboration is thought about in terms of inter-personal communication, organization, procedures, emotions, motivation, leadership, team spirit, etc. But, biological strategies deal with collaboration at a far more fundamental level; where individuals act independently; where they collaborate without instruction and with no direct communication between each other.

It may seem impossible for collaboration to to take place under these conditions, but this is the way it is done in nature.

Biological strategies are about creating systems where people collaborate because it is in their interests to do so. Through participation they become nodes of a self-organizing intelligent network, where humans - not algorithms - are providing the intelligence.

Biological system strategies arrange for human intelligence to combine and complement, to self-organize, to become focused and used with maximum efficiently - but within a flexible framework that allows maximum scope for individual initiative.

The main thought to bear in mind is that biological strategies are used to create a system of human collaboration. The information and its organization emerge later - as a consequence of the system being put into operation.

Biological systems break all the rules

To a business executive, biological systems will seem to break all the rules of both logic and commonsense.

Business strategy and management techniques are based upon the premise that collaborative systems have to be ordered and brought under control. This seems the only rational way to be able to specify results, to set and achieve goals and targets. The idea that a collaborative system should be deliberately designed to be unstable and chaotic would seem to be utter madness. Yet, this is the way biological systems work.

Is it any wonder then, that biological system thinking is so slow to be incorporated into computer applications and mainstream business strategies?

Yet, it is patently obvious that biological systems can be highly organized and efficient. They can possess abilities to process some kinds of information even better than the most powerful computer systems. How do they do it? This is what this paper is going to explain.