Leading complexity thinkers apply biological principles to enterprises: The Biology of Business is a set of essays by ten researchers and practitioners in Complex Adaptive Systems (CAS).
Virtually Networked Business Teams
We have argued that the new emerging form for teams in enterprises is the “virtually networked business team” – a complex cocktail of team members from different organisations, departments, professions, locations, using different technology platforms and engaging with varying levels of team involvement.
We have proposed that these kinds of teams could be more effective if they designed their operations around the principles which underpin nature’s most successful teams. rather than the traditional command and control structures.
We coined the term “bioteams” – business teams based on sound biological principles which have made it through millions of years of evolution’s “survival of the fittest” – the ultimate seal of quality!
The Books Core Message in a Nutshell
The Biology of Business is a set of essays by ten researchers and practitioners in Complex Adaptive Systems (CAS). As is often the case with a collection of papers the coverage is very rich but at the cost of making it challenging for the reader to locate the core message.
CAS also has its own specialised vocabulary of terms such as Fitness Landscape, Requisite Variety, and Edge of Chaos, which though initially off-putting are worth exploring as they do actually define some important ideas.
For me the best part of the book was the section written by Philip Anderson of the Tuck School of Business at Dartmouth College. In a chapter entitled “Seven Levers for Guiding the Evolving Enterprise” Philip shows very clearly how enterprises can adopt an evolutionary and self-organising approach. This is illustrated using a case study from Capital One Bank who became one of America’s fast-growth success stories in the 90’s using such an approach.
Anderson shares some valuable insights which we can adapt to help us with bioteaming:
- how to define the bioteams boundary and space of operation through Tagging
- how to develop the bioteams network of strong and weak relationships through Social Network
- how the bioteam can engage in experimentation and rapid learning through the practice of variation, selection and retention
So What problem is CAS attempting to solve?
Anderson argues that all organisations left to their own devices will start to breakdown. There are two solutions:
The Command and Control Solution – which involves trying to manage and control the organisation better and the Self-Organising Solution – which tries to create the necessary conditions for order to emerge from chaos. The book advocates the latter on the basis that:
“In natural systems order emerges as long as a system has an inflow of energy, enough parts, enough interconnections, and positive feedback loops….Such systems tend to evolve to a state between inertia and chaos called “self-organisation” or “the edge of chaos”.
The three key elements needed for evolutionary systems
Philip goes on to suggest that all evolutionary systems depend on just three elements: variation, selection and retention.
Take the example of the giraffe:
- Variation – first some giraffes, through random mutation are born with longer necks than usual
- Selection – secondly these giraffes can access some food sources the other ones cannot and therefore are likelier to breed more successfully
- Retention – thirdly the longer necked giraffes pass on their genes to their descendents who also have longer necks
Over many generations the population of giraffes increasingly becomes longer-necked because they breed more successfully than the shorter necked ones
Anderson goes on to suggest that the most powerful way to consider an organisation from the evolutionary viewpoint is as a network of social relationships and suggests four rules for “Social Network Analysis”:
- Evolution proceeds more rapidly when networks are partitioned – small groups with strong ties linked to other groups via weak ties
- Chaos may signal that a network is too richly interconnected – too much connectivity is just as bad as too little!
- A slow rate of evolutionary improvement may reflect too much interdependence – too many strong ties slow the whole system down
- It is more important to identify the worst performing element in a network than the best one – contrasting fundamentally with the current approach which focuses on identifying best practices and standardising them across the organisation
Organisational Evolution in practice – Capital One Bank
Capital One’s approach to organising is highly biological, for example:
- Rapid Evolution – it conducts some 15000 new product introduction (credit card) “experiments” per annum. Each of these is low cost to run and only 1% of them are taken forward based on the early pilot market feedback. Anderson refers to the importance of having “Evolving Vicarious Systems”. In other words having some way to make a rapid prediction of the likely value the market will place on the prospective new product before costly roll-out – a kind of “market proxy”
- Autonomy – it is everyone’s job, not just the organisational leaders, to manage “organisational white space” and operate outside the traditional boundaries whenever the need arises
- Swarming (i.e. Rapid Deployment) – once Capital One identify a product as a potential winner they deploy exceptionally quickly and with force to attempt to dominate and cherry pick the niche before the competition can catch up
- Leadership – the job of the leaders at Capital One is not to control but to define what is important. CAS calls this “Tagging” which is about how we creatively use terminology and language to define what is important and encourage radically new ways of thinking which break with tradition (“legacy tags”). Management are also responsible for recruiting the best people into the network, keeping the network on its “sweet spot” (the balance point between chaos and over-organisation) and providing coaching to staff
So can we apply this to bioteams?
CAS has not yet become as mainstream as it should have. I personally believe some of its difficulty stems ironically from its difficult terminology – ie how it tags itself! Nevertheless the principles of Complex Adaptive Systems are hugely valuable at both the organisational level and the bioteam level.
In our manifesto we identified 12 traits of successful bioteams – for example, here are three very practical ways the Biology of Business can help:
- Tagging can help us define the bioteam’s boundary and its space of operation (Trait 1)
- The four rules of Social Network Analysis can help develop the bioteams network of strong and weak relationships (Trait 9)
- The three elements of evolutionary systems i.e. variation, selection and retention coupled with the idea of a “vicarious selection system” can help a bioteam engage in highly effective experimentation and rapid learning (Trait 10)
The Biology of Business – Decoding the Natural Laws of Enterprise, edited by John Henry Clippinger III, Jossey-Bass, 1999, pp 113-152
Ken is an expert practitioner, author and speaker on Collaboration, High Performing Teams, Change Management, Business Strategy and Leadership Development.
2 Replies to “Complex adaptive systems and virtual team collaboration”
it would be helpful to have a collective intelligence approach to your research approach; i.e. what other reviews, what other deli reviews, diggs, etc..? what are other voices saying? what outbound links to those voices would be helpful to gain greater context?
This article gives support to my conclusion in a recent presentation that I published on slideshare and entitled “Build on Your Weakness”. I quote Item 4 from this post, which states “4.It is more important to identify the worst performing element in a network than the best one – contrasting fundamentally with the current approach which focuses on identifying best practices and standardising them across the organisation”.
The link to my presentation is
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