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PART C – NETWORKS & KNOWLEDGE SHARING
INTRODUCTION
“Today we increasingly recognize that nothing happens in isolation. Most events and phenomena are connected, caused by, and interacting with a huge number of other pieces of a complex universal puzzle. We have come to see that we live in a small world, where everything is linked to everything else. We are witnessing a revolution in the making as scientists from all different disciplines discover that complexity has a strict architecture. We have come to grasp the importance of networks.” Barabasi (2003): 7
In this ‘small world’ (Buchanan 2002), individuals and groups are as likely to reach out around the globe for knowledge as they are to visit their next door neighbour in search of information with more and more people using the Internet to make knowledge-sharing connections (Adamic et al. 2003).
Manuel Castells (1996) was referring to the complexity of the network society in the mid-1990s. His work offers a comprehensive grounding in the strengths and weaknesses of networked society. At the same time Lipnack and Stamps (1994) had also realized the significance of the networked society to organisations and began producing practical guidelines on organisational principles for networked organizations.
Given such complexity, how do we provide a platform for a networked community?
A starting point may be to divide the activities of individuals into five distinct knowledge (K) domains, as follows:
K1: Knowledge Worker (the knowledge a worker uses to perform their daily tasks);
K2: Knowledge Networker (the contacts that are relied upon for knowledge);
K3: Knowledge-based Organisation (the knowledge contained within the organisation’s structure and culture);
K4: Knowledge Networker of Networks (the knowledge contained within partnerships);
K5: Knowledge Architect (the technologies that are relied upon for gathering knowledge, for example, conversations, email, text messaging etc.).
Any knowledge base would need to reflect these domains if it is to create a shared learning and collaborative space. This space would then act as a gathering place, a space for democratic engagement and create a dialogue through which occupants of the space could progress on an individual and group basis.
SIX DEGREES OF SEPERATION
The number of connections within a network can be expressed as follows:
n*n-1/2
In this equation, n is the number of nodes (organizations or individuals) within the network. This is multiplied by the number of nodes minus one as a node, clearly cannot be connected to itself. This is then divided by two as all other nodes cannot be connected to themselves.
Following this equation, in a network of 30 nodes, the total number of possible connections is 435:
30*29/2=435
Can knowledge be managed given such complexity? The answer to this question may be no BUT knowledge can be accessed, created and shared effectively if we know in what way we can use the network.
One way of accessing knowledge within networks is through the use of six degrees of separation (Watts 2003), that is, someone you know knows someone else and so on. In a short space of time you have built a personalised network which reaches around the globe.
For fun, take the example of the Spice Girls and Monica Lewinsky:
1. The Spice Girls were in Spice World with George Wendt 2. George Wendt was in Cheers with Ted Danson 3. Ted Danson was married at Martha’s Vineyard and Bill Clinton attended 4. Bill Clinton knows Monica Lewinsky
In this example, there are only three degrees of separation.
THE STRENGTH OF WEAK TIES
The sociologist, Mark Granovetter (1973) undertook some research in Boston, Massachusetts during the 1970s in areas of high unemployment. He discovered that those who were most successful at gaining employment were not those who used friends and relatives for employment opportunities but were the people who could find out who knew who within networks. This phenomenon has come to be known as ‘The Strength of Weak Ties’.
During the 1960s, however, the anthropologists, Barnes (1969) and Clyde Mitchell (1969) hinted at such tendencies in their ethnographic studies.
Nevertheless, it is a phenomenon which is very familiar in the 21st century where managers rely heavily on personalised networks. These are networks where key players have relatively few key contacts but use them, in combination with various technologies, to access others for knowledge. The strength of weak ties operates according to a law called ‘Power Law Distribution’.
Power law distribution means that there are many nodes with few links at one end of the curve and few hubs with many links at the other end.
Think of how this differs from a traditional Bell Curve?
You should NOT fall into the trap of believing the old adage ‘It’s no what you know it’s who you know’ in relation to the strength of weak ties as it is about more than know who. It’s about:
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