The last decade has seen considerable progress in the scientific appreciation of how networks are structured. There are two reasons for this; the increase in the availability of data and information about real world networks, and the increased attention paid to the field by the scientific and mathematical research communities. Analysis was hitherto primarily the domain of sociologists and was hampered by their inability to undertake anything more than small scale, qualitatively based research, where in some cases the research process itself distorted the results. At first blush, it is difficult to see how a series of number crunching exercises on a university’s mainframe computer can help any of us in the prosaic, street level business of getting our names and talents known in the right places. However some of the insights this research provides are revelatory, and the dispassionate outlines of academic findings resonate directly with real world experience. The research helps us because a network is an organic, natural phenomenon, built on a string of huge numbers of relatively tiny exchanges, decisions and interactions. Although each decision making process in social networking is itself complex and unique, analysis of the sum of these decisions provides some relevant lessons.
DISPELLING A MYTH? – SIX DEGREES AND SMALL WORLDS
The popular belief that we are all connected by a short series of acquaintances – the Small World Theory – acquired substance in 1967 when the social psychologist Stanley Milgram began a celebrated series of experiments. These entailed asking subjects, who were chosen at random, to get a package to somebody they had never heard of and who lived in a different part of the United States. Participants had to pass the package by hand to somebody they knew, who they thought would be a step closer to the target, and who was asked to continue the chain in the same way. A number of chains were completed, and those that did contained an average of six steps between sender and target. These results were published in a popular psychology magazine and caught the public imagination. Dinner party conversations would centre on the apparent fact that if you knew, say, fifty people quite well, and they knew fifty others, and so on, by the time you took these links six stages you would have a network greater than the world’s population (50 to the power of 6 is 15.6bn.) Unfortunately this neat argument is flawed (even if it were not it would be useless in practice). Later research found shortcomings in Milgram’s research methods, and unpublished papers revealed that the ratio of completed to uncompleted chains was so low (5% in one case) that the conclusions were of dubious validity. The jury is still out; the Small World Project at Columbia University is running a much larger, e-mail based version of Milgram’s experiments. Preliminary results released in 2002 showed that of 60,000 chains started across 171 countries, aimed at 19 targets, only 380 were completed; these had an average length of 5 links, increasing to 7 when borders were crossed.
WHY DOESN’T IT WORK?
In a word, homophily – the natural human tendency to associate with people like ourselves. Homophily leads to clustering, which we can describe as the formation of tightly linked, highly interconnected sub networks with limited external links. Clustering is an important aspect of network behaviour to which we shall return; for now a brief summary of another follow up to Milgram’s work will demonstrate its power. In 1976 JM Guiot asked 52 French Canadians living in Montreal to contact a prominent member of that City’s Jewish community, using telephone chains of acquaintances. They achieved an 85% success rate – the point being that once you had penetrated the tightly knit (i.e. clustered) Jewish community you could very quickly get to anybody in it (although limiting it to one city was also a factor). I mentioned that even if the six degree theory were valid, it would not help us, and to explain why we need to visit the world of mathematicians and Erdõs numbers. Paul Erdõs was a prominent, and brilliant, Hungarian mathematician, an itinerant individual who collaborated prolifically. Mathematicians make ideal subjects, because when they work together they publish papers, making it relatively easy to analyse the structure of their collaborative networks. This type of network is useful to us because it has many of the same qualities as the professional networks we need to develop. An Erdõs number is a guide to an individual’s proximity to Erdõs, based on published papers. So Erdõs himself has a number of 0, whilst all the people who co-wrote with him have a number of 1 (there are 507 of them!). Those who wrote with his collaborators, but not with him, have a number of 2, and so on. The game for mathematicians was to find out their own Erdõs number. In his book “Six Degrees”, Duncan Watts describes how his colleague Steve Strogatz needed two days of concentrated effort to find out his (it was 4). The problem is that the range of potential links expands geometrically at each stage. It is difficult enough simply to establish who your own collaborators have also worked with, while the task of exploring the next level is overwhelmingly complex.
CLUSTERS, WEAK TIES AND STRUCTURAL HOLES
The next diagram, which is simplified, highlights two different styles of networking behaviour. Bill and Adam are, respectively, Sales Director and Head of New Product Development for a niche consumer audio products manufacturer. Both are highly effective in their roles. Bill is very gregarious and manages his team in detail, regularly socialising with them (and with key customers). The ties within this cluster are very strong and information passes freely, quickly and effectively. His success as Sales Director is built on his ability to motivate his staff and develop close links with his customers; it owes more to maintaining high levels of energy than to creative or original thinking. Adam on the other hand is more remote, an austere individual who prefers to work alone. His talent for innovation centres on an ability to spot promising technologies and incorporate them into products that attract consumers. The diagram shows his links with external component suppliers, whom he keeps at arms length and interrogates about new developments by exchanges of e-mails and technical papers. Diagram 4. Bill’s highly clustered Sales Department on the right is in stark contrast to the sparse set of distant links that Adam maintains with the component suppliers whose new technologies enable his own product development. When the company is acquired by a larger competitor which has no need of Bill or Adam, they both decide that their futures lie in building portfolio careers as consultants and non-executive directors. Which of them is better positioned to build a new network on which to find these roles? In 1973, sociologist Mark Granovetter published a ground breaking paper called “The Strength of Weak Ties”. In this and subsequent research he demonstrated that the valuable connections are those that link us, perhaps tenuously, with distant groups or networks. When it comes to moving on, it is not those to whom we are closest that can help, rather those we know less well but who can open the door to new opportunities. For example he demonstrated that white collar workers achieved much greater success in finding new roles through connections with people they barely knew, and that social activist movements in Boston (acting against urban development) were far more effective when they established links across different communities. His paper triggered a slew of further research, which showed that: Complex networks have “Structural Holes” – that is, areas where interconnectedness between clusters is very low. In our diagram we can see such a hole between the sales team and the new technology / product design area. Members of each group are well aware of the other, but tend to focus on their own activities (e.g. hitting the month’s sales target); Those who own or control the links across the holes are in a powerful position, as this ownership gives them a competitive advantage. Because they control a flow of information, they are of interest to people across a wider range of groups than those who operate inside a tight cluster.
In essence, Adam has a great store of Social Capital which he can transfer to a new role, whereas Bill’s social capital derived from leadership of a group of which he is no longer a part, set in an environment in which he will no longer operate. Social Capital as a concept is in its infancy, and definitions vary, but it can be thought of as a metaphor for an individual’s competitive advantage arising from their position in a network structure. When he had his job, Bill’s social capital arose from a high degree of Closure; by this we mean that his actions were highly visible to his immediate contacts (colleagues and customers) and hence he built trust and respect. Adam operated in a looser network with a far lower degree of closure (people didn’t know him well enough to develop trust) but the social capital he possesses as a function of his ownership of a range of weak ties linking separate but related networks is of much greater use as he contemplates life outside the corporate cocoon. The tsunami of research which followed Granovetter’s work provides overwhelming evidence that individuals whose networks span structural holes achieve greater degrees of success. Ronald Burt, whose Network Structure of Social Capital has already been cited, identifies survey after survey reaching this conclusion. Hence a foundation of our approach to Transition Networking is that we do not rely on contacts to whom we are close, hoping that they in turn will know somebody who knows somebody who will want what we have to offer. Nor do we simply try to make as many new contacts as possible in the hope that one in a hundred will pay off. We are looking instead for structural holes in networks, areas in which we are clearly qualified to add value. It is highly likely that in order to position ourselves to add value, we will be relying on weak ties – contacts who know us little or even not at all – to make introductions and to convey messages. By definition weak ties offer little in the way of closure, and therefore the messages we send across these links must be Robust and Sticky.