Whilst complexity theory and systems thinking suggest that we cannot treat organisations like simple machines whose moving parts can be dis-assembled and re-assembled at will, that does not mean that we cannot hope to analyse and predict their behaviour with a view to improving organisational development. There are a variety of approaches to observing and measuring the behaviour of an organisation or social network, and indeed a number of different measures to use.

Established methods of online application development often observe individual user behaviour at the point of human-computer interface; this usually takes the form of usability testing on new applications and is guided by study into the nature of Human Computer Interaction (HCI). Software designers use this at different stages of iteration to ensure that what they build is usable for the target audience, and by observing how users go about certain tasks when faced with a visual interface they are able to learn something about whether the system they are building meets its requirements.

Recently, some people have extended this process by using ethnomethodology , a perspective founded by the American sociologist Harold Garfinkel, and outlined in his 1967 book "Studies in Ethnomethodology." The term simply means the study of ways in which people make sense of their social world, based upon the assumption that social order is illusory, constructed from our impressions and experiences, which we then try to organise into a coherent pattern. Garfinkel suggests that the way we make sense of our social world is through a psychological process he calls "the documentary method," which consists of selecting certain facts from a social situation, which seem to fit a pattern and then making sense of these facts in terms of the pattern. Once the pattern is established, it is used as a framework for interpreting new facts, which arise within the situation. Another concept he uses is “indexicality,” which means people make sense of something by reference to its context – in other words they “index” it to particular circumstances.

Ethnomethodologists are concerned only with observation, not theory, which is why the approach has often been adopted by those who are looking for a framework to study social networks and interaction, such as the Knowledge in Organisations Research Group (KORG) at ManchesterMetropolitanUniversity. Because this approach does not presume a social order or system, it can be used as a neutral way to analyse dialogue and the development of social constructs. It has been used quite successfully to inform the design of computer systems and applications, and has produced an interesting collection of behavioural patterns observed in the workplace that provide useful pointers for application and interaction design. 

Whilst HCI informs the way we observe individual (human-computer) behaviour and ethnomethodology can help us study online social interaction, entirely new approaches have emerged whose aim is to help us understand online networks and social behaviour on a more general level.

Social Network Analysis has been around since the early Twentieth Century as a way of analysing connections and inter-relationships between people, and it is has been used extensively in psychology and anthropology to map different forms of social interaction. It involves mapping and measuring relationships and flows between people, organisations (and sometimes computers) via links that show the relationships between these “nodes” to create a visual and mathematical analysis of a social network. It seeks to quantify the “degree” of a node’s position in a network (how many connections it has to others), its “betweenness” (the extent to which a node connects otherwise un-connected network regions) and its “closeness” (a measure of how closely connected the node is to others). In this way, social network analysts can build up a detailed picture of the real activity within a social network, which can often differ markedly from official hierarchies and formal structures within organisations.

Laura Garton, Caroline Haythornthwaite and Barry Wellman provide a good basic guide to analysing social networks, with particular emphasis on online communication, in the Universityof Southern California’s Journal of Computer-Mediated Communication. There are also a growing number of simple software tools available that can support the task of analysing social networks. For example, in an article entitled E-mail reveals real leaders in Nature magazine, Philip Ball looks at how HP Labs have experimented with the automatic analysis of email archives to map the real communities of practice that exist in a large organisation. This use of email artefacts as a dataset for social network analysis looks set to become a standard technique in this field. A useful guide to different methods of visualising online social interaction can be found atInf@Vis , whilst a number of other such tools can be found in Roland Piquepaille's Technology Trends.

At the point where social network analysis meets complexity theory, several writers have attempted to analyse the transmission of ideas and social epidemics, most notably Malcolm Gladwell in his book “The Tipping Point.”   Gladwell seeks to understand why some ideas become so widespread so quickly, whilst others just fade away. In tracing the spread of social epidemics, he identifies three psychological types who play a key role in disseminating ideas: mavens, connectors and salesmen. He defines Mavens as “data banks, they provide the message,”whilst Connectors are “social glue: they spread it.”Salesmen are people “with the skills to persuade us when we are unconvinced of what we are hearing... they are as critical to the tipping of word-of-mouth epidemics as the other two groups.”

Identifying and feeding these people with ideas for mass dissemination is every marketers dream, and many of them are continually trying (usually in vain) to create artificial social epidemics with viral email campaigns and so on. But, how many organisations or online social networks can really claim to know who their connectors, mavens and salespeople really are? There are two potential lessons here for developers of online social applications: firstly, that these applications should help identify such roles within their networks; and, secondly, that they should support and reinforce the behaviour of such people.

As well as looking at social networks and individual relationships, many organisations also try to map the product or outputs of these relationships. Within large organisations and business networks, the practice of flowcharting organisation structures, processes and value chains is now fairly well established. It is upon this basis that many large business process systems have been constructed. However, as Verna Allee writes in her book “The Future of Knowledge ”:

“The popular model of the value chain is also an engineering concept, derived from expanding the process view to the business as a whole. But modelling a business as a value chain does not help us analyse the myriad of value-creating activities that take place across the enterprise.

Another danger in organizing around business processes is a tendency to embed them in rigid bureaucracies, technology systems, and structures such as ERP and SAP systems. If, for some reason, the process needs to be transformed, it is very difficult to change because so much structure is wrapped around it.”

Allee is a proponent of a more holistic mapping practice aimed at identifying value networks, which she defines as “a web of relationships that generates economic value and other benefits through complex dynamic exchanges between two or more individuals, groups or organizations. Any organization or group of organizations engaged in both tangible and intangible exchanges can be viewed as a value network, whether private industry, government or public sector.”For Allee, the value that her approach seeks to map – an organisation’s intangible assets - consists primarily of knowledge and relationships. Similarly, but from a different perspective, Chris Macrae , Group Partners and others are using this approach to help companies map their interconnectedness with themselves and the wider world to develop greater awareness of their positioning through systems thinking.

Another related approach is knowledge mapping, adopted by Valdis Krebs and a host of others over the past five years in an attempt to audit the intangible value of an organisation’s knowledge stock. Krebs has taken this further with his company orgnet , which has developed a widely used organisation network analysis software productthat maps knowledge exchange, information flow, communities of practice, alliances and other networks within and between organizations. When applied to large data sets, this can uncover some interesting features of social networks. For example, by analysing the results of Amazon’s collaborative filtering feature (customers who bought xalso bought y), Krebs found that the book he was interested in buying was actually the one common purchase among four distinct clusters of books. Undertaking a similar study, but focusing only on strong ties between purchases of political books, he found a clear division into two clusters with a remarkable consistency within each and only one book acting as a bridge between the two schools of thought. As Krebs points out, quoting network specialist Ronald Burt , this illustrates the point that a closed network “amplifies predispositions, creating a structural arthritis in which people cannot learn what they do not already know.”

In both studies quoted above, Valdis Krebs discovered individual books that acted as a bridge between networks. If we assume that these books are proxies for the views of their readers, then we can extrapolate that the purchasers themselves operate in relatively closed networks that tend to reinforce existing views and prejudices. This speculative conclusion is supported by the work of Ronald Burt, who has conducted extensive research into network behaviour based upon four years of data relating to the social networks of bankers in a large organization. Burt demonstrates that people who play a bridging role in social networks are key to the formation of social capital, and themselves possess greater competitive advantage, because they overcome structural holes in networks. He also discovered that bridge relationships decay faster than other types of network linkage, which in turn has implications for the social capital of the networks they are part of. However, by virtue of the fact that they sit astride different networks with their own ideas and perspectives, people who bridge networks are more likely to have good ideas .

In Tipping Point, Gladwell describes “Connectors” as "people with a special gift for bringing the world together... the kinds of people who know everyone.”He says they "are people whom all of us can reach in only a few steps because, for one reason or another, they manage to occupy many different worlds and subcultures and niches...,”and concludes that “by having a foot in so many different worlds, they have the effect of bringing them all together."

“Connector” is a general network role, but Burt’s research and Krebs’ mapping work suggest that it is the combinatorial and transformative character of, specifically, bridge relationships that creates the greatest advantage and social capital. Yet, as we know from the real world, a bridge is only as good as what it connects and what that connection achieves.