Social Software adapts to its environment,
instead of requiring its environment to adapt to software.
Last week there was a meeting at Clay Shirky's in NY to talk about social software, whatever that is. By coincidence I was in NY for other reasons. There were at least a few bloggers at Clay's meeting. Why is no one is talking about it? [Scripting News]
Here is Clay's write up of the event agenda.
I don't know why attendees are not covering it. But the general lack of discourse may be for three reasons: its a multi-disciplinary concept, barriers of legacy and the lack of a defined value proposition.
People are talking about it, from the perspective of three converging domains: Social Networks, Human-Computer Interaction (HCI) and Web Services. Social Network Analysis reveals the dynamic links and groupings software must adapt to. HCI reveals how software adapts to users. An aspect of Web Services is how loosly coupled software is adapted to software.
Valdis Krebs offers a Social Network Analyst's view of Social Software...
An organization's data is found in its computer systems, but a company's intelligence is found in its biological and social systems. Computer networks must support the people networks in today's fluid and adaptive organizations -- not the other way around.
[from Jon Udell's piece on Seeing and Tuning Social Networks]
Social Network theory, deeply rooted in sociology, has recently found a home in the business world by applying Social Network Analysis to understand informal networks. New visualization tools are just being developed. There is also a dearth of data from organizational settings [my mapping project with Valdis makes a small contribution]. And most importantly, we are just beginning to understand and model the patterns of complex and dynamic social interaction. See the work by Valdis, Karen Stephenson and Albert-László Barabási.
Joel Slayton offers a computer science-centric view of Social Software...
Software need not be tied exclusively to components alone. It would appear that software is, to some degree, shaped by the sub-cultures of data relations from which they are composed...
Software drift is the continuous structural change evidenced as software seeks to both sustain and re-define an appropriate ontogeny. It is an ontogeny that is simultaneously context and environment, application and human interface. Associative rules appear to guide software drift in the form of integrative or dissociative processes of feedback and constraint. And perhaps, just perhaps, the social fabric of software, the ontogeny we observe, is merely a combinatoric of these drifting strata of identity. Three conceptual frameworks need be addressed: Scaled States, Interiority/Exteriority and Cross-Domain Referencing...
Scaling occurs across three parallel trajectories: technical, semantic and behavioral...
To speak of Interiority/Exteriority is to proclaim the autonomy of a unity....
Inferencing is a social action. There are two primary types. One is based on knowledge models and the other on analogy, or cross-domain inferencing.
Realizing these models requires a fundamental change in architecture. You won't see SAP release a "Social Software Module" or Peoplesoft announce an "Enterprise Social Software Management" product. If that was the case, we would all be talking about it, but there is too much legacy. Perhaps this is the opportunity, for major categories of enterprise software to be fundementally revisited by new companies, but that depends upon the value proposition.
The value proposition of Social Software must be more than intuitive (if software adapts to me and my relationships, I will spend less time adapting to it, or not using it). Social Software will definiately offer new collaborative functions, but that's not the core value either. The value of Social Software is its embedded economies of scope. The ability for an asset to adapt to new uses (its environment) without large transaction costs.
Most of the cost of enterprise software is in custom implementation, adapting to business processes. Business processes take an environment-dependent input and produce and environment-effecting output. This labor and time-intensive process supposedly reaps the rewards of automation. But the problem is that business processes constantly require redesign because of environmental changes.
People are smart about how they get their work done. If a software-driven business process fails to serve their activities, they will adapt using their informal network resources to get it done. In other words, when business process fails, business practice takes its place. This is a major point of John Seely Brown's Social Life of Information.
If Social Software continually adapts to its environment it doesn't risk obsolecense. This proposition can be quantified as a reduction in cost to model, map and adapt to business processes.
My model for timing your business case, may reveal a challenge in communicating its value proposition. Social Software will initially arise offering new functionality that is appealing to innovators. However, we are far from realizing software that truely adapts without requiring behavior change, a risky ROI. And primary theoretical benefits are in relative cost reduction (TCO).