Designing Social for the Enterprise

Enterprise

I remember attending a local unconference for social startups several years ago. This was in the heady days when social was fresh and much had yet to be defined. Session after session plumbed the myriad possibilities of mining user-generated content for valuable information. We had conversations about tagging, meta data, and standards — and the spirit of social sharing was genuine as tech-heads considered an ecosystem of open and federated social messaging, shared user activity, and notifications.
What struck me then, as it still does, was the emphasis on information over communication. It struck me because the activity behind the information produced on social tools usually comes from communication — posts, comments, gestural activity, and many other kinds of social interaction. Even “utilitarian” activities like list-making and curating are communication — users do them because there’s an audience for them.
In my view, all online social activity is a form of communication. I think of social tools as “tools of talk.” They may depend on software and technology to operate; and their “social space” is distant, absent, and discontinuous in real social terms. But they serve to mediate social activity. Consequently, the data or information they produce (capture and distribute) is created with social intent. It is information that means to communicate.
It may be a different market, but enterprise social is also a space in which buzz tends to focus on information: e.g. big data, social data, knowledge. Here again, we tend to gloss over the fact that this information is a great corpus of social interactions. These social interactions become “social facts” by virtue of digital materialities. Individual and personal statements, requests, responses, gestures, greetings, invitations, offers and more are all but linguistic productions of a social world. So the data they produce — content artifacts, texts, images, videos, and gestures — are the production of communication.
To view this “information space” as communication is an important shift of interpretation. And many big data experts know this. For communication does more than create information (or content) — it refers also to social relationships and to the rights and responsibilities of communication between individuals. It says more than it says. This difference is simple for us to see, but much harder for machines.
What’s interesting in the enterprise social space is that its sociality differs from that of the open and public social space. It’s organized, instrumental, purposeful and role-dependent. Different opportunities and constraints govern, if you will, the mediated talk that occurs across enterprise social.
Most fundamentally, this kind of talk is work talk. Talk that gets things done, that builds consensus, that coordinates activities and reproduces the organization day after day. So, in fact, information as content is in cases subordinate to the action-orientation of communication.
Any design of these enterprise social tools should therefore accommodate the specific needs of organizations and their employees. Artifacts are produced not simply to get attention or benefit their creators, but to serve organizational purposes of timing, aligning, connecting, transacting, obligating, and otherwise carrying on the business of work.
The design challenge, then, is to architect for interactions and communication. To design for intent and meaning, preserving as much as possible of the social characteristics of communication as of the information communicated. The designer adopts a new frame — one of users interacting with users, not with application interfaces. This frame provides the context for methodologies interested in social architecture, and in events over time. For communication is order and organization of social activity with duration and persistence. Information, viewed traditionally, is the content left behind.
Indeed our tools recognize much of this implicitly. Feeds, activity streams, and notifications all perform the service of binding activity to and over time. Content artifacts such as posts, comments, messages, and gestures permit forms of talk that easily connect to other relevant and related content. And all of it is and will be mined for meta content — trends — and for details.
(It’s interesting, in fact, that the tools designed for enterprise social increasingly embrace messages, not pages, as their platform. This shows that we have graduated from a web publishing content model to a communication/interaction model. Messages have content, like pages, but are talk, not writing. They’re addressed to people.)
The design methodologies for these kinds of products are still catching up to the paradigm shift inherent in our evolution from desktop to networked computing. Much remains for user experience and interaction design to do, in constructing models and heuristics, in moving past personas to contextualized activities, and in articulating “use cases” and flows that better reflect social activities.
Fascinating challenges lie ahead for user experience design, interaction design, and indeed social business design. But they all begin with recognition that behind all that data is communication and its intents. And thus there is always much more than what is said.
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  • http://twitter.com/marie_wallace Marie Wallace

    Great article :)

    Your point about lnformation Vs. Communication from a design perspective is mirrored in the analytics space. I’ve spent the last decade working on analytics with specific focus on workforce or people-centric analysis, and one of the things that has surprised me about the evolution of analytics in social media has been this over emphasis on information, ie. content analytics, and lack of attention paid to the interactional aspects, ie. social network analysis. Things are changing but its been slow.

  • http://www.gravity7.com/blog/media/ gravity7

    Thanks Marie,

    No doubt conversation analysis (content and relationships) is hard, even sentiment analysis is fallible. Analyzing for competencies (e.g. some of what Klout does) is also hard. But I think all these are coming with time. In the meantime, we balance art and science ;-)