
The original idea behind social collaboration, especially enterprise social networks, was that by using social media’s conversational type of communication scheme -- microblogging, for example -- organizations could interact in ways that were previously quite difficult.
That’s because freeform social communication had limited advantages. Entrenched applications and techniques, especially email, were more familiar and performed basically the same function. As social collaboration software evolved, vendors focused on adding more features to help workers find value in these new platforms, including content sharing, lightweight workflows and most recently, integration with systems of record such as CRM. All of these new additions were designed to make social collaboration a part of the daily working life of the average knowledge worker.
Too Many Choices
Yet, a large number of knowledge workers still do not use social collaboration products even though their companies pay for it. That should change somewhat as social collaboration becomes better integrated into company processes and lightweight workflows help teams to work better together. Still, those improvements won’t be enough. For the most part, social collaboration is still a “build it and they will come” affair. Companies deploy a large variety of features, often in the name of choice or flexibility, which leaves knowledge workers with the unenviable task of trying to figure out how to them work into their environments and processes, and in a way that best supports their individual job functions.
In a nutshell, plugging dozens of social features into new places won’t help enough.
Context-Based Collaboration
The next generation of social collaboration platforms -- successful ones, anyway -- will deliver all of the current features but firmly in the context of individual knowledge workers’ daily work experiences. Features will be pre-selected and organized for specific workflows, supporting common processes and producing desired outcomes. Instead of providing for the maximum set of possible use cases for social collaboration, features will be focused on a handful of use cases that drive daily work within vertical industries.
The best way to create context-laden social collaboration would be to automatically analyze the participants, processes and past uses of a social collaboration interaction and to empower knowledge workers to alter the predefined features and workflows as called for by the current situation. By observing these adaptations, the social platform would further refine the context based on observed changes and successful outcomes, enhancing the user experience over time.It is unlikely we will see this type of sophistication soon.
Learning Opportunities
For a while, at least, expect this to be a manual process.IT professionals and knowledge workers will have to work together to develop templates that users can deploy and modify to their individual circumstances. Each template will encode the type of context that makes the social features relevant to the participants. Social platform analytics do provide insights that help the refinement process but much of it will be trial and error. It is reasonable to expect that software vendors will try and understand the use cases that benefit from social interactions and provide starting templates for common processes in vertical industries -- or at least their consulting arms will.
In order for companies to see the real benefits of social collaboration platforms -- i.e., more efficient processes, better quality work, the breakdown of the artificial silos within companies -- the features must be delivered in a manner that is most relevant to the knowledge workers that are expected to use them. More features no longer matter. Better baskets of features that make sense and are relevant to the work knowledge workers do are what will encourage adoption.
Title image courtesy of Evgeny Korshenkov (Shutterstock)
Editor's Note: To read more of Tom's thoughts on the social enterprise, see his Social Collaboration in 2012 - Moving at Light Speed