Following up, and wrapping up actually, on the short series I have been publishing on social media as an interim (but essential) step towards collective knowledge I’d like to cover a draft version of the framework I see for social knowledge.
You hopefully have been keeping up, reading all about the evolution to social knowledge, the definition for social knowledge, and some of the other writings about knowledge management I have been publishing around the world (thanks to my sponsors for this topic: Coveo, Moxie Software, and Stone Cobra).
Now, publishing a framework in a blog post is not bound to be very effective – after all, you can build entire methodologies around frameworks (and you know that a methodology is not a short 2-pager or anything close to that). However, I feel that discussing the high points of what is necessary for a KM solution to evolve into a social knowledge solution is very important.
I spend a lot of time talking to people (vendors, practitioners, consultants, influencers, and thought leaders, and more). In these conversations these past few months a common element or issue has been showing up more and more: what to do about collective knowledge. The quick rise in social networks and communities has brought a very big problem to organizations: there is a lot of value (potentially) in those channels – but we are not sure how to leverage that.
As I have been saying for a while, and most recently in previous posts in this series, this is an evolution – not a revolution. You won’t be able to get value from using social channels and communities unless you prepare your systems to take advantage of that. With that in mind, here are the top six things you have to remember as you embark on the road to social knowledge:
Subject Matter Experts. The key to both social and collaborative knowledge is to have the right experts at hand. The evolution of knowledge is to focus more in those subject matter experts, be able to identify them, have them accessible and use their knowledge to answer questions and update content. The evolution towards social knowledge will need a solution that can “manage” these subject matter experts as the source of knowledge and maintenance of that knowledge.
Collaboration within Established Workflows. Just because we are going to use people instead of static knowledge bases, which still won’t disappear, does not mean the need to generate and maintain entries into those bases goes away. The established workflows for content generation and maintenance need to be upgraded to both reflect the use of different sources as well as more relaxed flows for dynamic, constantly shifting knowledge.
Aggregation. Of course, once we have several sources for knowledge the issue of federated knowledge bases comes up very quickly – and while important, it is not as critical as being able to aggregate the real-time knowledge from communities and SME. Definitely a framework to migrate forward in knowledge must include a way to aggregate all this knowledge: static and real-time, and the in-between use of SME.
Multi-Channel. As much as I would hope this goes without saying, I am still getting calls and inquiries from customers that are not sure if they should use one source of knowledge for all channels (in their defense, they do think it is a good idea – they are just not sure of how to do it, or if their solution can do it). This goes without saying now: single source of aggregated knowledge for all channels.
Three “R”s. The concept of the three R’s (right answer, right channel, and right time) talks to timeliness and accuracy more than it does to being able to distribute over multiple channels (see point #4 above). Under the assumption that we can distribute to all channels equally, the next consideration is making sure the right answer at the right time reaches the intended recipient – being able to deliver (leveraging real-time knowledge from SME) is a key feature of these evolved scenarios.
Evolutionary. Proposing an evolution from current KM to social knowledge and eventually to collective knowledge means migrating existing solutions to the new models. This migration requires the new solutions to temporarily support the old models to ensure a graceful transition (especially when using federated knowledge bases with partners or non-traditional contributions to the knowledge base).
Can you see the framework taking place? Can you see what elements you need to adjust and change in your solution? How to evolve?
Did I miss something? Would love to hear what you have to say below.