I see the critical aspect to social learning to be ‘diffusion’. Knowledge ‘flows’ at specific speeds, and complex, technical details have high viscosity. Some nodes are efficient at in-flow (fast learners), some at out (teachers). Excessive turnover removes nodes before their knowledge has spread to the rest of the group. Isolated groups fail to transmit their knowledge. Again, if I were debugging a company I’d want to measure this. How long before a new product feature is well understood by sales? by management? Does R&D know about current marketing efforts? How much does a idea change as it’s communicated through the company? Are there particular points where ideas get stuck, or particularly garbled?
There is a lot to unpack from this paragraph and it highlights many of issues around learning in the enterprise. It’s not just about having access to knowledge or people but getting ideas flowing throughout the organization. Redundancy comes to mind as a principal for supporting social learning diffusion. There has to be more than one way to communicate or find something.
Just because something was blogged, tweeted or posted does not mean it will be understood and eventually internalized as actionable knowledge. The more complex or novel the idea, the more time it will take to be understood. Often I have revisited articles and only understood them when I have read related views or had a chance to find examples of some new concept. Understanding networks, for instance, is easier when you live and work with them and can see examples of network effects.
Diffusion – Viscosity – Flows – Redundancy