The phrase – “Smart push, warrior pull” (described here). is a very useful military principle for maximising knowledge bandwidth. In the military case the bandwidth is often restricted by hardware rather than by attention, but the principle is a good one.
The US Department of Defence operates a global broadcast system (GBS) which acts as a knowledge and information transfer system to troops. Like any such communication system it suffers from bandwidth issues, so the transfer of knowledge and innovation must be strictly prioritised. “Smart push, warrior pull”, inevitably shortened to SP/WP, is a widely-applied principle to do this prioritisation. It represents the two following components;
Intelligent transfer, from central command to the troops on the ground, of the information and knowledge they need at that moment and nothing more.
The option for further requests for additional information and knowledge from the troops to the centre.
It ensures that people get the right knowledge at the right time, with no waste. Send people what they must have, and let them pull what they might need.
The armed forces and intelligence units operate this way because of the bandwidth limitations of the GBS, but there is no reason why a similar principle cannot be used within organisations: “Smart Push, Front-line Pull” (SP/FLP) for example, where the customer facing staff, or staff conducting operations or projects, are provided centrally (or automatically) with the knowledge they need for that customer, or that operation, or that project, with the option to ask/search for more if needed. To do this effectively, the “senders” in the centre must anticipate the needs of the front line, so this “push” is probably best managed by the communities of practice and/or the domain experts.
Although organisations are less likely to have infrastructure bandwidth limitations, there is definitely an attention bandwidth issue, also known as “information overload”. A principle such as SP/FLP would improve the efficiency of the KM system by reducing “knowledge waste” and minimising information overload.