Yesterday I blogged about the challenge to revolutionise the productivity of the knowledge worker, and how the first step was the division of knowledge. The second step is the automation of knowledge work.
|Image from wikipedia commons|
Automation was one of the factors that helped revolutionise the productivity of the manual worker. The blacksmiths hammer was replaced by the hydraulic press, the auger by the electric drill, the wheelbarrow by the forklift truck. Machine power augmented muscle power. Automation, combined with the division of labour, gave us the modern assembly line.
Automation is one area where KM has done well. Perhaps we should say augmentation rather than automation. As Tom Davenport points out, smart technology is not yet replacing humans, but augmenting their power. Much as a hydraulic press augments the metal worker rather than replaces him, smart KM technology augments the knowledge worker, rather than replacing her.
- Knowledge bases augment the knowledge worker's memory. Rather than keeping our own notebooks, or trying to remember details of a process or procedure, we can consign it to a knowledge base. And if this is a shared knowledge base, then we have access to the knowledge of many people, rather than just our own.
- Search engines augment our power of recall. without significant mental effort, we can retrieve a fact or an image or a process from deep within a knowledge base, thanks to the power of search, be it keyword search or semantic search.
- Smart technology can also take the role of a mentor, and suggest knowledge to use when we need it (based on where we are in a process or a task), even before we ask for it.
- Technology can also augment our personal networks, allowing us to ask not just our immediate colleagues for help and advice, but hundreds or thousands of co-practitioners we may never have met.
- Technology can augment our ability to communicate, allowing us to hold virtual meetings across continents and timezones.
- Technology augments our ability to see patterns in vast quantities of data and information, and to apply our knowledge to make sense of these patterns, and use them to support decision making.
Automation/augmentation is an area where already great strides have been made in helping increase the knowledge workers' productivity. However this is not the only area that needs to be addressed, and tomorrow we will look at the third component, the Knowledge Supply Chain.