It is widely known that searching, with respect to a buying decision, is a transaction cost that must be considered as an important part of any purchase process. This is true whether we are in the market for a pair of shoes, an automobile, or a million dollar piece of machinery. The more expensive the potential purchase the more willing (and likely) we are to incur additional search based costs.
Why do we search? Obviously, we search in order to gather the information necessary to make a prudent and knowledgeable decision. At some point we stop searching and rationalize the information that we have gathered. The stopping point occurs when we have found all the pertinent information (rarely), when the search-based transaction costs begin to exceed the relative value of the purchase (sometimes), or when we get tired and bored and want to get on with life (almost always).
The same principle applies when we search for information related to decisions we need to make in order to complete our work assignments. What would happen if we could, within certain decision domains, drive the search-based transaction costs close to zero? Obviously, we would make better decisions faster, at the same time dramatically improving productivity. This is essentially the Holy Grail of KM: get the right information, to the right people, at the right time.
Our crude attempts at solving this problem to date has centered on building bigger and better repositories (e.g. specialized databases) and improving full text-based search techniques. There is widespread agreement that these improvements have been beneficial. In the aggregate, two technologies, search engines and email, have dramatically accelerated the velocity of information worldwide and have been the prime movers in the creation of the largest library that the world has ever known.
As important as web-based technologies are and will continue to be, they do not constitute a breakthrough in KM. Searching for information, irrespective of how fast we can make it, will always take longer than we would like it to. Context sensitive content provides a step in the right direction. The software development process has been improved significantly by the inclusion of rich context sensitive help systems within state of the art Integrated Development Environments (IDE’s). While the availability of specific information related to our current context does not constitute knowledge transfer, it does serve as an effective starting point.
If you accept the premise that knowledge transfer requires human dialog then by definition improved search technologies will never quite get us where we need to go. I present some plausible scenarios, implementable with existing technologies, which represent the KM future according to Leyva. The scenarios include context sensitive rich content as the starting point that leads to on-demand real-time conversations when required.