The knowledge management model: Putting the pieces in place

The knowledge management systems market is moving forward in a curiously composed single file, not as an advancing front.

At the head of the line are The Big Guys. The infrastructure software players know that enterprisewide deployment of process improvement tools--work management--is the arena in which they can execute the global penetration demanded by their ambitious business plans.

IBM/Lotus, Microsoft, Open Text, Documentum, and the ERP holy triumvirate (SAP, PeopleSoft, BAAN) need the pathways carved by deep corporate initiatives, like knowledge management, through which to extend their influence throughout enterprises.

Next in line are the agile, nomadic start-ups for which a KM market represents the only fertile and unique ecosystem in which such creatures would ever evolve. This group is represented by the likes of Kanisa, KnowledgeX, Grapevine, BackWeb, Net-It Software. Like the squiggly things that live in volcanic vents at the bottom of the ocean, these new vendors, also, need a special environment like KM in order to exist. They need no convincing that in KM lies their future, and they pursue it hungrily.

Then there's the pack. Among this restless herd are hundreds of component players from many disciplines who believe in KM, but haven't yet taken a number. This group includes hardware vendors whose products provide the physical plant on which a knowledge network must rely. It also includes software developers who have perfectly happy businesses providing, for instance, transaction-support tools in (as they see it) discrete processes with narrow fields of application. KM is OK, they say, it's just not what we do.

Component categories have unique and vital roles in KM and they should remain open to all possibilities ... including the one that embracing KM might actually enhance their business and help their customers.

I'll start with capture--data capture and image capture. It is the clearest example of a "traditional" process that evolves naturally into serving a KM systems function.

A new white paper by Tony McKinley, titled Knowledge Management Demands a Total Capture Solution, states:

"Paper accounts for more than 90% of all information, and it's growing. Since 1995, the paper document systems industry has grown from $12 billion to $110.1 billion ... The message of this imbalance is clear: To help organizations harness the benefits of knowledge management, the information systems industry needs to provide a total and efficient approach to data and document capture."

Tony argues that document capture (imaging) solutions aren't keeping up with the demands that KM places on them. Imaging systems could do a much better job converting paper to a digital format that can be efficiently retrieved based on content AND context. But that's not what most imaging systems are designed for. Imaging remains focused on the artifact of a process--the document--not the purpose of the document--its content and the context in which it was created. In their reliance on a value-free, dumb index number as the sole retrieval mechanism, most imaging systems show their bias toward clerksmanship, not knowledge.

Can knowledge be gained by analyzing the mere flow and pattern of document traffic as it enters your organization, moves to nearline accessibility and onto archival storage? Some. But not that much.

The greater value for pure document imaging lies in efforts to attach meaning to the document image. Sure, you should provide the image as a conveniently formatted display of data, designed and laid out to most effectively communicate its information to a human reader.

But other attributes, equally or more important than the image, are the classification under which the document exists (its place within a corporate taxonomy), the context under which the document was created (its metadata) and the ease with which it can be retrieved enterprisewide (its accessibility through an intranet or Web site and its links to other relevant documents and data).

That's document imaging's future in knowledge management.

Now, what about imaging's smarter brother, data capture? Also loosely known as forms processing, data capture is broadly accepted as a transaction processing tool, a way of getting information from a process-unfriendly medium (paper forms) and into data processing systems where it can do some good. Period.

But to stop there is missing a critical fact of life: The ebb and flow of data--raw data--that surges through your organization is like its pulse. The steady predictability of it underlies your ability to forecast and plan; the spikes and dips that punctuate the regularity are like heart monitor alarms that help you react with instinctive speed and accuracy.

Business intelligence that proceeds from data analysis is only as good as the raw material you have to work with. And data capture, like image capture, can be applied for a greater purpose.

If you view forms processing as getting the tracking number off the waybill for tomorrow's package tracking, that's fine. But if you can imagine how business information could one day yield an unknown opportunity, assuming you can measure the pulse of your business, then you understand the knowledge-building power of data capture.