Knowledge Management (KM) means different things to different people.
Based on its experience and on the existing large body of knowledge management literature, the team decided that knowledge management software should provide virtual “places” where users can organize information, services, and tools to support their particular needs, while at the same time maintaining and updating information in a more general context.[1]
Or, in other words, Lotus thinks KM is the creation of a communal library. This notion of KM as the construction of a communal library is made clearer by a recent IBM publication touting something Satyam developed for the petroleum industry called Spandan, which is “a complete knowledge management (KM) portal built from several IBM Lotus and IBM WebSphere software products.”[2]
Spandan consolidates all the knowledge in the R&D organization into a central knowledge repository, organized in a taxonomy that makes sense to everyone," says Agrawal. "It captures lessons learned and best practices as they're created or refined. It enables users to quickly find both explicit knowledge, such as knowledge in documents, and tacit knowledge, such as knowledge in discussion threads or in an expert's mind through a single unified search. And it combines all these functions with collaboration features, such as instant messaging and teaming, that help people work together in context with knowledge.
Of course, there is a problem with communal libraries, ones that are created by the users of a system or the knowledge workers in a company. Not everyone wants to contribute to them. In fact, not everyone wants to even bother using them. Companies often have to resort to forcing people to use them and to contribute to them.
Satyam proudly announced its solution for this:
Satyam configured Spandan to automatically award knowledge-points, or "K-points," to scientists as they contributed to the system, and to tally and publish K-points for each scientist at the end of every quarter. Maybe more important, Satyam preloaded the system with knowledge and data that was most important to the scientists. "We populated the repository with the previous five years of project reports, technical data sheets, tour reports and all documents types they identified as the ones they consulted most," says Agrawal. "This made them start using it, and once they saw how useful it was to be able to find important information quickly, they were motivated to add more."
Their message is clear. If you make people use a collaborative library they will. (And otherwise they aren’t likely to.) Personally I haven’t been in a library, virtual or real, in twenty years. Guess I wasn’t offered enough K-points.
(Of course some people do contribute to communal encyclopedias like Wikipedia. But it is a really small proportion of the community does so.)
What is the real issue in KM? This is easy to answer.
Libraries are about your attempts to find information outside your normal activities. Well-indexed libraries make information easier (though often not easy) to find.
In life, the bulk of information finds you in the course of your every day activities, when you interact with other people in the enterprise, or when a colleague needs your help on a problem. Or, most importantly … when you are reminded of something you have already experienced. There are two points to be made here.
1. People do not usually seek information – it seeks them.
2. When people do seek information, their greatest source of information is themselves and they find what they need without actually having to try.
Any KM system that hopes to work in a real world where people act like people and not like members of a community where they have to play their part in order to get K-points needs to be built around the following principles:
1. Information finds the user by knowing what the user is doing and therefore knowing what information the user might need.
2. Users do not ever try to add information into the KMS. Their work is naturally part of the KMS and is added automatically.
3. The KMS knows what it knows and is getting smarter all the time.
For people who work in the real world, the key issues must find them in their natural environment without expect them to start searching for them.
It takes special circumstances to get people to contribute to the library. Here it is, again from the cited IBM article:
But like most expert communities, the oil company's R&D scientists were reluctant at first, and saw knowledge sharing as a potential threat. "The scientists were worried that contributing and sharing knowledge would lessen their importance in the organization," Agrawal says. "For example, if one scientist was the exclusive expert in a certain area, and a question in that area came from the Parliament or the Ministry of Petroleum, that person got his or her chance to shine and to feel important. Our challenge was to convince them that they became more important by contributing, rather than hoarding."
Scientists in any industry are not even remotely like people who work on real life everyday jobs. Scientists publish papers about original ideas and they worry that those ideas will be stolen. People with more normal jobs worry about doing their jobs properly and receive information and work within the bounds of e-mail and an enterprise software system. They do not expect to do research in a library like a scientist would. And, they may not even know when they need more information, while it might be very important for the enterprise if they did. These are very dissimilar worlds.
Any KMS for the normal world of work must understand and have a detailed model of the world in which that work is taking place. If the knowledge to be managed is shipping knowledge, then the KM system must know about shipping in detail so that it doesn’t even for a second think that a bridge procedure refers to a card game, and it cares about weather information if and only if a ship it cares about might encounter that weather. A KM for shipping needs to know about issues about particular ships, and ships like those ships, and what to do about similar issues when they happen in new circumstances. In short a KM for shipping must serve as a corporate memory that knows more than any one individual might know. It must track what is going on in daily events and relate what is going on at the moment to what has gone on in the past to see if it can help manage goal conflicts and hence manage risk.
In order to use such a KMS, the system must use indices that find knowledge that are intuitive. But, what is intuitive in one line of work is not intuitive in another. For shipping the system must speak shipping language and use shipping concepts to index shipping information. Any system that did not d o this would be about as useful as hiring a librarian who specialized in English literature to catalogue you companies knowledge.
In a KMS that uses roles and tasks to describe actions there is an implicit assumption that given an action, it is reasonable to expect another particular action to follow.
The organizational principles of a KMS for real life tasks must contain predictions and expectations about the normal flow of events in standard situations. Whenever an expectation derived from that structure fails, its failure must be marked. Problems must be stored with respect to the action sequence in which they took place. Real world corporate processes are not like science. These processes are predictable and understood. The question is not how to manage document flow but how to manage processes for opportunity and for risk. KM for industry is not KM for scientists.
The problem for KM in the corporate world therefore, is to make use of the organizing principles in a work situation and utilize them in a KMS that organizes the information in that domain. These organizing principles will certainly be about roles and tasks and the goals associated with them. The ways in which goals can be satisfied or blocked and the plans that are used to execute those goals must be the cornerstone of any KMS.
[1] The Lotus Knowledge Discovery System: Tools and experiences
W. Pohs G. Pinder C. Dougherty M. White, IBM SYSTEMS JOURNAL, VOL 40, NO 4, 2001
[2] Satyam’s IBM Lotus KM Solution helps petroleum company fight change with knowledge, (IBM publication on the web)
Based on its experience and on the existing large body of knowledge management literature, the team decided that knowledge management software should provide virtual “places” where users can organize information, services, and tools to support their particular needs, while at the same time maintaining and updating information in a more general context.[1]
Or, in other words, Lotus thinks KM is the creation of a communal library. This notion of KM as the construction of a communal library is made clearer by a recent IBM publication touting something Satyam developed for the petroleum industry called Spandan, which is “a complete knowledge management (KM) portal built from several IBM Lotus and IBM WebSphere software products.”[2]
Spandan consolidates all the knowledge in the R&D organization into a central knowledge repository, organized in a taxonomy that makes sense to everyone," says Agrawal. "It captures lessons learned and best practices as they're created or refined. It enables users to quickly find both explicit knowledge, such as knowledge in documents, and tacit knowledge, such as knowledge in discussion threads or in an expert's mind through a single unified search. And it combines all these functions with collaboration features, such as instant messaging and teaming, that help people work together in context with knowledge.
Of course, there is a problem with communal libraries, ones that are created by the users of a system or the knowledge workers in a company. Not everyone wants to contribute to them. In fact, not everyone wants to even bother using them. Companies often have to resort to forcing people to use them and to contribute to them.
Satyam proudly announced its solution for this:
Satyam configured Spandan to automatically award knowledge-points, or "K-points," to scientists as they contributed to the system, and to tally and publish K-points for each scientist at the end of every quarter. Maybe more important, Satyam preloaded the system with knowledge and data that was most important to the scientists. "We populated the repository with the previous five years of project reports, technical data sheets, tour reports and all documents types they identified as the ones they consulted most," says Agrawal. "This made them start using it, and once they saw how useful it was to be able to find important information quickly, they were motivated to add more."
Their message is clear. If you make people use a collaborative library they will. (And otherwise they aren’t likely to.) Personally I haven’t been in a library, virtual or real, in twenty years. Guess I wasn’t offered enough K-points.
(Of course some people do contribute to communal encyclopedias like Wikipedia. But it is a really small proportion of the community does so.)
What is the real issue in KM? This is easy to answer.
Libraries are about your attempts to find information outside your normal activities. Well-indexed libraries make information easier (though often not easy) to find.
In life, the bulk of information finds you in the course of your every day activities, when you interact with other people in the enterprise, or when a colleague needs your help on a problem. Or, most importantly … when you are reminded of something you have already experienced. There are two points to be made here.
1. People do not usually seek information – it seeks them.
2. When people do seek information, their greatest source of information is themselves and they find what they need without actually having to try.
Any KM system that hopes to work in a real world where people act like people and not like members of a community where they have to play their part in order to get K-points needs to be built around the following principles:
1. Information finds the user by knowing what the user is doing and therefore knowing what information the user might need.
2. Users do not ever try to add information into the KMS. Their work is naturally part of the KMS and is added automatically.
3. The KMS knows what it knows and is getting smarter all the time.
For people who work in the real world, the key issues must find them in their natural environment without expect them to start searching for them.
It takes special circumstances to get people to contribute to the library. Here it is, again from the cited IBM article:
But like most expert communities, the oil company's R&D scientists were reluctant at first, and saw knowledge sharing as a potential threat. "The scientists were worried that contributing and sharing knowledge would lessen their importance in the organization," Agrawal says. "For example, if one scientist was the exclusive expert in a certain area, and a question in that area came from the Parliament or the Ministry of Petroleum, that person got his or her chance to shine and to feel important. Our challenge was to convince them that they became more important by contributing, rather than hoarding."
Scientists in any industry are not even remotely like people who work on real life everyday jobs. Scientists publish papers about original ideas and they worry that those ideas will be stolen. People with more normal jobs worry about doing their jobs properly and receive information and work within the bounds of e-mail and an enterprise software system. They do not expect to do research in a library like a scientist would. And, they may not even know when they need more information, while it might be very important for the enterprise if they did. These are very dissimilar worlds.
Any KMS for the normal world of work must understand and have a detailed model of the world in which that work is taking place. If the knowledge to be managed is shipping knowledge, then the KM system must know about shipping in detail so that it doesn’t even for a second think that a bridge procedure refers to a card game, and it cares about weather information if and only if a ship it cares about might encounter that weather. A KM for shipping needs to know about issues about particular ships, and ships like those ships, and what to do about similar issues when they happen in new circumstances. In short a KM for shipping must serve as a corporate memory that knows more than any one individual might know. It must track what is going on in daily events and relate what is going on at the moment to what has gone on in the past to see if it can help manage goal conflicts and hence manage risk.
In order to use such a KMS, the system must use indices that find knowledge that are intuitive. But, what is intuitive in one line of work is not intuitive in another. For shipping the system must speak shipping language and use shipping concepts to index shipping information. Any system that did not d o this would be about as useful as hiring a librarian who specialized in English literature to catalogue you companies knowledge.
In a KMS that uses roles and tasks to describe actions there is an implicit assumption that given an action, it is reasonable to expect another particular action to follow.
The organizational principles of a KMS for real life tasks must contain predictions and expectations about the normal flow of events in standard situations. Whenever an expectation derived from that structure fails, its failure must be marked. Problems must be stored with respect to the action sequence in which they took place. Real world corporate processes are not like science. These processes are predictable and understood. The question is not how to manage document flow but how to manage processes for opportunity and for risk. KM for industry is not KM for scientists.
The problem for KM in the corporate world therefore, is to make use of the organizing principles in a work situation and utilize them in a KMS that organizes the information in that domain. These organizing principles will certainly be about roles and tasks and the goals associated with them. The ways in which goals can be satisfied or blocked and the plans that are used to execute those goals must be the cornerstone of any KMS.
[1] The Lotus Knowledge Discovery System: Tools and experiences
W. Pohs G. Pinder C. Dougherty M. White, IBM SYSTEMS JOURNAL, VOL 40, NO 4, 2001
[2] Satyam’s IBM Lotus KM Solution helps petroleum company fight change with knowledge, (IBM publication on the web)
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