KM encompasses such a broad range of meanings that everyone has a different definition. It’s rather like an elephant – one person holding onto the trunk says knowledge management is about enhanced document retrieval software; another holding the tail claims it’s a searchable repository for technical support calls. And there’s a lot to cover in between!
Too broad a definition of knowledge management can mean too many choices when it comes to selecting a KM system. You have to describe the elephant.
If you are trying to acquire KM technology, it is absolutely critical that you precisely define what your organization means by “KM.” Wikipedia’s definition is a good starting point as you try to develop the questions that need to be asked:
“KM is the process of capturing, developing, sharing and effectively using organizational knowledge.”
In your organization, does capturing mean simply storing knowledge or does it require gathering it as well? Storage is pretty simple – similar to putting carrots into a fridge – and finding software for that is like shopping for a fridge. You’ll know what you want when you see it.
Gathering knowledge, however, is a complex process more akin to growing carrots. Seasoned KM practitioners will tell you that creating a “culture of contribution” in your garden of organizational knowledge is an extremely challenging mix of engineering, values, culture and reward systems. Great technology alone will not carry the day. You’ll need a partner who will help you build a knowledge sharing ecosystem.
Knowledge in most organizations is a by-product of work. People generally learn by doing. If there is a significant research aspect to your organization’s activities, it should be pretty straightforward to tap into it. It’s critical that people are motivated to contribute (and rewarded for doing so) if they must do it proactively. Alternatively, hook your KM application into the tools used daily by your co-workers, and it becomes possible to surface a lot of interesting knowledge and expertise. This latter approach is technically more difficult, but side-steps some of the challenges of getting people to contribute to the knowledge base.
Technology makes it relatively easy to share information. Organizing your content by subject area, source, author and audience can make the experience of looking for it faster and more intuitive.
If you do run into a problem with sharing, it is probably not the technology, but is likely related to organizational culture, and a lack of incentives for individuals to contribute their knowledge. People will throw up millions of false objections, such as “it takes too long,” “the application doesn’t work,” “I can’t remember my log-in credentials,” etc. Nine times out of ten, though, it comes down to values.
If your KM system’s user interface is inviting and it is chock full of valuable content, your most important task will be to promote its existence. Too often, your intended audience simply doesn’t know what is available. So promote shamelessly. The more people use it, the more usage will increase.
If we don’t first describe and understand the elephant, it is easy to see how challenging it can be to feed it, make friends with it, choose the right tools to take care of it, and get people comfortable with the fact that it’s in the room. The benefit? It will never forget your most important institutional knowledge!
Stan Garfield on KM thought leader Cindy Gordon who focuses on ethical AI, AI governance, and AI for business.
Stan Garfield on KM thought leader Nancy White who supports communications for NGOs and NPOs thinking in, out, around, and beside the box.
Stan Garfield on KM thought leader Beverly Wenger-Trayner who develops strategies for cultivating communities, networks, and social learning.
Knowledge curation is part of KM and involves taking existing information and making it more useful.
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