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KMSS03: KM trends and challenges as I see them

Christian asked KM Summer School 2003 organisers to reflect on key issues and challenges of KM based on our observations during last week. I believe this may be useful for a broader audience (and please don’t forget that these are my personal biased views 🙂

One trend I could observe is that “KM is about technologies” is not there anymore. We didn’t have to convince the participants about it. But it’s difficult to say why: we made the program without much space to talk about technologies and may be we just have not attracted “technology-oriented” KM crowd.

Action research is gaining momentum as research methodology in KM. It could be considered as a good sign, as action research allows better connection between KM research and practice. From another side, action research is still not widely accepted in academic circles that could lead to alienation of KM researchers who use it from “mainstream” research. I’ve got an impression that many participants liked the idea of doing action research, but I suspect that they are not aware that producing valid scientific results using action research requires a serious look at methodological issues and methods to be used. We didn’t have much discussion on this “practical” side of action research.

KM research challenges

Understanding how to make things work. Going beyond models and theories. Implementation. Acceptance by people. This brings the main research challenge – understand how KM initiatives could be connected to our everyday practices without being an “extra thing” or answering What’s in it for me? question (I’m so biased here, this is my own research focus 🙂

The related research/practical challenge is to understand emergent and self-organising nature of knowledge work and knowledge networks. I share beliefs of others that you can’t manage it, but I can also understand that in business context you need to do something with it. So, I would put it as understanding how to manage (=facilitate, or suggest better word) emerging complexity (still talking about KM context here).

Speed up learning curve for young researchers: it’s important to know the basics, but there is a need to go through them faster and join current discussions.

  • Getting rid of old models (everyone is starting from Nonaka SECI model and is loosing much time on it, instead of reading something more advanced or at least critics of Nonaka next to him).
  • Another observation feeds this – many of KMSS participants seem not to be aware of storytelling research, so they proposed and supported a “research proposal” to reinvent the wheel instead of going further.

Practice what we preach. Do KM in KM research community next to studying it. Build on results of others instead of reinventing them. Keep and eye on trends. Share and learn proactively.

Archived version of this entry is available at http://blog.mathemagenic.com/2003/09/18.html#a754; comments are here.

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