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I was recently speaking with someone whose background was all in business intelligence and data.   They had years of experience building data warehouses and datamarts.  They knew how to create cubes of data and slice and dice and store and manage all the financial and customer data you could imagine.  Because this person was from the "structured data" world, they just couldn't wrap their arms around the concept of knowledge management.  And we began a lengthy conversation about this abstract concept of knowledge management (KM).

Knowledge management -- the buzzword of decades past that might be synonymous with other buzzwords like collective intelligence or intellectual capital.  Or maybe you've heard of tacit and explicit knowledge -- differentiating between what is in our heads vs what's written down.  From a technology perspective, KM represents the mounds of documents, information, conversations, blogs, wikis, emails, social networks, knowhow, and expertise .... it's all the "stuff" that continues to overload us daily and continues to present challenges for individuals and organizations in filtering out what is important vs. what is just noise.   KM is also about the way we create, collect, manage, consume, share, and leverage the unstructured information combined with the structured data my colleague was so familiar with.  It's about learning, learning curves, and reuse - be it structured or social or organizational.   And KM can be also be about talent, innovation, revenue and costs as well...

Ultimately, KM is about individual, group, and business performance and providing a competitive advantage.  KM is also about adapting to change and managing it as the more you or an organization knows, the better decisions it can make and quickly recognize the need to change, adapt, and drive innovation.

As I explained and defined KM to my colleague and what this abstract buzzword KM is really about...he then said to me:   "Rich, it sounds exactly like what I've been doing for the last 2 decades with business intelligence... figuring out ways to collect, organize, structure, and mine data to help businesses make better decisions".    And the reality is my colleague was right.   BI has many parallels to KM... and at the end of the day it's all about being able to filter out the noise, identify all the variables in the equation, and make the right decisions based on what you know and assume to be true -- be it structured or unstructured.

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