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The Key to Knowledge Management and Innovation is Knowledge Flow: Part 1
The need to manage knowledge goes back literally as far as we can look. The very act of recording knowledge is what enables us to look backwards at all. Paleoanthropologist Adam Benton explains in his article, Why did prehistoric people make cave art?
“…cave art was an attempt to keep a record of species seen before, preserving the knowledge of them for when they returned.”
In his 1997 paper titled Knowledge Management: Where Did it Come From and Where Will It Go?, author Karl M. Wiig, explains the evolution of Knowledge Management.
“Early on, the focus [of Knowledge Management] was on concerns with how to make the most with limited resources. Later, the focus shifted to making clever products. Presently, advanced organizations focus on creating ingenious solutions and developing broad relationships to make customers succeed in their business.”
Wiig goes on to explain how Agrarian, Natural Resource, Industrial Revolution Product Revolution, Information Revolution, and Knowledge Revolution economies all applied the concept of knowledge management differently but with similar intent. He concludes that prioritization of knowledge management as a specific competitive advantage by corporations in the late 70s and early 80s was an inevitability.
In 1997, Wiig predicted what he thought would happen to knowledge management in the next 20 years.
“Similarly to what happens to other management directions that prove vital to enterprise viability, we can expect that KM — as an explicit and primarily stand alone management initiative — will disappear from view within a decade or two.”
We are less than two years from Wiig’s 20 year prediction and organizations still have Librarians, Taxonomists, and Chief Knowledge Officer. In fact, these roles are still increasing. It’s safe to say that knowledge management hasn’t yet dissolved into the organization quite like he predicted. In his defense, the Big Data revolution was likely not on his radar, which has exponentially increased the need for KM as an initiative, if not an imperative—and while Wiig was wrong in predicting the extinction of KM-specific titles, he was correct in identifying its importance as a core competency of an organization.
The Sharepoint Era
Capture & Categorize
SharePoint was released in 2001 and became the most popular tool for knowledge management in an organization. It was considered the first integrated and comprehensive solution for sharing information, files, applications and websites in the network. (Sharepoint); born out of a rudimentary idea: to simplify sharing documents.
To be truly effective, SharePoint is dependent on strict classification and procedural adherence to accurately describing assets and people. Taxonomy building and maintenance is necessary, as well as training.
Some 15 years into SharePoint’s existence, the data landscape has changed radically and companies are beginning to realize that there is a big difference between a document repository and knowledge management system.
A knowledge base is not just a document repository — it’s a body of knowledge that is continuously evolving. Knowledge consists of answers shared by experts, information hidden away in emails, ideas and feedback found in article comments and community forum discussions. — SharePoint vs. Knowledge Base Software
The governance of SharePoint sites across the enterprise is particularly poor at most companies. It is hard to get users to agree on a taxonomy, let alone standard vocabularies for tagging files to enable effective retrieval. Since the user community cannot coalesce on a communal approach to how content should be managed, they determine it is an IT problem to solve. — Déjà Vu All Over Again: Knowledge management is not an IT problem, but a challenge to the culture of an organization
It’s not an IT problem, it’s a flow problem.
A knowledge base is not just a document repository — it’s a body of knowledge that is continuously evolving. The future of knowledge management is about understanding and providing relevant and timely access to the ideas inside of a corporation’s information assets and allowing users to easily obtain, share, and apply that understanding.
For years the SharePoint approach has been showing cracks, but the the final straw is the explosion of data that we’ve had in just the last two years.
The Big Bang of Big Data
Unlocking the potential of Big Data is a puzzle for business executives and entrepreneurs, but also an opportunity. Large data sets and sophisticated analytics can create new products, enhance existing services, significantly improve decision-making, mitigate and minimize risks, and produce valuable insights about operations and consumer sentiment. — Big Data and What it Means
90% of the data in the entire world has been created in the last 2 years and the cost of storage continues to plummet. The result is piles of documents and a scale of information that the build-a-better-taxonomy approach simply can’t keep pace with.
Companies are now faced with a serious challenge. Do they invest more money and resources into better taxonomy building and better enterprise search? Or do they find a new way to leverage knowledge?
“The significance of Big Data to businesses, marketers, and the entire global economy is well established. One important caveat hasn’t been emphasized enough though: without strategic vision and careful planning, even a treasure trove of Big Data will only serve to distract business operations rather than drive business success.” — Big Data and What it Means
Having lots of data to analyze is exciting but it can also be a distraction. Early criticisms of Big Data analytics explain that while the available visualizations are interesting, they are failing to provide actionable insight. This is unsurprising. Big Data requires a different type of thinking.
“Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn’t fit the strictures of your database architectures. To gain value from this data, you must choose an alternative way to process it.”— What is big data?
Companies are quickly realizing that new approaches are needed to manage their data and how people interact with it. These new approaches are what comprise the next generation of knowledge management. So what are these new approaches?
Solutions are Getting Close
Knowledge Management in the enterprise is transitioning from iteration 2 to 3.
Iteration 1: Companies realized that knowledge management wasn’t just about document management and started looking at enterprise social networks and premium content subscriptions as a way to further expand and connect knowledge in the enterprise.
Iteration 2: Realizing that these systems in and of themselves are still deficient, tool and process optimization has happened around where these expanded approaches intersect. Mainly: expertise location, curation and publishing and enterprise search.
Iteration 3: Realizing that there is still room for improvement, companies are now aware that the integration of these efforts is just as important. Realizing that data analytics need to be able to be conducted by more than just data scientists, realizing that people need to find things they don’t know how to search for and that experts can be anywhere in the organization, they are looking to fill in the last bit of this diagram, Flow:
In Christian Buckley’s article, Build Better Knowledge Management, he identifies four things that next generation Knowledge Management platforms must do:
- Improve the distribution of knowledge and ideas, quickly and seamlessly
- Automatically identify patterns and themes within that content
- Expand upon, refine and convert that knowledge based on those patterns, and in context to our requirements, ultimately making it searchable (i.e. findable)
- Correlate those patterns and themes, and take appropriate action – with those actions also tracked and measured, as an extension of the idea”
This ideal solution doesn’t replace any of the circles mentioned above, but rather, sits between them, meaningfully connecting them. The bad news is that Buckley is speaking wishfully. Most companies have no such platform. The good news is, the time and technology is right, and they won’t have to build it themselves.
In Part Two of this series I’ll talk about the reality of a next-generation platform and how to develop a KM system that finally moves an organization towards using their knowledge instead of merely storing it.
This is the first post in a two-part series titled “The Key to Knowledge Management and Innovation is Knowledge Flow”. You can read the second post here.