What does it really mean to manage knowledge?

The term manage is used in almost every business application that contains content, yet the range of capabilities that truly perform a management function in these applications vary. Most content systems and knowledge systems store content effectively, but simply storing content isn’t managing it.

Think of this in terms of people management.

You may have a facility where people reliably report to their jobs and can be found. No one would say the building is managing these people. We should hold our content tools to the same standard.

So what does it really mean to manage knowledge? Just as in our simple example, it’s the people who do the managing, not the tools. Our tools provide us the ability to manage the content that forms our knowledge and the automation to manage more of it. Here’s my definition for what it means to manage knowledge:

Knowledge management is the implementation of systems and processes that actively expand codified knowledge, enrich and organize it for locatability, structure it for use in all channels, and maintain the full lifecycle including actively destroying assets which are ROT (Redundant, Obsolete, Trivial).

There’s a lot in there. Let’s break it down into four key parts:

  1. Expand codified knowledge.
  2. Enrich and organize it for locatability.
  3. Structure it for use in all channels.
  4. Maintain the full lifecycle including actively destroying assets which are ROT.

In many senses, these are just the principles of content operations applied to knowledge content. Let’s examine them one by one.

Expand Codified Knowledge

Codified knowledge is knowledge that is recorded in a sustainable way.

This means knowledge that is stored inside a system with the proper workflow, governance and other lifecycle tools that ensure confidence and correctness throughout the lifecycle. Knowledge recorded in collaborative wikis or in documents in enterprise content management systems typically don’t meet this standard because the lack of governance makes it difficult or impossible to know if the content is current, accurate, complete and approved.

A great example of codified knowledge is a procedure that has been created using structured content, which is stored in a system that dictates periodic review. The procedure would then be pushed out to other systems or provided via a fixed URL (or both) to ensure it remained the single source of truth.

The only knowledge which is reliable for the organization is properly codified knowledge.

An organization needs to actively work to expand this base of knowledge. Too often this doesn't happen. Many organizations take the crowd-sourced or open collaboration approach to getting knowledge into their knowledge management systems.

Another way to represent this is these organizations buy a tool (generally a wiki of some sort) and hope people will put stuff in it. This is a passive approach. It will yield some results, but they’ll be suboptimal.

To actively expand knowledge coverage, organizations need to create ownership with personnel whose primary responsibility is managing knowledge and clearly defined processes for everyone else who contributes. With these professionals properly empowered and equipped, an organization will see its codified knowledge expand consistently and reliably.

Related Article: Reboot Knowledge Management for the Post-Pandemic Workplace

Enrich and Organize It for Locatability

Notice I didn’t say searchability.

Search is just one part of the puzzle when it comes to delivering content to a user. Successful knowledge management implementations are able to provide a high-quality user experience to browse, search, and unrequested delivery.

The challenge here is that while search feels automatic (even though it’s not), organizing content for great browsing experiences very much is not. Perhaps a day will come when AI can organize our content for us, but it isn't here yet. People do this. So you must create optimal environments for these people to build and organize that content in. A foundation of strong practices and workflows for organization of content is essential to providing a really great experience.

Past browse and search, unrequested delivery is an underappreciated category. The concept is simple: deliver the user knowledge before they ask for it. In the simplest case, this is something like context-sensitive help, but with the advances we’re seeing in AI, it can be much more than that.

Learning Opportunities

In the near future, AI will be able to detect that a user has made a mistake or is having a problem before they’re aware of it. Your knowledge content will need to be properly enriched with metadata so that it can be selected and delivered to the user in this case. To be clear, this doesn’t mean AI will magically make this work, it means that AI will provide tools to implement these kinds of systems. It will still be up to the knowledge managers to use and manage them properly.

Related Article: (I Can't Get No) Search Satisfaction

Structure It for Use in all Channels

One of the core failures of historical knowledge management projects was using the library model. This is where a knowledge-base is created as a distinct digital place, akin to a physical library in the middle of a city. Users are instructed to go to that place if they want knowledge. For many reasons, this is a bad model.

A delivery approach uses a combination of web-publishing, integrations and content-as-a-service to put knowledge where users are. In order to make all of that possible, the knowledge management practice must be built on a foundation of structuring the knowledge content.

Users expect content continuity across all the ways they interact with your company, in other words, an omnichannel experience. And omnichannel experiences require structured content.

Creating a robust and scalable structured content practice for knowledge content requires the focus of a multi-faceted team. Knowledge management groups that decide to move towards an omnichannel approach will need to pull in content strategy specialists and technologists to work alongside them.

Related Article: Defining the Knowledge-Centric Digital Workplace

Maintain Knowledge Through Its Full Lifecycle and Destroy ROT Content

This is a big one. Maintaining knowledge content through its full lifecycle is undeniably challenging.

Having ROT content in your knowledge base is every bit as bad as missing important pieces of knowledge. ROT really covers two major things: inaccurate knowledge content and unnecessary content.

The danger of inaccurate content is easy to understand, as having any knowledge that isn’t completely accurate presents a risk. This risk may carry a substantial financial weight, regulatory risk, or it may simply erode user trust. The second case is more common because it’s impact is less acute, but that doesn’t mean it shouldn’t be treated seriously.

Knowledge bases are only as valuable as the trust users place in them.

Unnecessary content generally receives less focus, but it can be a significant threat to user experience. Unnecessary content clogs up search results and makes articles more difficult to read. When users find content that doesn’t help them, it can be worse than finding nothing.

After all, it takes more time to read something and determine it’s not useful than it does to walk away from a dead-end search.

Managing knowledge is the foundation of both employee efficiency and strong customer experience. Organizations that are focused on this effort will see a significant competitive advantage over their peers as the world shifts toward being fully digital-first.

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