Feb 7

Evolving from Knowledge-in-Storage to Knowledge-in-Use

I am often asked what are the innovations in knowledge management, what is new and different – and until recently I was not able to say much: it was more of the same, maybe a tad faster.  The problem was that the same old models and actions were used – it was not about technology being new, it was about not doing something different.  Knowledge has not changed much, honestly, so why should we do things differently?

Because the change has been in how we use it, not what we call it.

While there is a little bit of action in collective knowledge, social knowledge, and even tribal knowledge – this is not where the most promise is held.  True, those are all great sources and they definitely can alter the content, the knowledge itself – but the evolution we are undertaking it not just about the underlying technology to store more and search faster –it is about changing the paradigm, about changing perceptions, models, and ideas on how to leverage technology better.

I wrote last year that Knowledge Management is one of the three unsolved problems in CRM, but that statement can extend to any enterprise system that requires knowledge to operate (and they are becoming more and more).  This change in paradigm requires us to reevaluate how we approach knowledge, from creation to use – and this is where we see the biggest change: we are demanding to have the right knowledge available at the right time, the right place, and the right way – without searching.  We are moving from knowledge-in-storage to deploying systems for knowledge-in-use.

The problem with knowledge management, or at least the biggest problem, was never generating or storing the knowledge; I know of certain organizations that have tens of thousands of articles: how-to, manuals, technical specification sheets, data sheet, and varied other items stored for use by service, support, marketing, sales and even other functions that are not client-facing.  Storing is easy to do.

However, the belief that a simple indexing of the content by keyword would be sufficient to find the information later works for small, static knowledge bases, but as soon as they begin to grow, become part of a knowledge repository, a federated knowledge base, or with constantly expanding content finding by indexed words is no longer feasible (in some cases, it takes longer – but mostly the sheer volume prevents from finding the needed piece of knowledge at all).

Stored knowledge also decays rapidly.

For knowledge to be effective it needs to have two attributes: repeatability (the ability to be used time and again, not a single time), and accuracy (reflect the changes in the knowledge since its inception – even if small).  Stored knowledge becomes inaccurate almost as fast as it is stored and finding the same piece of knowledge twice in a large repository is almost impossible.  At the rate humanity creates knowledge these days knowledge becomes obsolete rapidly.  This is why we are witnessing a move from knowledge-in-storage to knowledge-in-use.

Knowledge-in-use refers to the ability to have the updated, accurate knowledge available immediately as needed and make use of it in the right setting, at the right time, for the right purpose.  The main difference between knowledge-in-storage and knowledge-in-use is the source: knowledge-in-storage has been in a knowledgebase for some time, likely, and found using an indexed search.  Knowledge-in-use more than likely comes from a SME (subject matter expert) or from a collective knowledge community, likely has not be indexed, and it is relatively fresh (in the vast majority of cases, produced to answer a specific inquiry and useful only for a limited time).

Moving to a model of knowledge-in-use requires the adoption and mastery of collective knowledge, a redeployment of processes, and a different mentality among users that not having a stored answer is acceptable, as long as the right communities and SME are part of the extended communities that are available to provide an answer.

The last benefit from knowledge in use is the speed to answer.  While simple inquiries are likely to be answered faster by a FAQ or a search box the adoption of knowledge-in-use is far superior for complex, real-time searches for knowledge.  In no event is a knowledge-in-use model going to complete replace the traditional knowledge-in-storage one for simple inquiries: there is no justification for this.  Alas, the best customer service organizations have known for many years to utilize different search and knowledge management techniques to answer questions.  This is no exception.

There is no preset model or methodology for an organization to adopt and embrace knowledge-in-use, but the first step is always the same: make sure it is the right approach for your organization.  If you find yourself updating the same articles time-and-again, or your entire knowledgebase seems outdated, or the information you manage changes rapidly – this may be the solution you are seeking.  Finding the knowledge in real-time, or near real-time, is not simple.  However, the results are outstanding.

Is this a model you are already implementing? Considering? Would never be able to do?

Let me know in the comments, looking forward to finding out more about how you use knowledge-in-storage and knowledge-in-use.

  • wimrampen

    Hi Esteban,

    I like the notion of “in-use”, although I think it’s probably better to talk of “knowledge-creation-in-use”. Yet knowledge-in-use works fine for me too ;)

    I agree that knowledge-in-use is about availability-in-(real-time-)context. On top I also think that knowledge-in-use should refer to the ability to co-create knowledge by actively combining different resources (text/video/audio) from different channels (blogs/social networks/knowledgebases/apps etc) and/or different actors (eg and SME) when the context requires it.. and then of-course bring it back to the knowledge-stock and allow it to flow where and when someone else needs it..

    Come to think of it.. we do this every day, just not very efficient. Providing knowledge-stock solutions does not cut it. The solution lies in understanding how people create knowledge-in-use (and context) and the jobs they are trying to do when doing so, and then fix in there what is not working..

    Now, replace “knowledge” for “value” in the above text and I get the feeling we are talking the same language. Don’t we?



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