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The disruptive future of knowledge management

In the next post we will be looking at the future of knowledge management (KM), specifically we will explore together the key tenets of what the field has to hold and how technology will change the role of the KM  practitioner.

Historical aspects of KM (some history nuggets that should be considered before reading on)

Three generations knowledge management

The following timeline showcases the three generations of Knowledge Management.

KM evolution is made up of three generations; there hasn’t been consensus on the third one and it´s not something that you will find in KM textbooks. However,  it is a picture of the reality surrounding KM at the moment.

  • It´s hard to pin-point an exact date for the beginning of KM. I personally like to refer to 1987 since in this year a very special book was published in England by Karl Sveiby and Tom Lloyd called “Managing Knowhow”. Although the term KM wasn’t used here it provided companies with a structured framework and business case in order to understand why organizations should start paying attention to their intellectual assets.
  • First generation KM was primarily IT driven and during this period we saw the rise of tools such as IBM´s Lotus Notes and the first Intranets (focus on information, not knowledge)
  • In 1995, Nonaka and Takeuchi published a book called the “knowledge creating company”. The Japanese authors warned KM practitioners that in order to drive KM success they needed to focus on people rather than IT. This advice would only be taken into consideration a decade later.
  • Nonaka and Takeuchi introduced the SECI model which became a cornerstone foundation for KM. Their approach meant that KM models should be looking closely at the way knowledge is generated within people in order to prepare a process to make knowledge generation and sharing much more easy (specially, in order to turn tacit knowledge into explicit).
  • Second generation KM was primarily people focused and looked to create processes based on Nonaka´s SECI model- how knowledge is generated, made explicit and socialised in organizations.
  • Following another 10 years we come to third generation KM and this is where something really interesting occurs. Going through the lessons learned obtained from many decades of work, third gen KM is founded on the idea of “going back to the basics”. What does this mean?

It means that KM needs to focus primarily on critical knowledge before investing in any tech solution or looking at specific actions. The reason I refer to 3rd Gen as C-Gen KM is because there are three powerful “Cs” present: Connectivity, collaboration and co-creation. In another post we will look at the underlying aspects of third gen KM but for the moment lets concentrate on some of the principal IT components surrounding the future of KM.

KM technology of the future (and right now!)

3rd gen KM doesn’t discard IT. On the contrary, it requires tech more than ever before. But what sort of technology are we speaking of? The specific tech that is made present in current times and which will definitely shape the future of KM are four forms of technology that combined will make a big difference in companies:

  • Cognitive technology
  • Robotics
  • Artificial Inteligence
  • 3D printing
What new forms of knowledge management technology are changing the way KM is done?

What new forms of knowledge management technology are changing the way KM is done?

This is the future of KM. Let´s dig deeper now.

Have your heard of IBM´s Watson?  #Watson is a system created by IBM that integrates natural language processing and machine learning in order to reveal insights from various data sources. In short, it is able to learn and provide solutions. If you are fond of Jeopardy, a very popular american quiz show, then you will probably remember the episode when Watson competed with human participants and won! In order to win, Watson combined two separate areas of artificial intelligence research with winning results. Natural language understanding was merged with statistical analysis of vast, unstructured piles of text to find the likely answers to cryptic Jeopardy clues.

How did supercomputer Watson beat Jeopardy champion Ken Jennings? (Photo source:

How did supercomputer Watson beat Jeopardy champion Ken Jennings? (Photo source:

So Watson in some way is able to replicate the human thought process in order to give meaning to the information it analyses. Powerful stuff for KM.

In fact, Watson is being used in medicine in order to provide expert advise to doctors who would have to otherwise undertake many hours or weeks of learning in order to correctly process information. For example there is a specific Watson solution for oncology in which doctors get  the assistance they need to make more informed treatment decisions. Watson for Oncology analyses a patient’s medical information against a vast array of data and expertise to provide evidence-based treatment options.

Watson-knowledge management

How is Watson helping the medical sector develop critical patient knowledge?

This new forms of cognitive systems that understand, reason and learn are helping people expand their knowledge, improve their productivity and deepen their expertise. In short, Watson is like an artificial brain. But a brain wont function unless it has a body and this is where advanced robotics comes in.

If we look at some of the advances in robotics, we find companies such as Boston dynamics that are capable of producing robots with amazing human movement skills. For example, one their robots “Atlas” has a humanoid form and possesses articulated, sensate hands which will enable Atlas to use tools designed for human use. Atlas includes 28 hydraulically-actuated degrees of freedom, two hands, arms, legs, feet and a torso.

Robotics in knowledge management

If we look at some of the advances in robotics, we find companies such as Boston dynamics that are capable of producing robots with amazing human movement skills

What would happen if these robots are plugged to a Watson like system? This is where cognitive technology and robotics give way to artificial intelligence.

If you got to this point, I am  sure that you might be thinking that this level of technology seems more sci-fi than reality. Just let me point out that this technology is already available and it is being used by a number of firms. You can even head down to the Watson portal, download the API´s and start using Watson at home!

Have you used 3D printing yet? I have, and I must admit it´s wonderful. I had second thoughts whether or not to include it as part of the tech that is changing KM, but I find it to be a powerful tool for tacit knowledge transfer. For example, two people working on separate locations can literally co-create prototypes as they share experiences and information. This means that you can touch and feel the outcome of the shared knowledge!

3D printing knowledge management

3D printing is a powerful tool for tacit knowledge transfer.

Not only can we facilitate tacit knowledge transfer this way. Virtual reality is also helping in this regard and with the recent advances in the field we might experience learning in a whole new manner. I would like to invite you to check out the HoloLens website so that you can see it for yourself.  Microsoft combined virtual reality with hologram technology so that users can actually interact with the objects they see. In this sense, imagine what a knowledge transfer session would look like using this tech! I´m very eager to try out!

Using the microsoft hololens to learn in space

Microsoft HoloLens (source;

So KM is finding new forms of technology as opposed to traditional IT that dresses in the form of Intranets, databases and social networks. The future in this regard is very exciting for KM and there and many things we can expect in the short term. KM practitioners will have to start learning about this technology and a radical shift in their future role is that they might be summoned to feed this systems.

However this doesn’t mean that we should forget the focus of KM. “Going back to basics” entails understanding first what knowledge a company should focus on as opposed to managing all of your company’s knowledge. This is not wise and very dangerous   as you might be allocating resources and time in order to develop knowledge that is not related to the company strategic plans or primary results.

So exciting times are waiting for KM. It would be interesting to discuss the use of this technology in companies (which is already happening as we speak). I am particularly interested in following the advances made by Watson in the medical field as it is rapidly impacting outcomes and providing doctors with a knowledgeable resource in order to take action rapidly.

© Jose Carlos Tenorio Favero

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11 Responses to “The disruptive future of knowledge management”

  • Avatar
    michael sequeira / Responder

    Nice one José

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    Giulio Groppi / Responder

    why “disruptive”? In my opinion a better qualifier could be “constructive”…

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    Shelley Coleman - Marsh / Responder

    Sure, but either way it makes for a lot more exciting ways of doing things/KM !

  • Avatar
    Lisa Miller / Responder

    Excellent! Everyone’s company has a wealth of internal knowledge that can be used to create content to humanize your brand and guide prospects.

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    Menno Mafait / Responder

    As long as scientists fail to define intelligence in a natural way, the field of AI and knowledge technology is engineering (specific solutions to specific problems) rather than a science (generic solutions).

    Scientists made a fundamental mistake 60 years ago:

    Intelligence and language are natural phenomena. Natural phenomena obey laws of nature. And laws of nature are investigated using fundamental science. However, the field of AI and knowledge technology is researched using cognitive science.

    As a consequence, knowledge technology is based on applying smart algorithms to keywords, by which non-keywords are ignored. Non-keywords provide information to our brain about the structure of the sentence. But by ignoring this structure provided by nature, the field of knowledge technology got stuck with “bags of keywords” and unstructured texts.

  • Avatar
    Menno Mafait / Responder

    Even Watson is unable to structure its own knowledge base. It needs raw processor power to find a “needle” in the “haystack” of unstructured texts. Like the rest of knowledge technology, also Watson is deeply keyword-based, having a keyword as output. The Jeopardy game version: “What is {noun}?” or “Who is {proper noun}?”.

    I am developing the world’s only self-organizing knowledge technology, by redoing the field of AI and knowledge technology largely from scratch, using fundamental science (algebra) instead of cognitive science (simulation of behavior):

    • I have defined intelligence in a natural way;
    • I have discovered a relationship between natural intelligence and natural language;
    • I am implementing these laws of nature in software;
    • And I defy anyone to beat the simplest results of my natural language reasoner in a generic way:

    It is open source software. So, everyone is invited to join

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    Janine Weightman / Responder

    What a fascinating read! I once dabbled in anarchy when I joined in a mosh pit and realised my bones weren’t built for that level of endurance so the prospect of jumping both feet first into ‘disruption’ as a KM practitioner is a thrill!
    I nodded extensively in agreement at your reference to the 3rd-generation KM going ‘back to basics and focussing on critical knowledge’ and the 3Cs of connectivity, collaboration and co-creation. I feel like the KM field is focussing on what really brings value to businesses and developing sophisticated and accessible technologies to advance our approaches. It’s a true match-making between minds and machines. I can’t wait to share this article with my organisation as it will certainly inspire. Thanks.

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    Mike McHugh / Responder

    This is an interesting post but, I have to say, it’s disappointing to me that KMI is hosting a piece showing evidence of memory loss regarding the pre-90s manifestations of KM.

    In the 80’s, knowledge-based systems (KBS) were all the rage; and I remember collaborating with “knowledge engineers” in eliciting engineers’ knowledge for one such system. I also conducted a KM feasibility study for a branch of the UK’s armed forces. At that time, the emphasis was clearly on trying to capture and replicate the knowledge held by people – with IT in a supporting role… no ‘focus on IT’.

    And, as part of my research for that 80s project, I discovered the early work done in the 60s on AI and robotics. So, I can’t see AI as being a characteristic of C-generation KM: that would be selective amnesia.

    So, it seems paradoxical that, in laying out the history of KM, KMers can reveal their own knowledge gaps!

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    Dave Tipping / Responder

    great post!

  • The Knowledge Management Civil War | Knowledge Management in Action / Responder

    […] collaboration technology have given rise to new tools that complement well with the fabric of KM (specially third gen KM). However this does not mean that by pursuing a tech solution KM will reach the desired results and […]

  • Avatar
    Eli Miron / Responder

    I think that “New hotizons for knowledge management” would be a more appropriate heading

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