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Complexity and Knowledge Management Navigators…

Are you model-dependent?

Over the next four weeks I am going to speaking at KMAsia, K-Net and the European Training Foundation KM Seminar.  I thought that I would share with you the core of my discussion; all three talks will revolve around the idea of the ‘future of KM’.

My argument is that organisations exist as model dependent entities.  Everything the individual and the collective does within an organisation is either informed or influenced by a model; from the mental models the individual constructs to make a decision to the organigraph, a simple model that illustrates the structure of the organisation.  Managers and executive teams love models, from PEST/PESTLE/PESTLE(C) to SWOT, to Porter’s Five Forces, to Force-field Analysis, to Cultural Webs, to Lean, to Action Learning.

Take a look at the foundation of any knowledge-intensive organisation; the operational aspects of the business are built upon a simple model of input (transformed resources) applied against transforming resources to produce an output that then links back to the input process through a feedback loop – simplicity itself!  Consider the macro implications for KM…Information is the input, people then transform that information – with knowledge as the output, expressed through services or products – which is then assessed against the boundary requirements of the organisation.

Models, models, models!  We even persist with models when they are clearly not functioning correctly!  Take KM and Nonaka’s SECI model, it clearly is not an operational model for Knowledge Management.  It is an interesting conceptualisation of how KM could work, but it certainly is not an operational model to be applied in an organisation; for a start, the model is incomplete – it might tell us the ‘what’ of certain preconditions, but it most certainly doesn’t show us ‘how’ those preconditions work together to produce an outcome.  Regardless, many organisations persist with the model, reciting its mantra of Socialisation. Externalisation, Combination and Internalisation, patching over its shortcoming with their own ‘work-around’  – even Nonaka had to develop a work-around to SECI, incorporating ‘Ba’ – all the while believing in the core tenet that Tacit can be converted into Explicit knowledge, which I would strongly argue that it can’t.  A good model is said to be defined through its ability to pass tests, such as ‘Comprehensiveness’, ‘Correctness’, ‘Usefulness’, ‘Clarity’ and ‘Conciseness’.  I would suggest that SECI fails badly when assessed against these criteria; for those interested my argument for this is set out in other blogs, such as ‘Nonaka, the wonderful wizard of KM‘.

Now, if we can agree that organisations, and the individuals that make up the collective, are model informed/dependent, then we have to accept that KM will only ever be as good as the models that inform the process.  This leads us to the hundreds of models that are available to the organisation.  Which is the correct one to choose?  The wrong choice can lead to dissatisfaction and, while many will argue that it is dependent on the situated need, my argument is that an organisation needs a general model to work from, a high-level systems overview, through which they can develop evidence-based operational models as a response to that need.  To do this there is a need to understand and map the general preconditions for knowledge driven processes.  Here’s the scary thing; for four years we have coded and mapped the functions and dimensional constructs that inform KM processes in organisations – some of the findings have been made available in this blog.  We have then compared over 100 models against that coding process and none of them have met the preconditions of the four functions and twelve dimensional constructs that we have identified. In fact, on average, models are generally only 62.5% complete; this is a reflection of only one aspect of what constitutes a ‘good’ model and, if we can accept this, then we also have to accept that these models will provide a distorted output that could serve to disrupt the environment they are constructed to serve, contributing to failure and breeding dissatisfaction.  People can, and have, rightly raised the argument that their models are ‘proven’ to succeed, but they do not profess them to be general models and, as I have already argued, they are often ‘adapted’ to overcome deficiencies in their design according to the situated need.

This is not to say that we are right and everyone else is wrong.  This is us saying that actually there are too many incomplete models out there and, if we can agree that organisations are model dependent, then we also have to agree that a lack of ‘completeness’ when it comes to preconditions for KM systems will result in system failure.  Ultimately, we need completeness when dealing with KM.  Without digressing too far into the theoretical aspects of our field, the KM system is complex by nature, which, accordingly, requires an approach to optimise the whole instead of a reductionist approach that focuses on the individual variables.

What I am suggesting, and something we are working on with Perigean Technologies in the US,  is the need for the M-Model, a meta-model if you will, for KM.  A model that sews together overlapping theories, concepts and models to develop a single M-Model for KM system design.  We accept the argument that situated need of any given organisation will distort the intensity in the preconditions and the programmed response.  However, we also contend that the preconditions remain the same, what we are ultimately speaking of are general preconditions that are adapted at an operational level; think of it in terms of granularity and the pixels that inform the picture as a whole – the picture is clearer at the higher level of magnification and becomes more distorted at the lower level of magnification, regardless, the pixels combine to make the whole.

This blog, by nature, will never be able to cover off all the arguments that inform this debate.  Also, I accept that I am opening a can of worms here by suggesting that ‘incomplete’ models are causing system failure and probably dissatisfaction.  I accept that people will put forward evidence to support their personal models.  I am only positing that our evidence base suggests the a lack of completeness to be a core issue for the model-dependent world that exists within public, private and third sector organisations.

Well, that’s the core of my Keynote addresses…with a lot of evidence sprinkled in for effect…hopefully it is seen as engaging and stimulates though provoking responses…

14 comments on “Are you model-dependent?

  1. Cory
    October 22, 2011

    All models are wrong but some are useful. George Box
    http://en.wikiquote.org/wiki/George_Box

  2. Md Santo (@md_santo)
    October 22, 2011

    Hi David,

    Frankly speaking, I’m not model-dependent, but I’m really paradigm-dependent. Although my KM model framework seems prominent at all time in every argument, my KM model is just derived or generated from my Knowledge paradigm.

    My Human System Biology – based Knowledge Management (HSBKM) model framework indicating that human Knowledge is not the matter of “what we know”, but it is the matter of “how knowledgeable are we as human being” assuming that knowledge said to be evolved, as emergent property in complexity, and considered as CONSCIOUSNESS through perpetual interaction of 9 (nine) Knowledge components comprising of 3 (three) Human Knowledge components, 3 (three) Nature Knowledge components and 3 (three) Nurture (man-made) Knowledge system components / Knowledge Management (KM). Both of those 9 (nine) components mutually interacting each other. The interactions actually are (educational) psychology phenomenon toward Knowledge evolvement as well as Knowledge sharing mechanism – http://bit.ly/p2v2ON (link for the members of “MOBEE KNOWLEDGE CoP”) or http://bit.ly/pazNF8

    On the contrary, Knowledge said to be created and recorded / administered as Knowledge assets from various knowledge sharing activities, considered as FLOW , eg through SECI model (Nonaka and Takeuchi)

    So, I’m paradigm-dependent in which Knowledge is the matter of Consciousness (as “entanglement” phenomenon), not the matter of Flow (as thing)

    Md Santo – Founder http://mobeeknowledge.ning.com

    • David Griffiths
      October 22, 2011

      Hi Md Santo –

      I think, unless that I am reading this the wrong way, that you are demonstrating my argument – You have created the HSBKM model to map your paradigm; we can argue semantics as to whether this is paradigm or model dependent, but we cannot deny that you are building macro and micro models.

      Also, the point of my argument is that we too often accept existing models, with all their flaws (incompleteness), without questioning the governing variables that exist as their preconditions – is it a good idea to synthesise incomplete models in the hope that saturation (breadth and depth) will compensate for their vulnerabilities? I don’t know about you, but I think we have to start from scratch, examining the governing preconditions, and rethink our strategies based on the findings.

      You know me, I have said this to you before, a model is only as good as the evidence that informs it and the tests that demonstrate that it can be operationalised – anything else, like SECI, is concept building; leaving tests to others, who too often waste their time with flawed models. I think there is a responsibility on the part of the model builder, or knowledge creator, to expose all underpinning assumptions and test their model, exposing limitations in order for the KM field to progress. Grand theories that lack a stable foundation are stifling our field and we need to provide evidence based solutions if we are to offer credible solutions for the management of organisational knowledge resources.

      As always, a pleasure hearing from you…. David

  3. Glenn Behenna
    October 23, 2011

    Hi David,

    An interesting and enjoyable read. I agree with your view of the need to provide evidence based solutions!

    Glenn

    • David Griffiths
      October 23, 2011

      Hi Glenn – Thanks for that…Always good to hear from you…hope we get a chance to catch up sometime soon!

  4. Hi David,

    The Input > @$&^#*$&^ < Output model is fundamental, but I don't agree that the output is knowledge – or rather – I don't agree that the output should be knowledge. Knowledge is not the end in itself. I find in many specialized domains, the fit within context is lost amid the struggle to get enough understanding and support to be able to contribute. The focus becomes KM, instead of what KM is for in a given context.

    Have a meta-model, as you say, so very interested to learn of what you develop. I think it important to approach these challenges from a variety of angles.

    Meanwhile, off to Shanghai … any chance our paths may cross again?

    Cheers,
    John

    • David Griffiths
      October 23, 2011

      Hi John – I can see where you are coming from. The point that I was trying to make with the Transformational model is that information is the transformed resource and people the transforming resource – Knowledge is the contributing factor to the output…product or service based.

      Always a chance that our paths will cross — keep in touch and let me know if you are ever in Europe.

      Cheers…David

  5. Nikolay Kryachkov
    October 23, 2011

    Douglas Rushkoff has a slogan: “In the emerging, highly programmed landscape, you will be either create the software or you will be the software.” If to use this analogy, the question is – what is the language (meta-model) is being used to create the software.

    • David Griffiths
      October 24, 2011

      Hi Nikolay… Interesting analogy – models and frameworks seated within the sweet spot for the Knowledge Economy, as defined by the OECD, and contributing to the outputs of knowledge-intensive organisations.

      • Nikolay Kryachkov
        October 24, 2011

        Hi David, I would like to see an example of Knowledge Economy meaning valuation of knowledge and how this economy handles with non-separated (from persons) knowledge for investments, loans and other knowledge collateral issues.

  6. Pingback: Are you model-dependent? | Knowledge Sharing | Scoop.it

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