I am currently working on two very different advisory projects; one with a government, looking at societal knowledge capacity building, and one with a membership driven organisation, looking at processes that are ultimately driven by a need to sustain and increase membership over the coming years.  We are using the same basic model with both and, though they are very different in almost every way possible, they share a common golden thread; they will start and be sustained by conversations.  So, for my 100th blog post, I want to reflect on this golden thread and my thinking from the past year…

For better or worse, I am a systems thinker.  I believe that we rely on good models to navigate the complex internal and external environments that organisations find themselves in; environments created by our actions and the actions of others.  I believe that even within complex environments there are disturbances (conditions) that exist, which, if not accounted for, will cause failure within the system – read my blogs and articles on the importance of HR for an example of what I mean here.

I believe that the system has to respond to variety in the environment with variety in the system design; that means we also have to analyse the cost for not acknowledging distortions within the system that require our response.  This can be analysed through Failure Mode and Effects Analysis - dissatisfaction with KM, anyone?

I’ll use HR as an example again:  We know that organisations transact in a Knowledge Economy; we know that this is driven by innovation (products or services); we know that people are key to that process; therefore, how severe will the system failure be if we do not acknowledge HR strategy, policy and processes within the system then we have to accept that the system is open to failure.

One of the most interesting ongoing debates that I have engaged in over the last two years has been my opposition to the techno-centric view of KM; the view that KM should be exclusively about the collection, collating and presentation of knowledge resources to inform the decision-making process. We are sold  on the idea that KM can enable the decision-making process; governed by algorithms that determine the media presented to us (see variety amplification and also ‘availability heuristic‘), software decides what we see, making us reliant on the skills of the designers and programmers to ensure that we receive the right information – it could be argued that we are being tightly coupled to a centralised view of the norm.  There are lessons from history here: Centralised decision-making was attempted in Chile (Project Cybersyn) by Stafford Beers in the 1970; he failed and retired to Wales – some would say that he couldn’t finish the project due to the government being overthrown, but in reality, his grand design for centralised decision-making was flawed.  The problem with centralised decision-making is that it attempts to control deviation from the norm and all too often misses local intelligence (variation) that is crucial to the decision-making process.  Some will say that it is about distributed decision-making and getting the right information to the person at the coal face to enable the best decision based on the best available intelligence – I would love to know how many organisations actually enable that level of distributed decision-making; in my experience it is usually more about centralised control.  The information has to be ‘sorted’ or prioritised in order to suppress information overload (variety attenuation), which takes us back to the dependence on the software that serves us and the amplification of the right information. Then the real problem emerges; the system is only as good as the information available within the system…and surprise, surprise, we are back to people!

People, complexity and decision-making….I’ve heard the argument that 911 could have been prevented, this was widely discussed in Taleb’s book, ‘Black Swan’; if only we had planned for the potential of the outlier…in one example, we might have removed cutlery from aircraft that could potentially have been used as a weapon in a hijacking.  Now, in hindsight, what do we do, remove cutlery from the system and in doing so, lower the risk of a similar event.  The problem is that we don’t seem to respond to all the anomalies within the system, even when we know the potential consequences.  For example, I recently flew out of Orlando airport and Outback Steakhouse (a restaurant in the departure area) provides you with an ineffective plastic knife and fork for you to eat your steak with (broke the knife twice!), no problem, we’re lowering the risk in the system – lessons learned and all that.  Except, if you fly business class, which I’m sure no respectable terrorist would ever think to do, you are provided with metal cutlery on board the aircraft – obviously people who pay for a business class ticket are far too civilised to think about hijacking a plane!

Rant over and back to the point of the blog…

Software solutions require people to input what they know into the system and as such they exist as a barrier to this ‘ideal’ when it comes decision-making processes; pure and simple, people decide when and if they will share what they know. Ultimately, decisions are all too often influenced by the ‘affect heuristic’; how do I feel, do I like it or not?  Evidence goes out of the window and the decision is taken on a feeling.

Where am I going I hear you ask…  People ARE the system; they don’t exist outside the system, they are the lifeblood of the system and connecting people is core to the KM process.  In both the projects I mentioned at the outset of this blog, we are working to get the various parts of the system talking to each other; the operative word being, talking.  The solutions both organisations seek already exist, they just don’t know it because the system is fogged.  Simple conversations defog the environment, existing component solutions that can then be adapted for the whole become apparent and organisations save money.  Am I oversimplifying a very complex process?  Perhaps, but ultimately, in my experience, every KM project we have been involved in has relied on the power of conversation.  And you know something, I would wager that the initial conversation, the crucial decision-making point of the project, was driven by the affect heuristic; evidence is often secondary at this point – do you like what is being proposed to you and, even more so sometimes, do you like the person who is ‘selling’ the proposition.

Can it be that the success or failure of what we do is actually driven by a single feeling in a single moment of time?  Do you think we scenario plan the impact of that decision at that time?  We make fundamental decisions every day based on a gut feeling of like or dislike; we are human, we are fallible and we have to ask whether that will ever change?

Reflecting back on this past eighteen months, the keystone for what we do is conversation, whether ‘selling’ solutions or passing on our insight into the complexity of this phenomenon we call KM.  The heart of what we do, how we think, is captured in the KM M-Model, but, when all is said and done, the keystone to any solution we have offered has been built on defogging the system and enabling conversation.

Concluding this 100th post, I want to return to a question that often comes up; ‘how do I sell KM?’  Well, it starts by understanding the needs of the organisation, the needs of the individual and the processes that bind the two together – we built the M-Model to help stimulate that thinking.  The rest, well that comes down to your ability to sell the challenge and the solution; and for that you need powerful conversations.

They certainly don’t solve everything, but they certainly help!

Whenever I speak at conference or organisation events I often get asked for KM solutions; my favourite, ‘what’s the solution to KM?‘, which often leads to, ‘the problem is that we can’t sell it to top management‘.

The problem is that the the question is FUQed and we will never get the answer to it!  What am I talking about?  A Fundamentally Unidentified Question; think about this, how do we stop global warming?  The response is far too complex to be framed within a short intelligible answer; for me, answers to these monolithic questions are governed by the Law of Requisite Variety and, as such, are FUQed:

Take a look at the external world (KM), then look at the cues that require response, then look at the conditions required to respond to the cues, and then we can understand the variation required in the solution – or, “Only variety can destroy variety” (Ashby)

Now, bringing it back to KM, too often we miss the cues and the required conditions; I’ll explain…

I’ve been reading a book by Daniel Kahneman lately, ‘Thinking, Fast and Slow‘, and it signposts some of the fundamental flaws in our way of thinking that, when you reflect on it, could be contributing to the challenges we face in developing KM solutions.  First, let me start with a question and response from his book:

An individual [in the United States] has been described by a neighbor as follows:  ‘Steve is very shy and withdrawn, invariably helpful but with little interest in people or the world of reality.  A meek and tidy soul, he has a need for order and structure, and a passion for detail.’  Is Steve more likely to be a librarian or a farmer?

Kahneman’s argument is that the vast majority of us would say that Steve would best be suited to becoming a librarian. However, the ‘facts’ behind the question suggest otherwise:  Apparently farmers in the US outnumber librarians 20:1 and therefore, though Steve might well be better suited to becoming a librarian, the data suggests that there is more of a likelihood that he will become a farmer.

Now, I realise that we can be critical of the question, discussing the cultural issues, motivation or capability that will ultimately guide Steve’s vocation, but what is being suggested is that our decision-making process suffers from the ‘availability heuristic’.  We are not given the whole picture and too often we give focus to the choices of others.  The questions we pose for ourselves, or, in this case, our field, are developed against a set of biases that are often informed by the information that is made available to us; think about what you consider to be the biggest challenges to world stability today and your decision-making bias will probably be informed by media focus and the choice of topic that is broadcast to us.

Back to KM…The same could be said for our field.  Look through the literature, explore it thoroughly.  Solutions and problems are abound, but all too often, as in the case with Steve, we don’t look at what sits behind the problem – we see the presenting issue, but, perhaps, we don’t really understand the problem.  How much of the literature out there actually talks about the drivers for the concept?  Where is the ‘down and dirty’ discussion on the drivers for organisational KM strategy?  What I am talking about here are the discussions on the environment, the Knowledge Economy and its related complexity.  That literature, I would suggest, is too few and far between.  Yet if we don’t understand this then we are missing the cue that requires a response; we then have a gap in our thinking; we missed one of the preconditions for the ‘solution’, that Holy Grail for conference goers all over the world.

Why does this happen?  Not only that, why, given this apparent gap in our thinking, do we decide to engage with KM in the first place?  Why do we fight the good fight to get senior management to engage with the concept, only for someone ‘up there’ to make a decision against our KM projects based on what, a feeling in his or her water on that particular day?  Welcome to the ‘affect heuristic’!  The argument being that ultimately decisions are taken with little sound reasoning at times, purely driven by a feeling of ‘like’ or ‘dislike’.

Where am I going with this?  Put the three points of discussion together.  We too often ask the wrong questions, questions that fundamentally cannot be answered.  We need to understand the preconditions in the environment in order to combat the variety associated with complexity (variety destroys variety).  KM literature appears to impact the decision-making process through the availability heuristic; we don’t often talk about the variety or environmental complexity that can really guide the solution.  This all comes together for the ultimate decision makers, who, perhaps lacking information, get a ‘feel’ for KM and decide they don’t like it; the affect heuristic.

Do we just give up?  No!

If you want to understand the solution to KM, then you have to understand the drivers for KM; from there you can begin to grasp the variety required in your response (take a look at the KM M-Model).  From there, hone your question, provide the right information for the decision-makers (combat the availability heuristic).  Next, hone your argument; align your thinking to sell the concept in such a way that it aligns with organisational needs – speak to need and demand and impact the affect heuristic.

Good decisions need to be informed decisions…hmmm, sound like one of the objectives of KM, to improve the decision making process…maybe we need to practice what we preach.  Perhaps then we wont find KM to be so FUQed.

Download the pdf here: K-Net_article

The KM M-Model has now been released with free access:  Click this link for open access to the KM M-Model web page - it can also be downloaded as a pdf (Note, this is v1.0) here:  The KM Meta-Model

The M-Model is presented using a concept mapping format; it sets out to examine what drives KM, the way in which those drivers impact an organisation and, from there, the constructs that a well designed KM function will need to consider

This tool has been designed by K3-Cubed and Perigean Technologies and is offered free of charge – the M-Model represents over 1,000 hours of research and design time, with much of the underpinning research published by the authors in academic and professional journals – to say nothing of the number of organisations, across sectors and geographic locations, that have contributed through their engagement with us.

The M-Model does not set out to provide a definitive solution for practice, the field is far too complex for that, and it will continue to evolve as part of an ongoing process.

We hope that the model stimulates your thinking and, maybe, changes your perception of what KM is actually about.

Please, get in touch and let us know what you think:

David Griffiths: david@theknowledgecore.com

Brian Moon: brian@perigeantechnologies.com

or just leave some feedback on this page.

***Model has now Launched – Jan 1st 2012 – Happy New Year!***

Jan Update – v1.02 (19.01.12) Now live

Please note:  This model will be made available at no cost as soon as the testing phase has been completed – access will be via a password allocated by K3-Cubed or Perigean technologies.

Over the past few months we have been working with Perigean Technologies, our strategic partners over in the US, to produce a KM M-Model for organisational learning and knowledge.  The model is not designed to be a KM solution; it is designed to stimulate the reflective practitioner/manager and, in doing so, identify areas within a complex environment that might be being neglected in existing practice.

The M-Model examines what drives KM, the aspects that it impacts in an organisation and, from there, the constructs that a well designed KM function needs to consider

The model is in beta format at the moment and we would be interested in hearing from anybody who would like to get early access, explore the model and, in return, provide us with some feedback – use the feedback form on the right hand side of this blog to get in touch.  We are limiting this test to 20 people and so please do not be disappointed if you do not make this first call for testing – we will expand availability as we acquire and address the initial feedback.

KM M-Model by David Griffiths & Brian Moon is licensed under a Creative Commons Attribution-NoDerivs 3.0 Unported License.

I recently had the pleasure of a conversation with Laszlo Balkanyi, a KMer from Sweden.  Aside from being highly knowledgeable and engaging, he reminded me of a piece of work that I had somehow forgotten about…one of those things I believed to be useless years ago that became enlightened in the context of our discussion. Laszlo was talking about a job interview and how he approached the classification of knowledge within a KM framework.  He cited the work of Jorge Luis Borges and his list of Animals, from the `Celestial Emporium of Benevolent Knowledge` in which it is written that animals are divided into:

1. those that belong to the Emperor,
2. embalmed ones,
3. those that are trained,
4. suckling pigs,
5. mermaids,
6. fabulous ones,
7. stray dogs,
8. those included in the present classification,
9. those that tremble as if they were mad,
10. innumerable ones,
11. those drawn with a very fine camel-hair brush,
12. others,
13. those that have just broken a flower vase,
14. those that from a long way off look like flies.

This classification has been used by many writers. It “shattered all the familiar landmarks of his thought” for Michel Foucault. Anthropologists and ethnographers, German teachers, postmodern feminists, Australian museum curators, and artists quote it. The list of people influenced by the list has the same heterogeneous character as the list itself.

So, where does this link to KM enlightenment?  It’s all about order and control…

What strikes me about our field is that we are constantly attempting to classify it.  I understand why we, as human beings, need to bring structure and order to that which we do not understand.  We combat ambiguity through familiarity and what better way to understand a nebulous and domain, such as KM, than through structure and order – enter advocates for taxonomies!  The problem, as beautifully illustrated in the work of Borges, is that our domain is dominated by context.

People in the KM field have been working for years on a KM taxonomy, but, as suggested by Borges, it is fraught with what appear to be insurmountable challenges; just look at the diffuse nature of the language we use to describe our field and the understanding that underpins that language.

First, have a think about this:

“…talking in the wrong language, or in too many languages rather incoherently, or in not enough languages… One way or another there’s a re-examination needed here, and I’d suggest we cast a harsher critical eye over our sloppiness, assumptions, half-baked metaphors and undigested analogies” (Ward, 2010)

Then, think about the breadth of KM practice that needs to be influenced, not just in terms of job sectors, but in terms of cultures.  We can catch an insight into the challenges by analysing the work of published authors, such as Holsapple & Joshi, two North American writers who attempted to construct a framework in 2004.  They attempted to address the need for a common language for the KM field, with a stated goal to provide, “a common vocabulary and frame of reference that can enhance the communication and sharing of ideas among practitioners” (p. 609). However, their approach, much like the highly contextual taxonomies that flood the KM-a-sphere, appears to have been flawed.  They employed an approach to the development of their framework that involved 31 of the most recognised theorists and practitioners in the field (including: Larry Prusak, Karl Sveiby, David Skyrme and Karl Wiig). The goal was to develop a unified language for the field, but the panel was biased towards “Northern Hemisphere” practice, with only one representative outside of a European-North America axis, coming from Australia.  Their classification appears to have died a quick death – do any of you use it?  This leads to the question of how a common language or taxonomy can be produced without representation from the wider global community?

So why do we keep trying to do this?  Perhaps it just goes back to Homo Faber, our basic need to bring order and structure, to demonstrate our intelligence as human beings through tools or models to explain the tools we use.  Who knows.  What does appears to be clear is that Pandora’s Box is open, the field is far too mature to attempt to control it now and, until something else emerges, we are going to have to get comfortable with ambiguity or heterogeneous networks where people enroll into belief systems that numb their uncertainty.

This is a Google translation of an article written for the German Community of Knowledge website by Ingo Frost and Kathrin Frank.  I would like to thank the authors for including me in their research and I am just happy to share our work and ideas with the wider business community.

Visionary knowledge management: Trends and Strategies

12th December 2011 by Ingo Frost , Kathrin Frank

The authors of this article go to the question of how organizations in 2020 to deal with knowledge. For this they have analyzed in a first step, national and international knowledge management conferences, publications and Internet publications to locate knowledge management visionaries. There are four visionaries are noticed because of your keynotes and their publications on knowledge management trends: David Griffiths, Dave Snowden, David Gurteen and Norbert Gronau. They are presented here together with their theories and visions for dealing with knowledge. At the end of these theories are compared and discussed.

Selection Process

How to find the interesting theories about how knowledge management could evolve? One way to come closer to this question is to examine knowledge management conferences and find out who has kept the keynotes to knowledge management developments. These nationally and internationally significant knowledge management conferences, the keynotes were considered from the years 2010 and 2011. Of the 105 keynotes 10 authors have explicitly addressed by knowledge management trends. The work of these authors has been examined in the second step, further scientific publications on the subject and on their interactions with the Internet community (for example, activity on blogs, newsletters, etc.). Here, the four above-named persons are particularly noticed something out of the research, depending on other perspectives on knowledge management and support others in their daily process of implementing knowledge management in practice.

David Griffiths

David Griffiths teaches at the University of Edinburgh in the field of learning and knowledge management and knowledge management is the founder of the consulting K3Cubed Limited. He has specialized in supporting organizations in dealing with knowledge and learning, lectures and talk about the topic to publish.
In teaching, he also deals with related issues concerning organizations, financial and production management.

Visions – theses about knowledge management trends

• Knowledge management is according to an international study technology still centered primarily understood and more operationally, and is still not the people at the center. This is the reason that there is a high level of dissatisfaction with knowledge management investments.
• Who wants to support organizations in dealing with knowledge should give up the technically inclined term knowledge management. Recognize organizations for other than technical challenges of knowledge management.
• Knowledge management should be seen as a strategic issue and support organizations in their current challenges, such as innovation, resilience, sustainability and growth (or even “healthy shrinking”).
• Knowledge management should be the heart of building the capacity for change. This can be stimulated and thinking forward-driving techniques such as scenario analysis can come to train.
• Knowledge management can drive needed impending paradigm shift in organizations.
• The role of knowledge in organizations is rising steadily since the 30s (the importance of intangible resources in organizations has grown from 30-40% to 90% with IT companies such as Google). Taking into account the long-term trends knowledge management can be defined as long-term task [1].

Dave Snowden

David Snowden, John is an expert on implicit knowledge and works as a lecturer, consultant and scientist. He is a visiting lecturer at the University of Pretoria, University of Canberra, University of Surrey and at the Polytechnic University of Hong Kong. In addition, Dave Snowden is the founder and scientific director of the Cognitive Edge Consulting Organization, which pursues an open-source approach to counseling: Materials and methods are freely accessible via the website. He has developed the Cynefin framework, which transmits the practical application of complexity theory to the topic of leadership in organizations.

As part of the Cynefin framework, problems are classified according to their nature and suggested an appropriate use of them:

• Simple problems based on clear cause-effect relationship: If a given initial situation is observed to take place on the basis of experience (“Best Practices”) an appropriate response.
• For complicated problems must be analyzed more intense situations before they can be responded to. There are often several ways to respond, which are similarly good (“Good Practices”).
• Complex problems are characterized by the fact that due to an initial situation, the effect of certain actions can not be predicted. Is thus viewed as an experimental approach to action (“try out, perceive, react”) proposed (“Emergent Practices”).
• Chaotic problems are such that no cause-effect relationships can be established. Thus, the recommended action is to act, perceive, react with the aim to stabilize the system. This experience created the sense of “practice novel”.

Visions – theses about knowledge management trends

• In the context of organizations should be distinguished from robust stable strategies: robust design (fail-save = drop resistant) should (save practicing safe-fail experimentation = fall) to be stable and thus krisenresistentem design.
• The management of knowledge is always voluntary and may never be enacted.
• We know only what we need to know. We react to perceived patterns (pattern-based intelligences), and no information processors (information processors) are.
• If there is a real need for knowledge, very few people will refuse to share their knowledge.
• Tolerated failure shapes the learning process better than success: Organizations should accept failure in a particular context.
• Talking about our knowledge is something other than our own knowledge
• We know more than we can put into words and tell us more than we can write down.
• Everything is fragmented, chaotic people seek connection (messy coherence) and just not too much structure, since it is quickly outdated and costly to maintain. Thus, the approach Semantic Web – that is a clear, structured description of importance of Internet content – limited. [2]

David Gurteen

David Gurteen has long been the software development manager and was with Lotus Development to ensure a uniform design of the Lotus products globally responsible.
Today he is an independent knowledge management consultant, speaker and moderator. He is in various fields of knowledge management present and organized regularly Knowledge cafes. He publishes on his blog (The Gurteen Knowledge Weblog) and on his website (The Gurteen Knowledge website) and reached its newsletter (The Gurteen Knowledge Letter) about 15,000 people.

Visions – theses about knowledge management trends

1. The sharing of knowledge and social learning – now perceived as extra work – is a welcome and normal part of everyday work. Ponder the future workforce is no longer alone in my room, thinking aloud and jointly with others.
2. Also work no longer takes place behind closed doors, but transparent and visible to everyone.
3. Instead of forcing the employees IT tools, they select themselves out of the tools that would be most useful. Likewise, we will select the information that you need, instead of allowing themselves to heap indiscriminately with everything.
4. Instead of controlling the people for fear of making mistakes, they get more creative freedom, and must bear more responsibility in return.
5. Information is no longer concentrated and “protected”, but is open and accessible. The information flow is less regulated.
6. The importance of context is more pronounced in the foreground. Rather than in isolation as information to examine the context, the flow circumstances / conditions more into consideration.
7. The world is perceived as complex and varied. The simple cause-effect model has become obsolete and will have to give other approaches. [3]
8. In today’s wealth grows at the (publicly available) information faster. It takes some time but mostly to understand the often complex and sometimes chaotic situations. Often helps to talk to others to make the many factual knowledge something useful – a methodological approach to this is the Knowledge Cafe. [4]

Norbert Gronau

Norbert Gronau studied mechanical engineering and business administration at the Technical University of Berlin. He completed a doctorate on the “concept of a strategy-oriented management information system for decision support in production management” and habilitated with the theme “Sustainable industrial information systems architectures for organizational change.” He holds the chair of computer science and Electronic Government at the University of Potsdam. His research interests lie in the areas of operational knowledge management and versatile ERP systems. He is also scientific director of the Potsdam institute settled Center for Enterprise Research (CER).

Visions – theses about knowledge management trends

1. Currently no organizational assignment of responsibilities typical of knowledge management in the organizational structure of enterprises is evident.
2. Competence and experience of people can not be replaced by the use of computerized systems. Still can not provide the necessary creativity and intuition.
3. In the area of inter-organizational issues of information security and protection against theft of intellectual property rights as major drivers of change have been felt. The assurance of intellectual capital is the task of knowledge management.
4. With the increasing popularity of social media in their private lives and in the company’s internal and external use, there will be more experiments with Web 2.0 technologies and approaches, and remove the uncertainty about social media use in organizations.
5. The bandwidth of the demand for knowledge management is significantly larger. More and more companies and public institutions is clear that the knowledge of their employees is a central element for competitive differentiation and represents the key to successful change is.
6. For the exchange of knowledge between institutions-personal knowledge, there is support suitable conversation and transformation in organizational forms and spaces and times must be supported.
7. Conversion pressure and demand of the employees generate new demands on IT. IT is insufficient competition threatens to fail by the knowledge holders. [5]

Discussion
Is perceived – David Griffiths shows that managers with knowledge management is less important – but also more technically oriented. Knowledge in organizations takes on an increasingly larger role, becoming a strategic issue.
Dave Snowden brings a different perspective: Best Practices – a standard method for experiential knowledge – only works for simple problems. Complex or chaotic situations require a different approach: first try, then act and react at the end. He points out that existing structures do not help to address the issues and a climate that is more important, the failure must be allowed for.
David Gurteen states that can be complex or even chaotic situations most likely to work through personal interviews: these must be created for such opportunities.
Norbert Gronau finds that the range of knowledge management is much larger: in addition to social media, intellectual capital and the pressure change in the IT context plays an important, new role.
David Griffiths also emphasizes the role of knowledge in connection with the conversion ability. From the perspective of an organization to its environment changes rapidly and unpredictably – among others due to various crises at the national and international level. Therefore assumes an important role versatility. Knowledge in turn is the basis for organizations to change, because change can be better estimated with the common knowledge of all employees. If their knowledge and creativity used, new approaches – and thus sustainable innovations – the first place.

Literature

[1] David Griffiths: The future of KM (7 / 2011) – theknowledgecore.wordpress.com/2011/07/16/the-future-of-km

[2] Dave Snowden: Judgement & resilience, KM Asia November 2010 Keynote – www.cognitive-edge.com/presentationdetails.php

[3] David Gurteen: World 2.0, in: Gurteen Knowledge: 10 Years in KM, 2010
gurteen.com/gurteen/gurteen.nsf/id/gk10km

[4] Elizabeth Wagner: The Gurteen Knowledge café for David. In: Project Magazine, Issue 21/2011

[5] Norbert Gronau: Challenges and trends in knowledge management (KnowTech 2011 – Keynote, Bad Homburg)

I am always looking for books or ideas that challenge my way of thinking. A recent read got me reflecting on a popular argument around the idea of ‘Best Practice’ – I’ve touched on this before, but some of the discussion from Tim Harford’s book ‘Adapt’ gave me reason to pause and revisit my previous blogs…what follows is not necessarily from the book itself, but is, in part, inspired by a good read.

The need for best practice will vary according to the knowledge intensity of the organisation’s outputs; think Coca Cola’s production facilities versus their R+D function. One is based on standardisation and minimal deviation from the norm (based on complicated, replicable processes) and the other is immersed in complexity, ambiguity and experimental approaches. The first, you may argue, is prime territory for ‘Best Practice’ the latter, less so. My argument: perhaps it is actually time to eradicate the term, ‘Best Practice’ from the business lexicon.

We are always looking for better products or services; quicker, more efficient ways (cost optimisation) of doing things (Lean/Six Sigma?).  The premise being that Best Practice attempts to limit variety in the environment to a standard way of doing something – eliminating waste and error from the process…doesn’t error bring about evolution and waste; and do you mean the time and space needed to effectively collaborate (I am, of course, being inflammatory)?  MBA graduates indoctrinated in the ways of Taylorism preach the mantra of efficiency, order, structure and the one best way. How about a spanner in the works: What about human and/or local challenges that require variation in the process?

The problem is that an organisation’s ability to evolve (to meet the needs of its environment survival of the fittest), informed by its adaptive capacity, itself informed by its dynamic capability, emerges from need/demand (again, from interaction with the complexity of the knowledge economy), requires an engagement with variety.  This leads to issues of complexity and the idea of Complex Adaptive Systems (follow the links for previous discussions in this area).  However, Best Practice appears to run contrary to the evolutionary process.  It seems to emerge from a natural human instinct to bring structure and order to our world; to replicate what we know already works. This can be traced back to philosophy and the idea of Homo Faber: Man the creator and man the wise, where man looks to control the environment; referred to by Henri Bergson (The Creative Evolution, 1907), where he stated that intelligence emerges through man’s  “faculty to create artificial objects, in particular tools to make tools, and to indefinitely variate its makings” -  the idea links to previous blogs where I have discussed the idea of the person human, and, as such, organisations, being model-dependent. What I would also suggest is that the more ambiguous, the more abstract the environment, the harder we seem to work to model, organise and structure that environment.  We look for patterns, fill in the gaps and build models that allow us to ‘recognise’ this world we are sensing.  Best Practice appears to respond to this primal need to bring order, but, even when looking at standardised processes, are we fooling ourselves – much in the same way that our brain fools us into ignoring our own blind spots in our senses; where the optic nerve exits the eye.  The problem is that if you subscribe to the idea of the organisation as a Complex Adaptive System then you also subscribe to two key dimensions: The human dimension and the local dimension. Why is this a potential issue?  I’ll give you an example:  In every organisation I have ever worked with, where there is a focus on Standard Operating Procedures, I have found local ‘work arounds’ – local procedures that work around the standard procedures set out by a centralised management function – these procedures often exist under the radar and, when they surface, are suppressed by the centralised approach to management…you wouldn’t believe the number of organisations that ignore feedback from their own people; people who are distanced from the strength of the centre and add unwanted variety to the organisation’s ‘one voice’.

Moving on…We need to understand that variety is critical to progress or evolution.  Some of the best inventions, products and services, have spawned variations on the theme – some work, some don’t, but the environment (in this case, customers) reward the strongest and condemn the weakest to the business scrap heap.  Take Apple’s iPad, how many variations are we now seeing on the market; how many are successful; how many fail (evolution and survival of the fittest) how many are moving the market forward; how is this forcing Apple to respond? Is this any different with highly standardised processes?  We are always looking for financial gain or competitive advantage through the optimisation of standardised processes; does a Best Practice approach really encourage or satisfy this need?  We need to encourage experimentation bound by the needs of the organisation, people and the local context.  We can give examples of existing practice, but perhaps that is where we should stop. Perhaps the answer is to respond to the need to evolve existing products/services/processes by allowing what exists to evolve, not replicated.  Peter Palchinsky suggested there to be three principles for engaging with complex environments and the resulting demand for an interface with variety:

1. Seek new ideas and try new things (Variation)
2. Scale failure so that it is survivable
3. Feedback and learn from mistakes (Selection)

We need to accept that Best Practice methods rarely, if ever, allow for the variety needed to fuel the navigation of complex environments.  We can be bold and dare to deviate from the norm, or we can tread the beaten path and follow others into obscurity.

We are social beings who come together through networks to form collectives.  These collectives can be static or dynamic.  What are we interested in within these networks and why?

Organisations have environmental load placed upon them that require them to become more adaptive, to innovate; whether speaking in terms of services, products or policy in the public, private or third sector.  This demand brings us to look at the networks that people create, how they use them and what it potentially tells us about their capacity for innovation.

People say that network size, the number of people an individual can keep contact with, is restricted by neocortex size.  This often leads to discussions of Dunbar’s number, being 148, which is often rounded up to 150 – the theory being, with a 95% confidence level, that we as humans can only maintain relationships of up to 150 people – the confidence interval actually gives us a range of 100-230.  Dunbar’s research has actually been challenged by Bernard & Killworth, who propose that our capacity for network relationships is more in the 230 range, or as high as 290.

So, we potentially have a large network of people to interact with.  However, within that network it is suggested that there will bestrong-ties weak-ties and directed-ties.  Bear with me here.  Generally speaking, at the core of your network  will be a group of up to 12 strong ties – beyond this the group becomes more conflicted and tends to fracture and form sub-groups.  This core group will usually have a focal point, an expert perhaps, who acts as the strong connector.  Outside of this we have varying degrees of acquaintance, or weak ties; being stronger the closer they are to the strong-ties and weakening as they move away from the centre – there tends to be a common social element here that exists as a ‘golden thread’ throughout the network. Then you have directed-ties; these are relationships that exists in relative isolation, islands if you will, existing with limited interaction and without the need to conform to the common social elements that exist with varying degrees of intensity throughout the network.  Ties between strong-tie clusters in networks are usually facilitated through weak links through commonality of need, demand or purpose.

The argument is that we often get drawn into the value of the strong-ties, when the real value, when it comes to developing our own dynamic capability, is in our weak-ties or directed-ties.  The argument for this?  To innovate there is a need for the individual to become more dynamic, which, you could argue, requires access to disparate ideas through a flow of heterogeneous information.  I would argue that there is more to this than becoming personally reflective and exploring the periphery of our network relationships.  I would argue that the way we focus our attention, and our subsequent ability to innovate, is actually based within our cognitive style.  The help distinguish the two, the following is taken from Wyss (2002); though, I have to say, the best book in this area is ‘The Adult Learner’.

Now, strong-ties are built around homogenous bonds.  There is a focus on conformity, reciprocal relationships, reproduction of the norm, high levels of intimacy, low levels of abstractness, established ways of thinking and there are usually links to status. Weak-ties, to a varying extent, and directed-ties, to more of an extent, are more heterogeneous, have significantly lower levels of intimacy, operate with higher levels of abstractness, appear to encourage deviation from the norm, experimentation and are not dependent on role based actors.  I would argue that a field-independent individuals are more likely to explore the fringes of the social network, to dabble with islands, or to operate more as an independent loner.  I would also argue that field dependent individuals are more likely to gravitate towards the norm, to be more interested in reproduction with minimal deviation from what is already known.

Reinforcing this view is the way in which individuals access information and the type of information available to them.  I would argue that field dependent individuals, focused on role-based, strong-tie, relationships are subjecting themselves to a form of variety attenuation that lowers abstractness and reinforces the norm.  I would also argue that this also links to critical thinking capacity and, as such, reinforces the variety attenuation process.  Information is often acquired through the social process and, as such, is often slower than other forms of information acquisition and can become tainted through the a social process that limits the capacity for deviation from the accepted norm.  On the other hand, field independent individuals have a greater capability for dealing with abstractness, have more of a capacity for critical thinking and are more likely to obtain their information from media sources, as opposed to relying on social diffusion.

So what?

Bringing this blog back to the question in the title, the point of reflection is whether the field independent loner, with a limited social network, a more innovative individual than a field dependent individual with a vast social network? What does this mean for an organisation?

It would seem that an awareness of cognitive styles is important within the decision-making process when it comes to understanding the capability and capacity for innovation, especially within knowledge intensive organisations.  After all, according to industry reports, such as The Economist 2020 Foresight Report, problem-solving and relationship building are two of the most vital skills needed by organisations today.