The implicit understanding here is that when we perform an everyday act of persuasion (e.g., I know more than you, so I must be right), we display a tacit knowing of what others believe  so that we can (a) determine that a shift in belief is warranted in the first place, (b) set the shift’s direction, and (c) apply the most efficient rhetorical strategy.

Humans are actually pretty good at using our linguistic ‘persuasion toolboxes’ to persuade and change the beliefs of others at the mundane level  (you could compile a substantial phrase book of such rhetorical devices). If we were not, nothing would get done and we would probably still be hunting-gathering. The efficacy of such actions is shown to be wholly reliant on speakers’ shared experiences and /or knowledge of context. This is precisely where organizational change management seems to get it wrong.

An organization wants to transform its culture to a more open, sharing and collaborative one. To do this, as one leading UK consultancy recommends, management needs to understand what people will have to believe, which is billed as ‘one of the secrets to successful change’. But does this  not effectively side-line the prevailing beliefs?  Logically, this kind of communication only deals with half of the equation in its formula of predicting people’s future beliefs, as it ignores their starting position. This is perhaps symptomatic of what Lee Bryant describes as ‘traditional change management’ with its top down, ‘big bang’ ethos  which, he claims, is prone to failure or, at best, unsustainable impact: the elusive unicorn that Peter Drucker talks about.

To attempt change in an organization is the attempt to persuade in order to manipulate belief. Recall Peter’s Drucker’s definition of ‘communication’ as being the action of the listener, not the speaker. The speaker merely utters: the utterance only becomes communication when it is understood. In my terms, the speaker broadcasts a persuasion action (which crucially orients to what the listener knows, thinks and so on); the listener accepts and applies it, in which case a communication is shown to have taken place as a collaborative action accomplished in social interaction. It works because speakers share common knowledge of experience and context, largely at the tacit level. Much of organizational change management practice simply fails to factor these fundamental human behaviours into the plan. Rather, it subscribes to the communication fallacy in differentiating between the communicator (the speaker) and the listener (the recipient). It treats humans as robots to be programmed.

Beliefs, according to Peter Senge’s Fifth Discipline, are often invisible, taken for granted, but influence action –how people accomplish things, set goals, figure out what is to be done and so forth (see Crane on tacit knowing,). Senge’s ideas find resonance in the earlier influential Theory of Planned Behaviour in which Icek Ajzen links beliefs with attitudes with beliefs as the antecedents to attitudes and behaviour. Further, Ajzen notes that we can only attend to a small number of salient beliefs at any given time because of memory limitations. This could explain how the ‘unexpected utterance’ is not heard (Drucker), or how participants failed to notice a man dressed in a gorilla suit wandering through a basketball game.

Despite a battery of conflicting claims and theories, some common features of beliefs can be drawn:

• They are often unconsciously acquired and stored;
• They are often unconsciously used and invariably influence what we do;
• Similarly to tacit knowing, we are not always able to articulate all that we believe with any degree of complete honesty.

From my own research, add another criterion:

• Beliefs are not static, enduring mental phenomena: they are fluid to, interdependent with, and influenced by context.

If you accept these propositions, then returning to the earlier argument – that successful persuasion requires knowledge and understanding of both the prevailing and future predicted beliefs – then we seem to have a complication. If people mostly don’t know what beliefs they possess, how can we possibly know what people believe in? Usually the simple answer is to just ask them, using a self-report questionnaire survey for example. That may only tell us what people think they believe in that instant, and most likely what they think we want to hear. There is an alternative approach.

If that which people believe influences what they do, then it influences what they say. Consider language as action with function and consequence in social interaction. As the British philosopher John Austin taught, when people speak, they do things with their words. To work up persuasion action in talk, for instance, is to display a particular belief, the strength of which can be measured by the rhetorical lengths taken to press the case, and its effect on listeners. So, rather than ask people what they believe, observe how and what beliefs are conjured in their everyday talk.

To conclude these points, if an organization wants to bring some kind of change into effect in a sustainable way, they need to ask more than what it is that people will need to believe in. They need to ask, what are the prevailing beliefs?  To do that they need to look to what actions people accomplish in their talk, what social realities are brought into being, what shared experiences are made live and contingent, and desist from de-humanising people. That would be finding the unicorn.

References

Ajzen, I. (1991) The Theory of Planned Behaviour.  Organizational Behaviour and Human Decision Processes, 50, pp 179 – 211

Austin, J. (1962) How to do things with words, (Eds) Urmson, J and Sbisa, M. 2nd Edn. Cambridge: Harvard University Press

Drucker, P. (2001). Functioning communications. In The Essential Drucker. London: Routledge

Senge, P. (2006). The Fifth Discipline: the art and practice of the learning organization. London: Random House

Simons, D. and Chabris, C. (1999). Gorillas in our midst: sustained inattentional blindness for dynamic events. Perception, 28: 1059 – 1074

About the author:

Dr. Lesley Crane specializes in effective human communications in organizational knowledge, learning and leadership, as both a consultant-coach, and researcher. Her forthcoming book, Knowledge and Discourse Matters, published by J Wiley & Sons, elaborates on the themes and ideas touched on here.

The modern practice of knowledge management (KM) emerged in the early 1990s in the resource drought left by the reverse-engineering debacle. The influential theory of the knowledge creating firm promoted by Ikujiro Nonaka and his colleagues offered 3 ideas which, although not new, were nonetheless embraced with enthusiasm perhaps because they came labelled with an attractive glittery badge called ‘knowledge’.

First, there was the idea that firms are not just input-output information processing factories. Instead they should be seen as knowledge and information generators, the success of which relies on efficient and effective interaction with the environment in which the firm operates.

Linked to this, the second idea promoted knowledge as the firm’s most important and valuable asset which in turn elevated the status of knowledge creating and sharing to top position on corporate agendas.

The third idea, and probably the most influential aspect of Nonaka’s theory, is the defined structure of knowledge as possessing two constituents – tacit and explicit. It is this last idea which has largely driven modern KM, arguably into a brick wall. Tacit knowledge – difficult to articulate, influential to action, the most valuable form of knowledge – needs to be converted to explicit knowledge in order to leverage its potential. This is a simplistic expression of the theory’s contents, but it is the version that has been most taken at face value. The upshot is a global industry and practice dedicated to harnessing (tacit) knowledge, largely through the application of technology. Little of which has actually worked by all accounts.

The typical KM practice within an organization is centred around some kind of monolithic database into which workers are expected to record their everyday experiences, share their professional profiles, and communicate with whoever. Sophisticated systems might even record and analyse people’s technology-use behaviours, generating data for predictive analytics (which practice has all the promise of evolving into a third myth). The focus then is on motivating and incentivising people to engage with technology. Whilst this is a satisfactory organizational aim in the generic sense, it promotes a de-humanized view of knowledge.

Similar to mono-directional and generalist organizational learning approaches, this approach to the management of knowledge misses the critical point about human behaviour. Most knowledge is shared and created, and most learning takes place in discourse in social interaction (see Nancy Dixon).

But there is more to it than this, and this is perhaps one of the greatest differentiators between intelligent machines and humans – perhaps even more than creativity and irrationality: tacit knowing. Paul Duguid, in his essay on The Art of Knowing, reasons that tacit knowing, or ‘knowing how’, makes explicit knowing -‘knowing that’ – actionable. You cannot do one without the other. Further, decades of research in cognitive psychology yields a view of tacit knowledge as that which the agent abstracts automatically and unconsciously from the environment, and which influences action. Connect this to the idea that around 95% of what we do in any day is done automatically without conscious control (see Bargh et al.). Conventional approaches to organizational knowledge management and learning ignore all this.

Here is the nub. To a larger or lesser extent people are continuously learning and sharing knowledge in social interaction. The ways in which we do this, and their consequences, are influenced and shaped by the contextual particulars in which we interact. This is, in essence, how we make sense – mostly automatically – of the environment in which we exist. Even when we read the words of another, the writer has no control over how we interpret and make sense of what is written. The writer and reader interact in much the same way as two folk talking. This is the stuff of innovation and new knowledge, the oil of decision-making and problem-solving.

To pay no attention to the influence and function of tacit knowing in the modern, technologically driven environment is to give primacy to technology. So what then happens when, as many predict, machines are developed which learn and think for themselves – IBM’s Watson, for instance? Promoted as leading to ‘human intellectual advantages’ by enabling new human-computer partnerships, Watson is still a highly sophisticated computer that is designed to learn and think. If the organizational practice of knowledge management, and other similar practices, continue to emphasise the use of technologies in, for instance, human knowledge sharing, then it is conceivable that in the future the human element may be deemed no longer necessary. Computers are better at sharing ‘de-humanized’ knowledge than humans are.

Tacit knowing is a common enough ability in humans, but irreplaceable by technology. As Paul Zak recently reminds us, Peter Drucker saw work as a social enterprise. He also envisaged social innovation as of far greater importance and impact than any technology. Draw your own conclusions.

Reference: Bargh, J. & Chartrand, T. (1999). The unbearable automaticity of being. American Psychologist, 54, (7): 462 – 479

About the author:

Dr. Lesley Crane is an independent consultant specializing in effective human communications in organizational knowledge, learning and leadership. Her forthcoming book, Knowledge and Discourse Matters, published by J Wiley & Sons, elaborates on the themes and ideas touched on here.