The Need for a New Perspective


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The world was a very different place in the time that Maslow developed his model (there wasn’t even the internet, for goodness sake – let alone WIFI) and it seems as though the pace of change is accelerating every day. Futurologist Watts Wacker described the context as the ‘500-year-delta’; the ‘age of reason’ we have been living in is passing away whilst what he terms the ‘age of possibility’ is just being born. The age of reason is one of linear understanding, of cause and effect and mechanistic thinking. The age of possibility is one arising out of the increasing complexity in the world – a direct legacy of the technical infrastructure of the industrial revolution and the intricate social arrangements that resulted from it.

This has spurred the knowledge and experience economies in which we now find ourselves where the models of old, such as Maslow’s, do not necessarily reflect the reality in which we live. As we are increasingly and systematica­lly bombarded with information, the need for systemic thinking has never been more apparent.

The information economy is serving to commoditise goods and services at an ever-increasing rate and, conversely, knowledge (‘know-how’) and experiences are the primary sources of value and, it follows therefore, competitive advantage. The ‘Blurred Economy’ where speed, connectivity and intangibles pervade, where the notion of the ‘offer’ supersedes product and service-orientated mindsets and where the notion of the exchange between producer and consumer has taken on far more profound implications than previously understood economics ever explained.

These changes are already upon us. We can already bear testimony to changes in our expectations as consumers as we become increasingly demanding as to the value we get for our money. As consumer expectations change so must the cost of doing business as transparency in the global economy comes to the fore. This is the real tangible effect of the internet revolution: The ramifications in terms of stock market valuations alone have been tremendous.

The notion of an ‘Atomic Corporation’, where the effects of the information economy will cause today’s big corporations to break-up under pressure and ensure the evolution of a new landscape populated by much smaller business entities is not unrealistic. None of the factors above is in itself capable of turning our business world upside down but in combination they are enough to tear apart even the biggest of our giant corporations.

At the heart of it all lies a single phenomenon – an emerging information infrastructure that alters dramatically the costs of co-ordination and dispersion of knowledge.

As Camrass and Farncombe suggest; “a new focus on agility is needed, and as you can’t be big and agile at the same time (the internal cost of movement is too high), fragmentation is looking more and more attractive. And breaking up has never been easier. The availability and breadth of communications channels between organisations is growing exponentially, which is sharply reducing the costs of doing business”.

Regardless of your view of this radical prediction, the truth is that in order to simply survive, an organisation has to be willing and able to mobilise and engage its people and supporting infrastructure when and where customers demand. Many will be dependent upon their ability to recruit and retain the best brains with the best attitudes who are able and willing to meet such extraordinary demand.

How is your organisation responding to this challenge?

Back to Basics: We love Maslow…and beyond


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One of the most memorable models I have worked with is one of the first I was introduced to in my days of undergraduate study and one that I am sure you will be familiar with too. The notion that I had a hierarchy of needs was not necessarily new; what was interesting was where, at the time, I perceived myself within that model.

In the 1940s, Abraham Maslow developed a model known as the ‘Hierarchy of Needs and Objectives’. The assumption behind the model was one of linearity – one cannot progress to the next level until the current needs and objectives had been satisfied. His model is comprised of five orders of needs and objectives that human beings seek in life.

The lowest order need in the model is Physiological. This refers to the promulgation of life and includes, therefore, food, water, shelter and reproduction, also referred to as sex. The next order need is safety, referring to security and protection from danger. Next is the social need: We are social beings and as such need social interaction. Cybernetics also gives us the notion of the purposeful system, which can mean family, community, organisation and so on.

The next order need is esteem. This is concerned with the need for recognition individuals have in themselves and in their behaviours. It implies that humans seek positive experiences (and therefore concurs with a view held by cybernetics: the view that systems do not purposefully seek to impinge upon the desired state of others). The final order is that of self-actualisation. This is the human desire for a sense of purpose.

Critics of this model rightly demonstrate the weakness of the underlying assumption that, as a linear approach, progression is deemed a systematic response to the realization of previous orders. The model also assumes that there is no regression in position. Yet we are all aware, especially in recent years, of how our need to feel safe and secure can frequently be at the forefront of our minds, challenged by our unstable external environment. Also, conversely, how culture can flourish even in wartime situations, or in environments such as refugee camps, where people reach ‘up’ to the arts even when their physiological needs are far from being met. You may well have seen the tongue-in-cheek adaptation of Maslow, where these days even before their physiological needs are met, many modern humans have an even more pressing need – the need for WIFI (cue groaning and rolling of eyes)…!

Maslow’s model may not be quite ‘right’ these days, but it is, I believe, useful, and modern evolutions give it further potential.

We are frequently engaged by clients seeking to understand, address and embed the values of their organisations. One of the tools we might propose early on in our approach to these kinds of values projects is a Barrett survey. Concerned with how the values and cultural traits of an organisation are perceived from within that organisation, Barrett evolved Maslow’s model for his own purposes. In the Barrett model, we find seven levels of consciousness, from survival, relationship and self-esteem – which roughly mirror Maslow’s physiological, safety and social levels – through transformation and up to internal cohesion, making a difference and service. Unlike in Maslow’s model, an individual or organisation does not progress through these levels; rather it is a spread of values across the spectrum that shows a healthy balance.

Whatever models we choose to apply to Complex Adaptive Systems, be they individuals or organisations, they need to be appropriate for the situation. Now we’ve gone back to basics, which still give us a solid foundation, it’s time to look at the challenges the modern business world throws at us.

People: Control, Freedom and the performance paradox


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Traditional economic theory held that approximately one-third of an organisation’s cost base was in its ‘labour force’, a term which refers us back to an industrial age where labour was just that; labour. In the information age, the capital of many businesses is weighted much more heavily towards human capital, or ‘talent’ – where the main work of employees converting ‘inputs’ to ‘outputs’ in order to generate value is intellectual. These employees (often referred to as knowledge workers) may be scientists, researchers, analysts, traders, engineers, accountants, software developers, designers and architects: anyone who ‘thinks’ for a living.

Maybe that’s you?

This shift away from physical to mental labour is interesting when we think back to the idea from cybernetics that people are a dynamic, purposeful component of the complex system. Perhaps when the majority of workers were concerned with the transformation of physical inputs into a final product, their scope for influence on the system was relatively limited, and the management hierarchy was relatively flat. Now though, we know this is rarely the case. Knowledge workers certainly fit the picture of purposeful components within a purposeful system, operating within a context of responsibility, which may be either management-driven or leadership-driven depending upon the developmental maturity of the organisation.

When we start to investigate the purpose of these ‘components’ in order to understand how they engage with the broader system, it’s useful to explore the different theories of employee motivation.

Douglas McGregor in the 1960s expounded the notion that workers conform to one of two types of categorisation: They are either Theory X or Theory Y. Theory X infers a dislike of work and a need for coercion, direction and control to meet the needs of the organisation: A need to be managed. Theory Y implies the opposite: Work can meet their higher psychological needs but to do so, self-direction and self-control must pervade. This is an interesting proposition. Considering we are all model-making, meaning-seeking beings this model immediately forces us to recognise that we may or may not be operating from one of these points of view. It is a potentially useful model as it allows us to consider where we stand vis-à-vis our colleagues and collaborators.

In the 1980s William Ouchi developed another category: Theory Z. This is an extension of the Y point of view, stating that people in this category actively seek responsibility and in light of this, organisations should empower these employees to participate in decision-making activities. (Interestingly, there had been proponents of this since the 1950s born out of disagreement with Taylor’s doctrine of ‘Scientific Management’). The notion of a ‘Self Managing Work Team’ was given a theory-based grounding and has since come to embody all that leaders desire and yet, simultaneously, fear.

Cybernetics: The Dynamic Model…


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What application does cybernetics have to our work? To many, the word cybernetics sounds futuristic. These days we tend to think of it in terms of technology, but its reach is far, far broader than that. As a discipline it draws on the fields of psychology, anthropology, biology, engineering and mathematics to answer the question – what controls how a system behaves? Let’s go back to the roots of cybernetics and see what implications it has for the complex systems we are dealing with today.

The term cybernetics was coined in 1947 for a new discipline that had emerged out of research into the control of physical systems. Norbert Wiener and colleagues chose a name adapted from a Greek word meaning ‘steersman’. This, it was felt, would invoke the rich interaction of goals, predictions, actions, feedback and response in systems of all kinds: mechanical and physical systems, but also biological, cognitive and social systems, abstract intelligent processes and language[1]. Wiener’s own simple definition for cybernetics was this: Communication and control in the animal and the machine.

Cybernetics is neither holist nor reductionist. Rather, it takes the philosophical perspective that the whole can be analysed as a set of components within the context of their organisation. It is that organisation which will account for interactions between components, and the way they in turn affect the system.

One of the most fundamental concepts of cybernetics is its approach to equilibrium and change. Cybernetics takes the position that an entity behaves in a way to keep certain conditions as close to a desired state as possible – an equilibrium – and then seeks to understand the actions required to maintain these conditions. This understanding is also fundamental when applied to a system’s effort to effect change by moving towards a goal (or new equilibrium).

These efforts will be composed of, for example, observing or perceiving, organising observations, comparing these organised observations to the desired state (which is a function of memory) and taking corrective measures should the gap between current and desired state be too large. A further role of the memory may also be to record previous corrective measures used and the context in which they were taken.

The ability of the system – be it the human body or a complex enterprise – to observe, make comparisons and decisions and then be in action is the very essence of ‘steersmanship’ and hence is cybernetic.

As you can see, the implications of cybernetics touch on the most philosophical questions of our work: observation, interpretation, meaning and understanding. They touch upon who we are, where we stand in the face of reality, what decisions we make and how we make them.

In business (and in life) we like to think we make decisions based on our knowledge of a situation, yet cybernetics’ epistemological approach – where the observer and the observed are both seen as parts of the same system – suggests that our perspective, and our behaviour, cannot be separated from the system itself. Cybernetics forces us to consider what the limits to our true knowledge are and we understand that our reality may be nothing more than a self-maintained mental construction to help us get along: A mental model. And as we’ve said before, (and will likely say again!) “all models are wrong. Some are useful.”

Cybernetics puts human perspectives and behaviours at the heart of any attempt to model the complex system of an enterprise. Since humans are capable of developing their own goals and desired states the implication is profound: We can define organizations as being purposeful systems of purposeful components – people. Thus by understanding more about the motivations of the people we will come to know what truly controls the system we desire to shape.

What is a model?


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‘Model’ can mean different things to different people, but in the context of our work, we mean a representation of reality intended to foster understanding.

Human beings use models all the time. Our observations, reflections and interpretations are all about creating mental models. Words themselves are models – a representation of reality. Just as the word apple is not the apple itself, a word, any word, is a concept we understand through agreement. Models provide a basis for conversation.

Friends at the Sente Corporation have put it this way:

“Depending on how you look at it, anything can be a model. Even reality – from one vantage point – is merely our own electro-chemical processing of narrow bandwidths taken from a sea of information”.

Why do we create models? Good models simplify our complex world, enabling us to communicate and appropriate complex ideas, notions, theories, and so on effectively and efficiently. We make our models to a scale where what they represent becomes understandable on an intuitive level. They enable us to develop the comprehension and insight from which we can begin to experiment. And through this, we learn.

In the context of enterprise, models enable us to examine a situation, analyse it and then draw out plans. Many of the concepts we grapple with in today’s organisations are so complex they are beyond the limits of our intuitive comprehension. Through modelling we attempt to strip away these layers of complexity in order for us to understand the context of the enterprise, the components within it and their relationships to each other and the external eco-system.

They do have their limitations. Models are fundamentally ‘reductionist’ in nature and there’s a balance to be struck between making the model sufficiently abstract that it can be understood intuitively whilst avoiding over-simplification. For example, in breaking processes down to constituent parts, the nature of the whole – the systemic dimension of the organisation – is all too often left neglected. The decomposition omits many of the complex interactions around a process, which is just a logical, linear sequence of activities. To document all such interactions would involve a mammoth effort of analysis, so the trick is to find the right mixture of reductionism and ‘holism’ or ‘systems thinking’. Cybernetics helps our understanding too, and I’ll come back to these points in later posts.

There is one fundamental pitfall to avoid when working with models: we must never forget that all our models – be they process maps, mind maps, spread-sheets, stories, physical or conceptual models – are abstractions. Therefore it is vitally important we remain vigilant in revisiting and revising them regularly, cognisant of the fact that, as George Box put it: “All models are wrong. Some models are useful”.

We must learn to be constantly critical and questioning, otherwise the very models we have constructed can be our own downfall as we cling on to them, attached to the comfort of a reality we perceive that may not, in fact, be appropriate. The only way of achieving a shift in our own perspective is through conversation. An intervention in our self-perpetuating thought processes can – if we are open to it – change our view of the world. Or our business.

At Innovation Arts, when we work with clients facing complex issues, we apply a rigorous approach to modelling. Dialogue and iteration are key to our approach, both during the Architecting and Building phases of solution design, but also when the new model is put to Use.

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