Some notes by JW
Given that information has never been so abundant or accessible it is surprising how much we don't know about the BIG questions. How will climate change affect agriculture and business? To what extent will the current spate of species extinctions affect human populations? Although decision-making has been made easier by immediate access to Wikipedia, or Google Scholar, the way information is distributed may be filtered by algorithms that tell us what would like to hear, rather than what we may need to know. These changes are affecting the culture of belief and establishing new ground rules within what has been described as 'post-truth politics'. In its 2016 edition, the OED claimed that, in terms of political allegiance, emotion and prejudice are now more influential than facts. On the one hand, the increasingly mercurial nature of information exchange enables powerful presidents and corporations to share big ideas quickly. On the other hand, it offers similar powers to dissident voters, whistleblowers and hackers. This is not only affecting those who crave supremacy in politics (as 'soft power'), or in business (as 'market dominance') but, also, at the level of everyday habits and practices. Just as algorithms and 'big data' systems look set to replace many blue-collar, and white-collar jobs, so cross-disciplinary research initiatives are delivering outcomes that call for new ways of thinking (e.g. hybrids that combine robotics, quantum computing, AI systems and bio-engineering). In short, in the era of so-called 'alternative facts', the idea of certainty is becoming less certain. But this does not help managers and decision makers. Despite the rising tide of 'known-unknowns', organisations must keep calm and carry on.
It seems clear that the immediate future will not get clearer anytime soon. Indeed, surprise will become less surprising than it used to be. This is not all bad news, as uncertainty is a rich source of opportunity. The bad news is that few, if any, of the most popular management tools were designed for times of great uncertainty. Rather, systems, such as SAP, Six Sigma, Lean, Prince 2, Scrum, and Kaban, were intended to make organisations leaner, better-focused and more efficient. This is not to say that efficiency is no longer relevant, but that what might be deemed 'efficient' in one context may be 'inefficient' in another. The notion of the 'wicked problem' (Rittel, 1984) emerged because of the circular nature of 'problem-solving'. For example, just as solutions are a reflection of how a problem is defined, so problem definition depends on the solution. 'Design-thinking' became fashionable in the latter part of the 20th century, when managers began to sense that we need more than the logic that is taught in business schools. Ironically, some of these issues can be traced to the late 1880s, when the emerging professions of design and management both saw their task as finding ways to achieve a preferred outcome, or set of conditions. However, although both emerged from this strongly predictive (i.e. teleological) mindset, managers and designers are taught in rather different ways. They also apply different modes of pragmatism. The more immediate pressures under which managers have to operate means that designers are more likely to seek 'unprecedented possibles', even though they know they are unlikely to find them very often. For this reason, the metadesign approach sees 'opportunity-finding' as being at least as useful as a 'problem-solving' approach.
If uncertainty and complexity are defining features of our era, what precedents can we learn most from, as organisations? What aspect of yesterday could inform the managers of today? From our own research at metadesign, the study of 'living systems' is the most relevant. Whereas few modern institutions have have lasted for more than a century or two, today's ecosystems have lived through countless unpredictable changes over hundreds of millions of years. Indeed, some experts believe that the way the human mind invents new things is a echo of the apparently 'creative' aspects of evolution (Bateson, 1980; Loreto et al. 2017). It seems reasonable, intuitively speaking, to cope with uncertainty by cultivating alertness, imagination, adaptiveness and resourcefulness. However, although this may suggest that living systems have a 'coping strategy', it seems unlikely that they 'think', or 'plan' using the methods that we, as humans, understand. In other words, we should check our assumptions and be cautious about what we learn from the living world. If the biosphere's complexity is beyond our full understanding it is important to acknowledge the difference between 'systems' and 'realities'. Although the term 'living system' includes biological creatures (i.e. 'living organisms' such as animals, molluscs, or bacteria) it can also be applied to a range of other things, such as sects, governments, corporate brands or paradigms. This is useful, as it means we can observe living systems in a systemic way, then apply our knowledge to the development of human organisations.
metadesign and 'Living Systems'
Let us clarify some of these terms. Living systems and living organisms are similar in a number ways. Each is autonomous and uses similar processes to help them survive. Both manage their equilibrium, and destiny, by orchestrating the flow of information, energy and matter. And they do so within the context they find in their external habitat. However, whereas living organisms have no pre-defined use, apart from their own survival, most non-biological 'living systems' were designed for a specific purpose. Over the over the next few years we are likely to read a lot about AI ('Artificial Intelligence') and 'smart systems'. Although, in some ways these entities resemble living systems, as 'tools', they have a low quality of 'organisational consciousness'. Inanimate systems, such as automata, algorithms or assembly-line systems, are designed for specific situations, a living system maintains its own survival by managing its internal 'metabolism' and, when required, adapting to its environment. Each of these processes operates in the living system's internal resources and capabilities. These also include the external resources that are available to it, including other organisms (or organisations). It may, therefore, find itself collaborating with, or competing with, other living systems. The whole process can be seen as a network of processes that act in order to regenerate, manage, and replicate aspects of itself. Although these definitions may seem vague, they make it possible for human agencies and organisations to learn from the biological interdependencies within ecosystems.
How might one be sure whether a given system is animate or inanimate? A useful starter is to ask whether the item in question has a 'purpose' (i.e. in the non-religious sense). No matter how 'smart', or 'intelligent', an inanimate system appears to be, its purpose will have been assigned by a person or agency. However, according to the metadesign framework, a living system has no intrinsic 'purpose', apart from sustaining itself within its environment. In other words, 'survival' can be defined as the organism's ability to maintain its 'unity', or 'identity', as a whole system. From this description it follows that a living system will perish once it fails to reconcile its internal identity with its external identity. Crudely speaking, this is the only way for it to die. The living system's immediate environment will consist of a mixture of assets and resources that include other living organisms. These will need to be identified, in order to ignore, avoid, or render them safe. If its own internal identity is inappropriately matched to its capabilities it may not be recognised by its allies, or fall victim to unfamiliar threats.
Our methods challenge a number of traditional assumptions that are embedded in the language of management and design. In terms of thermodynamic efficiency we have long known that ecosystems are better than machines. Why, then, did successive industrial revolutions choose a more mechanistic approach? One reason for this is that 'dead' systems are more predictable than 'living' ones. This can be seen from the parallel developments in classical science. Figure 1 shows how, although living systems (on the right-hand side) are characterised by diversity, interdependence and stability, they are also more difficult to control. On the other hand, although the physics of large things (on the left-hand side) seems more predictable, these items will not readily organise themselves into efficient systems. Yet, in some ways, we tend to find the distinction between 'living systems' and 'inanimate systems' perplexing. For example, although there has been much interest in 'bio-mimicry' and 'bio-engineering' (apparently on the right-hand side of the diagram), copying 'bits' of living organisms in order to use them as tools is not what the metadesign framework understands by 'living systems'.
It is not surprising that science chose to learn more about the simplicity of dead things, rather than the complexity of livings ones. Many scientific observations, including early medical investigations, had been filtered through the mechanical technologies that were available at the time. These informed philosophical thought and had a strong effect on society as a whole. For example, until church bells first began to regiment daily habits of work, worship and play in the thirteenth century, the ebb and flow of life had been regulated by diurnal and seasonal cycles. By the fifteenth century people saw, for the first time, minute hands on clock faces. This would have made it much clearer who was 'early' and who was 'late' for an appointment. By the sixteenth century, Galileo had invented the thermometer, (1597) and Cornelius Drebbel (1572-1633) had developed a thermostat that regulated the temperature of an oven. Shortly after the time that Renee Descartes announced that humans were 'self-moving machines', Blaise Pascal (1623-1672) caused a stir by parading himself in public with a small clock tied to his wrist. By the time the first patent for a factory clock had been granted (1880) the clock-driven timestamp had already been in use for some time. By the 20th century, Henry Ford's assembly-line management approach had become copied throughout the industrial world.
We can get a sense of how mechanistic our thinking has become by reflecting upon our trust in clocks, thermostats and money. The underlying principle behind these systems is a strange one, given the emphasis on absolute quantification (e.g. temperature, hours and minutes), rather than on the relative quality of what is produced, or enjoyed (e.g. willingness and wellbeing). Even today, many of us tend to assume that clocks 'measure' time, but this is not the case. Indeed, early mechanical clocks needed to be kept in strict isolation from human movements, otherwise it would fall out of sync with other clocks. Although most of us knows that conventional clocks are oblivious of our presence, we may still notice ourselves asking them, tacitly, whether we need a coffee break, or snack. Similarly, it seems entirely normal to trust 'smart' domestic thermostats to override our body's internal system of self-regulation. The clock and the thermostat formed part of the basis for automata and the subsequent digital culture. Of course, they are becoming a little more attuned to human behaviour, thanks to innovations such as the Apple Watch and FaceTime. Nonetheless, the new AI products are likely to encourage people to acquire an even greater faith in inanimate systems, rather than developing their own senses and values. A similar story also applies to the way the money system works. In each case (i.e. time, temperature control and money), the 'thing' to which we assign value is merely a set of arbitrary, context-free numbers in a database. Even though we know this, we still find it easy to project our deepest hopes, desires and values onto them.
As humans, our blind faith in mechanisms is not a recent development. William Calvin (1997) has suggested that our ability to reason was acquired over millions of years of evolutionary development; emerging partly from the logic of lifting, carrying, dragging or throwing weighty objects around. This part of the brain is well-developed. Even a chimpanzee has a shrewd idea where the banana will land, once it leaves her hand. It is interesting to note that the Greek word for ‘problem’ also meant something (i.e. some ‘thing’) that is thrown, or placed, onto one’s path. In a sense, notions of ‘problem’ and ‘project’ therefore share the same metaphorical allusion. It was Galileo's hunch that heavy objects move in a predictable way that led Newton (1642-1726) to create his universal 'laws' of motion. Pierre Laplace (1749–1827) was so persuaded by Newton's grand hypothesis that he thought we could eventually use it to predict the future with total accuracy. However, this idea was soon invalidated by Henri Poincaré (1854–1912), whose work led to the subsequent discovery of 'chaos theory'. This shows that complex systems are, in the long run, fundamentally unpredictable. Although scientists can predict how a dead body will decompose under laboratory conditions, the granularity of numbers makes mathematics unable to predict the destiny of a newborn infant. This has a bearing on management cultures that understand 'accountability', rather than 'responsibility', or 'impact', rather than 'synergy'. In short, if organisations are run purely according to the bureaucratic language and logic of dead objects, we risk treating living systems as though they are zombies.
This is a very serious matter, especially where highly complex 'known-unknowns', such climate change, education and healthcare are managed by setting targets, as we know that this does not work. Whenever we resort to mechanistic language, we risk adopting behaviour that is mechanical. In recent years, terms, such as 'projects', 'aims', 'targets', 'objectives', or 'outcomes' have slipped into everyday speech, often to describe complex and subtle matters, like career aspirations, or family holidays. In 1997, Donella Meadows criticised the use of terms, such as 'targets', in an attempt to catalyse desired changes in whole communities, or paradigms. Goethe (1749–1832) warned scientists that they would never prise Nature's secrets from her with ‘levers and springs’. It would seem that many of us have yet to understand the subtlety of this idea. For example, the concept of the lever is still used in business to describe the setting up of reciprocal deals. This is strange, given how clumsy 'leverage' is, as a metaphor. Effective negotiation is neither clumsy, nor heavy-handed. It is a subtle art that calls for a range of skills, such as empathy, logic, inventiveness and good timing. This is not a pedantic point about which words are most appropriate or precise. It is intended to remind us that human behaviour is shaped, not only by the tools we hold in our hands but, also, by the theories and models we hold in our minds. The language we use has a formative influence on what we recognise, or fail to notice. This, in turn, affects our ability to harness practical opportunities. When discussing climate change, James Lovelock (b. 1919) reminded colleagues that the term ‘tipping point’ is dangerously misleading. He reminded them that meteorological systems are unlikely to 'tip back' when CO2 levels rise above a critical point. He suggested ‘sliding point’ as a more fitting term.
This short article began by asking how an organisation trained for self-discipline and compliance can suddenly cope in an era of uncertainty and disruption. Can it, for example, become far-sighted and near-sighted at the same time? Here, we can learn from the cognitive systems within animals. For example, many birds are better at detecting predators with their left eye than with their right eye. This is because their left brain hemisphere (governed by their right eye) is better at focusing on tiny details that are very close. This ability is made possible by a sophisticated structural asymmetry within the brain that enables these creatures to deal with local, specific tasks whilst remaining vigilant to opportunities and dangers that may become urgent at a later time. Unfortunately, as McGilchrist (2009) points out, our society has built many of its institutions on a back-to-front reading of how this works. He points out that our rational skills (i.e. left brain hemisphere) evolved to co-ordinate bodily events that have already taken place, rather than ordering future actions. We may fail to notice this, because the brain can easily misrepresent what has just happened by assuming that it was an intended action.
Although this article on 'Living Systems' does not try to explain how the practical metadesign tools work, it is offered as a brief insight to some of the thinking behind them. Our research has prompted us to explore how self-organising systems re-scale themselves, work co-dependently with other organisms, co-create new processes and change their own structure in radical ways. They have helped us to devise methods that, although they may differ from orthodox management thinking, have been welcomed as 'common sense'. Arriving at new ways of thinking in order to adapt to unfamiliar situations is seldom easy. It usually means challenging, or changing, the habits, assumptions and beliefs to which we have become attached. In addressing this problem, many commercial and public organisations hire in external 'creatives', who offer read-made solutions to problems. We are unlikely to do this, because we are not specialists with the specific expertise that our clients have. Nor do we subscribe to the myth of 'individual genius'. The most brilliant individual is useless, unless she, or he, is welcomed and listened to. Moreover, her ideas then need to be shared, and understood, at all relevant levels within the organisation. Even when this happens, unless the relevant people are willing, and able, to implement them in an appropriate manner, the mission may fail.
Although this article may have dropped a few hints about the metadesign System, it has not explained how we help organisations behave more like living systems. This is too big an issue to address within a brief paper. However, suffice to say that some attributes of living systems are embedded in the metadesign System's diagnostic mapping tool. And some have informed the practical criteria that enable organisations to operate more effectively. Part of our work also includes translating our knowledge into appropriate terminologies that are accessible and helpful to our clients. For example, we have devised methods to raise what we call 'organisational consciousness' which, in a single concept, enables organisations to summarise many useful attributes, such as attentiveness, and playfulness, alertness, insight, responsiveness and adaptiveness. Similarly, the notion of 'symbiosis' has helped us to evolve tools for creating what we call 'simple synergies'. These transcend some of the familiar boundaries of asset management and the language that describes it. More specifically, 'synergy' can be described as a free bonus we may get by cleverly combining things we already possess. Ultimately, our creative tools emulate the way that Nature replenishes itself through 'sexual reproduction' or, to use the more precise term: 'sexual recombination'. Our definition of synergy as a mode of recombination is crucially important, as it reminds managers that they may have misunderstood, overlooked or underestimated the value of entities they may not have noticed, or had assumed to be worthless, or negative assets.
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