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  • Writer's pictureAdam Timlett

How to recognise organic work in your organisation, and why.

Updated: Jun 24

The PDF of this article is available for download here

How to Recognise Organic Work in Your Organisation and Why
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The context of organic work by organisations

Firstly, what is organic work, and what is an organically managed organisation?

Let's start with the background to this, which is the use of mechanical metaphors in management.

The Mechanical Metaphor

The management of organisations, like the science of human minds, became dominated by metaphors of machines, largely in response to industrialisation which meant machine-made things began to dominate many industries. Due to industrialisation, many formerly craft workers were reduced to machine minders. Work went from crafts with inbuilt creative aspects to machine made, factory based production lines, such as in the emergence of textile factories that replaced people who made rugs by hand.

In addition to this, the machine metaphor simplified the approach to many management problems, even outside of factories and began to dominate management culture in the early 19th and 20th centuries. The industrial concepts of standardisation, resource allocation (where people can be regarded as uniform resources) and inputs and outputs to uniform processes began to dominate the thinking of management across industries, regardless of how they were actually constituted and what they did to create value. The most prominent version of this was known as ‘Taylorism’ and began in the late 19th century.

Photo Credit: James Robert White

Organic Metaphors for Management

However, when we take inorganic metaphors, such as mechanical metaphors and apply them to try to understand organic work, it can lead to nonsensical and inappropriate responses. An example from the mind as machine metaphor comes from the psychologist Jonathan Haidt, who in his book the Happiness Hypothesis, describes his experience as a boy riding a horse on holiday.

Haidt was riding on a path, one side of which was a sharp drop and the horse was running out of path, because the path was about to turn sharply left, leaving the sheer drop straight ahead. Jonathan wanted to ‘steer or drive’ the horse away from the edge, but another horse and rider was in the way as they rode beside one another. He froze, petrified and didn’t tug on the rains, whereupon the two horses, as one, simply turned left avoiding each other and the sheer drop, without the need for any intervention from Jonathan.

Jonathan realised his panic was completely nonsensical because he was thinking of the horse as if it was a car that needed to be driven. But in fact the horse knew, better than he, how to react to the problem and had no intention of falling to its death, anymore than Jonathan, especially as it had ridden this path many times before.

Management in organic organisations is also more like this than driving a car. Rather than planning, and driving results forward based on steering with certainty and full control towards certain milestones or goals, management of organic work understands that control over the work is only partial; The system has its own logic, concerns, agency and power. It would not be such a problem to manage things which are organic, but management culture is now still heavily biased towards thinking of organisations to be managed as one would manage a machine.

The job market reveals mechanical thinking still dominates management

If we take a cursory look at job adverts for management jobs we see that certain phrases with mechanical metaphors predominate. ‘As a manager of x you will be results driven’. ‘As manager of your team, you will drive this programme forward’. ‘You will be focused on delivery on these key results by your department by meeting the agreed milestones’. Jonathan argues that metaphors like this can have a huge impact on how we as managers approach problems, specifically how we manage work and work with others, and even how we relate to our own selves, which is the subject of Haidt’s book.

There is little acknowledgement in the mechanical metaphors we use, that you, rather than the driver of a vehicle you control, even as a manager, may be just one part (often redundant) of a bigger system, like the rider of an elephant, in the analogy from the writings of the Buddha, also quoted by Haidt. Haidt gives the example of the human mind, with its desires and sometimes uncontrollable emotions. Rather than driving your team or organisation like a car, pulling various levers to get this or that predictable reaction, and planning every action of your team, you may need to listen and understand what a team is capable of before thinking of how you might be able to add value as the manager.

Acknowledging that you may be a mere ‘rider’ (often redundantly) resting on top of something far bigger, more powerful and knowledgeable than yourself, has concrete implications for how you plan, communicate, ‘steer’ towards certain desired outcomes. This is true for management just as, as Haidt argues, it is true for managing your own emotions and desires.

The insight of Turing Meta, is that Haidt’s analogy is especially true of management when the work being managed is organic. So, for organic work, i.e. horses and elephants, rather than cars, the organic approach also has a big effect on how you successfully manage, and deal with risk and uncertainty. That inorganic metaphor, when used to manage organic work, significantly contributes to bad outcomes akin to trying to drive a horse as if it is a car.

As Jonathan Haidt points out, in previous generations the metaphor of managing one’s desires and emotions as the rider of an animal bigger than oneself was a very natural metaphor. But it is an alien metaphor to many modern managers who very often will have had very limited experience of this type of relationship to a larger animal. Instead, we all drive cars and are more familiar with this type of relationship to a mechanical device and the prevalence of technology in modern life influences us profoundly as human beings.

The contribution of Turing Meta to managing organic work

While Haidt talks about ancient wisdom, things have also changed in our modern understanding of biology, the ultimate source of all organic work: Turing Meta can take this modern biology research and translate it to businesses to help them to understand how to recognise and manage organic work with scientific rigor. This dimension was missing from previous generations of intuitive management, even though the metaphor of management of self as riding a horse or, as the Buddha said, an elephant, would have been very natural to apply to managing others. This new emerging scientific model of organic work is going to become essential in modern organisations which rely on consensus and collaboration backed up by metrics, data and statistics to support decision-making and understanding, and explicit, as well as tacit knowledge, to support effective communication and leadership.

The key to understanding the modern difference here, is to utilise Turing Meta’s knowledge of concepts, metrics and translational research from biology to inform management practices that characterise effective management of organic work. This translational research stands on the shoulders of recent decades of biology research and closely related complexity science. This can help to back up challenges to change metaphors with facts about organic work and what it looks like from a modern perspective in a modern world of work. Turing Meta can combine adapted training in organic metaphors of work for staff and managers based in psychological research, such as that of Haidt, and Edward Slingerland in his book ‘Trying not to Try, with facts, metrics and techniques for modelling organic work translated from modern biology.

From here, we can approach the management of organic work, like horsemanship would be, as a scientific and objectively different kind of thing to learning how to drive a car, with completely different metaphors, approaches and new methods for classic management problems, while also connecting it to the ancient wisdom about life, which Haidt and Slingerland summarise so well, and successfully connect to modern psychological science.

Why technology paradoxically leads to more organic work

Technology itself, now leads us towards organic work, but it does so, synthetically, by mimicking the complexity and methods of organic systems. As a result, paradoxically, modern technology increasingly creates organic work in organisations. An early example of this synthetic organicity, is computer viruses as the early analog of biological viruses. Like their organic equivalents they are not ‘alive’ in a straightforward sense, but they are somehow not simply a passive thing either. They have a simple agency.

It wasn’t possible for cars to catch viruses before computers, only horses. But now things have changed, because cars carry, in many cases, up to 11 different computers on board. Also, before modern computers it wasn’t possible for cars to construct an opinion how to get from A to B, or actually try to drive you there themselves. Horses used to do the same thing and could take a drunk or asleep rider home without their intervention. The simple analogy demonstrates the point that technology synthesises organic kinds of behaviours, because it involves systems with simple agency. However, with AI and machine learning set to revolutionise many industries, they will create the need to organically manage this synthetic organic work carried out by semi-autonomous systems, at an alarming pace.

What being an organic organisation means according to modern biology: Recognising organic work

Power Law Dynamics

In an organic system, power law dynamics often govern key organisational processes and value generation for organic work. A power law just means that when we look at the value of some input, that as we vary the input, the output is not linear, but a result of multiplying the input by some ‘power’ of the input. For example, as you increase the length of the side of a square, s, the area increases by a power of the side, i.e. the sides time itself, s squared. What this means in practice, is that when we look at the organic work that ultimately creates the core value of a given organisation, that work may be highly variable in the monetary or other value from item to item and doesn’t vary in a linear way. So if we arrange the work in order of value, it doesn’t form a line ascending like a staircase, but rather stays flat and then suddenly goes nearly vertical. This is often a feature of organic work, work that requires creativity, such that no two works are the same.

Power law graph, showing non-linear curve, no labelled dimensions

Source Wikipedia

For example, in the music industry, no two songs are the same. So we are not in a factory situation where we strive to make each product of a uniform set of characteristics. This is directly to do with the definition of organic work highlighted so far. It is due to the lack of complete control by the artist over the quality and value of the work they produce from the perspective of an audience. They are not in a factory. As 'creatives' they are riding an elephant, that has great powers, but doesn’t always produce the goods. Even a great artist David Bowie, couldn’t write another song like Is there Life on Mars? on demand. And so, when we look at the monetary or other value of musical works such as songs, we see a ‘power law’ distribution. It is ‘non-linear’ when graphed, such that the vast majority of songs make very little return in terms of sales or plays on radio and TV, etc. However, a small minority that are often very hard to predict, will make a great deal of money which would be the values to the left of the graph above.

In other creative industries it is also the same story. Movies, musicals, book publishing, etc, all are, at their core, producing organic, creative work, and so showing this power law distribution due to the organic nature of their production. The creators are not in full control of what they can produce. A lot of it is down to serendipity, inspiration, luck, chance collaborations and external intervention and events.

It is also the same in research institutes, such as universities, where we see a power law distribution of citations of research papers. This has significant knock-on effects when trying to manage the value of researchers, because one shouldn’t expect all researchers to have similar outputs, just as one shouldn’t expect all musicians to sell like Ed Sheeran or Adele. Like the creative industries, research is about trying to produce things that are hard to reliably predict or plan in advance. The phrase often heard is: ‘If I knew what I was doing it wouldn’t be research’. This affects how we manage and stimulate research, and how we frame research grants and manage people who ‘under produce’.

However, it is thanks to research in biology by complexity scientists that we know that this power law distribution is often a key characteristic of biological, organic systems. Therefore, we can use this information to trace how this affects the management of organisations that are based on organic work and understand how to manage the knock-on effects of organic work.

· In creative industries such as the music industry the power law describes the return on value of work. Managers then need to better understand the best ways to manage, artists, repertoire and data that is of highly variable value.

· In Biotech and Pharmaceuticals the biological component concerns both the research problems themselves, and the nature of the biological systems being studied. Neither behave in predictable and reliable ways. Therefore, returns on research investment is subject to the power law.

· AI or Machine Learning companies are also subject to this, due again, to both research problems, and also due to the fact that machine learning is based mostly on analogs of biological systems, with feedback loops, ‘black box’ characteristics, and so not fully predictable in their behaviours or outputs. Further, the way they may be used when released commercially, can also be highly unpredictable.

· Art Schools and Places of Learning for Creative Skills are where creative people go to learn how to be creative, in other words, how to harness organic work. Therefore, again, no two students can be taught or assessed in the same way, and the perceived value of their work by audiences is likely subject to a power law distribution.

· Hospitals and Therapeutic Centres are also places where the organic, this time in the form of disease and ill health interact with human organisation. In this context, no two patients are identical, and it is normal for there to be ‘co-morbidity’ (an intersection or 'coincidence' of multiple separate pathologies in a single patient). Further, the risks of interventions are subject to a power law. A very small number of cases may be subject to catastrophic harms by interventions by health professionals.

Other key signs of organic work, explained via biological research

Complex feedback loops tend to govern processes in organic work

In biological systems, complex feedback loops tend to emerge from natural processes of growth, adaptation and regulation. Examples are in the case of metabolic pathways, or in the case of gene regulation or signalling pathways for cellular communication. Hence, organic work which is subject to less planning, more unexpected knock-on effects, etc, tends to be controlled better by complex feedback loops than simple assembly line type processes.

· In technology, synthetic organic examples of AI and machine learning are areas, where as we mimic organic systems, feedback loops are fundamental to how the technology works. As a result, specific risks related to this predominate, such as unpredictable outputs, of unexplained reasoning of unknown reliability. As we introduce this technology into our organisations, the complexity and skills needed to manage and control these feedback loops and utilise recommendations and outputs by AI and machine learning suddenly become vital to many organisations that would not have experienced managing organic work in the past.

Examples are too numerous to mention, but self-driving cars in the automotive industry is an obvious one, Chat-GPT is another.

· Such feedback loops often become important in managing complex work, such as working with large technological systems. In the technology industry this has led to the development of a culture of ‘agile working’, which depends on making small changes or experiments and responding to feedback. However, managers in the rest of the business are less familiar with the reasons for introducing such feedback loops and uncertainty into their processes and management. Without explicilty recognising that this is organic work and should be informed by understanding of biological systems and relevant metrics, too often agile work is misunderstood and managed badly within the technology sector, too.

Organic work is often part of an ecosystem with uncertain value of relationships, changing relationships

The ecosystems of creative industries demonstrate how important networks of relations are in organic systems. This is also a commonplace of biology, that genes, cells, organisms are all part of a complex network of relationships, or, in fact, part of a network of networks. As a result, it is far less clear which relationships are important than when compared to even a complex machine like an aircraft engine. Also, relationships are also subject to a lot of dynamism and change, requiring methods of management suited to this.

· Examples in the music industry are fluid and increasingly numerous collaborations between artists, between artists and record producers, and relationships between artists and their managers and entourage and record company executives and labels.

· In AI and machine learning, uncertain relationships emerge from the nature of the system. Examples are systems that ingest large amounts of data from the internet on which training is done. It is then very unclear what information or copyright may have been violated if any, because the lineage of inputs to outputs is a ‘black box’ rather than being transparent. This is a simple result of the organic design of the technology.

· In many industries, the ESG (Environmental, Social & Corporate Governance) agenda, and in particular, climate change management are highlighting the ecosystem in which organisations are embedded. As a result, the outlook for organisations is to manage, what are effectively organic relationships. However, managing the relationships in this ecosystem requires the recognition that such complexity is indeed inherently organic, as relationships are uncertain, and the value of interventions within the ecosystem is often unclear and unpredictable. In addition, ways to incorporate goals into primary value creating activities are inherently uncertain, and do not respond well to mechanical metaphors by management.

Summary of increasingly important industries, built on organic domains

Types of industry that are affected by organic work are growing, and are firmly in the organic domain, built on organic work:

· Creative industries

· Biotech and Pharmaceuticals

· The Research Centres of Universities

· AI companies

· Art Schools and Places of Learning for Creative Skills

· Hospitals and Therapeutic Centres

Kinds of organisations moving into the organic work domain

Kinds of organisations moving into the organic domain, with more and more organic work:

· Technology-centric, AI impacted

· ESG sensitive and Climate Change affected or affecting

Organic Intersectionality

Finally, it is worth noting how many organisations are organic through multiple intersections of organic work. E.g. PPL in the music industry, is managing organic work because it manages the repertoire and licensing of recorded music by artists. However, it also is working in a highly technology focused, complex environment. It is part of a complex evolving ecosystem of data sharing and music collections globally. In addition to all this, it is also getting involved in the technology of AI and machine learning for its own use, and also in being invovled in the wider conversation of AI and machine learning as it affects music. Finally, since the Black Lives Matter movement, PPL is increasingly concerned with the its ESG contributions both in society and the environment.

What are the implications of managing a more organic organisation?

More organic work requires that we manage such work organically, with organic solutions to organic problems, just as, by crude analogy, you need horsemanship skills rather than a driving license to successfully ride a horse.

· Training in how organic work feeds through in your organisation and what it means can be provided.

· Training your personnel in organic metaphors for management can be provided.

o Jonathan Haidt’s book 'The Happiness Hypothesis' provides the relevant analogies for organic systems.

The concept of organicity is made more concrete in this article by Turing Meta

o Invoke the book ‘Trying not to Try, by the researcher, Edward Slingerland applied to your own mind, but also as a metaphor for leaving space for others.

§ There is the simple example in an organisation of this, of sufficient contingency in plans.

· Don’t try to use all the available resources. Leave room for organic processes to work. They also have agency.

· For organic work, such space can have an upside, rather than simply using up spare resources.

· Training in organic solutions to delivering complex work can be provided.

o An example of this, is not making big decisions as managers, but many smaller decisions, with the right info.

o Further training in recognising appropriate management, metrics, etc. can be provided.

o Some major examples of metrics and concepts are on the Turing Meta website:

§ Modelling organic work for qualitative understanding, not prediction or planning.

§ Option Farming

§ Agile Working, done scientifically

§ Understanding False Fitting

The PDF of this article is available for download here

How to Recognise Organic Work in Your Organisation and Why
Download PDF • 329KB

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