The Tao of Systems: Stocks and Flows

The Universal Tendency to Drift

Every once in a while we find ourselves in a place where we need to change something in our lives. We make a resolution - as befits the beginning of a New Year - and usually one of a few things then happens: we pursue our resolution with too much enthusiasm and are quickly met with an injury perhaps or rebuttal of some kind, forcing us to put off our plans. Or, after an initial show of good results we plateau and soon get bored. Often we find ourselves drifting back to our old ways. The resolutions slip, the discipline wanes.

Or, we may be in a situation that needs changing - a job, a relationship, a cycle - but can't seem to break out, no matter how hard we try. ‘We don’t rise to the level of our ideals, we fall back to the level of our systems’ goes a recent saying. We might begin to imagine that the fault is somehow with us. That we lack some inherent drive, some crucial ingredient, hence our 'falling' back. Yet perhaps the mistake we are making here is that we are assuming that we are outside or 'above' the system. We are looking inwards when we could be zooming out.

We may see a successful person, a high achiever, or someone who managed to quit a destructive habit, and assume they must have vast reserves of willpower. If only I had some of that we might say. What is their secret? But we are missing two important factors here. The first is the support system that these folk have put in place - which may include the friends, community, team, finances, the personal assistants, the time and so on. Secondly, what these individuals have often established are simply positive feedback loops; finding something they wanted to do, getting some reinforcing feedback and using this to accrue a sustaining cycle. This, more than anything else, is the source of motivation. 

Thinking in Systems

The idea of systems, as a discipline in itself, has been around for around a century. Of course, humans have been ‘thinking in systems’ for far longer than this. Neolithic structures like stone circles are evidence that our ancestors were living in a system-oriented way for millennia. Yet in the past hundred years ‘systems theory’ has been formalised by biologists, mathematicians, computer scientists, engineers and so on, to try to model features common to a vast array of disparate systems - weather patterns, economics, city planning, health, pretty much anything. What is a system? An authority on systems theory, Donella Meadows, describes a system as ‘a set of things - people, cells, molecules… - interconnected in such a way they produce their own pattern of behaviour over time.’

Thinking in terms of systems can be different from traditional ways of thinking, which often involves tracing paths from cause to effect in straight lines and breaks reality down into small and understandable pieces. It can challenge common sense assumptions. For example, rather than regarding, say, an addict as a self autonomous agent responsible for their choices, it understands addiction as something inherent in a system. It’s futile blaming a politician for a recession as these are likewise inevitable behaviours of a certain system. Unfortunately in popular discourse and social media the blame game still runs riot, restricting our understanding of the true causes of our various ills.

Viewing the systems rather than the parts often turns causality on its head, opening up new possibilities. Does eating too much make you overweight or does being overweight make you eat too much? If so, how does this happen and what can be done about it? Am I failing to get fitter / healthier / happier because I’m not working hard enough, or actually because I’m working too hard, but pushing in the wrong direction? Why do attempts to fix a problem often make it worse? 

Another key benefit of systems thinking is that the basics are relatively straightforward and don’t require any specialist knowledge to understand. You can grasp the fundamentals in an afternoon and then have fun applying them to whatever you like.

Stocks and Flows

‘The world is a collection of stocks along with mechanisms for regulating the levels and manipulating flows’. While this statement is unlikely to provoke mystical awe or appear on a tea-towel it does neatly sum up the core ideas of system thinking. We’ll start with stocks. 

A stock is the thing or memory of the state of the thing that the system is attempting to conserve. It can be physical such as a body of water in a reservoir, or psychological such as well-being, or even a mixture of things like physiological reserve - the body’s capacity to withstand stress and survive. Another way of regarding the stock is as the thing that is present before time begins acting on it. When the time element starts, we now have flows.

Stocks are connected by flows. Again, flows can be physical - a stream, cups of coffee sold, traffic on the road, heat leaking from a room - or they can be information. Information can be virtual, like computer data, or encoded in something physical like money or DNA. 

A basic stock and flow diagram. The ‘T’ shape represents a tap to symbolise how flows are increased or decreased. Of course, any given stock will be connected to any number of other stocks, with multiple in- and out-flows, extending ad infinitum.

A simplified systems diagram is based on a stock with inflows and outflows. If the sum of the inflows is the same as that of the outflows then we have dynamic equilibrium. One of the less obvious features of a stock is that it can appear static, yet be in a state of continual flux. For instance a reservoir may appear as an unchanging body of water, yet have millions of gallons flowing in and out every minute. Similarly the human body regenerates most of its cells and tissues over the course of months to years (with the exception of neurons). You literally have changed (mostly) in the past decade!

While we can get a good idea of the size of any given stock by looking at it, we often underestimate the momentum of a stock. Stocks may have been increasing or decreasing for a long time beneath our awareness before crossing some threshold, triggering some action. We can then be surprised at how long it takes to return to ‘normal’ levels. This is because while the in- or out- flow of a stock can change quickly the stock itself does not change so quickly. Invariably there is a lag. Examples include:

• turning a tap on full blast yet the bath will still take time to fill

• a new government / management takes charge yet the promised changes may take years to come to fruition (or damage from previous administration to show)

• you take a holiday after a stressful few months only to find your stock of stress has only just started to drain by the time you return to work

• I start physiotherapy for my back pain and am disappointed when I realise it’ll take weeks to month to correct the imbalances and build the stock of strength to full functioning      

  
  

It is important to note that this slow momentum of stock can be a source of stability as well as frustration.

Stock and Loops

To complete our simplified model, systems also have feedback loops which maintain the stock. Often there is an ideal level of a stock, which in turn implies a way to perceive the level of the stock. This is not always the case. A cooling cup of coffee could be seen as a system, with the ‘aim’ of reaching the same temperature of the room, and the loop in this case is simply the discrepancy between the coffee and the room temperature, but in complex systems there is usually some mechanism for perceiving the stock.

A physiological example is the ‘hypercapnic’ drive involved in breathing. When carbon dioxide levels increase in our bloodstream, say if we’re exercising, this is detected by receptors which then tell the nervous system to stimulate deeper breathing in order to blow off the CO2. Once blood CO2 returns to expected levels the mechanism settles down. A balancing feedback loop. Some feedback loops are reinforcing. This is when a stimulus sets off a loop which is able to reinforce itself each time, eventually leading to a cascade effect. The human body has a few of these too, but are always set off alongside balancing loops which eventually bring the systems close to balance.   

It is worth recalling that the classic stock and flow diagram is a simplified model of reality only. It allows us to focus on any given system, describe a stock, look at the flows, find patterns of behaviour and even uncover any goals or functions (often the most important, yet hidden, part of a system). Whichever system we chose, whatever boundary we want to put around the system, is a matter of convenience. In reality there is never a single system acting in isolation. Everything is indeed connected, but we need to draw limits or be completely overwhelmed. 

Delays and Oscillations

A pattern of behaviour which is almost universal across systems is the tendency of stocks to oscillate, to fluctuate between big and small, lots or little, fast and slow, often cycling between them before stabilising. An example would be a population of rabbits, breeding rapidly and growing in size (in a classic reinforcing feedback loop) before dying off from lack of food. The food supply is restocked, the rabbits begin to breed again and so on, until usually some kind of stability is achieved, often involving the interplay of other systems such as predators. Other examples might be the boom and bust cycles of capitalism or the all-or-nothing behaviours of the addictive personality. My ‘fitness’ stock tends to oscillate dramatically between zero and quite a lot of exercise. Is there any way to break this pattern? 

The Power of Less is More

One of the most obvious ways to avoid fluctuations like this is to keep an eye on the stock, not just the flows, to try and avoid letting a stock get too low or high. This really boils down to the common sense advice to tackle problems while they are still small - ‘a stitch in time saves nine’. There is another way of damping fluctuations and this is a bit less intuitive. When we do notice that the stock has drifted off course, rather than reacting quickly, the evidence actually suggests that slower reactions lead to less oscillation. 

To illustrate how delays cause oscillations we could imagine a cafe owner trying to maintain a stock, an inventory of coffee beans. Let’s say there is a sudden influx of customers. The stock suddenly dips. The owner may react by calling the supplier for an extra delivery. Meanwhile the customers keep coming and the stock falls further. The order has been made but it takes time for it to be sent out. A point worth emphasising is that stock will continue to change even after it’s been noticed and the information can only affect the future behaviour of the system. Delays are inevitable. Meanwhile, the flow of customers has returned to a steady trickle, just in time for the delivery to arrive. There are now too many beans, so the owner has to hold future orders. The stock once more goes down, then down some more until…and the cycle repeats.

A common cause of oscillations has been shown to be actually acting too quickly on a perceived change in stock.  This sounds paradoxical, but experience provides many examples such as the hasty car driver who accelerates whenever a gap opens up in front of them before braking suddenly and doing this over and over. We might also include  impulsive exercise routines, crash diets, ‘never again’ promises, and so on. In such cases, overall momentum of stock over time is a more useful guide to action - or watchful waiting - than reacting to what the current flow is doing.

Obviously it takes some fine tuning to find the Goldilocks zone of reacting to changes. Responding too slowly can cause the stock to reach a threshold (which can be too low or too high) beyond which it is hard to correct. For example, doctors often advise patients who suffer from migraines to get in early with the painkillers in order to vanquish the headache before it takes hold, often requiring far more analgesia.

Perception delays can sneak up on us, especially if we are distracted by other priorities. Inexperienced marathon runners are prone to collapsing mid-race, the reason being they weren’t drinking enough fluids, because the ‘thirst centre’ in the brain is actually quite slow to perceive the sudden demand for water. An incremental increase in demands can also sneak under the radar of our perceptions. A classic example is burnout, where our stock of well-being, patience, joy..etc is gradually drained and we don’t realise the deficit until we’re running on fumes. 

Once the stock has been depleted (or accumulated) in this way it can take a long time to restore to an ideal level, often far longer than anticipated. A fortnight on holiday or half decent night’s sleep, or new medication usually isn’t going to do it. This can be demoralising, we might feel that nothing’s working or blame ourselves for not being resilient enough, but this is to lose sight again of the inherent momentum of stock, which always moves slower than the flows around it.

In summary: Systems can be regarded as stocks with in-flows and out-flows, and feedback mechanisms that aim to maintain the level of the stock. Fluctuations in stock are inevitable and are often due to delays in information flows. However our actions can often exacerbate these fluctuations, causing instability. We might not be paying enough attention to the momentum of the stock or reacting too quickly to perceived changes. Robust systems are sensitive to the momentum and flows of the stock. They avoid letting stocks get too low or high, but if this does happen, as it will do in the real world, they have ways of dealing with this. They have redundancy built into the system; a ‘just in case’ rather than ‘just in time’ mindset.

Delays in perceiving issues with our stocks, momentum of stock versus speed of flow, oscillations…these are just a few of the ways systems can surprise us. Yet, by recognising that these are patterns inherent in systems, some of which we can control, we can hopefully avoid falling into the traps of blame and frustration. In order to change a given thing, consistency in small amounts is more effective (and less likely to result in boom-or-bust fluctuations) than dramatic leaps. Which I will remember when I eventually get around to making my New Year resolutions.