COVID + drunk park-goers = a great example of how systems thinking can help technologists
By: Vikram Singh
Tags: Systems Thinking, Design Thinking, Coronavirus, UX, Design

One frustrating aspect about working in digital technology is that your ability to make an impact is limited by a rather constricting medium. All you have as your tableau is a computer or a mobile phone. The way that you go about understanding a problem is necessarily through the purview of a screen.

Not only does this force the problem into a space that isn’t always applicable to addressing the problem, the problem you are trying to address often doesn’t even have a neat centre to be addressed. Even thinking of what you are trying to address with your designs as a problem is uh…problematic.

Simply put, there’s limitations to how technology can be effectively applied given that human problems are spread across different dimensions.

By pulling out and viewing the problem space we can get to grips to with the limitation of technologies in the face of the complexity of the problem space — and even highlight unexpected areas where technology could possibly make a positive impact.

To grasp this, we can conduct a systems mapping exercise. As an example, let’s take some of East London’s parks.

East London has had a problem with its parks, in that there were too many people in them. And too many of these people were drinking too much. This happened because bars and pubs closed due to coronavirus, and parks became the go to place for having a drink or 7 with your friends.

This is a ‘systems problem’. Indeed, all problems are. Systems problems involve factors others than those that are immediately relevant to the problem itself.

So, let’s think of people who go to the park to be with their friends as flows. The naturally flow into parks, or anywhere that you can have a drink with your friends. The problem is parks have a total carrying capacity. In this case let’s focus on Haggerston Park, Victoria Parks and London Fields. I should add that I am acutely aware of the parks I am describing here because they’re all in my lovely East London neighbourhood.

In the diagram below, the circle’s solid colour represents how full the park is, the circle’s border represents how porous the park is (i.e. the rate at which people were entering the park), and the arrows represent the amounts of people finding a place to drink with their friends.

I’ve borne witness to the parks filling up more than usual. Victoria Park is very large, but even it was filling up after coronavirus hit.

But, rather suddenly, Victoria Park closed its gates to all park-goers. People were flaunting the social distancing rules and getting too close to one another.

It’s easy to imagine what happened next. People were diverted away from Victoria Park to two other nearby parks. In this case London Fields and Haggerston Park. That is, the flow stayed the same but the total carrying capacity of the parks in the area decreased.

This put pressure on other parks and their capacity began to get full up.

Over time, Victoria Park reopened, and people were allowed back in, releasing the pressure on other nearby parks. Except by now, something had happened. The rules had changed and you were allowed to meet up with multiple people (as long as you stayed a certain distance away).

This incentivised people to go to the parks. The flow was drastically increased as people felt there was a stronger reason to go, yet the park capacity remained the same. The loop reinforced itself. The amount of people going because of the relaxed rules made more people go and because those people had friends, they could all go too.

So even though Victoria Park was reopened, the amount of people increased and the effective pressure on the parks remained the same or increased.

This in turn increased the usage of toilets and the flow of garbage given the higher number of people in the parks. This is especially true of London Fields, which is a hipster hangout.

This rightfully pissed off local residents who found themselves facing people urinating and doing other worse things in and around their homes. Huge amounts of garbage piled up across the park. Public tolerance for the inflow of people dropped.

Let’s add more parts of the system to reflect this.

So what happened? In an effort to disincentive people from going to London Fields, drinking in London Fields was banned!

Did this solve the problem?

Well, people were disincentivised to go to London Fields. But people were now diverted from the now unattractive London Fields to anywhere nearby. Flows were simply diverted elsewhere, again.

Because there were no convenient parks nearby, people started heading to the streets to drink and be with their friends. The same thing happened in Soho, where pubs opened, but space is limited — so people went to the streets.

The behaviour of the system was not effectively changed. So the public was happier — but only temporarily. Soon their streets began to fill with drunks and their, uh, leavings.

The quagmire seems endless. People need to go somewhere but their moving impacts the system in other ways. Every action has a reaction.

We could try to increase the amount of public space for meeting and drinking with friends. This may be very difficult to do, however, and would have other impacts on local residents, as we’ve pointed out above. In any case, increasing capacities is a less than prime solution for any system. Donella Meadows, one of the most important systems thinkers, calls these ‘buffers’. She argues that these are the worst way to change a system because they don’t actually change the behaviour of it.

So how can systems like this change fundamentally? How can we change a systems behaviour? Through technology? Is there any tech that could help with this?

Well in order to understand how technology can help we have to understand take on what we’ve learned here: the problem has no centre to solve for, and imposed solutions create new problems.

Technology by itself cannot do much. It can’t increase the space in parks, or the amount of garbage that parks can handle or the amount of toilets the parks can support.

But what mapping this out does it allows to examine the connections between problem spaces and understand how impacting one area may impact another. Solutions can be examined in terms of how they would impact the larger system. Only from there can we imagine how technology could impact this system.

What if we tried another of Donella Meadows’ solutions, adding a feedback loop? She describes feedback loops as a part of a system wherein increasing inflow will increase outflow and vice versa. In this case, we balance the amount of people going in to a park with those going out. Technology could help. An app that allowed for ticketing, or that showed the speed at which the flow was moving would help users. Well, it might change the rates of flows, but likely wouldn’t change the system — at least not in any immediate manner.

A stronger method for changing system that Donella Meadows describes is altering information flows. This is an area where information technology is — predictably — at its strongest. We could we warn users not to go to certain parks that were being overwhelmed. We could highlight issues that may affect the potential park attendees such as the fact that fines will be given out for people littering, or that the toilets have exceptionally longs queues. Something like this may help.

This, of course, would require the user to get this information (by downloading an app, etc) and care enough to take action. This is also where enormous amounts of app and information technology initiatives fall down — the attention economy and privacy issues create a quagmire for locally relevant information — it simply can’t keep up with the billions of pounds that tech savvy business can mobilise to compete with local initiatives. And would this actually ‘change’ the system behaviour? Maybe somewhat, but people still want to drink with friends, and still need space to do so.

And indeed, any technology would only create more changes to the system that have to be adapted to. The system cannot be separated from the issue. The ‘issue’ isn’t an issue at all but interacting parts of a system. And what I’ve described here only constitute a minority of the system.

Other factors of the system may include the psychological (evaluating the coronavirus rules), semiotics and semantics (signs, icons in parks), culture (what rules mean to people, drinking culture), environment (weather, transportation), biology (drunkenness, health), mental state (anger, loneliness), skillsets and knowledge (knowledge of coronavirus regulations), the economic (other options for people) and many others.

But understanding the system and respecting a system is a vital first step. Only then can multi-dimensional approaches be put forth to alter the system.

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