Predictable Imbalance; The Hard-Wired Nature of Efficiency

If you are reading this, chances are you will have heard of the Pareto Principle. My aim is not to provide you with another run of the mill article on how you should identify the most critical 20% of what you do to yield 80% of your results.

No, although I will make mention of it later.

My aim is to reframe the 80/20 rule for you, to help harness the nature of the original theory from Vilfredo Pareto. It’s about ways, as curious people, we can think less linearly and a little more interconnectedly about our research and processes.

The 80/20 Principle is pretty easy to apply, but it is hard to predict

Here’s an example of the 80/20 rule in action:

PROMPT: Good morning Horace! Could you please describe the Pareto Principle 
to me, in a way I could use as a few sentences in a blog? 
 
OUTPUT: The Pareto Principle, also known as the 80/20 rule, suggests that  
roughly 80% of outcomes come from 20% of causes.  
This principle can be applied across various fields, like business,  
where 80% of sales often come from 20% of customers, or time management,  
where 80% of productivity can be achieved with just 20% of focused effort.  
By identifying and focusing on these critical 20%, one can optimize  
efficiency and effectiveness.

[Yes I call my Capacities AI ‘Horace’; and yes I asked first.]

Fantastic, now we can all understand the 80/20 principle in a way that has been forged by the words of millions of people gone before us, and in a way that saved me a decent amount of time. No use reinventing the wheel here.

A comparatively simple concept, the reality is that this principle revolutionised businesses in the 70’s and 80’s. And the other reality is, that as curious people, we feel we do need to reinvent the wheel. We aren’t looking at what has gone before, we are interested in what will come and what we don’t know yet.

[On a side note, old research papers are a gold mine of ideas and curiosities, and should make us realise a. how much they understood about the world 100–150 years ago and 2. how many of their questions still go unanswered today…]

The Pareto Principle is a static observation in time. But the numbers which form it have a past and a future. Think of it like a peeky window into the complexity, efficiency and organisation of a system.

Richard Koch, author of ‘The 80/20 Principle’, suggests that this principle has its roots in chaos theory. The universe, it seems, doesn’t operate linearly. Even a slight imbalance tends to amplify itself, but tantalisingly this imbalance creates a predictable disproportion in outcomes. The Pareto Principle as we see it now, has its roots long ago in a small few percentage points change that happened x time ago. Kind of like a snowball effect, but if we can identify the cause, it’s predictable.

What do the ecologists — and me — think?

Natural world scientists frame the Pareto concept slightly differently. They use terms such as ‘Pareto-efficient’ and ‘Pareto-optimal’. These terms describe systems where resources are used so efficiently that any reallocation would negatively impact the outcome.

In other words, its nature’s way of maximizing results with minimal waste.

This efficiency often manifests as “complementarity effects” in ecosystems, where the whole becomes greater than the sum of its parts. It’s a beautiful dance of interconnectedness that often leaves us in awe of nature’s ingenuity. And it’s flipping difficult to understand.

But that’s partly because we a wired to think linearly, where a causes a proportional change in b, or if we change c by this much, we’ll get this output from d.

[Write every day, they say, on social media, they say, and you’ll be rich in 6 months, they say — this is linear thinking. Input = output. But it depends on what is actually limiting you in the first place.]

To a certain extent, the Pareto Principle is about identifying the most important limiting factors — not just any limiting factor, but the most important limiting factors.

In many natural systems, nitrogen is a limiting factor; apply some nitrogen to a natural system and you’ll see the Pareto Principle in action. In many also, it’s water. Having enough nitrogen available in the soil, is actually one of the main constraints for soils to sequester more carbon from the atmosphere.

[And no, before you suggest ‘let’s just add nitrogen to the soil and we’ll solve climate change’, rather ironically, nitrogen fertiliser production is one of the biggest producers of greenhouse gas. Legumes, through symbiosis, fix nitrogen directly from the atmosphere and are a better option. So eat more peas, beans, lentils and peanuts, seriously!]

I think if we can identify the most important limiting factors at any point in a system, then we can harness the future ‘predictable imbalance’ the Pareto Principle explains. And likewise in science, we can work back in that respect.

The Pareto Principle in action

For curious people like you and me, it can be challenging working out what an 80% result looks like. Is it that we learn more? Or write more? Or think more? Publish more?

Maybe. It’s also about understanding cause and effect.

I have been giving it some thought recently. I have, for example, realised I take too much time transferring the notes I make on paper copies of articles into Capacities. I need to find a way to reduce this time. There is absolutely no point in me trying to read more, if I can’t transfer this information quickly to where I need it. This is a more practical example, but how can we use the principle within research more holistically?

1. Embrace imbalance: Rather than fighting against uneven distributions, recognize them as natural and potentially beneficial. Ask yourself: “Does this element add to system organization or disorganization?”
2. Focus on complementarity: Look for ways your research components can complement each other, creating a whole greater than the sum of its parts. This could apply to methods, teams, and even interdisciplinary approaches. Don’t just get someone on board because they are a ‘very important person’, ask what they contribute.
3. Identify ‘leverage’ points: Recognize the things that will have disproportionate impacts. Prioritize identifying and acting on this stuff. Look at others ahead of you to help gauge what to aim for.
4. Gradual improvement: As James Clear says in ‘Atomic Habits’, aim to get 1% better every day. Trust that the Pareto Principle will amplify these small gains over time. Even if all I do is aim to improve my average note-making speed a little each day, I can rely on predictable imbalance to do the rest. [What of course is better in this particular example, is tackling some bigger wodges of time because it has cascading impacts to other aspects of my work like reading and writing].
5. Optimise resources: Consider how you can achieve Pareto-efficiency in your research process. How can you allocate your time, energy, and resources for maximum impact? Are you Pareto-optimised? If someone else had the same resources as you, what would they do differently?

And what about how we can apply the Pareto Principle in our real, nitty gritty research work?:

1. Experimental Design: Consider any system you’re studying as self-organizing. Design experiments with this in mind, focusing on scale, the most important causation factors, and likely impacts. This approach can help you identify the vital few variables that drive the majority of effects. Also use it to think in reverse.
2. Data Analysis: Expect non-linear relationships in your data. Look for the factors that disproportionately explain your results. These are your 20% that will likely account for 80% of your findings.
3. Results: Identify the 20% of your results that tell the most important story. Focus on presenting these in your graphs and tables.
4. Discussion: Spend about 80% of your discussion section exploring the implications of your most significant findings (the 20% you identified earlier).
5. Time Management: Optimize 20% of your week for directly tangible outputs, such as creating important graphs or writing key sections of your paper.
6. Networking: Aim to maintain meaningful relationships with about 20% of the people you connect with professionally, especially those at a similar career level.
7. Flexibility: Know it may not always end up exactly 80/20. It could be 70/30 or 90/10. The principle is a guideline of minority cause to majority effect, not a rigid rule.

By thinking about these strategies, we are not forcing efficiency necessarily — we are instead ensuring we align our seemingly chaotic work behaviours and thoughts, to embrace the natural tendency towards organization and impact.

Rest safely in the knowledge, the Pareto Principle will carry us to Pareto-optimal conditions with any actions we take everyday. Remember nature has had 4.5 billion years to get to Pareto-optimal status so I think we’d be forgiven for thinking it may take us a little while to get there. But an understanding of how to get there faster, by tackling the most limiting factors and understanding the unbalanced impacts of causatory factors and what we do and end up with, is what can set us apart.

To summarise, don’t worry, just do you! Because natural systems are hard-wired for unbalanced efficiency, you’ll get there someday. No need to go and crazily streamline all your dashboards. Know building and optimising things slowly will get you there in the end. Just focus on the things that limit you most first and you’ll get there a bit faster.

Hope this helps you in your research! If you liked reading this and are interested in more nature-inspired research learnings, I publish a weekly newsletter on Substack. I’d love for your support.

👇 Sign-up below:👇

🧠 Brain STREAM | Knowledge Ecology | Substack

Thinking, as inspired by the natural world. Click to read 🧠 Brain STREAM, by Knowledge Ecology, a Substack publication…