• Shane Thomas

Powering Agriculture with Systems Thinking

Updated: May 30, 2020

Most people have been taught over the course of their lifetime to see things linearly. We see things in a cause and effect fashion. We learn about a beginning and then an end. We see a problem and then a solution. From every action brings a reaction.

We simplify things so that they fit into this model of thinking. We see two variables out of the many involved in any situation. This is considered linear thinking.

The problem with linear thinking is that it is too narrow. It ignores complex systems and instead focuses on one aspect of a system. Reality says that there is much more to consider at any given time than a start and finish or singular cause and effect. Yet linear thinking leads us to believe that is all we need to know or understand.

To me, linear thinking is product thinking in traditional agriculture. Not product in the sense of how Silicon Valley thinks about the utilization of their digital product, but from an agronomist, salesperson or farmer perspective where the solution is looked at simply as the product (eg: fungicide or herbicide) to provide one specific outcome.

Applied to Farming

In farming we have long thought about improving output with the mindset that there is a silver bullet. As agronomists, we want the one product that will increase plant health, reduce disease, increase yield, quality and profitability. And products in farming have traditionally been marketed in this regard. Use product x achieve y outcome. For example, spray your herbicide, weeds die, yields go up. Simple. The reality is that it has never and will never be this easy. Crop production is a system, with the need for long term thinking. Organizations in the crop input business have known this, building out marketing systems that layer together supplemental products to one another.

Digital Technologies

Digital technologies are complex. When we talk about digital platforms, we are talking about numerous tools and technologies that are integrated into one “product”. As an industry we are trekking further down the road of digital technologies. Systems thinking has always been required, but with digital technologies being layered onto farming and production, systems thinking has never been required more. Digital technologies are not a “one and done”, they require a systematic approach to using all layers of a farm operation or agribusiness.

What is Systems Thinking?

To define a system first, it must be both dynamic (constantly changing) and evolving. It must be connected to elements, actors, agencies, nodes, stocks or ‘parts,’ and have a boundary.

To apply systems thinking requires considering what can’t be seen. Systems thinking expands the range of choices available for solving a problem by broadening our thinking and helping us articulate problems in new and different ways. Systems thinking also requires second order thinking. The ability to think beyond the initial need or problem at our feet.

The principles of systems thinking make us aware that there are no perfect solutions; the choices we make will have an impact on other parts of the system. By anticipating the impact of each trade-off, we can minimize its severity or even use it to our own advantage. Systems thinking therefore allows us to make informed choices. When we begin to consider this within the context of complex topics like sustainable practices, it is very apparent systems thinking is necessary.

What is Product/Linear Thinking?

Linear thinking is the process by which we put things in order as we experience them. Thinking process proceeds in a sequential manner, like a straight line. A straight line between two points is the most efficient way to get from one place to another.

Why is This Important in Agriculture and Farming?

The linear or product thinking approach is challenging for agriculture because everything is interconnected; sustainability, profitability, one season to the next season and 5 seasons after that, fertility rates inherently impact plant and root health which changes the dynamics of disease susceptibility and therefore needs for fungicides which have further impact on fungi in the soil and so on. Everything needs to be considered in the context of a system. On top of this when we layer digital technologies on, the approach to them as an agribusiness or farm needs to be considered around how it will be integrated into the business in terms of objectives, processes and execution.

Where to Start?

Shift your mindset. A few years ago, I read a piece on systems thinking that had a great lay out and fits well within this post regarding the pillars of systems thinking:

1. Interconnection – Everything is interconnected in some way, shape or form. A plant is not a plant. It relies on medium, sunlight to run the process of photosynthesis, nutrients and water obtained through the medium to enable and so on.

2. Synthesis – The ability to integrate and grasp the interconnection together. Thinking through the different components and how they are connected and why it matters.

3. Emergence – From simplicity and smaller parts, larger, more complex systems can occur. The quote I wrote in my notes was that “nothing about a caterpillar tells you it will become a butterfly”.

4. Feedback Loops – These occur in biology, but it is how the various components of a system influence one another, positively or negatively. If the loop is positive, then the system gets stronger. In ag this might be as simple as when I apply more Nitrogen, I get more yield, so the next year, more nitrogen is applied to get even more yield until a negative feedback occurs, such as lodging. To take this a level up one might consider how to integrate data and machine learning, or digital tools within this context to supercharge that feedback loop and ensure that it optimizes the system accordingly.

5. Causality – Within the context of the feedback loop, what is causing the good or the bad or the system to operate more efficiently? For embracing digital tools on a farm or within an agribusiness, what is causing the friction? What decreased the friction and increased uptake and how do you integrate more of that into the system?

6. Mapping – This could also be known as a workflow of sorts in the way that you think through the entirety of the system to ensure all aspects of it as working in accordance with one another.

From here you can identify the goal of the system. This at a macro level might be “being sustainable” or maximizing yields or profits or eliminating the biggest challenge on one’s farm but starting much smaller and identifying the smaller systems and first principles then building up will provide better opportunity to reach those macro goals over time. Eg: implementation of a sound integrated pest management plan to tackle the pest challenges that have been occurring.

One Example:

With Plant Growth Regulators these are often thought of within the context of the current crop input system and as a bolt on. However, where they become a powerful tool for agronomists and farmers is through what they allow you to do within the system of crop production.

PGR’s have an influence on the entirety of the plant physiology, but primarily the focus is on what they do to the stature of the crop decreasing height and therefor, often lodging.

But the goal isn’t to shorten the crop, the goal is to maximize production. Two very influential aspects of production, and lodging, are variety and nitrogen application.

If we have the tool to shorten the crop now, we can select a variety that might be more fit for our region. In many instances, a shorter stature wheat variety is chosen to manage lodging. But sometimes these varieties might not be the highest yielding option or have the best disease resistance. Now, that I can better manage lodging, I can choose a variety that might yield better given my area and have a higher disease resistance to fusarium head blight.

On top of this I might have been applying less nitrogen to manage the lodging. But now that I can better manage the lodging, I can look at was to apply higher rates of nitrogen to increase yields without having to worry about harvest challenges and yield losses due to significant lodging. Now consider this in the context of a digital tools being layered in to understand how to apply the plant growth regulator in a VR format, identify the stage or utilizing modelling and utilizing N models to determine when and what rate of N to apply.

There are more interconnections here with fungicides and other nutrients and seeding rates too, but I’ll leave it there. You can see that because of one small introduction into the system, you can now change and challenge other aspects of the system to better optimize for the outcome. This was done through interconnection (standability impacted via variety and N rate), synthesis (how they influence one another), feedback loops (apply more N because you get a higher yield and have less worry about lodging), causality (the variety and N rates are paramount to the lodging) and mapping out what can be changed and inserted where to obtain better outcomes.

This is only one small part of a farm, or what an agronomist might be thinking, or what an agribusiness might be considering when going through the crop input process with a farmer. For simplicity sakes I kept it agronomic. The interconnection and synthesis of everything occurs from understanding how each influence the other, feedback loops in terms of understanding more clearly how each influences the other and adapting based on the experiences and identifying causality over time, and finally mapping them all together – which might even be apart of a bigger digital strategy on farm.


Everything is connected in farming and business. Seeking to learn about the dynamics behind each piece and the interconnectedness is necessary as technologies and demands change faster than they ever have before. In order to stay ahead, we must think bigger picture and longer term vs. linearly and in a first order way.

All systems have good and bad, but if you apply systems thinking and systems thinking concepts, it can be easier to identify the “bad” within the system – enabling resilience to challenges and better outcomes.

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