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Software Foundations in Agribusiness: Control Points and Industry Influence, Digital Integration and GenAI
A look at an integrated value chain, crop protection company digital strategy and GenAi in agribusiness software.
Index:
Overview: Control Points
The concept of Control Points within agribusiness is crucial to understand in the context of the three articles below. I also think it is a crucial concept for anyone operating in the software space of agriculture.
Businesses want a single point of action across their company. They don’t want ten different softwares; they want one.
The way to become the “one” is to own a control point.
If a software company doesn’t own the control point, they will struggle with adoption, stickiness and value creation over time making their software more prone to being displaced.
A Control Point is the most important application in a software customer’s feature suite. It is the last software users turn off at the end of the day or the first one they look at in the morning. Some might refer to this as a core operating system.
There are typically only one or two control points in any segment: one in the front office that touches the customer and drives sales, and one in the back office for operations and management.
In the world of large-scale row crop farming in North America, the most influential groups tend to be the retail input providers and the grain originators— these are also the points where transactions occur either to purchase inputs or services or for a farmer to be paid for their grain.
From the early 2010’s into the early 2020’s, many in the industry thought the control point was agronomic software— but it’s not.
In the value chain, farmers work closely with grain origination companies, retailers and dealers, and the control point for those entities is not agronomic software or farm management software— it is the transactional and financial software driving the day-to-day commerce functions of the ordering, invoicing, CRM, contracting grain etc.
On top, those entities back office needs/management needs, aren’t typically connected to agronomic software, but they are to the transactional softwares, like grain merchandising software or ERPs for example.
The organizational workflow builds around the control point.
The company that owns the control point can layer on other software, more functionality, and is best positioned to win and accrue value. A control point software is difficult to displace and is the point where value for the customers and returns for the investor, stem from.
Control Points are important to consider in the context of operating systems for the industry, generativeAI interfaces and digital initiatives from corporates.
That brings me to the first article:
A Control Point is a concept from Tidemark that I have been applying to the ag industry. Tidemark is a vertical SaaS investor and they have other frameworks that are useful for thinking about software, including a new one they call the industry ledger— a concept I have referred to as an operating system. The ledger is a trusted value chain integrator and orchestrator of data, insights and accountability. It strengthens the ties between companies engaged throughout the value chain enabling new services, reduced friction, embedded products and better outcomes for all participants:
The most successful vertical ledgers won’t just organize an industry’s data; they’ll strengthen the relationships that keep the industry running.
I applied this thinking to AgVend (Tidemark portfolio company) previously but the “industry ledger” concept provides more foundational nomenclature to apply to other companies throughout the ag value chain.
If you buy into the concept of control points, then that lends well to thinking through crop protection and seed company digital initiatives:
Divergent Digital Strategies
Crop protection and seed companies have been realigning their digital initiatives over the last 5 years.
The initial idea was to go direct to the farmer and charge a per acre fee. For the crop protection companies, this largely was ineffective, in part for reasons such as perceived bias, expense, unwillingness to pay, and lack of control point ownership.
Since then, we have witnessed a divergence in some respects from that effort:

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