A Supply Chain Solution for Grain Grading Frustrations
Technology has played a major role in the transformation of agriculture. Our supply chain specifically has been a benefactor of this technological shift, but we can’t expect to see anything other than incremental gains unless we improve one very important element.
Samples hold a lot of power in the supply chain – it determines what and where we sell, and we cross our fingers that these samples are representative of our supply. But representation of samples is only one part of it. If we were to show the same sample to multiple people, we get different grades! Why? Because we all see and perceive things slightly differently.
And this hasn’t changed for anyone in the supply chain for over 100 years.
Our supply chain is complex – it has many stakeholders, product changes hands multiple times, and everyone has competing objectives – except one common objective we all share – deliver product to the next person down the line and get paid doing it. Our supply chain is just that – a chain – each stakeholder is like a link in the chain, and each link must work together for it to be successful, as we all know, one link on a chain can’t do it all – the whole chain is needed. When it comes to samples and quality information, our supply chain doesn't always work as a whole chain though, it works as a bunch of links just side by side, and that doesn't make our supply chain the best and strongest it can be and leads to a whole pile of frustrations, felt by all in the chain.
These frustrations we experience as a supply chain are not new and stem from the largely manual, subjective and visual process we use for quality assessment and grading. Our current process takes a lot of time, requires us humans to do the exact same thing the exact same way every time, multiple times and as a result leaves us open to risk on a global scale. Its not enough that we have an abundance of product to offer the market, we must ensure we have consistent and reliable quality to offer in abundance. Our speed to market becomes a huge hurdle with increasing competition globally, and our inability to assess quality quickly and reliability doesn’t help us to overcome that hurdle.
But what if we could say “I can’t believe we used to grade grain by hand!” in the same way we now often say “what did we do before auto steer!”. What if we utilized the entire supply chain beyond the physical movement of grain and in the process removed the subjectivities, complexities and inefficiencies we experience today? What if we used technology like AI to do the things that us humans face barriers with? AI doesn't suffer the same hang ups humans do – and we can put it to work for us.
Thats what makes our approach at Ground Truth different – our infrastructure is backed by powerful AI machine learning models and NIR calibrations to able to grade grain in the exact same way no matter where it is in the supply chain, and no matter who is running a unit. That’s key in this entire process – to be able to grade in the exact same way on bulk, high throughput grain without kernel staging. We achieve that with units on farm, in facility and anywhere along the supply chain that transacts and moves grain by automatically capturing and analyzing grain quality. Our three different units – benchtop, on-combine, in-line offer automated grain grading using the same technology, and analyze the grain in the exact same way, removing the subjectivities, inconsistencies and inefficiencies we see today. The result? A more accurate, consistent, efficient and comprehensive process the whole way through the supply chain.
At Ground Truth Ag, we don’t change the supply chain; we just change how we handle quality assessment throughout the supply chain. We harness the power of AI and tech to deliver automation where it makes sense and generate that real time grain quality data, we all transact and move grain upon. We drive technology in a way that connects the links in the supply chain, alleviates frustrations with grading today and brings real opportunity for industry changing gains.
