Data Modeling + Branding = Market Development
Commodity marketing is only about liquidity and profit-maximization. Value creation brings in the right storytelling, and data to back it up.
Over the years, many have tried to ‘tell the story’ of modern agriculture. Those stories all carry a similar tone that seems to speak to producers, more so than consumers.
This research series seeks to unveil opportunities to create new revenues for farmers and the supply chain, in addition to the base value for commodities. Tapping into these new demand segments requires both data and a clear explanation of what happens to bring farm products to market.
Beyond Price Discovery
Functioning markets offer choices based on accurate information that reflect the trade-off between quality and price. In planning to adapt to the future, companies must recognize that lucrative new quality attributes in agriculture and food can’t be measured by standard grades, nor factored into the price.
That hasn’t stopped these attributes from being monetized, creating some winners and losers along the way, however not via market premiums and discounts. The global commodity supply chain can’t accommodate those at a reasonable cost.
Instead, farmers may receive payments for managing their land differently, for example through contracts to create conservation easements. We are also hearing more and more about low-input regenerative farmers receiving favorable borrowing rates from their banks.
Farm Economic Modeling for Profit-Maximization
The traditional model of commodity profit-maximization takes into account only yield and price in establishing revenues. The cost side of the equation counts only production expenses.
A fuller model is needed to account in economic terms for the externalities created by different farming practices. Without factoring in subsidies, taxes, interest rates and other forms of financial incentive, land owners are making decisions that lead to vulnerability, rather than profitability.
Story = Brand
A growing body of research points to some markets’ rejection of the story of commodity agriculture, which is one of deforestation and the breaking up of virgin land across much of the Americas. That doesn’t have to be the story going forward - for any corporation - because they control their own brands.
Companies’ communications departments see the opportunity to tell customers how they are working to reverse the damage, as the plethora of regenerative agriculture claims demonstrates. It’s not a story that many senior merchants trading commodities globally are familiar with though, which is where branding exercises can help.
Traditionally, commodity merchants invest heavily in relationships to maintain market share, i.e. conferences and meals. Because of this reliance on relationships, when individuals change companies, the business usually goes with them and over time, colleagues often follow.
Traders stumble when asked specifically about the origin story of agricultural commodities, because that’s rarely been part of their work experience. A good branding exercise needs to include training the customer-facing merchandising teams in basic agronomy, animal husbandry, and supply chain emissions, so that they can knowledgeably back up corporate messaging to customers.
Data = Market Share
In trading products that are standardized and blended, corporate marketers can say whatever they want about the origin story… but this is getting risky. Given the enormity of the opportunity to validate regenerative claims right now, investing in a data model appears minor in comparison.
A data model is a framework for capturing information at the source of the supply chain and throughout for end-use customers and/or regulators. In grain, it could be as simple as a report showing the amount and timing of nitrogen fertilizer applications for all the crops that make up a shipment, signed off in a producer affidavit and attached to the cargo release documents.
Summary
Of course, there will be some primary commodity producers that severely balk at these requirements, which could represent lost business and damaged relationships in the country. Fears that these will be significant are one reason why the agriculture industry has failed to move forward with data modeling for primary production thus far.
It’s a terrible trade-off. At the other end of the supply chain, costs could include lost market share and public trust, brand damage, regulatory fees, and litigation.
But consider for a minute, if avoiding these new risks might be… kinda fun. Could it look like an empowering team-building exercise where individuals from different divisions come together to contribute to elevating the company’s brand, and along the way, learn new things about the value chain that employs them?
This is the work of Prairie Routes. To learn more and request a quote, please reach out to me directly at hello@prairieroutes.ca.