By Aaron Hutchinson, Co-Founder and CEO, CropTrak

Our world is more intertwined than ever before, causing our actions to impact others down the line. Only with data can we quantify and limit those impacts throughout the food supply chain.

I recently had the pleasure to speak at the American Seed Trade Association (ASTA) Leadership Conference in Indianapolis. After several years of supply chain turmoil, global market volatility, and increasing calls for sustainability, the question ‘what’s next?‘ dominated the conference.

From my point of view, working with partners across multiple interlinked supply chains, from seed to farmers to food companies, the answer is clear: a data explosion. Significant increase in how much data will be required to run an operation and how much will need to be shared to make it work for better supply chain resource management and transparency.

For more than a decade, CropTrak’s mission has been to harness the power of data to identify and address systemic supply chain problems that limit the availability of safe, affordable, and sustainable food. Today, we work in more than 70 countries, with 70+ crops and eight languages. Yet we believe we have barely dipped our toes into the impact of, and need for, data in agricultural production systems.

Without Data, We’re Just Guessing

Big data has for several years been touted to enable smarter and better-informed decisions within the constraints of seed, farm, or food production. However, you’re not making the best decisions without timely, accurate, and complete data; you are guessing what actions to take, especially as they impact your operation’s future.

At the same time, global food system stakeholders are demanding even more compliance data today than ever before. New product delivery contracts now require even more complex and voluminous data packets about field activities and observations.

This data drive is powered by the need to document provenance, sustainability, compliance, and traceability. The food companies need to document progress toward climate change goals by making their products use less water, fertilizer, and reduce waste, thereby showing they are doing better with less. These companies are responding to the demands of a consumer base that questions the metrics of their marketing claims, not at the end of the process but at each production step.

We are also seeing this higher order of sustainability requirements in public policy. Like the U.S. Securities and Exchange Commission’s (SEC) proposed climate risk disclosure rule, which would require publicly traded companies to forecast the climate impacts of their operations, ultimately forcing a lot more data collection. A trend we’ve already seen applied in Europe and goes broad and wide. For example, the Europe Union’s (EU) Farm to Fork Strategy goal is to reduce fertilizer use by 20%, not just for EU farmers; they expect every Global EU food supplier to participate in saving the EU 20% of their nitrogen use.

All this reporting will require even more data reporting than today. Actionable data. Data that can be shared and applied across the supply chain and to all the certification and verification entities.

Limiting Factors to Data Systems Adoption

While we see rapid digital system adoption rates when there is a specific need, like the need to fill out a metric form to enter a new market or a market-driven sustainability data push, we do not see it happening at a high rate in general.

The same barriers to data and technological adoption persist as they have since the beginning of the agtech revolution. For example, aging, less-tech savvy operators see no reason to upgrade their flip phones and learn a whole new way of approaching their operations as they reach the end of their farming careers. Similarly, businesses with long-established systems and cultures are frequently unwilling or unable to make the systemic changes needed to adopt these new technologies company-wide. And rural infrastructures are still spotted with Wi-Fi dead zones that limit access to data platforms, robotics, and other agtech innovations.

What’s more is that the broad supply chain itself remains siloed, rigid and fraught with fragmented data sets that all limit clear decision-making.

As we shift to the future, we must close the technical gulf for future farmers and their industry partners to enable the next cycle of data science and agtech revolution. A great place to start is with a common language (data dictionary). Non-standardization in the ag data industry is creating added complexity, especially for small and middle-scale operators, in conducting business on a global scale. In addition, the inconsistency of data requirements between vendors, certification, and countries is creating a significant ‘global gap’ and making data collection even more extensive and expensive.

Accelerating adoption will take all of us embracing some standardization of data requirements. Not just at the farming and technology level but with our supply chain partners.

Broader Perspectives Unlock Opportunities

Amongst all the barriers to data are vast opportunities. We encourage our customers to look at data differently to see it from a broader supply chain perspective.

Currently, typical supply chains are hampered by silos. Not just silos within organizations but silos between companies and between steps along the chain. As a crop moves through the supply chain, each step has its own business and organization requirements with contracts, logistics, compliance, and products that need to be tracked and documented.

In the seed industry alone, we have separate supply chains for R&D, stewardship, production, and sales. And the same is true for every step within each supply chain. All this can seem overwhelming. But, if a company has complete visibility to understand their data, they can give and receive better customer data and insights to understand relationships that could never be seen looking at their data alone.