Seana Day
Institutional capital allocated to agriculture for decades. Following the 2008 financial crisis investment in the sector surged as institutional investors sought safer, real asset alternatives to the financial markets and provided a hedge against inflation and currency protection. Capital continues to flow into the Food & Ag (F&A) sector in recognition to the growing global population that offers attractive investment opportunities for investors, seeking to meet sustainability objectives and ESG goals.
According to a 2019 investment report by the HighQuest Group, global F&A fund managers have approximately $130 billion in assets under management. Why is this noteworthy for AgTech start-ups? Asset managers are data junkies, who have long struggled with a lack of data in the asset class.
A recent AgFunder report illustrates early-stage investors’ enthusiasm for the sector with FarmTech startup investment growing from 370% since 2013, and reaching $4.7 billion in 2019. The maturing of FarmTech during this time has created an opportunity for asset managers to influence adoption of the farm to address three key portfolio management objectives:
1. Asset managers need normal, trustworthy data to measure and benchmark performance;
2. Many funds are committed to sustainability but need verification and reporting; and
3. Investors are conditioned to believe in data-driven decision making, climate shift, environmental patterns, uncertain trade conditions, labor and natural resource pressures. The old way of depending on gut feeling and intuition are no longer adequate to manage portfolio risk.
The Value of Farm Data is Coming Into Focus
As a result of my background in capital markets and investment banking, I have always thought what an institutional Ag investor may look like in the future. Following this year’s release of my 2020 FarmTech Landscape that I use as a heatmap of activity, I believe the future is coming into focus. Technology is now offering fund managers an edge in analyzing Ag land acquisitions, capex management, risk mitigation, and when to market hedge crops, commodities, and inputs. I am particularly intrigued by the emergence of startups integrating FinTech and AgTech to enable financial product and business model innovation.
The emerging arsenal of tools is enabled by basic digitalization, growing data sets, and accessibility of AI/ML and vision system capabilities. It is estimated that an average-sized farm will produce more than one million data points a day. That said, how will asset managers leverage an “unfair advantage” with that data?
Land acquisition intelligence platforms like CIBO Technologies and Granular’s Acre Value help buyers and sellers understand valuation and productivity characteristics.
New models for data-driven underwriting and the creation of financial products like FarmOp Capital funded by Finance of America, a subsidiary of Blackstone.
Faster adoption of Farm Management Information Systems like AgWorldConservis, and AgSquared for specialty crops can offer agronomic and financial benchmarking, planning and budgeting, better inventory tracking systems, more precise overhead allocation, leading to insights about the true cost of production per acre, field or farm.
Technologies that help in analyzuing market data can have a significant impact on profit by improving buy/sell decision, making FarmLead for commodity row crops and AGTools for fresh produce.
Water availability, quality, and reporting technologies like Aquaoso and SWIIM System are especially valuable in the Western States where lenders and investors are continually monitoring water risk in their portfolios.
Sustainability reporting will continue to be a driver for digitalization as data is shared downstream with buyers and brands responding to consumer demands. For investors, this can take the form of ecosystem service models and carbon credits, which require data to verify regenerative practices that can then be reported through the value chain (and hopefully drive crop premiums).
Capabilities to analyze capex vs. opex decisions as equipment and input providers explore new business models, including XaaS and outcome-based pricing models.
What it Takes to Be Great
I have already seen savvy fund managers and bankers these technologies to improve their analysis of fund returns and manage portfolio risk. Yet, we can’t forget that the key driver in asset performance is a great farm operator.
For startups, the takeaways for building a solution that becomes an integral part of the farmers took kit are:
1. Develop a UX / UI design and clear ROI to drive adoption.
2. Develop a solid understanding of how your technology fits into a system and how your data is combined with other datasets to enable operational or financial decisions? This requires a willingness to forge partnerships and collaborations.
3. Understand the totality of the farming operation and ecosystem of influencers. If your technology aims to make a key part of the farm support team, redundant the barriers to purchase are higher and probability of success can be diminished.
In my conversations with financers over the years, one thing stands out: the great operators know how to make money in both good and bad times because they track and manage efficiency and productivity affording the time to work ON the business, not just IN the business.
