By Sarah Nolet and Matthew Pryor - AgThentic
Read the full article here.
Silicon Valley, where I (Sarah) grew up, and I (Matthew) lived and worked during the dot com era, is known as the birthplace of the modern tech industry, responsible for the reinforcing loop of entrepreneurs and venture capitalists, and the resulting disruptions to most major industries. But one industry where this hasn’t yet played out is agriculture- the incumbents today are largely the same firms that have dominated since the industrial and green revolutions enabled the shift to modern day farming practices.
But agriculture has not resisted digitization due to a lack of effort on the part of venture-backed startups or investors. In 2013 after Monsanto acquired the Climate Corporation for nearly $1B (one of the only exits of this size in the sector to date), venture capitalists (VCs) saw an opportunity. Pitch decks explaining how “ag is the least digitized industry”, and quantifying the potential ROI of “feeding the 10B mouths of tomorrow,” helped investors to increase agtech venture capital from $6.4B in 2014 to over $30B in 2020.
The silicon valley playbook expects unicorns, exits, and digital transformation of industries, yet to date in agtech, we are yet to see this happen at a mainstream level. Some claim that venture capital isn’t a fit for ag- that the timelines of complex natural systems, lack of underlying infrastructure (e.g., rural connectivity), and the relatively older user population make ag less susceptible to being eaten by software.
Our argument is slightly different. We believe that venture capital is a fit for agtech, but that the silicon valley ‘template’ of investing has set agtech back a decade, and that only by looking beyond the templated business models and tech stacks that work in the valley can we realize the returns and impact that will come from transitioning to a digitally native future for agriculture.
The silicon valley template
Venture capital is often about pattern matching. Two common patterns, or templates for business models, that exist in traditional tech venture capital are:
(1) User is the Customer- In this template, the customer is the direct beneficiary of using the product. Given the customer gets the value, they also pay for the product (through various models, such as SaaS and Freemium). The company can leverage network effects to grow their customer base, meanwhile making incremental product improvements. Examples here abound, such as Slack (freemium) and HubSpot (SaaS).
(2) User is the Product- In this template, the user gets value from the product but they are not the beneficiary, nor do they pay. Instead, the company monetizes the user, often through advertising. This template also has network effects, where as the product gains more users, it becomes more attractive to both other users and to the end customer. A classic example of this template is Facebook.
Both templates tend to rely on common attributes of software-enabled, low marginal cost business models. A constant stream of new features can enable rapid customer acquisition, and once the audience is large enough, it can be monetized via models like freemium subscriptions or selling targeted user data for advertising.
But it’s perhaps the propensity of VCs to apply these templates that has contributed to the misalignment in agtech investing thus far, as there are several reasons why they are not well suited to agriculture.
First, the number of possible users in agriculture just isn’t at population scale, so the deferred monetization strategy has no real payoff. Second, the ‘User is the Product’ template usually relies on a value exchange where the user gives away information about themselves and what they might want, and gets access to features in return. Farmers already face great uncertainty with weather, prices, and labor availability, so free or low cost incremental improvements are never going to balance out the possible consequences of giving away yet more control.
But investors didn’t know this in the early days of agtech. Startups saw the opportunity to bring new tools to farmers to help them save money and time, cut costs, and increase yields. Investors saw opportunities to digitize and disrupt a new industry. Unfortunately, the promises these companies sold in their pitch decks rarely played out in the field: adoption of on-farm tech remains low across industries (in fact below 25% in almost all the industry surveys we’ve seen).
Why? In most cases, though the farmers are the users of these solutions, they are not often the beneficiaries. This means farmers are being asked to bear the costs — buy and install new hardware, change practices, pay for a subscription, etc. — without realizing the benefits.
The wine industry presents an illustrative example. Wine makers often contract the growing of some or all of their grapes to other growers. This makes sense to get to scale and mitigate risk, but this distributed production method poses serious challenges for managing the cost and quality of wine making. Despite the fact that good tools are available to assess grape quality and yield as harvest approaches, individual growers are not likely to take them up as the ROI for their business is not strong enough. For the wine maker, though, these tools are invaluable: over supply, under supply, and poor grape quality all have major financial implications for winemakers. In other words, though the growers are the users, the real beneficiary is the winemaker. Therefore, until winemakers create incentives, and perhaps even supply the tools directly to the growers, growers are unlikely to adopt and the benefits from far greater visibility of the yield and quality of the coming harvest will remain unrealized.
Another notable characteristic of agtech 1.0 was that as this dynamic played out again and again, agtech companies (and their investors) blamed the farmers! Agtech conferences and industry reports featured claims about “laggards,” pointing fingers at the users for being “traditional” and “resistant to change” in an industry “based on handshakes.” In reality, the problems were with business models and incentive alignment.
The second wave of agtech companies got a bit smarter, attempting to solve the adoption challenges in two ways: getting into the channel; and building better, cheaper technology. Unfortunately, both of these approaches were problematic.
Agriculture has established channels with significant power and access to customers, so from the outside, partnerships make sense. However, access to customers does not solve the fundamental problem of poor economics: the customers, and sometimes also the channel, were still not the beneficiaries.
Strong channel partnerships did enable some exits, though, as incumbents with scale and reach could monetize the benefits of digital technology- namely by selling more of their existing products (e.g., as DuPont has done with Granular). But these “protect an existing revenue stream” exits have failed to deliver the kind of industry transformation that many startups set out to achieve, as the incumbents were enabled rather than disrupted.
Agtech 2.0 companies also started building better products, and, as underlying technologies advanced, were able to sell them at lower costs. The theory behind this approach was that farmers weren’t adopting because the price tag was too high. However, cost was not the issue. So, not only did this fail to solve the problem, but it also created a race to the bottom for agtech companies who were then stuck in a vicious cycle of price competition and poor unit economics.
The end result in many cases for agtech 2.0 companies was large venture capital investments that went to zero, as the failing business models caught up with investors.
Moving beyond Silicon Valley templates and turning to the supply chain
Silicon Valley may have set agtech back a decade, but today we’re seeing new approaches that have learned from the mistakes of the past. How? By looking at the supply chain.
In agriculture, the vast majority of the value accrues in the middle of the supply chain, with the traders, manufacturers, brands & retailers that transform food from farm-gate to consumer. These players can afford to bear the costs of change, and have the incentives to innovate, given they will realize the benefits of digital transformation.
Business models that align the power of the supply chain to create incentives for adoption upstream (i.e., on-farm) can truly move the needle on industry transformation. We’re seeing this today in the carbon space: asking farmers to change practices or adopt more tools for data collection is expensive and unlikely to work; however, dangle the carrot of a carbon neutral branding opportunity to a CPG company alongside the stick of ESG pressures, and it’s easy to see why they’d subsidize or outright pay for the practice change and toolsets for their grower-suppliers.
Bushel’s recent acquisition of FarmLogs is a salient example of how a supply chain-centric approach can help to overcome the challenges of the silicon valley templates. FarmLogs, founded in 2012 at the peak of agtech 1.0, raised $37M from venture capital investors including Y Combinator. But like with many farm management software companies, long term value creation remained a slog (the users weren’t the beneficiaries!). Enter Bushel, founded in 2017, who started downstream in the supply chain with tools to help agribusinesses digitally buy, sell, and manage grain. These agribusinesses have a strong incentive to make it easier for farmers to transact and share information, and in turn are able to provide a strong incentive for growers to digitize (i.e., connection to the downstream supply chain). In 2021, Bushel, backed by several specialist agtech funds, acquired FarmLogs, exposing the fragility of the old model and demonstrating the power of starting with the beneficiaries in the mid supply chain.
With this new approach that focuses on the supply chain and selling to the beneficiary rather than the user, there is an enormous opportunity to build the digitally native agriculture of the future. We are only just seeing these business model innovators emerge, and as they do, we expect to see lasting digital transformation and wholesale disruption of key elements of the agrifood supply chain.
The investing templates of silicon valley may have set agtech back, but as the agtech industry has evolved, it has created and attracted investors and entrepreneurs with experience not only in tech, but also in food and agriculture value chains, who are leading this new wave of agtech innovation. The question is whether this evolved approach to innovating and investing will realize the potential and deliver profitable, scalable business models that align better with agriculture.