Michael Sykuta is Associate Professor, Agricultural and Applied Economics, and Director, Contracting Organizations Research Institute at the University of Missouri.
The US agriculture sector has been experiencing consolidation at all levels for decades, even as the global ag economy has been growing and becoming more diverse. Much of this consolidation has been driven by technological changes that created economies of scale, both at the farm level and beyond.
Likewise, the role of technology has changed the face of agriculture, particularly in the past 20 years since the commercial introduction of the first genetically modified (GMO) crops. However, biotechnology itself comprises only a portion of the technology change. The development of global positioning systems (GPS) and GPS-enabled equipment have created new opportunities for precision agriculture, whether for the application of crop inputs, crop management, or yield monitoring. The development of unmanned and autonomous vehicles and remote sensing technologies, particularly unmanned aerial vehicles (i.e. UAVs, or “drones”), have created new opportunities for field scouting, crop monitoring, and real-time field management. And currently, the development of Big Data analytics is promising to combine all of the different types of data associated with agricultural production in ways intended to improve the application of all the various technologies and to guide production decisions.
Now, with the pending mergers of several major agricultural input and life sciences companies, regulators are faced with a challenge: How to evaluate the competitive effects of such mergers in the face of such a complex and dynamic technology environment—particularly when these technologies are not independent of one another? What is the relevant market for considering competitive effects and what are the implications for technology development? And how does the nature of the technology itself implicate the economic efficiencies underlying these mergers?
Before going too far, it is important to note that while the three cases currently under review (i.e., ChemChina/Syngenta, Dow/DuPont, and Bayer/Monsanto) are frequently lumped together in discussions, the three present rather different competitive cases—particularly within the US. For instance, ChemChina’s acquisition of Syngenta will not, in itself, meaningfully change market concentration. However, financial backing from ChemChina may allow Syngenta to buy up the discards from other deals, such as the parts of DuPont that the EU Commission is requiring to be divested or the seed assets Bayer is reportedly looking to sell to preempt regulatory concerns, as well as other smaller competitors.
Dow-DuPont is perhaps the most head-to-head of the three mergers in terms of R&D and product lines. Both firms are in the top five in the US for pesticide manufacturing and for seeds. However, the Dow-DuPont merger is about much more than combining agricultural businesses. The Dow-DuPont deal specifically aims to create and spin-off three different companies specializing in agriculture, material science, and specialty products. Although agriculture may be the business line in which the companies most overlap, it represents just over 21% of the combined businesses’ annual revenues.
Bayer-Monsanto is yet a different sort of pairing. While both companies are among the top five in US pesticide manufacturing (with combined sales less than Syngenta and about equal to Dow without DuPont), Bayer is a relatively minor player in the seed industry. Likewise, Monsanto is focused almost exclusively on crop production and digital farming technologies, offering little overlap to Bayer’s human health or animal nutrition businesses.
Despite the differences in these deals, they tend to be lumped together and discussed almost exclusively in the context of pesticide manufacturing or crop protection more generally. In so doing, the discussion misses some important aspects of these deals that may mitigate traditional competitive concerns within the pesticide industry.
Mergers as the Key to Unlocking Innovation and Value
First, as the Dow-DuPont merger suggests, mergers may be the least-cost way of (re)organizing assets in ways that maximize value. This is especially true for R&D-intensive industries where intellectual property and innovation are at the core of competitive advantage. Absent the protection of common ownership, neither party would have an incentive to fully disclose the nature of its IP and innovation pipeline. In this case, merging interests increases the efficiency of information sharing so that managers can effectively evaluate and reorganize assets in ways that maximize innovation and return on investment.
Dow and DuPont each have a wide range of areas of application. Both groups of managers recognize that each of their business lines would be stronger as focused, independent entities; but also recognize that the individual elements of their portfolios would be stronger if combined with those of the other company. While the EU Commission argues that Dow-DuPont would reduce the incentive to innovate in the pesticide industry—a dubious claim in itself—the commission seems to ignore the potential increases in efficiency, innovation and ability to serve customer interests across all three of the proposed new businesses. At a minimum, gains in those industries should be weighed against any alleged losses in the agriculture industry.
This is not the first such agricultural and life sciences “reorganization through merger”. The current manifestation of Monsanto is the spin-off of a previous merger between Monsanto and Pharmacia & Upjohn in 2000 that created today’s Pharmacia. At the time of the Pharmacia transaction, Monsanto had portfolios in agricultural products, chemicals, and pharmaceuticals. After reorganizing assets within Pharmacia, three business lines were created: agricultural products (the current Monsanto), pharmaceuticals (now Pharmacia, a subsidiary of Pfizer), and chemicals (now Solutia, a subsidiary of Eastman Chemical Co.). Merging interests allowed Monsanto and Pharmacia & Upjohn to create more focused business lines that were better positioned to pursue innovations and serve customers in their respective industries.
In essence, Dow-DuPont is following the same playbook. Although such intentions have not been announced, Bayer’s broad product portfolio suggests a similar long-term play with Monsanto is likely.
Interconnected Technologies, Innovation, and the Margins of Competition
As noted above, regulatory scrutiny of these three mergers focuses on them in the context of pesticide or agricultural chemical manufacturing. However, innovation in the ag chemicals industry is intricately interwoven with developments in other areas of agricultural technology that have rather different competition and innovation dynamics. The current technological wave in agriculture involves the use of Big Data to create value using the myriad data now available through GPS-enabled precision farming equipment. Monsanto and DuPont, through its Pioneer subsidiary, are both players in this developing space, sometimes referred to as “digital farming”.
Digital farming services are intended to assist farmers’ production decision making and increase farm productivity. Using GPS-coded field maps that include assessments of soil conditions, combined with climate data for the particular field, farm input companies can recommend the types of rates of applications for soil conditioning pre-harvest, seed types for planting, and crop protection products during the growing season. Yield monitors at harvest provide outcomes data for feedback to refine and improve the algorithms that are used in subsequent growing seasons.
The integration of digital farming services with seed and chemical manufacturing offers obvious economic benefits for farmers and competitive benefits for service providers. Input manufacturers have incentive to conduct data analytics that individual farmers do not. Farmers have limited analytic resources and relatively small returns to investing in such resources, while input manufacturers have broad market potential for their analytic services. Moreover, by combining data from a broad cross-section of farms, digital farming service companies have access to the data necessary to identify generalizable correlations between farm plot characteristics, input use, and yield rates.
But the value of the information developed through these analytics is not unidirectional in its application and value creation. While input manufacturers may be able to help improve farmers’ operations given the current stock of products, feedback about crop traits and performance also enhances R&D for new product development by identifying potential product attributes with greater market potential. By combining product portfolios, agricultural companies can not only increase the value of their data-driven services for farmers, but more efficiently target R&D resources to their highest potential use.
The synergy between input manufacturing and digital farming notwithstanding, seed and chemical input companies are not the only players in the digital farming space. Equipment manufacturer John Deere was an early entrant in exploiting the information value of data collected by sensors on its equipment. Other remote sensing technology companies have incentive to develop data analytic tools to create value for their data-generating products. Even downstream companies, like ADM, have expressed interest in investing in digital farming assets that might provide new revenue streams with their farmer-suppliers as well as facilitate more efficient specialty crop and identity-preserved commodity-based value chains.
The development of digital farming is still in its early stages and is far from a sure bet for any particular player. Even Monsanto has pulled back from its initial foray into prescriptive digital farming (call FieldScripts). These competitive forces will affect the dynamics of competition at all stages of farm production, including seed and chemicals. Failure to account for those dynamics, and the potential competitive benefits input manufacturers may provide, could lead regulators to overestimate any concerns of competitive harm from the proposed mergers.
Farmers are concerned about the effects of these big-name tie-ups. Farmers may be rightly concerned, but for the wrong reasons. Ultimately, the role of the farmer continues to be diminished in the agricultural value chain. As precision agriculture tools and Big Data analytics reduce the value of idiosyncratic or tacit knowledge at the farm level, the managerial human capital of farmers becomes relatively less important in terms of value-added. It would be unwise to confuse farmers’ concerns regarding the competitive effects of the kinds of mergers we’re seeing now with the actual drivers of change in the agricultural value chain.