An Introduction to Digital Agriculture: Part 2

Source: Start Co. | Oliver McIntosh

This two-part blog post provides a basic overview of the emerging digital agriculture segment. Part two summarizes future challenges and frontiers in the segment as the market and technologies progress. Part one introduces the existing technology and concept of digital agriculture. 

Breaking the connectivity barrier

Although data-generating tech is quickly becoming more accessible, there remain critical steps to bringing the full potential of Digital Agriculture to the farm. Complex software must be developed, tested, and demonstrated to successfully aggregate the massive amounts of agricultural data into actionable and user-friendly insights, an area in which entry costs remain high. Development of successful intermediary software requires extensive collaboration and consensus between the various steps in the supply chain, ensuring sufficient usability for the input provider, the farmer, and the distributor. As a result, hard information on the long-term benefits of a fully connected digital agriculture system remains relatively scarce, and the ability of providers to make a strong business case for farmers to surmount entry costs will be constrained until this analytic software is further developed. 

Just as importantly, a foremost prerequisite for adoption of digital ag technologies is a strong, reliable connection between all network elements, from the fields to the data-collection devices to data analytics centers. Many areas of the country, particularly rural areas, offer little or no high-speed connectivity, and those that do may be subject to signal interruption or loss. Development of economical and effective means to extend network connectivity to all farms is thus a basic prerequisite and central obstacle to widespread adoption of digital agriculture principles. 

The race to the data: developing market frameworks

This quickly-developing nature of this segment may present opportunities for market positioning and consolidation as participants in the supply chain work to develop their data-use capabilities. Input providers, still developing data-use capabilities internally, could see a “data race” of who can gather and mobilize data fastest, with the winner consolidating the position of connectivity software supplier directly to the farmer. Both agribusiness input providers and “legacy” big tech have a stake in the game; agribusiness could leverage its greater proximity to farmers to roll out software packages directly to farmers, or tech firms could leverage their extensive data-handling capabilities (Amazon Web Services, for example) to consolidate and cut out the agribusiness middleman. With this potential in mind, private enterprise and research academia are solidly incentivized to develop these extensive data-access and data-handling capabilities to effectively bring digital agriculture to the farm. Consulting firms, research universities, and NGOs have to date produced extensive work on digital ag, while tech companies like Microsoft and Amazon have launched forays into digital ag research, and agribusiness firms, through acquisitions and consolidations, also dip into proprietary data collection in attempts to capture this expanding market.

Summary

The Digital Agriculture sector is developing quickly, as each sector of the agricultural supply chain seeks to implement data-driven software into their particular segment. Some critical elements in farmer adoption of digital ag technologies require further development, however. The bridging of the connectivity gap for rural farmers, and the development of tested and reliable network software to link data-collection software, as well as an established business model as to which companies will deliver and administer these technologies directly to farms are critical next steps in realizing the full potential of digital agriculture technologies for farmers. 

See Part 1 for previous overview of existing technology and concepts of the digital agriculture segment. 

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