Proving Damages from Loss of Yield Monitor Data: Forensic Economics and Farm Data Valuation Part 1

Previously, I described how damages could be proven in the event that farm data were misappropriated (i.e. when farm data disclosed such that it was used in a manner not consistent with agreements although the farmer still had complete access to the data). Working on that project with Ashley Ellixson reminded me of serving as an expert witness on  a case where farm data were destroyed such that the farmer no longer had access to that data (not misappropriated or disclosed but destroyed). In this article, I explain how the value of that data was estimated to the specific farmer.

Description of Farm Data Loss Scenario

The farmer desired to determine the value of the lost farm data in anticipation of building a case against the negligent party. Without disclosing details, the facts of the case were that the yield monitor on the combine harvester was destroyed while the combine was being serviced by a third-party service provider. The third-party service provider admitted fault and agreed to replace the yield monitor,  however they argued that the data on the yield monitor had no value and were not willing to compensate the farmer for the data. The farmer believed that the data did have substantial value and had intended to use that data in their farm management decision-making process. Therefore, the farmer argued that the service provider should compensate the farmer for the lost data. The farmer has a history of using yield monitor data for farm management decision making including on-farm experiments that tested products and rates of inputs under their management practices under environmental conditions of their fields.

Estimating Damages
To reiterate the importance that farmers place on their data, farmers’ willingness-to-pay for data sensors and collection tools (commonly referred to as precision agriculture) indicate farmers readily invest their financial resources in this technology. The substantial amounts of money invested to collect and store site-specific data indicate farmers at least perceive value in the data collected for farm management decision making purposes. Surveys and industry data support the idea that substantial proportions of farmers and even higher percentages of farmland are being harvested with with combines equipped with yield monitors capable of collecting site-specific data. In addition to direct investments in sensors and data management services, investments in human capital to management farm data are substantial.  

Given that the direct damages of the physical components were not contested, the remaining two types of damages including 1) consequential and 2) speculative are being examined. Consequential damages, otherwise known as special damages, are damages that can be proven to have occurred due to the failure of one party to meet a contractual obligation (goes beyond the contract itself and into the actions garnished from the failure to fulfill). Speculative damages are damages claimed by a plaintiff for losses that may occur in the future, but are highly improbable.

Consequential damages resulting from foregone revenue from lost data are considered in Part 2. In Part 3, speculative damages with respect to 1) foregone opportunity to participate in ‘big data’ communities, 2) the increased risk of damaging field equipment, 3) inability to negotiate with landowners, and 4) lack of information to base improved drainage structures are described.

Terry Griffin, Ph.D.

@SpacePlowboy

twgriffin@ksu.edu