Tackling the Global Food Challenge With a Data Strategy — Story of John Deere
John Deere provides agricultural machinery that essentially allows farmers to mechanically farm, grow crops at scale, and enable the farming industry to meet the current demand. By 2050, the global world population is estimated to grow to 9.6 billion. World Resources Institute estimates that to feed this massive population we will need to produce 69 percent more food calories in 2050 than we did in 2006. This industry needs all the innovation it can get, and data will definitely play a key role.
In a previous article (link below), we established that data strategy defines how your organization leverages data to achieve sustainable competitive advantage. In this article, we will look at how John Deere has successfully developed a great data strategy and is executing it to position itself ahead of its competition and unlock new values for the farming industry.
Business & AI Outlook
As a farm equipment provider, John Deere operates in a fairly competitive environment. Some of their largest competitors include Caterpillar (U.S.), CNH Industrial (U.K.), Kubota Corp. (Japan), AGCO (U.S.), and Claas KGaA (Germany). Therefore a robust business strategy shouldn’t rely only on market growth. The overall strategy is to be a agricultural tech (or precision ag) company and offer additional services powered by data.
One of the upcoming services that John Deere will offer is the autonomous operation of its tractor powered by AI. Operating a tractor is a skilled job that demands high seasonal labor, and automating this has tremendous potential for farmers. Another area where John Deere is applying AI is on weed sprayers. John Deere claims that See & Spray™ can help farmers reduce their herbicide use by 77% on average by targeting and spraying only weeds.
Business Strategy
John Deere shared their vision, Farm Forward, on 2013 in this video. A refreshed version (Farm Forward 2.0) of this was posted in this video in 2019. This vision of a futuristic farm has the following main segments:
- AI-Powered Equipment: AI holds huge potential for the farming industry as it can automate monotonous tasks (i.e. driving a tractor) and make operations more efficient (i.e. spraying weed).
- Integrated Platform: Bring all the components of smart farming under one umbrella and simplify access to data.
- Remote Expert Monitoring: Lower the cost of having experts input with remote connectivity and monitoring for interventions.
- Augmented Reality (AR) Applications: Adaptation of new technology is a challenge in the farming industry. Empower the farmer and take control of these complex technologies simple with voice-enabled command and augmented reality.
Currently, most of the components above are offered as services to the farmer. Going forward, the role of data strategy should be to position these services uniquely in the market by providing sustainable competitive advantages.
Data Strategy
The business strategy explained above lays a great foundation for shaping data strategy. To formulate a strong data strategy, we first need to understand customer value. For instance, there is a huge shortage of seasonal skilled labor to operate tractor machines. If this problem can be solved with autonomous tractor, it will unlock tremendous new value for the customer. However, to fulfill this use case, John Deere needs to collect images from their tractors. This requires upfront investment to modify their tractors, building a platform, and allocating skilled resources to productize AI.
Next to the image data, tractors are a data source for other strategic datasets. Strategic datasets are important assets that your organization can leverage to gain a sustainable competitive advantage. For instance, together with the machine attached to the tractor, crop yield data can be collected and is needed for providing remote expertise. At CES2022, John Deere stated that 50 million RGBD (red, green, blue, and depth) images were collected from six stereo cameras for building an AI model for autonomous tractor.
In the long run it is possible that competitors also introduce the same features, either by using their own AI system or a third party company. Data strategy needs to ensure that going forward these datasets continue to be a competitive advantage. Furthermore, nowadays farmer’s doesn’t only produce crops but also a ton of data! John Deere is in control of a significant portion of that data, but it definitely not full set. Michael Porter, who is one of the most influential minds on business strategy, saw this transformation coming in 2014 and wrote an article on HBR. In this article, he observes how companies like John Deere is broadening their capabilities by building a platform, and purposefully positioning themselves as a system integrator. He also further continues and states that companies that fail to adapt may be relegated to the role of OEM supplier.
John Deere’s platform, MyJohnDeere, enables third parties to build applications on their platform. As these applications can readily leverage data collected from machines and data from other providers (i.e. weather, soil conditions), the incentives for third party to build their application on MyJohnDeere and be part of their ecosystem is very high. Currently, this platform can also be integrated with suppliers to manage “Just In Time” supplies at the farm, things like seeds and fertilizers as such.
As John Deere installs more sensors and onboards more third parties to their platform, the amount of data they can leverage increases dramatically. Which is great, as providing expert intervention remotely requires vast amount of data from all different sources. By collecting data from their machines and monetizing it with AI and services; John Deere positions themselves and their products uniquely at the farm, unlocks new customer value, and paves the way for meeting the food demand of the future.
Disclaimer: I am not sponsored or associated with John Deere (in any way). I have been following them due to my professional interest in Data Strategy. The information gathered for writing this article was done so by gathering information from public sources, for which I put the links below.
References
Focused on Unlocking Customer Value, Deere Announces New Operating Model — https://www.deere.com/en/news/all-news/2020jun17-new-operating-model/
John Deere Reveals Fully Autonomous Tractor at CES 2022 — https://www.deere.com/en/our-company/news-and-announcements/news-releases/2022/agriculture/autonomous-tractor-reveal/
John Deere launches See & Spray™ Select for 400 and 600 Series Sprayers — https://www.deere.com/en/our-company/news-and-announcements/news-releases/2021/agriculture/2021mar02-john-deere-launches-see-and-spray-select/
Farm to Data Table: John Deere and Data in Precision Agriculture — https://digital.hbs.edu/platform-digit/submission/farm-to-data-table-john-deere-and-data-in-precision-agriculture/
From product to platform: John Deere revolutionizes farming — https://digital.hbs.edu/data-and-analysis/product-platform-john-deere-revolutionizes-farming/
Data Dominates — https://www.bcg.com/publications/2020/how-data-can-create-competitive-advantage
