At SAP Leonardo Live last month, one of the most interesting presentations was by Cristiano Buss, the CIO of Stara S/A. Stara is a Brazilian manufacturer of farm equipment. The company has gone through two transformations. In 2005, they began manufacturing their own sensors, software, and computers. Then in 2015 they launched a Telemetrics System.
Today, Stara is not a commodity supplier of farm equipment; they provide “precision farming” solutions. For Stara, that means that 21 percent of their revenue is now derived from computer hardware and software revenues; 40 percent of their revenues comes from products launched in the last three years. For farmers, it means better yields, produced more economically and sustainably.
The core idea behind precision farming is that a farmer should not uniformly apply seeds, fertilizer and other inputs to their field. The farm is carefully mapped using machinery with the appropriate soil sensors. Then the farmer’s smart machinery applies seeds and fertilizer at variable rates based on the soil characteristics – nitrogen levels, organic matter content, moisture, etc. – at different points in the field.
There are far more sensors being used, and many more being developed, than you might guess. There are twenty sensors on a seed spreader machine, for example. These sensors measure not just how much seed is being applied, but the quality of the seed based on its size and shape. If the system determines that the seed is of relatively poor quality, the seed spreader in real-time “decides” to apply more seed. This real-time decision making capability is supported with in-memory computing supported by the SAP HANA platform and cloud-based analytics.
Mr. Buss asserted that the savings from variable seed application is 15 percent and are 19 percent for fertilizer. And these inputs are not cheap; a kilogram of soybean seed can cost $45 and a large farm can apply 18,000 kilograms of seed.
There are also savings from 6% savings on seed from overlap control. The idea here is that when the spreader comes to the end of the row and turns around, the turn is precise because of GPS-guided automatic steering and internet-connected telemetry systems. Thus, no piece of land is getting fertilizer or seed put on it twice. Mr. Buss said the precision of the moves was down to less than 2 centimeters of drift.
One of Stara’s large customers is quoted in an article saying “People didn’t think it would pay off to invest in tractors with infrared sensors. The sensor alone is a third of the price of the tractor, but … in two years I was able to recover my investment and significantly increase productivity.”
This is an Internet of Things solution because data is collected by sensors mounted on the GPS-equipped farm equipment. This is also a big data solution, telemetry generates huge volumes of data. And Stara has used these technologies to create a digital platform. The idea is that all farm machinery should connect to their platform, and in the future drones and satellite data as well. Further, the vision is this is not just an analytics platform, that the platform can be used integrate with suppliers to improve the inbound supply chain, farmers to share intelligence, and 3PL partners to reduce crop wastage from inefficient logistics.
Precision farming is perhaps the best current example of how IoT and related technologies can be used to transform business models to the benefit of both solution providers and their customers.