business “Before some products are even developed, we have customer focus meetings all the time,” Nelson says. “We even have our own research group that takes a look at all of that, because we have to try and figure out 10, 20, 30 years from now, where is agriculture headed and what are the needs in the future?” But that isn’t to say the data farmers share can’t be significant. “Right now farmers can opt in to allow us look at machinery issues,” Nelson offers as an example. “Say we’ve got 1,000 combines working out there and if we’re able to get the machinery information, maybe we find out 400 had this bearing fail in a certain time period.” That level of insight helps the company reassess specific shipments or parts suppliers and that’s the sort of customer knowledge that leads to build better machines moving forward. The question, though, is whether Deere can generate similar kinds of analytics, not just on its machines, but on its farm customers too. So far, that seems to be a step too far. Ag-chem companies, for instance, can crunch their sales numbers and figure out who their most valuable customers are, so they make sure they fight harder to retain their business by, for instance, sending agronomists to the farm, supplying extra technical support or perhaps offering great seats at an NHL playoff game. They can also analyze their data to look for opportunities to up-sell or cross-sell. But beyond that, the science hasn’t gone all that far.
Think ‘group’ It’s a point that Peter Gredig, a farmer and ag technology expert based near London, Ont., believes is very important for farmers to understand. One person’s information alone is not especially useful to anyone. But volume changes everything. “A lot of the data that’s collected, socalled big data, they don’t care who it is,” Gredig says. “Marketers, advertisers, and manufacturers want to be able to aggregate it. And with that, comes power.” Consider a phone app he helped to develop years ago called the Aphid Advisor. After scouting a soybean field for aphids, you input your observations and the app will tell you whether or not a spray application is warranted. “If you check off ‘I’m OK to share,’ it generates a data point so that researchers know where, when and what the environmental conditions were on a map of February 2, 2016
Ontario,” Gredig says. “In real time they would be able to see where that pest is manifesting and, I mean, how would we do that otherwise?” Where information sharing leads to greater good for everyone, Gredig says he has few concerns about giving access to his own information. Understanding the intentions of anyone who asks for your data is the critical thing in his mind and not something anyone’s being very diligent in explaining up front. “I’ve loaded apps or other pieces of software and the terms and conditions are in there, and I don’t think the lawyer who wrote them has read them,” Gredig admits. “If you’re going to hand off data to somebody else, at that moment, questions have to be asked; how are you using it, what access to copies will I get, and how will I be kept informed about it?”
Company marketers tap your purchase data to customize their sales pitches. But that’s just a start Gredig says if you don’t like the answers you get, you don’t have to give your consent. But if there are benefits to be gained in exchange, think carefully. And if your concern is someone else’s ability to profit by having it, well, chances are good they won’t because it doesn’t seem like anyone in the industry has figured out how to really profit from all this data yet. “The ability to collect is well beyond our ability to assess,” Gredig assures me. Basically, agribusiness right now is in the same spot crop producers were during the release of yield monitors in the late 1990s. “The idea was, we would just stare at these maps and all would be revealed,” Gredig recalls. “I have the feeling that agribusiness is going to end up staring at stuff and wondering how to get some value out of it.”
The limitations Kolodziejak says the limitations of data management create a real hurdle for analyzing customer information. So much decision-making depends on the emergence of patterns, but it’s extremely difficult not only to see from the data when
a few isolated events actually become a pattern, but also whether the pattern will eventually be influential. Even if you could do that much, Kolodziejak says, you’d still be trying to sort out the complications that can arise from external factors, such as weather events, that have a big impact on the outlook of farming customers. For instance, if a particular region got too much rain during fall harvest last fall, could that mean that their survey responses are artificially low? It’s her job to decipher when data like this is being skewed, or the company could respond to a business issue that isn’t really an issue at all. Then there’s an additional complication. Farmers who have good experiences in customer service outside of agriculture expect such services to be provided within the industry too. Sometimes, negative feedback isn’t because of bad customer service from an FCC transaction, Kolodziejak explains. “It is because they have the experience of buying a condo on an iPad, and those experiences are shaping their expectations of working with us.” If customers continue to expect improved customer service, at accelerating rates, technology is going to have to take more of the manual labour out of her job going forward. “Excel is a great tool for so many things but if you have to go through and manually enter all of that information, the likelihood of you doing that is less,” she says. New technology needs to be developed to collect information easily, as well as analyze it. “You see other examples of technology that are good cases,” Kolodziejak says. Her personal favourite is the Nest Smart thermostat. “So many of us have programmable thermostats, we might have taken the effort to do that initial setup but it’s cumbersome, and all of a sudden you go away for a week and you don’t change that program. The Nest will learn, based on motion sensors, if you’re even at home, will adjust the temperature based on that, and then it gives you a report that allows you to see the trends and patterns yourself to make decisions. She wonders what an equivalent to this technology to help collect data in agriculture might look like and what more it could show her from the data she’s collecting. It’s a huge opportunity, Kolodziejak believes, and it is definitely attracting application developers, tech companies, and venture capital to agriculture. CG country-guide.ca 25