Editor’s note: This is the fourth of a series on questions growers should ask before investing in new ag tech. Because fresh produce is a high-value segment of agriculture, there are a lot of options available to spend money on, but asking the right questions before a purchase can save time, money and headache.
A lot of tech out there today either runs on data, generates data or both. Whether this is a connected internet-of-things-style irrigation sensor or a logging program to keep track of driver miles or a system that tracks harvest records that ties to payroll, there are some questions you should ask if data is involved in a new ag tech purchase.
They include:
- Do I have what I need for this tech to be useful to me?
- How usable (and actionable) will the data be?
- How can I use that data with artificial intelligence (AI)?
- Is this tech (and its supplier) right for me?
- Does it work with my business’ workflow?
No. 1: Do I have what I need for this tech?
This one might seem a bit basic, but it still bears asking. You can’t really have a useful “internet of things” system if, for example, you can’t get an internet connection out to your orchard.
Lack of connectivity was a reoccurring issue that Liz Turner, marketing and special project coordinator for Croptracker, a precision ag tech software provider serving the fresh produce industry, encountered in her work early on.
“People were not taking into account that a lot of the data capture needed to happen where there wasn’t a lot of signal. And so missing data became an issue,” she says. That pushed Croptracker to develop offline data collection strategies. So, if your answer to “Do I have sufficient connectivity for this system to work?” is no, then you should likely ask the ag tech supplier if they have a system that can handle offline data collection.
But checking in on if you have what is needed for a data-focused ag tech system or solution can be less direct too. Because it takes a lot of data to help get the most out of data-focused ag tech, Chris Higgins, general manager of Hort Americas, a components and materials supplier for CEA growers, stresses the importance of having historical data well organized.
“Five years ago, I would have said that the largest growers were not even ready to have the tech conversation because their data was unorganized,” he says. The large growers have gotten organized since then, he adds, but smaller growers are still struggling with data.
“The smaller growers are battling the fact that, ‘Oh yeah, one guy knows all of this data.’ Now getting that guy to sit down and put it into an Excel spreadsheet is very, very challenging,” Higgins says.
Turner specifically recommends growers have an eye to the future of data — i.e. AI — when they think about the organization of their historical data.
“Thinking about ways that you’re organizing and maintaining your historical records, even without a big clear vision about how AI is going to replace XYZ processes in your operation, is really important because that historic data can become really valuable for future AI uses,” Turner says.
She urges growers to think about how their historic records and data, things like production practices and fertilization records versus yield records, might fuel a personalized predictive model in the future.
“It’s important to consider that you’re not just capturing [that data] for now or for a government regulation,” she continues. “You can be capturing it for the future. That historic data that’s specific to your farm and your location and your varieties is very valuable to you and should be treated as such.”
No. 2: How usable will the data be?
This was the most common recommendation from all sources The Packer talked to when it comes to investing in a new precision ag system or data-generating sensor. It’s a key question because, if the data coming out of the system isn’t usable to you, there’s little point in investing in it.
Unusable data will just become an expensive dust (or storage space) collector, as Steve Mantle, CEO and founder of Innov8.ag, a data- and AI-focused tech consulting group that works with permanent crop produce growers, experienced.
“There was one grower I met with recently who had a stack of basically two reams of paper soil fertility reports, and you could tell they’ve been sitting there for several months,” he says. The grower told Mantle he’d “paged through” the data a bit, “but, it was clear that it wasn’t really actionable for them. It stopped at the owner’s desk. It hadn’t trickled down to those other tiers that actually could make a difference with that data.”
Turner also highlights the importance of the data being usable to the right people in your organization. This involves thinking about who will be using the data and what format that data should take to be most useful to them.
“For the most part, people at a desk making decisions about packing or quality or sales aren’t going to be able to look through every single QC form,” she says. “So it’s thinking about not just ‘I need all of this information,’ but ‘I need my sales desk to be able to look at a single screen and read that information in a way that can actually action on it.’”
Actionability, the correct next step, is the key difference between useful tool generating usable data and a cluttered dashboard according to Roy Levinson, commercial lead for digital farming and water meters at Netafim North America.
“Remember that information is great, but if you don’t have the tools to actually execute on the information you are gathering, you are wasting resources,” he explains. “Be sure that if you are implementing a tool that gathers information, you then will also have the ability to apply changes because there is nothing worse than not having the ability to do anything when you know you should.”
No. 3: What can the data do with the help of AI?
Mantle recommends growers ask AI-related questions of their suppliers when it comes to selecting a new data-generating ag tech product or system.
For example, he suggests growers ask how the data, once extracted, could be used and translated by non-proprietary AI tools.
“I think a really good way to ask tech providers is: ‘How can I use other tools like large language models that are relatively accessible to people now to input and think about this data differently?’” he suggests.
“If the answer is you can’t or haven’t thought about it or ‘Let’s have a discussion about it,’ then maybe you’re not talking to the to the right guys,” he adds.
No. 4: Is this tech and its supplier the right one for me?
Mark Lukenbill, commercial leader at MileMaker, a trucking-focused software solutions arm of Rand McNally, also suggests growers ask some specific questions about the suppliers of any data-focused ag tech under consideration. For example, what is that supplier’s security history?
“Security is important,” he stresses, adding that growers should ask about data breaches and potentially steer clear of companies that have had them.
When it comes to the specific sensor system or program or other precision ag item you are considering, Lukenbill also urges growers to ask: “Will this put me into tech debt?”
“For instance, if I go buy an iPhone 11 right now, I’m in tech debt because even though it’s a new phone to me, that phone’s going to be obsolete in two years,” he explains.
The risks of going into tech debt by investing in older technology include the limitations of that older technology compared to competitors, plus needing to upgrade more often and sooner than otherwise, Lukenbill adds.
“Implementing especially big, big tech inside your business is a big undertaking,” he continues. “It’s going to create a lot of friction. There’s costs. The fewer times that you can do it over X period of time, the better off you’re going to be.”
No. 5: Does the tech work with my (team’s) flow?
Speaking of the potential of causing friction in your business or on your team, Turner recommends growers ask if a system or new data-generating tech item works with how things already work on your operation. She pointed to wisdom learned in supporting berry growers with harvest tracking and payroll solutions.
“[Berry pickers’] pay depends on them moving quick, so delays where you are making them wait and stop so that you can take account of that inventory is detrimental to everyone’s productivity,” she notes. “Is your software able to support that speed or does it slow it down?”
She gave the example of an inventory system that allows for quick picker badge scan followed by scanning in of the berry totes compared to a system that requires someone to type even one number into a device. While the former allows everyone to move in their rapid flow, the potential slowdown of the latter could mean it’s more efficient for everyone “to count everything at the end while the workers are doing something else,” she explains.
“Whereas the benefit of having it in real time means that traceability is more secure, it’s more one-to-one, you’re less likely to make mistakes,” Turner says. “But if that process is too slow, then it’s not worth it.”
Basically, if a potential new system or device doesn’t work with the existing workflow, it might be skipped, bypassed or otherwise not used to its fullest potential. Which means the team or people who will have to use it need to be consulted, she says.
“The biggest things that we try to get people to ask is ‘Who should be involved in making the decision?’” Turner says.
This usually translates to ‘Who’s going to be the most impacted?’ she adds. “Our most successful onboarding for payroll processes and inventory tracking and things like that happen when the person who’s going to use that data for reporting and payroll is in conversation with the person who’s on the field capturing that data.”
This usually means bringing in, at least, the field supervisors into the decision soon “so that they can test out the flows,” Turner says.
Next week’s installment of the Tech Questions series will dive into this topic even more by focusing on what questions growers should ask their team before investing in new ag tech. Catch the rest of the series here:
