What is Ag Big Data? How 8 Companies are Approaching it

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Ag Big data is a phrase that has integrated the world of technology across industries in recent months and years. It’s about capturing relevant data from the huge number sources collecting it today, and translating that into actionable information to improve business processes and insightfully solve problems at scale and speed.

As an industry where farmers and agribusinesses have to make innumerable decisions every year, agriculture has been an obvious target for big data. Arguably tougher climate and commodity price conditions are making it all the more relevant for farmers to use any information they can get their hands on to help make critical farming decisions. Big data has been a key driver of the progress made in precision agriculture, whereby farmers and agribusinesses are using the resources at their disposal in the most efficient way possible to get maximum yields.

So in recognizing the huge potential benefits that access to big data analytics can have on the farm, a number of different ag big data technologies have cropped up for farmers and their various service providers to use.

On the hardware side, you have sensors in various formats collecting data. These include devices you stick in the ground to measure soil moisture and nutrient density; devices fitted to a tractor that can measure crop yields; predictive weather stations; and image-capturing satellites and drones mapping out land and measuring crop health.

Then there’s the software side, which collects, processes and analyzes the data, typically with the goal of presenting rich insights to farmers in a consumable format. Some companies offer both hardware and software in a vertically integrated offering — and usually those selling hardware will have a software program included — whereas others offer just the software.

This software will use data from the hardware sources described above, which is either owned by the farmer or by hardware businesses that the software provider will partner with such as machinery manufacturers. Or it will use data provided by farmers, from third party data organizations, or from publicly available resources such as local governments.

The way this data is then presented, or analyzed, varies depending on the software. But most programs are now accessible through computers, tablets and smartphones, and often include a customizable dashboard of the various data sets he or she is tracking.

Key decisions that software helps farmers make include when and how much to irrigate a field, based on soil moisture data, weather predictions, and crop health; and planting and harvesting decisions, based on yield data or weather. Fertilizer applications can be much more prescriptive, based on factors such as soil nutrient density, enabling farmers to save money on areas that don’t need as much, but also optimize yield across a property.

Big data analytics can also alert farmers to problems on a certain field, such as a pest infestation, or drought conditions, reducing the need for manual checks of every piece of land regularly. With existing and increasing labor shortages in agriculture, the ability for big data analysis to create efficiencies that reduce the need for physical manpower is a big benefit for the industry particularly for very large scale operations.

The opportunities to improve farming efficiency are seemingly endless, which is why there are an increasing number of options on the market for farmers. But with that opportunity, comes a range of challenges for the industry as it develops.

One clear challenge is adoption and how to make the data collected relevant and useful for the farmer you are targeting. For many agricultural operations, acquiring and using a software system like many of those on the market will be a big adjustment from the Excel spreadsheets and paper/pen approaches that many farmers still rely on. So not only do ag big data companies need to convince a farmer to make the switch, but they also need to make sure that the user interface is easily usable and that the farmer will see an obvious return on investment in a relatively short timeframe.

Some farmers might be relatively tech-savvy and want a system that is quite advanced, whereas others are really starting from scratch. So how will companies appeal to the wide spectra of technology ability, operation size, and type of farming operation in the industry?

The size of the agricultural operations using the technology is also important. Many of the options out there today target the very large operations in the US, which will likely be much more complex, with more equipment and teams than smaller operations. So how does a technology address the needs of both big and small operations?

It’s worth bearing in mind that some of the big data technology companies out there are targeting a B2B business model, and not intending to interface with the farmer at all. Is that a scalable model?

Collecting data where a farmer does not own his own sensory hardware, or where there aren’t existing images or databases, will be another challenge. As will building the algorithms and technology needed to standardize the data no matter where it comes from.

There are also some concerns about data privacy that could have an impact on the progression of the industry. Without any current laws or regulations enforcing the data arrangement between farmers and data analytics providers, it is unclear how this will play out in the future.

On a mission to help paint a clearer picture of the emerging technologies out there, AgFunderNews recently spoke with eight agriculture big data companies to learn more about what they offer their customers, how they define big data, and where they see the sector heading.

These eight, while by no means exhaustive of all the products in the market today, have all successfully raised venture capital funding. They are also some of the more advanced offerings available to agriculture businesses today, and they represent a mix of the different technologies operating in the big data sphere.

Company: The Climate Corporation

Location: San Francisco, California

Interviewee: Anthony Osborne, vice president of marketing

Data Source: A combination of public data, private data sources, and data that farmers choose to provide about their operations.

Product: Software and hardware.

Software: The Climate FieldView platform, which combines farmers’ field data with real-time and historic soil, crop and weather data to help them efficiently manage their operations and gain insights about their fields.

Hardware: A precision agriculture kit. (It recently sold Precision Planting to Deere & Company)

Target Customer: Farmer

“For us, big data involves digitizing everything the farmer does to their field, as well as all the info that we can gather from a sensor or satellite image about that field, and what is going on in that field or the atmosphere around that field.”

Big Data Insight:

“Our biggest challenge is really deciding where to focus our resources first. During the time our customer starts planning for the next season, plants the crop, and harvests at the end of that season, we have identified over three decisions that are crucial in impacting their economics. Our biggest challenge is prioritizing those and solving the biggest ones first, as opposed to solving everything at once. It’s a tremendously large space of opportunity for the company.”

Company: aWhere

Location: Broomfield, Colorado

Interviewee: John Corbett, co-founder, CEO, and president

Data Source: Multiple sources including aWhere’s weather data observation stations and satellite data.

“Big data is the power and technology to pull all applicable data from multiple sources to develop better decision making at the location at an appropriate time. Big data has to understand the nuances throughout the farming process. It is not just weather. It is the right piece of decision support at the right location at the right time.”

Product: Data Supplier

“We provide the agronomic data through thresholds and numerical values that each of the intermediaries or software providers use to make that final text message or interpreted advice to the farm.”

Target Customer: Intermediaries and software providers

Big Data Insight:

“You have to have domain expertise in agriculture. The coolest thing in this world is how we produce food. People don’t realize how heavy it is and how fast you have to move to get it to people fresh. I think big data will protect our food supply because weather variability will hammer ag globally. Accurate, symmetrical data will smooth that, so big data is hugely important to our food supply.”

Company: FarmLogs

Location: Ann Arbor, Michigan

Interviewee: Jesse Vollmar, co-founder and CEO

Data Source: Public weather data, satellite imagery, FarmLogs hardware, user data from farmers.

Product: Software and hardware.

Software: FarmLogs platform providing digital field monitoring software and a mobile app.

Hardware: FarmLogs Flow, a hardware device that automatically connect combines to the FarmLogs platform and creates instant yield maps as fields are harvested.

“We utilize software, data science, and machine-learning technology to capture, collect, and analyze data sets and massive amounts of data from the field and data generated by sensors in combines and transform it all into simplified, actionable field-level intelligence so that farmers can make better, data-driven decisions.”

Target Customer: Farmer

“Ease of use is important, but it also needs to be valuable. We don’t want to just give them data that we think is cool as scientists. It has to be useful and impactful on their operation.”

Big Data Insight:

“We don’t define the term big ag data. FarmLogs focuses on figuring out how to extract value for farmers from big data—be it small or large ag.”

Company: OnFarm

Location: Fresno, California

Interviewee: Lance Donny, CEO

Data Source: Data partners that collect data on behalf of the grower.

“The grower is the owner of the data, we are building software to display and digest their data. We do not purchase data.”

Product: Software – farm management tool

“OnFarm is a farm management tool that displays and analyzes data from many different sources in a single, easy-to-use application. Every grower is different, regions are different. Our drag-and-drop dashboard allows them to put data models, analytics, and types of data sets right where they need it. They’ll get busy, they’ll get tired of looking at the same image. If we can run analytics against an image and look for water pressure, stress, disease, we can place something on the map that says there’s a problem at a specific point.”

Target Customer: Farmer

Big Data Insight:

“To us, big data is really just the quantity and velocity of data that we receive. We consume a lot of sensor readings all day long from tens of thousands of sensors. But, the grower doesn’t really care about that. The grower cares about how you take the information they are overwhelmed with and give it back to them in ways they can use to make a decision. They don’t want big data. They want to know what they need to be worried about on this field and what they should do about it.”

Company: FarmersEdge

Location: Winnipeg, MB

Interviewee: Wade Barnes, CEO; Ron Osborne, VP division of new technologies – hardware

Data Source: FarmersEdge hardware, universities, government agencies, key partners, key suppliers, proprietary hardware.

Product: Hardware and software. The FarmCommand system, includes a small, rugged device that automates the collection, reporting of real-time costs, equipment data and work information seamlessly and easily.

“Our service offerings utilize proprietary hardware, customer aftermarket and OEM hardware, cloud, mobile and embedded software, and the expertise of our global team in order to deliver real value to our customers and partners. You’re either agronomy, or software, or hardware—you are never all three and we are all three. Two years ago, when we were out raising capital and I told investors we do agronomy, software, and hardware they all laughed at me, saying I was unfocused and that it isn’t a good idea. They aren’t laughing anymore.”

Target Customer: Farmer

Big Data Insight:

“Most of the agtech world created out of Silicon Valley is coming from people that have experience in big data in other sectors, but they haven’t really implemented this into a real life ag experience. I think some of these people are really bright and bringing in ag people to sit on their boards. Truly, we eat, sleep, and drink this. We touch the farmer and the field every day. This is such a small component of what farmers do. I think it will be hugely important—it’s the next big thing. My fear is they will never get there if we make this so complicated. If you get multiple people in the same room, it will make it tough for it to be successful. The science part, as dumb as it might seem, is an easier problem to solve than the problem of getting the right, consistent data from the field. Our concept is bringing the data from the ground up, whereas others look at it bringing data from the cloud down. The winners and losers won’t be about who can create programs. The winners will be the ones that take data from fields and create a solution for the grower that is effective. It’s going to come from the ones that get good, field-centric data.”

Company: Agribotix

Location: Boulder, Colorado

Interviewee: Jason Barton, director of business development

Data Source: Drones, private weather data.

“Less than half of the data that we process comes from our drones. Sixty percent comes from people flying drones they’ve built or bought and they upload data to our cloud based processor.”

Product: Software

“We are a software company that’s gotten good at hardware out of necessity. The data processing is definitely our strongest suit. We have built a couple of drones just integrating off the shelf technologies because, until recently, there have not been drones purpose built for ag–or very few.”

Target Customer: Farmers and intermediaries.

“Our direct customer is typically an agronomist, tractor dealer, or crop consultant. It’s all different depending on where you are. We have a number of service providers who purchase our drones and provide drone services to a variety of industries, not just ag.”

Big Data Insight:

“Precision ag can create a lot of value for farmers while also creating jobs to deliver that value I like that we can help create jobs in places that are important to us. I think gaining trust is going to be difficult. A lot of what I really respect about agriculture is not falling victim to trends, not jumping after every newfangled idea that comes along. That’s positive. But, we’ve got some new ideas now. Part of the challenge to gaining that trust is that there are going to be bad technologies, crummy companies, or poor products on the market. I have met farmers who have had bad experiences and been burned in the past. It makes it harder to get them on board with the technology.”

Company: AgDNA

Location: Brisbane, Australia

Interviewee: Paul Turner

Data Source: Data licensing agreements with tractor manufacturers — John Deere, Case New Holland, and AGCO –, user data, smartphones and tablet images, GPS data and other spatial information.

Product: Software

“We provide a platform as a service to large ag equipment dealers as a branded solution. So, it has their logo and branding front and center and they in turn sell that as their own data management solution to their grower clients and they sell it on a per acre basis. The beauty of this is because of our data licensing agreements with manufacturers, it means the dealer can offer a system that integrates seamlessly with the machinery that’s already on the farm they sell to the growers. It’s a pure digital service. We deliver all the data by the cloud and that’s available either through an online browser or a native app in the smartphone or tablet for both Android and Apple devices.”

Target Customer: Ag equipment dealers and farmers

“Our primary method of sales is B2B. So, they are our direct customer, but of course they sell the service to their growers on a per acre basis. We do offer a direct-to-grower, simpler solution software as a service. It already has tens of thousands of registered users in 164 countries encompassing 4.3 million acres of fields under management. That’s quite a broad solution and it gets a lot of attention, but our main commercial driver is the B2B model.”

Big Data Insight:

“I’ve spent the last 15 years in the precision ag sector. AgDNA was founded on the basis of making growers’ lives easier and more profitable. In 2012, I got the idea for AgDNA on how to bring the easy button to growers, but doing it in such a way that we leverage the local dealer. They are an integral part of the whole farming community and a key stakeholder in the farmers’ world, as well, so that was always a go-to-market strategy. The other real key for big data is that it has to be seamless and fully integrated across the entire farm. We are seeing too many piecemeal solutions–narrow verticals of niche products–but a grower doesn’t want to deal with 20 different apps and data sets because for the most part none of them interact with each other. That’s the key to our platform. We take a holistic approach. We are looking at the beginning of the season from initial planning and tillage ops, all the way through planting, spraying, crop care, and finally harvesting.”

Company: Conservis

Location: Minneapolis, Minnesota

Interviewee: Chris Benyo, chief revenue officer

Data Source: Farmer data, weather data, private databases.

“Historically, it has been all the farmer’s data. Weather is the first outside piece we have integrated to provide an additional layer of information. We partner with Iteris, who has been in the business for a number of years and recently transitioned into the ag space. We have access to some outside databases that have application rates for pesticides. We are building a more robust integration for this so the farmer can just go to a list of chemicals, see when he should enter the field after spraying, how to spray it, and the weather conditions around spraying time. It’s all available but difficult to organize and get pulled in. We are also working on the first pieces of machine integration right now with John Deere and looking at pulling in a broader set of machine data.

Product: Mostly software.

“We primarily offer a software solution, but in this market you kind of get into helping people with hardware. Bluetooth adaptors are something we put together for a half a dozen types of truck scales so we provide those to the farmer to make sure those get done. It’s easier for us to take care of that for the farmer.”

Target Customer: Farmers

Big Data Insight:

“Our focus is helping farmers use their data and information to their advantage. So, our goal in helping them gather this data is to find ways that they can make their own data more useful. At the same time, there is an aggregation opportunity in the sense of what is going on in the country, region, or state can benefit one farmer. We see that big data aspect as really a byproduct, but it’s also something that we will use to drive back into the farmer’s businesses to help them. As far as the future, what we see is a need to help farmers make sense of all the information coming at them and make sense of it it rather than having them go to 25 different places and expect them to draw a conclusion. There has to be a roll-up of that data into something more useful.”

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Image credit: Camelia.boban

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