Business intelligence is helping growers connect operational and financial data to manage risk, improve efficiency and make more informed decisions
Every day, commercial growers make decisions worth thousands, or even millions, of dollars. Should another fungicide application be made? Is a new sprayer worth the investment? Can another 500 acres be added without hiring more people? Today’s farms generate enough data to answer those questions. The challenge is turning that information into decisions before the opportunity passes.
That’s why business intelligence is becoming a fast-growing investment among large commercial farming operations. Rather than treating production, financial and operational data as separate pieces of the business, enterprise growers are increasingly bringing them together into centralized dashboards and forecasting tools. The result is a clearer picture of where money is being made, where costs are increasing and where problems are developing before they become expensive mistakes.
“The future isn’t about collecting more data,” said Greg Christensen, go-to-market manager for high-value crops at John Deere. “It’s about turning information into action.”
From Data to Decisions
Precision agriculture has been collecting information for decades. Tractors record engine performance. Sprayers document application rates. Irrigation systems monitor water use. Accounting software tracks expenses while agronomic platforms capture crop records. Each system performs its job well. The difficulty comes when managers try to connect them.
“20 years ago, most farm decisions were made with experience, paper records and a lot of windshield time,” Christensen said. “Today, growers have more information than ever before, but more information doesn’t automatically make decisions easier.”
The industry’s focus has shifted accordingly.
The most successful operations aren’t necessarily the ones collecting the most data. They’re the ones that can easily access it, trust it and act on it. — Greg Christensen, John Deere
Several years ago, many growers primarily wanted equipment information such as engine hours, fuel consumption or maintenance schedules. Those questions still matter, Christensen said, but conversations today revolve around much broader business issues. Growers want to know which fields consistently deliver the strongest returns, where labor costs are highest, which equipment is underutilized and whether expensive inputs are generating an acceptable return on investment.
Answering those questions requires combining operational and financial information rather than viewing each independently.
“We’ve seen a shift from equipment dashboards to business dashboards,” Christensen said. “Growers don’t just want more data. They want answers.”
That evolution is allowing technology to move beyond operational efficiency and become a strategic management tool.
“The default stack is spreadsheets, WhatsApp, email, and decades-old software,” Steele said. “The leaders are those collapsing operations, accounting and supply chain into a single system of record, so the order, its traceability and its ledger entry are the same object.”
Connecting the Entire Operation
William Steele, an independent technology consultant who previously worked at Harva, an AI platform for the perishables trade, said fragmented information remains one of agriculture’s biggest business obstacles.
“The default stack is spreadsheets, WhatsApp, email, and decades-old software,” Steele said. “The leaders are those collapsing operations, accounting and supply chain into a single system of record, so the order, its traceability and its ledger entry are the same object.”
That single source of truth becomes increasingly valuable as businesses expand.
Steele said many successful grower-packer-shippers still operate separate inventory and accounting systems, making it difficult to accurately understand profitability by product or customer.
“It’s common to find sizable, well-run operations that have a separate inventory system from their accounting system, so expansion decisions get made without a clean view of what the business actually earns at the SKU level,” he said.
Cash flow represents another blind spot. Produce businesses routinely handle products with short shelf lives while operating under payment cycles that can stretch well beyond harvest. Without visibility into receivables and future cash positions, a profitable business can still experience financial strain.
“A produce operation can be profitable on paper and still get into real trouble because receivables came in two weeks late during peak season,” Steele said. “Visibility into every open invoice, payable, and collection pattern turns that from a surprise into a managed variable.”
Turning Insights into Action
Business intelligence only delivers value when information leads to action. For instance, Gary Schaefer, chief commercial officer at InnerPlant, a company that develops crop-sensing technology, said growers are looking beyond dashboards filled with numbers. They want technologies that identify emerging risks and provide actionable recommendations while fitting into existing management systems.
InnerPlant’s technology monitors biological signals within the plant, detecting stress hours after it begins rather than days later when symptoms become visible. Those insights can be delivered through text messages, email or integrated directly into the John Deere Operations Center, where disease alerts can automatically create work orders identifying which fields require immediate attention.
“The information itself is fine,” Schaefer said. “It’s knowing what to do with that information and creating an action-oriented result that is most powerful.”
That approach is helping growers move beyond simply monitoring operations toward actively managing risk before problems become costly.
Building a Business Case for Investment
Connected data is also changing how growers evaluate major investments. Purchase price remains important, but enterprise operations increasingly need to understand how equipment, automation and infrastructure will affect labor, productivity and return across the entire business.
“The most successful growers are looking beyond purchase price and focusing on return,” Christensen said. “The real question is, ‘How does this help my operation become more profitable?’”
That distinction matters as growers consider autonomous equipment, precision application systems, irrigation upgrades and fleet-management tools. A technology investment may reduce the number of operators needed for a task, allow crews to cover more acres during narrow production windows or improve the consistency of work across distant blocks.
Those benefits can be difficult to quantify without reliable operational records.
Equipment utilization data may reveal that an operation can increase output from its existing fleet rather than purchase another machine. Labor records can show whether automation would reduce overtime or relieve pressure during a critical spray window. Application records can help determine whether precision technology would generate enough input savings to justify its cost.
“The best investments aren’t always the biggest investments,” Christensen said. “Often, they’re the ones that solve the biggest problem.”
Precision application offers one example. Smart Apply uses LiDAR to measure tree or vine canopy size and density, then adjusts spray output according to the crop in front of the machine. The system documents where and when an application occurred, adding another layer of information growers can compare with costs and production results.
The value isn’t limited to reducing product use. Accurate application records can improve regulatory documentation, reveal inconsistencies among operators and help managers evaluate performance at the block or row level. Small improvements can become substantial when multiplied across hundreds or thousands of acres.
Managing Variability Instead of Averages
Business intelligence becomes especially useful when it exposes differences hidden by whole-farm averages.
After all, no two blocks perform exactly alike. Soil, water, disease pressure, labor requirements and crop vigor can vary significantly within the same operation. Treating every acre the same can obscure where money is being made and where resources are being wasted.
InnerPlant’s crop-sensing technology is designed to identify that variability before it appears visually. The company uses plant-level signals to detect disease stress and deliver alerts that can be translated into field assignments.
Avoiding an unnecessary application can be just as valuable. Fungicide treatments can cost as much as $40 per acre, Schaefer said, creating a meaningful financial difference across large farms when disease pressure doesn’t justify spraying.
That information also helps managers prioritize labor and equipment. A disease alert can identify which fields require immediate attention, allowing an operation to direct sprayers and agronomists toward the greatest threat rather than working through a fixed schedule.
“Farmers are getting larger,” Schaefer said. “Prioritized workflows are a really big deal.”
The future isn’t about collecting more data. It’s about turning information into action. — Greg Christensen, John Deere
Making Data Easier to Use
The promise of business intelligence remains constrained by a practical reality: Many growers already feel overwhelmed by the information available to them.
Schaefer noted technology adoption can stall when platforms are expensive, difficult to navigate or unable to translate information into a clear next step.
“There’s a real big data overload,” he said. “It’s one thing to create these data systems and platforms. It’s another to make that action tangible for the farmer in a
simple way.”
That challenge explains why integration matters as much as innovation. Growers are less likely to embrace a new platform that requires another login, dashboard and workflow. They are more receptive when information enters systems their teams already use.
InnerPlant, for example, can send disease alerts through text or email, while growers using John Deere Operations Center can receive the information within that platform and generate a work order from the alert.
Steele sees the same issue on the financial side. Technology can make business data easier to access, but implementation depends on whether employees trust the system and use it consistently.
“The constraint isn’t the technology anymore,” Steele said. “Building the tools isn’t the hard part. Training people to use them is.”
That makes data quality and organizational discipline central to any business intelligence strategy. A dashboard built on incomplete field records, inconsistent product names or delayed financial entries can create false confidence rather than better decisions.
Christensen recommends beginning with a specific business problem rather than attempting to digitize everything at once. Labor, equipment utilization and input use are logical starting points for many specialty crop operations. Once field boundaries, machine connections and digital work records are established, growers can build a dependable operating history.
“The most successful operations aren’t necessarily the ones collecting the most data,” Christensen said. “They’re the ones that can easily access it, trust it and act on it.”
From Reporting to Prediction
Artificial intelligence could move business intelligence from explaining what happened to helping growers anticipate what comes next.
Most farm reports remain backward-looking. They show completed work, previous costs or last season’s performance. Predictive systems are beginning to identify which blocks may need attention, where equipment could fail and how labor should be prioritized before a problem disrupts the operation.
“The biggest change is that growers will spend less time looking backward and more time looking forward,” Christensen said.
Plant-level data could strengthen those models. InnerPlant is using artificial intelligence to process the large volume of signals generated throughout a crop’s development and improve its ability to identify risk earlier. Unlike a static product, a data model can become more useful as it receives additional observations.
That doesn’t eliminate the need for grower judgment. It gives managers another source of evidence when weather, markets, water availability and labor conditions are changing quickly.
Steele expects natural-language tools to accelerate that shift. Instead of waiting for a controller or analyst to produce a report, managers may soon ask a question from the field and receive an immediate answer based on operational and financial records.
The dividing line, he said, won’t be between farms that have data and those that don’t. Nearly every operation already has information somewhere.
“It’ll be who has trained their people to make it work for them,” Steele said.
That may be the clearest measure of business intelligence maturity. The strongest operations won’t necessarily have the most sophisticated dashboards. They will have systems that help people identify risk earlier, allocate resources more confidently and make decisions while there is still time to change the outcome.
Publisher’s Take
The Big Picture: What to do Next
1. Turn data into decisions
Collecting more data isn’t the goal. The most successful operations use integrated information to make faster, more informed business decisions.
2. Connect your systems
Bringing production, financial and operational data into one platform provides a clearer picture of profitability, equipment utilization and labor efficiency.
3. Measure return, not just cost
Evaluate technology investments based on how they improve profitability, reduce labor demands and increase operational efficiency, not just their purchase price.
4. Focus on actionable insights
The best business intelligence tools identify problems early and provide clear next steps, helping growers prioritize resources before issues become costly.
5. Invest in people as much as technology
Even the most advanced data systems are only effective if employees trust the information, use it consistently and turn insights into action.
Frequently asked
How are growers using business intelligence today?
Rather than treating production, financial and operational data as separate pieces of the business, enterprise growers are increasingly bringing them together into centralized dashboards and forecasting tools.
What should operations focus on when adopting BI tools?
Christensen recommends beginning with a specific business problem rather than attempting to digitize everything at once. Labor, equipment utilization and input use are logical starting points for many specialty crop operations.
