How a Pacific Northwest Hop Grower Cut Labor Costs by 13% Using Oxrow.ai

This multi-ranch hop grower was struggling to manage increased labor costs until Oxrow provided the transparency to uncover hidden profits in its data.

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The Challenge

With thousands of acres and over 300 workers in motion during peak season, this grower was stuck reconciling spreadsheets after decisions had already been made. They tried to make it work with a combination of field notes, monthly ERP exports, and management instinct but they couldn’t break down the cost of each field, or understand where their labor plan was slipping.

The inability to see detailed cost drivers created several business problems. Resources couldn't be allocated optimally. Management struggled to fairly assess crew performance for incentives or training. Operational accountability was weakened, and strategic financial planning became more complex. The 10-20 hours analysts spent each week manually compiling data was an inefficient use of time, increased overhead, and introduced the risk of errors in financial reports.

“Being able to take labor planning down to the microscopic level of what it should cost to prepare a new field for planting - this is the theme we're constantly talking about here since we started using data.”
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The Solution

The solution was to bring all data together into a centralized location instead of it sitting siloed across different systems. They chose Oxrow because of its unique position as an AgTech specialist, integrating with the farm management tools they already use. Oxrow’s AI insights take the system beyond data storage and allow growers to find actionable insights to optimize their profits. With the data centralized, this hop grower was able to start benefiting from these insights.

Almost immediately, data became central to operational and financial management. Weekly planning meetings focused on insights from Oxrow dashboards, addressing how to optimize cost and quality based on historical performance and planned work. Historical job cost analysis provided a foundation for budgets and operational targets. Near real-time performance visibility allowed for quicker operational adjustments impacting costs.

Oxrow provided intelligence that moved beyond basic labor reporting. The Operations Manager gained the ability to analyze costs "down to a microscopic level," enabling accurate cost projections for planning new fields. Side-by-side crew performance comparisons informed work allocation decisions. Identifying performance outliers quickly highlighted potential cost or quality issues, allowing intervention in hours, not weeks.

“Oxrow gives us different ways to see the data, depending on who I'm talking to. If I'm talking about efficiencies it's acres-per-hour. If I'm talking to the owners then it's the dollar labor cost-per-acre.”
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The Results

With Oxrow, this grower replaced loose estimates with data-driven labor budgets and operational plans, improving financial control and forecast accuracy. This led to visibility into performance variations, enabling management to identify cost-saving opportunities, and address those inefficiencies.

They reduced total annual labor costs by 13% compared to the previous year, directly increasing profitability.

They saved 10-30 hours per week of analyst time previously dedicated to manual data handling.

Too many growers across the industry find themselves guessing their labor costs and staffing budgets. This leads to inefficiently allocated labor and higher overtime. Farms all over the country struggle with finding ways to improve their profitability without sacrificing quality. Oxrow’s AI solution finds it for you.

“Every week we have new questions for the data and [Oxrow’s AI] makes it easy to answer them quickly.”