Corteva Agriscience > Case Studies > Making Profitable Decisions with Data

Making Profitable Decisions with Data

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Company Size
11-200
Region
  • America
Country
  • United States
Product
  • Granular
Tech Stack
  • Data Analytics
  • Mobile Applications
Implementation Scale
  • Enterprise-wide Deployment
Impact Metrics
  • Cost Savings
  • Productivity Improvements
Technology Category
  • Analytics & Modeling - Big Data Analytics
  • Functional Applications - Inventory Management Systems
Applicable Industries
  • Agriculture
Applicable Functions
  • Business Operation
Use Cases
  • Predictive Maintenance
  • Supply Chain Visibility
Services
  • Data Science Services
About The Customer
Running Lake Farms is a family-owned farm located in Pocahontas, AR. The farm was started in 1980 by Gregory Baltz, a graduate in Agricultural Engineering from the University of Arkansas. The farm primarily grows rice but also cultivates soybeans, corn, and peanuts. Over the years, the farm has been growing steadily. Gregory Baltz, the CEO of the farm, is actively involved in the daily operations of the farm and is constantly communicating with his crew to ensure smooth operations.
The Challenge
Running Lake Farms, a family-owned farm in Pocahontas, AR, was facing challenges in forecasting its profitability at the beginning of each season. The farm's profitability was dependent on various factors such as the cost of inputs, yield, and market prices. The farm was also struggling with identifying unprofitable fields and understanding the reasons behind their lack of profitability. The farm needed a solution that could help them analyze their data and make informed decisions.
The Solution
Running Lake Farms implemented Granular, a software solution that helps farmers manage their operations with data. Granular allows the farm to keep a full record of their input applications, helping them understand the cost of production per field. The software also provides analytics that help the farm identify which fields are more conducive to certain crops. This allows the farm to change their cropping plans based on expected financials. The farm uses Granular to analyze the previous years' production and identify profitable, marginal, and unprofitable fields. They then try to understand the reasons behind the profitability or lack thereof of each field.
Operational Impact
  • With Granular, Running Lake Farms has been able to add the financial aspect to all of their activities, allowing them to understand the cost of production per field.
  • The farm has been able to identify which farms are more conducive to certain crops, allowing them to change their cropping plans based on expected financials.
  • The farm has been able to identify unprofitable fields and understand the reasons behind their lack of profitability.

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