Corteva Agriscience Case Studies Making Profitable Decisions with Data

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	Making Profitable Decisions with Data Corteva Agriscience

Making Profitable Decisions with Data

Corteva Agriscience

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
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. Read More
About 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. Read More
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. Read More Log in to view content
Contents

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

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.

About 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.

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.

Impact #1	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.
Impact #2	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.
Impact #3	The farm has been able to identify unprofitable fields and understand the reasons behind their lack of profitability.

Impact #1

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.

Impact #2

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.

Impact #3

The farm has been able to identify unprofitable fields and understand the reasons behind their lack of profitability.

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Overview

Making Profitable Decisions with Data

Operational Impact