Corteva Agriscience Case Studies Using Machine Data For Profitability

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	Using Machine Data For Profitability Corteva Agriscience

Using Machine Data For Profitability

Corteva Agriscience

Technology Category	Analytics & Modeling - Big Data Analytics Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries	Agriculture
Applicable Functions	Discrete Manufacturing Logistics & Transportation
Use Cases	Asset Health Management (AHM) Farm Monitoring & Precision Farming Supply Chain Visibility
Services	Data Science Services
Challenge	Anson Family Farms, a large farming operation spread across 20,000 acres in 8 counties in Indiana and Illinois, was facing challenges in managing and utilizing the vast amount of data collected by their John Deere equipment. The data, which included information on planting, spraying, harvesting, etc., was primarily used for crop insurance reporting. However, the farm was unable to use this data to optimize operations due to technological limitations. The data was initially stored on a desktop machine, then moved to a server, but both methods were slow and cumbersome. The farm also struggled with real-time data access, which made it difficult to identify and correct errors in a timely manner. Read More
About Customer	Ben Singleton is the CFO of Anson Family Farms, a large farming operation that farms around 20,000 acres in 8 counties in Indiana and Illinois. The farm primarily grows corn and soybeans, using a 50-50 rotation, and practices no-till farming with cover crops on most of their acres. Ben grew up on a small cattle operation in Indiana and has an accounting and finance degree. He initially worked as a public accountant before joining his wife's family's farming operation. In addition to his role as CFO, Ben is also involved in the operational side of the farm, managing their soybean planting and one of the harvest crews. Read More
Solution	The farm started using Granular's mobile app to manage their machine data. The app allowed workers to receive work orders and enter data on the go. The data from the app was then cross-checked with the machine data to identify and correct errors. The farm also moved their data to the cloud, which improved access and speed. Looking forward, the farm plans to use the data for more than just crop insurance reporting. They want to use the data to compare the profitability of different types of ground and to determine whether they would be better off running more equipment or farming less but more profitable land. They also plan to use the data for activity-based costing and to filter the data in meaningful ways. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Infrastructure as a Service (IaaS) - Cloud Computing

Applicable Industries

Agriculture

Applicable Functions

Discrete Manufacturing

Logistics & Transportation

Use Cases

Asset Health Management (AHM)

Farm Monitoring & Precision Farming

Supply Chain Visibility

Services

Data Science Services

Challenge

Anson Family Farms, a large farming operation spread across 20,000 acres in 8 counties in Indiana and Illinois, was facing challenges in managing and utilizing the vast amount of data collected by their John Deere equipment. The data, which included information on planting, spraying, harvesting, etc., was primarily used for crop insurance reporting. However, the farm was unable to use this data to optimize operations due to technological limitations. The data was initially stored on a desktop machine, then moved to a server, but both methods were slow and cumbersome. The farm also struggled with real-time data access, which made it difficult to identify and correct errors in a timely manner.

About Customer

Ben Singleton is the CFO of Anson Family Farms, a large farming operation that farms around 20,000 acres in 8 counties in Indiana and Illinois. The farm primarily grows corn and soybeans, using a 50-50 rotation, and practices no-till farming with cover crops on most of their acres. Ben grew up on a small cattle operation in Indiana and has an accounting and finance degree. He initially worked as a public accountant before joining his wife's family's farming operation. In addition to his role as CFO, Ben is also involved in the operational side of the farm, managing their soybean planting and one of the harvest crews.

Solution

The farm started using Granular's mobile app to manage their machine data. The app allowed workers to receive work orders and enter data on the go. The data from the app was then cross-checked with the machine data to identify and correct errors. The farm also moved their data to the cloud, which improved access and speed. Looking forward, the farm plans to use the data for more than just crop insurance reporting. They want to use the data to compare the profitability of different types of ground and to determine whether they would be better off running more equipment or farming less but more profitable land. They also plan to use the data for activity-based costing and to filter the data in meaningful ways.

Impact #1	Improved data management and access with the use of cloud technology and Granular's mobile app.
Impact #2	Ability to identify and correct data entry errors in real-time.
Impact #3	Potential for more strategic decision-making based on data analysis.

Impact #1

Improved data management and access with the use of cloud technology and Granular's mobile app.

Impact #2

Ability to identify and correct data entry errors in real-time.

Impact #3

Potential for more strategic decision-making based on data analysis.

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Overview

Using Machine Data For Profitability

Operational Impact