IDS Case Study: Increasing Efficiency of Farm Equipment Maintenance

By Keiter Technologies

IDS Case Study: Increasing Efficiency of Farm Equipment Maintenance

How can data be used to serve the agriculture industry?

Data Science can help you achieve your business goals with tailored advice specific to your organization. Learn more about how Keiter Data Solutions solved a similar problem for one of our clients in the below case study.

Challenge and Opportunity

A Keiter Technologies client and retail agricultural cooperative serving the agronomy, energy and farm supply needs of its members and customers across eight states wanted to help its members by creating a tool they could use to predict when its tractors needed maintenance service.


Our Approach

  • The team carefully analyzed the data provided by members of the cooperative regarding the tractor’s maintenance schedules recent repairs, brands, and usage hours.
  • Using Python, the team developed a predictive model which specifically outlined when equipment would need repair or maintenance.
  • The model was created to be easily accessible to the cooperatives over 200,000 farmer-members.


The model successfully predicted tractor maintenance needs and reduced offsite equipment failure rates by 90 percent. This resulted in increased profit for the cooperative’s members.


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About the Author

Keiter Technologies

Keiter Technologies

Keiter Technologies focuses on serving businesses with their strategic technology needs through data science, cybersecurity, and IT audit and consulting.

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The information contained within this article is provided for informational purposes only and is current as of the date published. Online readers are advised not to act upon this information without seeking the service of a professional accountant, as this article is not a substitute for obtaining accounting, tax, or financial advice from a professional accountant.


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