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Ohio State University Extension


Developing a Farm Digital Strategy 1 - Introduction

Agriculture and Natural Resources
John Fulton, Professor and Extension Specialist, Department of Food, Agricultural and Biological Engineering, Ohio State University
Jenna Elleman, Integrated Solutions Consultant at Ag-Pro
Elizabeth Hawkins, Field Specialist, Agriculture and Natural Resources, Ohio State University Extension

Digital technologies today are shaping how we do business and how we conduct our personal lives. Smart phones, iPads, tablets, and other devices are used daily by people of all ages around the globe. Precision agriculture (PA) technologies are also now common on farms. Farm machinery comes from the manufacturer with technologies already embedded including internet connection capabilities already installed. This abundance of technology is capable of collecting large volumes of data for a field.  Tractor cab with technology installed

A study conducted by the Ohio State Digital Ag team in 2017 collected 60.4 petabytes of data using commercial precision and digital agriculture technologies for a 100-acre field. This included PA data layers such as yield maps, as-applied maps, as-planted data, remote sensed imagery, weather, and scouting data. The project illustrated the volume and complexity of data that can be collected with commercial technologies. The study team encountered 39 different and mostly proprietary file types that required several software packages to access and use the data.    

With the evolution of digital agriculture globally, farmers need to consider how they plan for, manage, and ultimately make use of collected data. Several types of farm data have the potential to provide value to farm operations. Some of the more notable field-level data layers include agronomic, machine, prescription, remote sensed imagery, and production data. With so much data being generated by machinery and technology today, in conjunction with PA services and digital tools offered by industry, it is important for farm operations to develop a digital strategy to ensure they derive value from data and retain control of their data. 

Developing a digital strategy can pose a challenge for many farm operations, however. This fact sheet, the first of three in a series, focuses on defining a digital strategy and identifying important questions a farm needs to answer during strategy development. Two subsequent fact sheets (FABE-556 and FABE-557) outline important details such as data collection, storage, sharing, and legal considerations.

What Is a Farm Digital Strategy?

A farm digital strategy, defined in the box below, provides guidance for data collection and use in the farm operation. Ultimately, it creates a framework for what data is collected, how it is managed, and how it is used internally by the farm and externally by others.  


Setting Goals for Your Digital Strategy

Most farm operations are already collecting data at some level, but may not recognize it. A good starting point in developing a digital strategy is to outline key ways data collected on the farm can be used to bring new insights into the operation. While developing the outline, focus on how to save, secure, and share data, as needed. While the strategy need not be complicated, it should be in computerized form and shared via either electronic file or hard copy with all those in the farm operation.

The first steps in developing a digital strategy involve documentation:

  1. Identify the PA technologies (hardware on equipment) being used on the farm.
  2. Identify the data collected by these technologies. 

A variety of technologies generate data on farms today. Make a list of all technologies being used that are capable of collecting and storing data, including mobile applications (i.e., APPs). This inventory will help you understand what data is being collected and is accessible for use.  

Next, answer the following questions:

  1. What is your objective for the data being collected?
  2. What data and digital tools do you plan to use to meet that objective and why?
  3. Are you using any digital tools (i.e., APPs)? If so, list.  
  4. If not using digital tools today, do you plan to use any in the future?
  5. What person and/or entity do you plan to share data with? List all.
  6. What specific data do they require you to share with them? List all.
  7. How do you plan to share data both internally and externally?
  8.  What is your internal plan to store, archive, and secure data?
    1. Do you have a local storage device at the farm (i.e., laptop, external hard drive, server)?
    2. Do you use a cloud storage service (i.e., Box, DropBox, Google Drive, etc.)?
    3. Do you use an agriculture cloud platform (i.e., JD Operations Center, Climate FieldView, Encirca, etc.)?
    4. How do you back-up or have a 2nd copy of your data?
  9. Do you have a means to review and understand data agreements?
  10. How will you define success and evaluate the outcomes of your strategy?

These twelve questions provide a great start for developing a digital strategy for the farm. The answers define what data can be collected, how and where it will be stored, and how it might be shared. Looking down rows of corn

The second fact sheet in this series provides a detailed explanation for developing these aspects of a farm digital strategy. The third fact sheet provides a detailed explanation for developing the second component of a digital strategy, which is to outline your data management plan. It describes the process of saving, securing, and sharing data. While some farmers choose to manage their own data, others choose to utilize an agricultural technology provider (ATP) to help with data management.


The advancement of digital agriculture has created an opportunity for famers to use data to improve efficiencies and maximize revenue potential. To accomplish this, farmers should develop a sound digital strategy that focuses on collecting, storing/archiving, and sharing data, and on managing each of those steps. Legal considerations should be included, as well. Farmers should start with an objective for their data and then consider how to meet it with the tools and data types they already have or can deploy.

When implemented well, data usage in agriculture has been proven to provide value. There are many situations where data-driven decisions can directly benefit the producer’s bottom line. By using farm data to drive input management and other decisions, farmers can identify and quantify variables that limit productivity, such as soil types, crop health/pest issues, plant populations, weather, machine efficiencies, and more. 


To learn more about farm data, review these resources:


The authors would like to thank the following for their time and efforts in reviewing this publication: Dr. Ajay Shah and Dr. Sami Khanal, Department of Food, Agriculture and Biological Engineering Department, Ohio State University;  Ben Craker, Kuhn North America; Deb Casurella, MyAgData; Jeremy Wilson, EFC Systems; Christopher Zoller and Jason Hartschuh, Ohio State University Extension; Joe Luck, University of Nebraska; and Bruce Erickson, Purdue University.

Visit The Ohio State University Digital Ag Program online at and the Agronomic Crops Network at for additional information on this topic and more.

Follow the Ohio State Twitter page @OhioStatePA and the hashtag #DataIntel for information related to farm data and its value.

Originally posted Oct 15, 2020.