Knowledge Is Power, Use Data To Fuel Better Decisions

Decision-making is part of everyday life for all of us. In fact, humans make an estimated 35,000 decisions a day. From what to wear to which route to take to which strategy to adopt, humans make decisions all the time. Some of those decisions might be made impulsively, through carefully balancing alternatives, by prioritizing, or even by pushing the decision off to others. 

If you are a farmer, everyday decisions and how you make them can have a big impact – on your business, on the environment, and on worldwide food scarcity. Agronomists, agriculture professionals, researchers, and policymakers have the same vast impact derived from their decisions. Those decisions will become even more important as the agriculture industry continues to face challenges like climate change and a growing population.  

As the world population approaches 10 billion by the end of this century, producing enough high-quality food to feed every hungry mouth will be paramount. And while the population will increase, the availability of arable land and other natural resources will not increase. Ultimately, this demands efficient use and protection of existing resources to maintain their viability well into the future. 

This means the impact of farmers’, agronomists’, researchers’, and other industry stakeholders’ decisions will be magnified. From determining the best crop rotation strategy to creating nutrient management plans to deciding whether to apply fungicide, farmers’ decisions will directly tie to their own profitability and viability as well as the sustainability of the world’s population. 

Decision-making in agriculture can be supported by the vast amounts of agronomic data collected in modern agriculture. Data science and data analysis provide information and insight that support balanced decisions. With advancements in agriculture data systems, it’s easier than ever for data to be a key support in making sustainable decisions. 

Types of Data in Agriculture 

Agriculture data science has evolved alongside the agriculture industry. Technology has enabled agriculture to grow in scale and precision; no longer are many tasks on the farm done by hand or row by row. Mechanization and automation have also created opportunities for additional data collection on the farm that add to the traditional methods of collecting data for decision analysis. Now, there are several types of data collected and used in agriculture. 

  • Non-tangible data: for centuries, people have used gut feelings and advice from more experienced people to inform decisions. Farmers are no different – and in some cases, farmers may have even used printed prediction materials like the Farmer’s Almanac to make decisions. These inputs to decision-making aren’t datasets that are scientifically collected or statistically significant, though they may still have value to a given farmer. 
  • Manually collected data: farmers have long been manual collectors of data. A peek inside a tractor or truck cab used to frequently reveal a stained notebook or two detailing weather patterns, pest pressure, or even charts of crop varieties by field. 

Some of this data is now collected automatically, though many farmers still manually collect weather data or crop scouting records. Today, many do so in mobile apps instead of with paper and pen. This is a valuable set of observations that works well in combination with automatically collected data. 

  • Automatically collected data: connected equipment can capture real-time, precise, and location-specific data. Drones and sensors on equipment – like irrigation infrastructure or row crop farm machinery – automatically gather data. In many cases, this data can be shared automatically with cloud-based systems to enable real-time adjustments. 
  • Shared data: open source databases or collaborative information shared between professionals is data that can enrich localized datasets. Agronomic databases like the Global Crop Nutrient Removal Database provide global, open, comprehensive information to support decision-making. This type of data promotes open science and collaboration, enabling the world’s best minds to work together to solve agronomic problems. 

Together, these agriculture data systems provide a complete picture of an acre, a field, a farm, or a production system. This collective viewpoint supports informed decision-making.  

Next-Gen Agriculture Begins With Data-Driven Decisions 

In today’s agriculture industry, critical decisions can be supported by accurate, real-time data. Many different stakeholders in the industry benefit from data supporting their decisions, including farmers themselves, agronomists, researchers, agriculture companies, and even policymakers. 


For farmers, data can support many decisions. Agronomic data science can inform decisions around varieties, crop rotations, application timing, and more. Smart crop monitoring, like drone-based imagery, can provide insight into remote corners of fields that are difficult to reach and understand. Monitoring crops for quality characteristics like moisture, or fruit color can help farmers harvest at precisely the right time to maximize crop quality. Data can even reduce the number of decisions that farmers have to make through data-driven automation and autonomy. 

Small-scale farmers and growers have much to gain from data-supported decisions. In one study, data-supported machine learning algorithms used in management practice guidelines on small-scale farms in Colombia led to high yields with less failure risk. McKinsey notes that the value of connectivity is higher in Latin America, Asia, and Africa, where yields are not yet optimized.


For the trusted advisors that help farmers optimize crop nutrition and manage pest and disease pressure, data is a critical input to decision-making. Access to near real-time data from a variety of sources – such as soil moisture sensors and nutrient sensors – can enable the swift creation of prescriptions to address nutrient deficiencies or pest pressure. 

The combination of the agronomists’ background, education, and localized knowledge with available datasets allow fast decision-making that protects yield potential. Agronomic data science plus a deep knowledge of fertilizer and crop-protectant technologies will help agronomists deliver unique perspectives and solutions to growers. 

Researchers and commercial companies 

For scientists, developers, researchers, and marketers, ever-increasing datasets allow enhanced collaboration, customer value, and innovation. The world’s best minds working together unlock maximum value from the data. This collaboration is key to overcoming obstacles on the path to innovation. 

Data can also support decisions end-use consumers make in regard to which companies’ products they want to buy. This is a key marketing tool for agricultural companies that want to address consumers’ desires to understand where their food comes from. Data is the foundation of food traceability

Data also supports researchers and companies in accelerating innovations through product pipelines. Time to market can be reduced through data collection on testing at scale. And decisions about product readiness and efficacy – as well as marketable claims – can be made confidently when supported by data. 


Data systems are critical for the development of agricultural policies and programs. Data-based models can be used for agricultural policy analysis and economic impact assessments. As policymakers create frameworks that drive sustainable natural resource management, data can help model on-farm decision-making and impacts on the natural environment. 

Data Alone Doesn’t Make Decisions 

Alone and without analysis, data is an ineffective catalyst for change. But when people are armed with data and the tools to use it, it can become an incredible basis for making crucial decisions. 

Agmatix, a global agro informatics company, creates tools that unlock agriculture data insights to empower field-level decisions. Agmatix’s suite of tools enables agriculture’s biggest stakeholders to communicate freely with the intent to solve agriculture’s biggest challenges. 

This starts with Axiom technology standardizing data into a single standard language with rules, ontologies, and taxonomy. When data is apples-to-apples, regardless of source, it can be used to provide context and perspective to support informed decisions. 

The Agronomic Trial Management solution supports the collection of critical data throughout the growing season. This system has end-to-end capabilities for planning, executing, and analyzing results from agronomic field trials. Ultimately, this connects trial coordinators, field technicians, and research scientists to real-time data throughout the field trial. This real-time data is a key input for real-time decision-making. Armed with this information, data can help support new innovations as they are assessed for efficacy, safety, and market potential. 

Digital Crop Advisor is a data-based decision support system designed to provide options to support agronomists in making the best recommendations in the context of real-world situations. Digital Crop Advisor creates crop nutrition plan options for up to 12 nutrients and over 150 crops; this provides flexibility for agronomists to combine the data-based options with their localized knowledge. Digital Crop Advisor also allows users to compare nutrition plan options and understand tradeoffs between sustainability and yield potential. 

Agmatix is committed to open-source data and believes in the value of collaboration for driving innovation. The Global Crop Nutrient Removal Database is one example of this. It was created in collaboration with the International Fertilizer Association, Innovative Solutions for Decision Agriculture, the African Plant Nutrition Institute, and Wageningen University & Research. It aims to support collaborative decision-making around crop nutrient needs to optimize for sustainability and crop productivity. 

You may be interested in:
Data Analytics at the Center of Next-Generation Agriculture
Turning Agronomic Data into Actionable Insights: An Overview of Axiom

The Importance of Data Standardization and Harmonization to Innovation

Data Supporting Decisions 

Agriculture is faced with many challenges, and the scale of those challenges will only increase with time. The decisions made by farmers, agronomists, researchers, and companies in agriculture add up to a big impact over time. 

That’s why it’s so important to leverage the available data and data tools to inform critical decisions. Agmatix is committed to supporting agriculture’s decision-makers with the tools and open data needed to confidently make decisions that balance both sustainability and crop productivity. 

When good quality data is placed in the hands of agriculture experts, decision-making isn’t driven by the data, it is supported by the data, leading to the most educated and effective decisions possible.