Agronomists Provide The Human Insights for Ag Analytics  

Ag analytics enhances your expertise but will never replace it. You know the fields, you know the agronomy, and your knowledge is a critical tool in creating useful information and insights.

Here at DXD Ag Insights, we keep agronomists in the driver seat of the ag analytics process. This is because agronomists are most likely to:

  • Ask the right questions of the data
  • Interpret the data in a useful way
  • Recommend appropriate action

Ask the Right Questions

Analytics should be purpose-driven, meaning that you have a decision or set of decisions in mind. You know the fields and you know what variability can be managed. Your goals impact the entire process, from the observations collected to the type of information and insights being explored, and what specific reports will be needed to communicate with partners.

Collect {just} the Right Data

The best way to approach your data collection is to start with the purpose in mind. Then you work backward to identify the specific observations and other data that will actually help you.

While the data collected in agriculture is increasing, there is often not a clear path from the data to a decision. Data is collected with the HOPE that it will be useful, rather than having an end in mind. However, we must be careful not to overvalue something just because it can be measured.

You (and the Computer) Interpret the Data

Knowledge of agronomy is required to properly interpret agronomic information. Agriculture is a dynamic system, with several important variables changing constantly through the season.

An expert using the right data analytics tools will be able to identify the insights that matter, as well as which insights need further study before being accepted.

Additionally, agronomists recognize which information is actionable, and which are just facts. Many variables are outside of your control. For example, you can't change the weather, but it's useful to recognize and study the likely impacts of the weather conditions. These facts might contribute to decisions later, such as when weather conditions are ripe for disease or pest issues.

You Recommend Appropriate Action

A colorful visualization can give the illusion that the data is all the information needed for a decision. Yet decisions that rely on data alone risk missing something important. The reality is that computers can't make decisions on the best course of action for your fields- that is the domain of the expert.

Agronomists can identify which insights are relevant to a decision, and also consider the feasibility and downstream impacts. Even if the ideal recommendation is to apply herbicide as soon as possible, there might not be equipment available, or the supplier is out of inventory, or the crop price doesn't support going over budget. Agronomists are also able to judge the risks of making the wrong recommendation.

While ag analytics can speed the process to a decision, it often can't take you to the finish line. For that reason, you can expect us to have put customers in control of running our data analytics tools and own the decisions.

The Human Insights Missing from Big Data:

For more context on this topic, check out this 2017 TED talk from Tricia Wang. Many of the concepts she discusses match our approach to ag analytics, even though she is working with different problems in different industries.

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Agronomist checking rice grain.
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