Be a Data Diva
I know. Nobody likes a diva. But when it comes to data, don’t hesitate to demand the best. You are making a significant investment in technology and, more importantly, the future of your operation. Messy, incomplete or — even worse — inaccurate data won’t cut it. Here are four data demands that every farmer should make.
1. Demand data that is validated by replication and analyzed by experts. The more data points, the stronger the data. Agronomic data that is backed by extensive replicated trials and undergoes a quality assurance process gives you confidence in using that data to make critical decisions. Crowd-sourced data that is collected from many farmers, aggregated and then translated into some sort of general conclusion may be cheaper, but it will not provide nearly the same level of specificity.
2. Demand data that is prescriptive, not descriptive. Many data sources offer a look back at past performance, but nothing that is future-focused. Your data should be prescriptive — that is, it doesn’t only provide a graph or spreadsheet, but rather data-driven recommendations for your fields.
3. Demand data that is specific to your fields. Your doctor doesn’t prescribe medication for you based on another patient’s condition. Likewise, your neighbor’s yield data doesn’t address your challenges and opportunities. In addition to analyzing data from YOUR fields, look for data that takes agronomic variability into account.
4. Demand that data be analyzed with the help of an advisor. Odds are you’re not a statistician or an IT professional. To build an ag tech toolbox that best fits your operation, a trusted local advisor can help you get insights from your data that can power decision-making for a profitable harvest.
So there you have it. Be a diva as far as demanding quality data. Otherwise, keep your feet firmly planted on the ground!
1. Demand data that is validated by replication and analyzed by experts. The more data points, the stronger the data. Agronomic data that is backed by extensive replicated trials and undergoes a quality assurance process gives you confidence in using that data to make critical decisions. Crowd-sourced data that is collected from many farmers, aggregated and then translated into some sort of general conclusion may be cheaper, but it will not provide nearly the same level of specificity.
2. Demand data that is prescriptive, not descriptive. Many data sources offer a look back at past performance, but nothing that is future-focused. Your data should be prescriptive — that is, it doesn’t only provide a graph or spreadsheet, but rather data-driven recommendations for your fields.
3. Demand data that is specific to your fields. Your doctor doesn’t prescribe medication for you based on another patient’s condition. Likewise, your neighbor’s yield data doesn’t address your challenges and opportunities. In addition to analyzing data from YOUR fields, look for data that takes agronomic variability into account.
4. Demand that data be analyzed with the help of an advisor. Odds are you’re not a statistician or an IT professional. To build an ag tech toolbox that best fits your operation, a trusted local advisor can help you get insights from your data that can power decision-making for a profitable harvest.
So there you have it. Be a diva as far as demanding quality data. Otherwise, keep your feet firmly planted on the ground!
