The Holy Grail of AgTech


Current developments in the agtech industry are indeed impressive. Farmers are being offered new precision farming technologies every day and they are more and more willing to adopt them. The vast majority of these technologies are focusing on collecting data about the farmer's field, which has a significant potential to bring benefits to everyone involved in the industry from a farmer to a final consumer.

However, without the decision making support tools, it can be very challenging to truly crack this data and use it to achieve desired goals. And this is exactly where prescriptive analytics comes into play.

The next big thing

Prescriptive analytics is commonly referred to as the next big thing in the world of Big Data. Basically, it is a way of measuring a sequence of best next actions in order to achieve the aspired goal. In its complexity and value, prescriptive analytics is superior to both descriptive analytics (looks into what has already happened) and predictive analytics (looks into what could happen), as prescriptive analytics provides actionable recommendations and suggests what we should do to achieve a longer-term goal.

Prescriptive analytics as a game of chess

To better illustrate how prescriptive analytics works, let's think of a game of chess. The ultimate goal here, of course, is to win. In this scenario the predictive analytics model would measure the success rate of each individual move, by analyzing such factors as the current position of the chess figures, the closest figures of your opponent or players skill level. Therefore, this approach would suggest the next best immediate move that you could make at that particular moment. This is indeed useful for the instant action, however, not for the ultimate goal. In fact, the easiest route that you can follow at the beginning of the game can often lead to a quick and painful loss.

On the other hand, prescriptive analytics model would recommend an optimal sequence of moves that are based on the desired goal - in our case, a victory. In other words, prescriptive analytics would find patterns in a vast amount of data and optimize a sequence of decisions in order to win the whole game, instead of separate battles. So, if you can apply it, prescriptive analytics truly is incredibly valuable, as smarter decisions inevitably bring better results.

From precision to prescriptive farming

Prescriptive analytics has enormous potential in a host of different industries. It has already proven its value in transportation (i.e. Google's self-driving car), business industry (i.e. resource optimization), finance industry (i.e. fraud prevention) and, of course, agriculture (i.e. actionable nitrogen recommendations).

As discussed above, many modern farmers have this immense amount of data, but they often lack the decision making support tools that would enable them to purposely use it. And even if a farmer would understand the provided data and could use the insights to their benefit, just as in a game of chess, there are no two growing seasons that would be exactly the same. Agriculture involves many variables, such as climate, temperature, rainfall, altitude, wind etc. Which means that successful long-term farming must be based on continuous learning.

With a little help from machine learning and artificial intelligence, prescriptive analytics finds new patterns based on the new data, re-learns the models and suggests farmers new course of action towards their goals. This shows how prescriptive analytics can close the loophole between the vast amount of data that agtech innovations provide and a final decision making by a farmer.

Vultus solution

Unlike a vast majority of other agtech companies, here at Vultus, we put the prescriptive analytics to use. Thanks to these technologies, we are able to provide farmers with the actionable nitrogen recommendations, that are based on the satellite data. These easy-to-follow prescriptions inform farmers of exactly how much nitrogen fertilizer their plants might need, and, in turn, enable farmers to stop over-fertilizing their fields, grow healthier plants at a lower cost and better care for the planet.