AI use case: predictive routing
Defining the Problem
Success in pest and disease control depends on choosing the right product and its correct application. Climate conditions should be favorable to the absorption and translocation of products. One common issue is for the product to arrive in suboptimal conditions, causing the customer to return the load. In addition to having an additional cost, this return overloads the routing team and impacts end customer satisfaction.
Solution
By combining delivery site data, we create a predictive routing model that takes into account the weather forecast at each destination and the estimated date of delivery. The probability of returning the load triggers the re-routing process
Results
Reduction of the Rate of Return of loads. Re-routing for routes with lower risk of severe weather (hail, floods, closed roads…). Higher response rate of 3PL to cargo supply. Increased customer satisfaction.
