Systems and methods for minimizing customer and jobsite downtime due to unexpected machine repairs

A system for minimizing customer and jobsite downtime due to an unexpected machine repair, comprising:

• one or more processors;
• and
• one or more memory devices having stored thereon instructions that when executed by the one or more processors cause the one or more processors to:
• receive, from a machine at a customer jobsite of a customer, sensor data from one or more machine sensors, wherein the sensor data indicates a machine failure;
• retrieve, from a network-accessible dealer site of a dealer associated with the customer, informational data about current repair technician backlog, shop availability backlog, and parts availability;
• input the received sensor data and the retrieved informational data to a machine learning model for computing an estimated time to when the failed machine will be repaired;
• retrieve, from a customer database, customer data about customer loyalty and importance;
• retrieve, from the network-accessible dealer site, informational data about dealer rental fleet availability for a model that is the same as or similar to the machine and informational data about loaner machines availability;
• compute an estimated financial impact from a potential loaner machine, based on availability of said potential loaner machine;
• determine a distance from a location of the potential loaner machine to the customer jobsite;
• input the computed estimated time to when the failed machine will be repaired, the retrieved customer data about customer loyalty and importance, the retrieved informational data about dealer rental fleet availability for a model that is the same as or similar to the machine and informational data about loaner machines availability, the computed estimated financial impact, and the distance from a location of the potential loaner machine to the customer jobsite to a decision tree algorithm at the server for computing an optimal solution for maintaining customer productivity;
• compute, by the decision tree algorithm, the optimal solution for maintaining customer productivity;
• and
• notify an entity at the network-accessible dealer site of the optimal solution, wherein the optimal solution is intended for the customer.

One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising:

• receiving, from a machine at a customer jobsite of a customer, sensor data from one or more machine sensors, wherein the sensor data indicates a machine failure;
• retrieving, from a network-accessible dealer site of a dealer associated with the customer, informational data about current repair technician backlog, shop availability backlog, and parts availability;
• inputting the received sensor data and the retrieved informational data to a machine learning model for computing an estimated time to when the failed machine will be repaired;
• retrieving, from a customer database, customer data about customer loyalty and importance;
• retrieving, from the network-accessible dealer site, informational data about dealer rental fleet availability for a model that is the same as or similar to the machine and informational data about loaner machines availability;
• computing an estimated financial impact from a potential loaner machine, based on availability of said potential loaner machine;
• determining a distance from a location of the potential loaner machine to the customer jobsite;
• inputting the computed estimated time to when the failed machine will be repaired, the retrieved customer data about customer loyalty and importance, the retrieved informational data about dealer rental fleet availability for a model that is the same as or similar to the machine and informational data about loaner machines availability, the computed estimated financial impact, and the distance from a location of the potential loaner machine to the customer jobsite to a decision tree algorithm at the server for computing an optimal solution for maintaining customer productivity;
• computing, by the decision tree algorithm, the optimal solution for maintaining customer productivity;
• and
• notifying an entity at the network-accessible dealer site of the optimal solution, wherein the optimal solution is intended for the customer.