Abstract: Various embodiments are directed to techniques for organizing fulfillment of enterprise products, such as by using a request manager informed by enterprise resources and resource utilization to recommend a facility to fulfill a product request. Some embodiments are directed to identifying a product request and determining the equipment and skills necessary to fulfill the product request. Based on this information and location data, embodiments may determine a set of facilities as candidates to fulfill the request. A machine learning model may be used to analyze current resource utilization of the facilities and predict facility availability and estimated completion times for the request fulfillment. A candidate facility may be recommended for fulfillment of a request based on facility availability and estimated completion times. In some embodiments, historical resource utilization may be used to inform further staffing and equipment service decisions.

Abstract: Various embodiments are directed to techniques for organizing fulfillment of enterprise products, such as by using a request manager informed by enterprise resources and resource utilization to recommend a facility to fulfill a product request. Some embodiments are directed to identifying a product request and determining the equipment and skills necessary to fulfill the product request. Based on this information and location data, embodiments may determine a set of facilities as candidates to fulfill the request. A machine learning model may be used to analyze current resource utilization of the facilities and predict facility availability and estimated completion times for the request fulfillment. A candidate facility may be recommended for fulfillment of a request based on facility availability and estimated completion times. In some embodiments, historical resource utilization may be used to inform further staffing and equipment service decisions.

Abstract: Various embodiments are directed to techniques for organizing fulfillment of enterprise products, such as by using a request manager informed by enterprise resources and resource utilization to recommend a facility to fulfill a product request. Some embodiments are directed to identifying a product request and determining the equipment and skills necessary to fulfill the product request. Based on this information and location data, embodiments may determine a set of facilities as candidates to fulfill the request. A machine learning model may be used to analyze current resource utilization of the facilities and predict facility availability and estimated completion times for the request fulfillment. A candidate facility may be recommended for fulfillment of a request based on facility availability and estimated completion times. In some embodiments, historical resource utilization may be used to inform further staffing and equipment service decisions.