Abstract: Systems and methods are disclosed for simulating and optimizing employee scheduling. In one embodiment, a decision engine includes a communication device, memory storing instructions, and a processor configured to execute the instructions to perform operations. The operations may include receiving service data including at least tasks of a first type, tasks of a second type, and a plurality of employee volumes, each indicating a number of first employees trained for the tasks of the first type, second employees trained for the tasks of the second type, and third employees trained for tasks of both types. The operations may further include generating, based on the service data a plurality of estimates, generating a simulation of some estimates, generating an optimized decision specifying an optimized number of first employees, second employees, and third employees, and causing at least one output device to display an interface associated with the optimized decision.

Abstract: Systems and methods are disclosed for simulating and optimizing employee scheduling. In one embodiment, a decision engine includes a communication device, memory storing instructions, and a processor configured to execute the instructions to perform operations. The operations may include receiving service data including at least tasks of a first type, tasks of a second type, and a plurality of employee volumes, each indicating a number of first employees trained for the tasks of the first type, second employees trained for the tasks of the second type, and third employees trained for tasks of both types. The operations may further include generating, based on the service data, a plurality of estimates, generating a simulation of some estimates, generating an optimized decision specifying an optimized number of first employees, second employees, and third employees, and causing at least one output device to display an interface associated with the optimized decision.