Workforce sizing and scheduling follow are so-called combinatorial problems – where we need to forecast various demand drivers, create shifts and pair individual employees to them. It’s a process that combines several interdependent decisions that must be made and requires obeying a set of rules/constraints to find a feasible solution.
We do not take the term optimization lightly. If the method can't prove a solution is optimal, then it is not the optimization in the mathematical sense. This is a key point in the approach we take at Houston Analytics. Most off-the-shelf software is built by coming up with answers for these points that would suit the widest types of clients possible. We reverse this logic, by relying on our technical capabilities to devise tailor-made models for a client-specific needs using dedicated optimization engines.