/ Scheduling /
Companies need to dynamically allocate resources across competing jobs or customers to cut costs, exploit opportunities, speed production, and improve service. Yet scheduling problems can be notoriously difficult to model mathematically. Analytics has both the deep domain knowledge needed to understand the complexity of industrial scheduling problems and the modeling and software development expertise to develop superior scheduling solutions.
A few examples of how Analytics helps companies optimize scheduling decisions across a wide variety of industries:
- Manufacturing: Developing custom software tools that determine the order to process different jobs or how often to change tooling.
- Distribution: Designing an optimal warehouse picking sequencing policy.
- Transportation: Developing and executing one of the fastest available plane routing algorithms.
- Services: Creating solutions that yield shorter call center response times, bring repair technicians to customers more quickly, or more efficiently schedule medical procedures.
Since Analytics is not tied to any particular software product or consulting methodology, we can craft solutions using the most appropriate off-the-shelf software or custom develop tools when necessary. As a result, our clients receive the most appropriate solution for their unique environment.