In most foodservice DCs, travel accounts for up to 70% of total order selection time. A big reason for this is that most DCs are creating units of work – two or three pallet assignments – using simplistic batching rules and sequence-based routing that takes selectors on sub-optimal travel paths.
Through Lucas Systems Dynamic Work Optimization solution, there is a way to attack this travel problem using AI that can improve selector productivity 8-15%, reduce travel 20-30% and optimize labor beyond order selection with intelligent task allocation and machine learning based analytics for slotting and workforce management. And the best part is you can do it without changing any of your existing systems.
