Each of the 200 warehouses of the global 3PL has a
challenge with cycle counting their Million+ bins.
The value of cycle counting, regardless of your method, is that you can gain a more accurate inventory assessment without having to halt operations.
Maintaining an accurate inventory count is crucial to achieving warehouse productivity and quality. Inaccurate inventory counts lead to delayed orders, lost time looking for items, and customers. Staffing to support traditional methods of inventory audits has been difficult to sustain due to ongoing industry wide challenges in employees recruiting and retention.
“Opportunity-based” cycle counting uses triggers like when an
item is ordered to be put- away. Other triggers include when the quantity of an item goes below a certain threshold or when a product is “short-picked,” in which your company ships with fewer items than an order specifies. Using Mlops, CBC data scientist accurately forecast the error rate on discrepancies in real time.
BENEFITS REALIZED BY CUSTOMER
Using AI/ML in the warehouses, the 3PL operator realized higher order fulfillment rates while saving labor productivity (of course,
much less error counts).