Case Study: Automated Inbound Parcel Sortation & Delivery

Inbound parcel sortation

System reduces staffing from 25 to 6 employees

The inbound parcel sortation system utilizing the latest in optical character recognition (OCR) and sortation manages the delivery of a wide variety of parcels where centralized receiving is required.

This system was implemented within a large bioscience campus located in Northern California with over 20,000 employees. Automated inbound parcel sortation systems are implemented for campuses, businesses, or anywhere with a centralized receiving warehouse.

This large campus had a centralized receiving warehouse to alleviate the disruption of multiple delivery vehicles roaming a secure campus. 2,500 – 6,000 parcels are received on a daily basis and delivered to the owner on the same day. Some of these parcels require signature and/or special handling services.

Previously this process was labor intensive and required a staff of 25 to receive, process, sort, and deliver inbound parcels. Process and delivery times were hours to days depending on volume.

With the OCR sortation system, parcels are received and inducted onto the conveyor system. The system provides the intelligence to read the inbound label, look up the receiver database, and place a sortation label on the parcel. In this circumstance, the OCR system deciphers information on the label such as the owner’s name, the purchase order number, and special handling instructions, eg. “Hazmat”, “Will Call”, or “Perishable”. An interface retrieves information on the host computer to find routing, delivery, or stop information and a label is automatically applied to the parcel and routed to the appropriate lane destination.

The implementation of this system reduced the staffing required to process the parcels from 25 to 6 employees, with the capacity to receive, process, sort, and deliver 2,500 – 6,000 parcels on the same day.