RESULTS
Man
Hours Saved
0 /year
Improved
Shipping Times
0 %
Staff Able to Focus on
Higher Value Tasks
0 FTE
Client manages national sales and distribution of grocery goods.


Client manages national sales and distribution of grocery goods.

The company relied on a multistep manual process of reviewing a mainframe-generated paper report, often several hundred pages or more, to identify and flag order errors or exceptions in pencil. The marked-up report would then be handed off to other team members who would make the corrections in the mainframe.
This required a large workforce spanning multiple shifts to manage the order load and meet shipping schedules. Whenever sufficient staff levels could not be maintained, processing slowed down and orders were lost. This led to costly customer service issues and lost revenues. Manual results were non-standard, inefficient, and prone to inaccuracy.
Instead of relying on a paper printout, SphereGen leveraged rules-based RPA to read report data output to a text file to extract only the valid exceptions requiring corrective actions. The corrective mainframe updates were then made directly by the automation.
In place of a manually initiated process every 2 hours, automations are run multiple times every hour on the hour ensuring that shipment timelines are always met; the need for customer service is minimized; and mainframe updates are 100% accurate. Email notifications are used in special cases.
Man
Hours Saved
Improved
Shipping Times
Staff Able to Focus on
Higher Value Tasks
The manual process required a full-time team of 9 people across 3 shifts to keep up with the order and shipping schedule. The automated process could complete the requirements in 3-5 minutes, therefore the team was reduced to just 3 people and the other staff members were re-allocated to higher-value tasks.
A fraction of the former team now allocates limited hours to review and take timely corrective actions on 100% accurate and complete standardized data.