Our client is a leading designer and distributor of rigid packaging products with over 40 locations worldwide. Private equity backed, the company has been in business for more than 100 years, and is private equity owned, with revenues of approximately $1 Billion.
The company engaged Auxis to assess and identify opportunities for process efficiencies and cost improvements for its business operations. Our client recognized that they had too many manual processes, and were looking for solutions to drive (down) costs and increase operational efficiency.
One process in particular, customer quotes, was very challenging due to the constantly changing vendor pricing. This process was highly manual, time consuming and prone to errors, which would directly impact sales and margins.
The Process Before RPA
Typically, vendors would provide updated price lists or individual item price changes for their products, via an email attachment (PDF or Excel file). In some instances, the file could be more than 20 pages long and contain hundreds of vendor SKUs. When a customer needed a quote on a product, the company’s Account Coordinators would be required to go into a central email box or onto a shared drive, match the vendor SKU to the company’s SKU and identify the most current price.
They would then need to verify that the price change was in accordance with established business rules (there were limitations, by vendor, on how frequently the vendor could change the price on a product and what percentage the price could be changed.) The process to identify the correct price typically took the Account Coordinators about 15 minutes per order.
“80% of the quoting process was spent just figuring out the right price to use. This time was equivalent to 108,000 hours per year or 52 FTEs”
This information would then need to be manually input into the company’s order processing system, with the remainder of the quote generation process taking another 3 minutes. Thus, more than 80% of the quoting process was spent just figuring out the right price to use!
Putting this into perspective, their 120 Account Coordinators will usually process on average, 3,600 orders each, per year, for a total of 432,000 total orders per year processed in this manner. With each order requiring approximately 15 minutes to determine the correct price to use, that means that 108,000 “people hours” were being spent by the Account Coordination team just to search for,
validate and input the correct price.
In order to help improve the productivity of the Account Coordinators on this task, Auxis designed a solution that incorporated Robotics Process Automation (RPA) and SQL Server Reporting Services to automate multiple steps in the process, including:
- Monitoring emails to identify any notification of any vendor price changes
- Opening any vendor price change documentation contained in the email and identifying any relevant item price changes, matching these items to the client’s SKU number
- Validating the price changes versus established contractual guidelines (e.g. time frame for change notifications, percentage of cost increase approved)
- Notifying key stakeholders of any price changes that were not compliant to established guidelines and required action
- Updating a Vendor Price Database (SQL Server) with current (valid) vendor prices, matching vendor SKUs to company SKUs
Account Coordinators now utilize a Vendor Price Lookup tool to view the most current vendor price in order to determine the price for the customer order, by inputting the company’s item number into the tool. The price lookup process, which previously took 15 minutes to complete, now could be completed in seconds!
This new quoting process has produced more than 80% productivity gains, and the 108,000 “people hours” saved offers a potential cost savings of more than $1 Million, with an ROI of less than one month.
This revised process not only increased operational efficiency and productivity, but also provided improved controls and risk mitigation related to inaccurate vendor cost used to determine the customer price and margin.