An industry that demands precision
Walker Edison is a furniture wholesale company with headquarters in Salt Lake City, Utah. They specialize in providing innovative home furnishing to major and minor eCommerce websites such as Amazon, Walmart, Home Depot, and many more. Since their creation in 2006, they have designed and distributed sleek products from living room couches to patio furniture. They are known for their ability to provide quality products at an affordable rate. Josh Rocha works on the operations team and is responsible for ensuring inventory levels are stable and accurate. In an eCommerce world, time is of the essence so it is vital to the success of the company that Josh accurately plans and forecasts demand. After weighing many options, Josh and his team chose Avercast to provide this crucial information.
Prior to Avercast, Walker Edison was using Excel sheets to plan and forecast demand. Josh and his team realized as they continued to grow, “you can’t just keep operating in Excel.” They worried, however, that switching to a third party software would give them less flexibility in customizing their forecasts. When they found Avercast, they saw the possibility of working with an excellent, customer focused software that would allow them, not only to keep the customizations they were used to, but develop even more.
Walker Edison uses NetSuite as their ERP so not only was it important for Avercast to provide customizations, they chose Avercast because it was able to pull all the data required from their ERP and run it through the over 200 algorithms in the software and provide the most accurate results. This was a major selling point for Josh and his team. Josh himself said “As we analyzed other advanced planning softwares, you maybe had 8 to 10 basic algorithms.”
The sophisticated algorithms used by the Avercast software allows them to confidently state that they have the most accurate forecasting tool. On this, Josh remarked “One of the great things Avercast did [was give] us the opportunity to take as many SKUs as we wanted and give them historical data and run the forecast in the system and see what that output was. I think that was a huge selling point for us because when I got the forecast back and compared it against our current forecast, variances were within plus or minus ten percent. For us that was a huge confidence boost.” Don’t just take Josh’s word for it. Reach out to Avercast today for a free demo and begin the process of optimizing your