Ubique Group improves their customer fill rate by over 15%

The company offers over 4,000 unique, highly-rated commercial and residential products with unparalleled marketplace distribution, including large outlets like Amazon and Wayfair. They have four distribution centers in North America, one in Europe, and one in China, and import over 90% of their items from China, India, Thailand, Taiwan, and Malaysia.

Although Ubique Group has 4,000 standalone product SKUs, once you include all the sellable items available through numerous combination options, this number escalates to over 100,000. Every customer has unique SKUs, and Ubique Group has thousands of customers.

Limitations with spreadsheets

Ubique Group’s spreadsheets had basic forecasting calculations and couldn’t sufficiently handle the company’s seasonal products. Additionally, due to scale issues, Ubique Group could only forecast at the item level, not the more granular SKU level needed. “Not only was it becoming increasingly more time-consuming to manage our forecasts, but the file size of our spreadsheets were becoming enormous and would take too long to update and refresh,” says Rubin Chen, VP of Supply Chain Planning at Ubique Group.

More in-depth forecasting was needed

Needing to forecast their inventory at an item, customer, and location level, through multiple distribution centers and needing to take seasonality into this mix drove Rubin to seek a fit-for-purpose solution. “My team and I used Netstock Predictor at a previous company. It made sense for us to implement it at Ubique Group so we could all use what we knew, loved, and had success with in the past.”

The impact of longer lead times, increased freight costs, and container shortages

Sales for certain product lines, such as school and church furniture, sharply declined due to COVID-19-related lockdowns. In contrast, residential demand increased as people improved home offices and furnishings. The radical shifts in demand for products, both upward and downward, during and after COVID necessitated a highly agile forecasting process. “It’s imperative for us to rapidly adjust to shifting demand and supply. Netstock Predictor allows us to correct irregular history while retaining actual sales visibility. As a result, our forecast accuracy has improved despite the challenging times.”

“We have been very happy with Netstock as a product and as a company and have reduced our operating inventory on active products by around $10 million while also improving our fill rate by over 15%,” concludes Rubin.