Dae Sizes Launch Inventory 50% More Accurately

Case Study: Dae x DAASH

When Dae prepared to launch a new product, the biggest question was not whether consumers would want it. It was how much inventory to build.

Like many brands, Dae had historically forecast launches using its own sales history. But previous products were not necessarily good proxies for a new innovation. A conservative forecast could lead to an early stockout; an aggressive one could tie up working capital in excess inventory. Dae needed to size demand against the market the product was actually entering.

The Result: A 50% More Accurate Launch Forecast

“Real category demand replaced internal-only benchmarks—improving Dae’s forecast accuracy by 50% and reducing out-of-stock risk.”

DAASH gave the team an external benchmark for demand. Instead of extrapolating solely from Dae’s historical performance, the team could see how comparable products were selling week by week, the volumes they were moving, and how performance varied by retailer.

That changed the basis of the forecast. Dae could size inventory against category demand and competitive velocity, giving the team a more realistic view of the launch’s potential before committing inventory.

The result was a forecast that was 50% more accurate, helping Dae better match supply to demand and reducing the risk that out-of-stocks would interrupt momentum when it mattered most.