# Turning a Covid supply shock into $3.8m of recovered revenue

> A premium global footwear and lifestyle brand · Retail & Consumer

A premium global footwear and lifestyle brand was left simultaneously over- and under-stocked when the pandemic disrupted its supply chain. QuantSpark built a single optimisation model, powered by machine learning demand forecasting, that recovered $3.8m in net revenue over six months.

## At a glance

- **$3.8m** net revenue uplift over six months

## What was the problem?

In 2021 the brand's supply chain was severely disrupted. Freight lead times had lengthened amid worldwide shortages, and power cuts had reduced capacity at overseas factories. The result was a business simultaneously over- and under-stocked at SKU level: roughly 384,500 units in excess and 175,800 in shortfall. Capital was tied up in slow-moving stock while priority lines risked going unfulfilled.

## What did QuantSpark do?

QuantSpark built a single mathematical optimisation model, powered by machine learning demand forecasting, that tied the excess-stock problem directly to fulfilment. The model forecast excess stock against outstanding purchase orders and reallocated production capacity to priority SKUs in shortfall; balanced ocean against air freight to protect availability while limiting margin erosion; and re-optimised a purchasing plan across roughly 1.3m items within production and logistics constraints. Product priority rankings let the model protect high-value lines. Multiple scenarios, including 15% and 20% air-freight budgets, gave a clear cost-versus-availability trade-off rather than a single fixed answer.

## What changed?

The engagement delivered a $3.8m net revenue uplift over six months from increased order fulfilment. It removed more than 64,000 units of excess stock and freed a 30% increase in available capacity, adding resilience for future seasons. In the primary scenario, the final stock position fell by 19% and shortfall across the top three priority rankings dropped by around 39%.

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