These shoes were made for walking … to the Edelman Award competition!

Each year, finalists in the Franz Edelman Award Competition demonstrate how advanced analytics and operations research are solving real problems at massive scale – from the products we buy and the packages we receive to the healthcare we rely on and the policies that shape our communities.

Joining me today is a member of the team from ECCO, the globally recognized footwear brand known for its vertically integrated supply chain and retail operations.

Managing inventory across hundreds of retail locations around the world is a massive logistical challenge. Historically, store replenishment decisions were made manually, which often led to inconsistent ordering, operational inefficiencies, and missed opportunities to optimize inventory placement.

To address this, ECCO’s data & AI team developed a powerful analytics system that uses large-scale stochastic mixed-integer programming to automate store replenishment decisions across their global retail network.

We are immensely proud about our effort and what we have achieved. And we’re so humbled by the fact we are standing among Microsoft, Google, NVIDIA. Also Chewy is there which is 10 times bigger than ECCO, measured in revenue. Then we have departments in the most populous country in the world. And then we have ECCO, small ECCO, a family-owned business. So it makes me really proud both for our own achievements but also for ECCO as a company.

Interviewed this episode:

Matthias Als

ECCO

Matthias Als is a lead data scientist at ECCO. For more than four years at ECCO, Matthias has built automated decision systems especially for inventory management problems combining the power of both machine learning and operations research. Matthias holds a MSc degree in computer science from the IT University of Copenhagen. In 2024/2025, Matthias was also on the board of the Danish Operations Research Society, DORS.

Related Episodes