Replenishment optimization has changed considerably over the past years.
Yes, that’s true. In the past, retailers made gut-level decisions, as in “Tomorrow is a holiday and the weather is supposed to be nice, so I guess I stock my stores with these products." There was no way of keeping track of the inventory in detail. However, in this day and age, retailers are no longer able to afford surplus inventory and elevated levels of waste because it is extremely expensive and could mean tarnishing the reputation of a company. When people find out that a supermarket chain throws away tons of groceries, it causes damages that go far beyond revenue loss. Having said that, customers still expect to find a fresh salad on Thursday evenings. Retailers need to consider all of these factors in their planning process.
You have specialized in food and fashion retailing. Why is that?
That’s because next to margin and revenue pressure, these areas are also very driven by online pure players. Added to this is that the shelf life of fresh foods in food retailing is limited and that retailers sell their merchandise right up to the expiration date. We support them in this by optimizing replenishment and facilitating flexible pricing. Things are different in fashion retailing, which is more driven by seasonal influences and needs to ensure its products in inventory have been sold by the end of the season to avoid sitting on unsold merchandise. We assist our customers by continuously adapting their prices, thereby significantly boosting their chances of selling their products.
You got the idea for your solutions from particle physics. How did this come about?
Blue Yonder originates in the data science field. The company’s founder Professor Michael Feindt is a former CERN scientist and noticed during his work that there are big parallels between particle physics and economic issues. After all, the challenge there is also to find connections in data that is so big to where a human being is no longer able to keep track of it – as is the case with the large and complex datasets created at the POS. We used this to develop our solutions, which can be applied in both online and offline retail.
Is artificial intelligence still a very abstract concept for the retail industry?
Actually, it no longer is. This term is currently being hyped up the same way big data was back in the day. I think the economic sector finally understands how these solutions can be incorporated into business processes to reap the benefits. In the case of Otto, for example, we optimize replenishment of the distribution centers with their partner retailers and we assist dm with forecasts its suppliers receive to deliver their products at a later stage. We also support the Magazine zum Globus AG with a pricing solution.
Does this make humans obsolete?
Unlike a human being, a machine is far superior in keeping track of large and complex datasets. That being said, a machine will never be able to make strategic decisions for us. Humans will continue to have to make those.