Otto Group uses predictive analytics to get to grips with forecasting, dynamic pricing and returns

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logo-transparentMichael Sinn, director supply and category management support, Otto Group, revealed how the world’s second largest multi-channel retailer, is using Blue Yonder’s predictive analytics for trend research, forecasting, demand planning, dynamic pricing and returns.

Sinn said Otto chose Blue Yonder because its forecasting technology, which uses an algorithm deployed by scientists working at CERN, provided the most accurate forecast to benefit supply readiness and reduce overstocks.

It is also self learning and with 5bn forecasts every year, is paving the way for a planning process that’s almost automated, said Sinn.

The online customer expects a reasonable price and loves sales, said Sinn.

“We don’t,” he added, but said Otto is able to optimise pricing and change prices daily or more than once a day. 

In a dynamic pricing pilot, Otto optimised sales by 9%, turnover by more than 6%, profit by 5% and reduced left over stock by 12%, Sinn revealed.

Optimised pricing has now been rolled out across the entire product range.

Returns management is fast becoming a number one critical success factor, Sinn told delegates at RBTE.

Logistics are a costly part of the online business model. Sinn showed how Otto has used analytics to understand returns and put in measures to reduce the return rate.

It found, for example, that the longer the lead time, the higher the return rate. 

Sinn said Otto was now able to deliver 90% of orders within two days to customers and the reduction in the number of returns has more than compensated for the cost of delivery.