How Germany���s Otto Uses Artificial Intelligence

Machine learning is trying to one-up just-in-time inventory with what can only be called before-it’s-time inventory. The Economist reports that German online merchant Otto is using algorithms to predict what you’ll order a week before you order it, reducing surplus stock and speeding deliveries:

A deep-learning algorithm, which was originally designed
for particle-physics experiments at the CERN laboratory
in Geneva, does the heavy lifting. It analyses around
3bn past transactions and 200 variables (such as past
sales, searches on Otto���s site and weather information)
to predict what customers will buy a week before they
order.

The AI system has proved so reliable���it predicts with
90% accuracy what will be sold within 30 days���that
Otto allows it automatically to purchase around 200,000
items a month from third-party brands with no human
intervention. It would be impossible for a person to
scrutinise the variety of products, colours and sizes
that the machine orders. Online retailing is a natural
place for machine-learning technology, notes Nathan
Benaich, an investor in AI.

Overall, the surplus stock that Otto must hold has
declined by a fifth. The new AI system has reduced
product returns by more than 2m items a year. Customers
get their items sooner, which improves retention over
time, and the technology also benefits the environment,
because fewer packages get dispatched to begin with,
or sent back.

The Economist | Automatic for the People: How Germany���s Otto Uses Artificial Intelligence