The IBM Data Science and AI Elite team tackles missed deliveries in the Nordics
In today’s increasingly complex and fast-changing enterprise environment, there is a pressing need to accelerate digital transformation and AI adoption more than ever. Private and public postal services are no exception.
As the size of e-commerce businesses increases every year and more complex patterns emerge, the problem of missed deliveries become more and more important for logistic providers since there is a serious cost involved when parcel delivery is missed.
Could IBM machine learning capabilities offer a remedy? To prove out the predictive capabilities of Watson Studio, PostNord, a Swedish-Danish logistic and postal operator, teamed with the IBM Data Science and AI Elite team on a data and AI strategy to increase the rate of successful first attempt of home deliveries.
Unsuccessful parcel deliveries are not only frustrating to customers, they’re costly to couriers and retailers. Planning and execution becomes especially important in high volume periods such as the holidays.
When we first started to work with leadership team of PostNord, we quickly realized that the company had an extremely data rich environment due to internal and external scanning events and this allowed us to have meaningful discussions around business operations and enrich the analytics pipeline as we moved forward…
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