ORDER TODAY, RECEIVE TOMORROW
Order today, receive tomorrow. This is the standard we accept today. For logistics service provider CB, this norm creates new challenges. They were searching for an answer to their daily question: “To what customers are we expected to deliver tomorrow and what quantity?” Mediaan Conclusion accepted the challenge of answering this transportation question, using artificial intelligence (AI). The result is a model that predicts orders per delivery address which increased planning accuracy by 80%, resulting in a 10% cost reduction. We guided and supported CB in numerous areas:
Design & branding
The aim was to develop a model that enables us to determine whether we can use AI to get a clear answer to the logistics question: “To what customers do we expect tomorrow to deliver how much volume?” Using machine learning algorithms, Mediaan has developed an AI model that allows CB to get answers based on our historical order data.
The biggest challenge is to get thousands of orders, the latest arriving at 11:00 pm, to be delivered the next day by the most suitable carrier. This requires not only smart and efficient scheduling, but also knowing how to deal with uncertainties and doubts.
MEDIAAN IN ACTION
This model has been developed as a ‘proof of concept’ in three weeks by four Medianers. A mix of young and talented data scientist and an experienced IT Architect. The developed model is designed so that CB can easily retrieve new features from the data and add it to the prediction. For example, orders per region and the relationship between bookshops and products.
WHAT OTHERS SAY…
“Although we make the basic planning for the next delivery day at four o’clock every night, we will know the exact information of location and how much needs to be delivered by 01:00 am the next night. However, we cannot wait for that, because we will no longer get the connections with external carriers, which means we will let down our customers. In order to make the right choices, the best possible prognosis is very important for our delivery process. At 07:00 pm and 11:00 pm we will rebalance, based on the latest information. The data of those different measuring moments ultimately determine what we transport as CB itself and which external carriers we use.”– Arjan De Jong, CB
“Because we are dealing with a huge amount of information and because the logistical process is complex and vulnerable due to time pressure, we have reached out to Mediaan Conclusion. The aim was to develop a model that enables us to determine whether we can use AI to get a clear answer to the logistics question: to what customers do we expect tomorrow to deliver how much volume? Using machine learning algorithms, Mediaan Conclusion has developed an AI model that allows us to get answers based on our historical order data.”– Arjan De Jong, CB
The Mediaan Conclusion forecast shows an improvement of more than 80% in predicting the number of addresses CB needs to deliver to, resulting in a 10% cost reduction. The AI model itself looks for patterns in the data that influence the forecast and, based on this, predicts the drop size per delivery address. This enables CB to further realize an optimization in cost, quality and efficiency. The power of the Microsoft cloud enables them to deliver a specific customized forecast in no more than half an hour for approximately 2,500 addresses.
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