Data Science

Supply chain algorithms: cost-effective, agile and customer-centric logistics

It has never been more difficult than today to win, inspire and retain customers. Customers in both the B2C and B2B sectors are increasingly demanding an individual approach and a shopping experience tailored to their needs.


It is no longer just the product, but the entire end-to-end shopping experience that is decisive for customer satisfaction. These requirements do not stop at the delivery of the goods either: customers want ever faster delivery and they want it cheap. In addition, customers expect flexibility in delivery, punctuality, convenience and real-time shipment tracking.

To meet this ever-increasing expectation, redesigning the supply chain around customer needs is critical. In other words, companies and logistics service providers must create a supply chain that is more customer-centric and responsive. This is no easy task given the challenges facing the logistics industry: rising costs, a skills shortage, and increasingly stringent environmental regulations are just a few examples of the issues that need to be addressed. Against this background, a redesign of the transport network, warehouse operations and optimization of transport routes are required.

But how can logistics be optimized so that the customer is served perfectly and costs are kept in check at the same time? This is where new technologies and algorithms come to the rescue: Through the interaction of machine learning and optimization algorithms, demand can be anticipated and orders automatically planned into efficient tours and routes. In this way, efficiency gains can be realized through better utilization of vehicles and warehouse space, and delivery times can also be minimized and transport costs reduced.

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E-commerce continues to grow in importance. Numerous studies forecast a considerable boost for online trade. In other words, more and more customers are shopping online, both in the B2C and B2B markets. The result? More and more packages to be delivered. According to experts at Oliver Wyman, the number of parcels to be delivered in Germany will triple by 2028: from 3.5 billion parcels in 2018 to up to 9 billion. At the same time, the cost of a doorstep delivery is also likely to rise from €2.50 to around €4.50. Complicating matters here is the increasing volatility of customer demand and thus a fluctuating volume of parcels to be delivered every day. The consequence? More than half (58.5%) of all truck trips in Germany are empty runs.

Without logistics, i.e. without the delivery of goods to the customer, the online sales process would simply not be possible. Logistics is therefore increasingly assuming the role of a main value creator for the customer. At the same time, customer expectations are rising. Particularly among today's digitally savvy consumers (most notably Generation Y), the online purchase decision is significantly influenced by delivery, returns, and the experience of doing so. But what exactly do customers expect? The following exemplary figures provide an impression:


  • 55% of customers expect one-hour delivery service in metropolitan areas (MetaPack Benchmark Study).

    49% of shoppers expect standard delivery to be free (MetaPack Benchmark Study).

    77% of shoppers are aware of or concerned about the environmental impact of their online deliveries (MetaPack Benchmark Study).

    93% of German shoppers track the status of their online order (MetaPack Benchmark Study).

The need to deliver more and more parcels faster and at lower cost is increasing the pressure on delivery service providers to find solutions for last-mile delivery, i.e. the last leg of the journey to the customer's door. According to a recent study by Capgemini, this last delivery step is the biggest cost driver in the supply chain.

For the logistics and supply chain of the future, this means creating a supply chain that meets the end-to-end customer experience. In short, the supply chain of the future must be intelligent, agile and customer-centric.


  • CUSTOMER-CENTRATED means the customer and their expectations should always be the focus. Companies must therefore anticipate the needs and requirements of their customers and adapt the supply chain accordingly.
  • AGIL means adaptability to changing market conditions as well as speed in service fulfillment. In other words, capacity flexibility, short lead times from order to delivery and fast reactions to a demand that changes daily are decisive here.

However, meeting these rising expectations and remaining profitable at the same time is a significant challenge in view of the enormous cost pressure (caused, for example, by high fuel/energy prices, high tolls and rising personnel costs). While the logistics industry is currently jumping from revenue high to revenue high, new directions must now be taken to remain competitive in the long term in the face of changing market conditions. This means that companies and logistics service providers must now improve their operations through the intelligent use of new technologies in order to increase process efficiency and reduce logistics costs. But how can new technologies help to deliver the mass of parcels flexibly, quickly and cost-effectively?



Meeting this challenge requires the interaction of various intelligent assistance systems that support logistics in two ways.

The use of machine learning methods to accurately predict pickup and delivery locations, timing and quantity of orders, so that capacity requirements (vehicle, personnel, warehouse, etc.) can be optimally planned.

These predicted orders then serve as input for the route optimization algorithms. Once the information on the orders is available, the next question is how to deliver them at the lowest possible cost. In other words, which orders should be bundled into a tour and in which order should the customers of a tour be supplied, from where and with which vehicle, so that the most cost-optimal transport is achieved?


Optimization algorithms are used to plan thousands of orders into optimized tours and routes fully automatically within a very short time, so that delivery times are minimized and transport costs are reduced. The methods and algorithms used are capable of finding quick solutions so that an already optimal route plan can be adjusted in real time. Dynamic route planning makes it possible to react in real time to events in the entire network in order to plan these directly into new, optimized routes and tours.

In a digitally networked supply chain, customer forecasts and special events can then be shared among the individual participants within seconds. This means that decisions can be made dynamically and staff are supported in their day-to-day work.



Supply chain management is poised to transform from a support function to a key enabler of better customer service. Innovative solution approaches, driven by new technologies from the field of Artificial Intelligence, are a key supporter and driver to help your company build a customer-centric supply chain that is resilient and flexible enough to meet these future demands. Companies therefore need to ask themselves the question now:

  • Are our supply chain processes set up in such a way that we can ensure agile and customer-oriented logistics today?

  • What investments need to be made now across the network to meet cost and performance pressures in the future?

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