21. February 2023

Digital logistics networks: More transparency and resilience in the supply chain

Focus on customer requirements

The world is currently characterized by many uncertainties – companies are still feeling the immense impact of the pandemic on global flows of goods. Moreover, they are confronted with the war in Ukraine, have to cope with the shortage of skilled workers and have to operate more sustainably in the course of climate protection. Logistics companies in particular are faced with supply bottlenecks and material shortages that put entire logistics networks under enormous pressure. The logistics industry is therefore facing enormous challenges. In order to remain competitive despite these uncertainties, there is no way around the digitization of processes. After all, modern digitization strategies pave the way to transparent, more resilient, and more sustainable logistics processes that can also be consistently aligned with customer requirements.

Big Data, AI and Analytics open up a clear view of operations

What logistics specialist is not familiar with this: tight margins, price wars and high competitive pressure – these are the conditions that determine the global logistics market. It has therefore become a very decisive factor that logistics companies make optimum use of their available resources and at the same time provide a high level of service along the entire supply chain. This is the only way to maintain long-term relationships with customers and meet their increased requirements. Accordingly, the future lies in digitized material and value flows. Only those who digitize end-to-end can save time, resources and costs, which in turn leads to efficiency gains.

Managing the supply chain optimally: resilient data is the new gold

“Data is the new gold” – this is often said in this context. New business areas or services such as analytics are based on such data. This enables logisticians to manage the supply chain more reliably and also more efficiently. However, an important condition is that the basic data is correct, validated and complete. If this is the case, the use of predictive analytics, for example, makes it possible to make precise predictions about requirements, delivery dates or, for example, sales volumes by collecting a large amount of real-time data from a wide variety of sources – such as an ERP system, the supply chain, retail terminals or even telematics systems. On the one hand, the goal is to replace manual and time-consuming planning and to specifically expand the reporting of a BI landscape through Data Science. This is because logistics experts are now in a position to create more complex analyses and reliable forecast models in addition to the classic standard evaluations. Machine learning models and the use of AI technologies enable logisticians to derive patterns that provide information about specific environmental and stress situations without much effort. In this way, the performance of the entire logistics network can be checked in real time and logisticians can react quickly to acute situations and, in the best case, ensure that they do not arise in the first place on the basis of reliable forecasts.

Real-time data warehouses and single point of truth

If all logistics processes, such as those described as examples, are bundled and interlinked in an overall architecture, logistics companies benefit from a so-called real-time data warehouse. In addition to information from enterprise systems, this brings together and displays data from IoT devices, such as scanners, as well as key business performance indicators (KPIs) in real time. From a large number of successfully completed projects, our logistics experts have come to the conclusion that hybrid analytical infrastructures are architectures that view the classic data warehouse and data science as complementary rather than separate. The decisive advantage of such an architecture: logistics companies use a so-called single point of truth for the same key figures and dimensions. Such an overall architecture is also characterized by high scalability, a modular structure and flexible adaptability, especially since supplementary cloud services can be easily integrated if required.

Our IT consultants always have an ear to the logistics market

Based on proven IT competencies and deep industry knowledge, we support and advise our customers in the planning and implementation of real-time data warehouses and link them to hybrid analytical infrastructures. In this way, logisticians gain a detailed digital image of their supply chain. In this way, we are creating the basis for logistics companies to fully exploit the opportunities opened up by data science and AI, and thus provide them with intelligent tools to counter the uncertainties in the global logistics markets. With the ISO27001-certified IT services of our sister company DATIS IT-Services GmbH, we also meet all the requirements that logistics companies place on modern and reliable system architectures. To enable them to focus on their core business in times of limited personnel resources, we support both standard software systems and specially developed, individually tailored IT solutions. With this professional application management, logistics companies not only save costs, but also gain continuity, flexibility and security.

Have we sparked your interest? Find out more about our extensive logistics service portfolio or contact us directly:

Gerd Minners

Key Account Manager

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