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Inside the Data-Driven Strategy at DB SCHENKER with Joachim Weise
Interview with Joachim Weise, SVP Global Technology and Data
Joachim Weise, SVP Global Technology and Data, joined DB SCHENKER in 2016 with a mission to build and lead the Data, AI, and Operations Research capabilities. Since July 2023, he has been heading the Global Technology & Data department.
His focus? Unlocking the power of technology and data for the success of DB SCHENKER. This means sparking innovative ideas in the data and technology services, and ensuring these services integrate seamlessly for a smooth, efficient experience from start to finish.
Logistics Matters: How can specific AI solutions at DB SCHENKER impact the efficiency, accuracy, and overall performance of our operations?
Interview Joachim Weise
Logistics Matters: Can you elaborate on the integration of AI within the technology and data infrastructure of DB SCHENKER, especially looking at the connection between data and AI solutions?
Joachim Weise: At DB SCHENKER, we are constantly pushing the boundaries of logistics. Some years ago, we started working on an Enterprise Information Management Platform, to build up a framework to combine the power of AI and business intelligence. This end-to-end hybrid solution enables us to manage structured and unstructured data efficiently across all businesses and leverage valuable insights.
Imagine a platform that acts as a central system, efficiently managing data across all our business units. It serves as a data lake – a repository to store data, a data warehouse – a central database to consolidate data from different systems, and at the same time as a workbench for MLOps – Machine Learning Operations – when we transfer our Machine Learning models into production and their subsequent maintenance and monitoring. This end-to-end solution empowers us to extend valuable insights from data, allowing us to make smarter decisions across the organization. The platform is managed by one team, which enables us to develop artificial intelligence and business intelligence together and avoid unnecessary gaps. As we harmonize our reporting solution, we are working closely on the topic of data governance. We are creating a data catalog and ensuring that we develop our employees with internal and external training courses on general topics of data and data literacy, as well as specific technical training for users in the individual systems.
At DB SCHENKER, data governance is not just a concept; it is a core principle and a collaborative effort between our business and IT teams.
Logistics Matters: How does the organization ensure the quality, security, and ethical use of data in AI-driven projects?
Joachim Weise: AI is a very broad field: we have use cases that would previously have fallen under statistics, but at the same time we have advanced AI use cases, particularly in computer vision and LLM, with large and complex data. In general, we follow all IT security guidelines and principles in all use cases and are in close coordination with Global Data Protection and their local representations to ensure that we comply with all legal requirements.
By embracing the full spectrum of AI capabilities, from the power of data analysis to the automation potential of LLMs, we are shaping the future of intelligent logistics. In that, we are committed to doing so responsibly, prioritizing security and compliance every step of the way.
Logistics Matters: Given the rapid advancements in Data and AI technologies, how does DB SCHENKER ensure that its technology and data frameworks remain agile and adaptable to emerging trends and innovations?
Joachim Weise: Staying ahead of the curve is crucial in today’s dynamic tech environment, and the various IT & Digital teams of DB SCHENKER are committed to achieving just that.
Within IT&D, we regularly review and evaluate the technology landscape, comparing the latest technologies on the market with the technology in use. Since we moved to the cloud a few years ago, we have now implemented the latest technology stack for our platforms. Within the cloud, we combine and complement best-of-breed for the respective functionalities’ applications, from data warehousing to MLOps, ETL - Extract, Transform, and Load data for further processing. We constantly monitor the market and see what we can develop in-house and what we can be covered by third-party suppliers. We make sure that we do not make a blind technology push but develop in close collaboration with the business and their requirements to ensure value and scalability for DB SCHENKER.
Additionally, we have a strong collaboration with the Fraunhofer IML since 2015. Together with our Schenker Enterprise LAB, we pilot innovative ideas and technologies for their usability and scalability for DB SCHENKER.
