The supply chain for a company as large as BMW is complex and consists of many moving parts, from the ideas offered during product brainstorming at brand HQ to the customer’ 3-Series arriving at a dealership for its first servicing. Now BMW is looking to add transparency and cohesion to their many departments through a partnership with Amazon Web Services (AWS) that will use AI and cloud-based services to predict consumer trends and demand for BMW vehicles and components.
The German automotive group will be integrating their engineering, manufacturing, sales and servicing data collected by their global operations to AWS. The data gathered from these numerous departments will be shared through the ‘Cloud Data Hub,’ which will allow the company to easily share vital information and have an overall view of operations.
With this collaboration, BMW will be transferring data from its business units and operations in over a hundred countries to AWS, a move that will take significant manpower. BMW will invest in training up to 5,000 Group-affiliated software engineers to make better use of the data—2,000 of these software engineers will be certified in machine learning and data analysis.
In recent times, BMW has also made good use of modern technologies like blockchain to ensure the traceability of components from manufacturers through their PartChain Platform. This service allows the company to ensure that materials are being sourced from parties in an ethically and socially responsible manner.
BMW will also work with Amazon SageMaker to examine data from vehicle subsystems to predict performance and maintenance using machine learning. This will examine the performance and maintenance of parts and inform suppliers of issues in the manufacturing process and how they can improve the quality of their parts.
The auto group suggests that through these technologies, it will easier to predict demand for new vehicle models and equipment on a global scale. This information can be used strategically to decide what kind of production schedule needs to take place, along with the ordering of materials through ethical and sustainable sources. With cloud-based technologies, it will allow for more cohesive and transparent decisions among departments.
