We translate your specific business setting into an analytical model for optimized decisions in procurement and supply chain management (SCM).
We identify and analyze large amounts of relevant internal and external data to optimize your processes in the procurement and SCM context.
We develop machine learning algorithms that to exploit Big Data for optimal decisions in procurement and SCM.
We analyze and benchmark the saving potential of various data-driven solution approaches for your specific challenges in procurement and SCM.
We design customized solutions for advanced analytics and data-driven decision-support in procurement and SCM.
We offer individual training and support to leverage data-driven insights for decision makers in procurement and SCM.
Originally founded as a spin-off from Technical University of Munich (TUM), prelytico offers data-driven decision-support solutions for procurement, logistics and supply chain management where processes and performance are significantly affected by external risk factors such as demand risk, supply risk, commodity price risk, exchange rate risk or freight rate risk. At prelytico, we combine methods from Operations Research (OR) with Artificial Intelligence (AI) and Machine Learning (ML) techniques for optimal data-driven decision-support by exploiting large amounts of internal and external data. More specifically, our customized solutions support decision makers in the fields of inventory control, commodity procurement, supplier selection, transportation optimization and supply network planning. Our prescriptive analytics tools are successfully in use in different industries and companies of different size.
Operations Research + Machine Learning
Minimizing purchase cost and risk
Maximizing customer service levels
Maximizing supply chain efficiency
Von Predictive zu Prescriptive Analytics: Big Data in der Rohstoffbeschaffung