prelytico
Prescriptive Analytics in Procurement, Logistics and Supply Chain Management

Our Services

Enhancing Performance in Procurement, Logistics and Supply Chains through Data-Driven Decisions
Go to MODEL

MODEL

We translate your specific business setting into an analytical model for optimized decisions in procurement and supply chain management (SCM).

Go to BIG DATA

BIG DATA

We identify and analyze large amounts of relevant internal and external data to optimize your processes in the procurement and SCM context.

Go to ALGORITHM

ALGORITHM

We develop machine learning algorithms that to exploit Big Data for optimal decisions in procurement and SCM.

Go to ANALYSIS

ANALYSIS

We analyze and benchmark the saving potential of various data-driven solution approaches for your specific challenges in procurement and SCM.

SOLUTIONS

We design customized solutions for advanced analytics and data-driven decision-support in procurement and SCM.

CONSULTING

We offer individual training and support to leverage data-driven insights for decision makers in procurement and SCM.

About Us

prelytico

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

Press

Von Predictive zu Prescriptive Analytics: Big Data in der Rohstoffbeschaffung

Link: Beschaffung Aktuell 04/2017

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