ML supported fuel demmand planning in MOL Hungary wholesale
In MOL Group’s integrated planning scheme, refined products sales plans determine crude oil purchasing. Therefore, wholesale fuel demand forecasting plays a critical role in integrated planning and in supply chain efficiency. In MOL Group’s integrated planning scheme, refined products sales plans determine crude oil purchasing. Therefore, wholesale fuel demand forecasting plays a critical role in integrated planning and in supply chain efficiency.In this case study, we present how the wholesale fuel planning process was enhanced by leveraging modern Machine Learning solutions. We show, how ideas become IT solutions through Proof of Concepts and Projects in MOL’s 3 speed IT approach.
Data Innovation Team Lead, MOL Group
I spent 20 years with designing and developing Data Warehouses for Banking, Governmental and Manufacturing Areas.
Now I’m leading the Data Innovation in MOL Group Oil and Gas company. MOL Group is the second largest company in the CEE region, with US and DS operations, 4 Refineries, 2 Petrochemical Units and 2000 Service Stations in the region. In the Data Innovation we test several new solutions like Hadoop, Machine Learning, Augmented and Virtual Reality, Blockchain for our business demands. In case of successful PoC we implement the solutions in the Group.
Enterprise Analytics & Data Innovation Manager, MOL Group
Daniel Kelemen graduated as an economist and has 10+ years of experience in data driven decision support & data monetization in Telecommunication, Retail and Oil & Gas industries. He started his career as a quantitative market researcher. Thereafter he focused on advanced analytics applied to the field of Customer Value Management. In his current position he is responsible for developing enterprise-grade Big-Data & Artificial Intelligence solutions.