Fuel Price Optimization
Problem
- In order to respond to market changes, our client needed to dynamically determine the optimum price for three different fuel types in selected filling stations
Action
- Developed sophisticated algorithms to identify the optimum fuel pricing considering the market price and distance to the distribution centers
- Built a data lake to store the required data sets and model output
- Identified KPIs and created dashboards to enable continuous model and process improvements by analyzing different scenarios
Tool Stack
- AWS, Python, PowerBI
0.
25
%Revenue increase
Fast and effective market response
Automated and simple BI dashboard