Analytics and Optimization Platform for a Petrochemical Company
Case Studies
Challenges & Solutions
Technical Environment
Results
Executive Summary
Client
A confidential petrochemical client
Industry
Energy & Utilities
Business Problem
Production planning, pricing, and margin decisions relied heavily on manual analysis and business expertise. The business needed a unified platform for forecasting, optimization, and operational planning across volatile markets and complex production constraints.
Outcome
Expected outcomes include:
- Modernized production planning through AI-driven forecasting and optimization.
- Reduced manual effort in production scheduling and business planning.
- Enabled faster, data-driven decisions through interactive analytics.
- Implemented three enterprise optimization models for price, production, and margin planning.
Challenges
- Integrating data from multiple SAP modules into a centralized analytics environment.
- Forecasting petrochemical prices using volatile market indicators.
- Optimizing production schedules across capacity, inventory, transition time, logistics, and operating constraints.
- Balancing demand, inventory, and profitability across multiple sales zones.
Solutions
- Designed and implemented an end-to-end Advanced Analytics and Optimization platform.
- Integrated enterprise data from SAP modules through automated ETL processes.
- Built a Production Optimization Model across capacity, inventory, transition, and logistics constraints.
- Developed a Price Forecasting Model using historical PLATTS and ICIS market data.
- Developed a Margin Optimization Model for product mix and regional allocation.
- Implemented SAS Visual Analytics dashboards and mobile access for KPIs, forecasts, and recommendations.
Technical Environment
- SAS 9.4 Framework (SAS Data Management
- Enterprise Miner
- SAS OR
- Standard Data Surveyor for SAP
- SAS Visual Analytics)
Results
Expected results include:
- Three enterprise optimization models implemented.
- Production planning automated across multiple constraints.
- Petrochemical prices forecast across product grades and locations.
- Margin and product allocation planning enabled.