Driving Petrochemical AI Excellence Through Data Quality and Governance
As petrochemical leaders transition toward AI-driven operations, the biggest hurdle isn't the algorithm it’s the data. They recognized that for advanced analytics and automated governance to succeed, the foundation of Master and Meta Data had to be flawless. By shifting from fragmented records to a standardized digital core, they have set the stage for a truly intelligent supply chain.
Pain Points
~20K Material Master Records, 100% Data Cleansed
Data Fragmentation
Inconsistent data quality standards (ISO 8000 & 22745) preventing the use of advanced AI and ML models.
High Data Redundancy
Approximately 10K duplicate records hindering the "Single Source of Truth" necessary for digital maturity.
Inaccurate Spend Analytics
Fragmented data preventing the identification of procurement synergies and scale benefits.
Opaque Technical Data
Incomplete technical attributes leading to 100% data quality gaps for critical asset objects.
Legacy Data Silos
Inability to link eBoMs and mBoMs, stalling the move toward "Next Gen" autonomous maintenance functions.
The Solution
ISO 8000 Material Master Cleansing
Implementing rigorous Material Master cleansing to meet global standards for AI-ready data.
SAP MDG Business Rule Implementation
Establishing automated governance through custom business rules to ensure data remains "Clean at Source."
Master Data & Meta Data Improvisation
Leveraging improvised meta data structures to enable faster ROI through sophisticated data governance solutions.
Integrated eBoM & mBoM Linking
Creating a 100% cleansed and linked data architecture to fuel predictive maintenance and AI forecasting.
Transform your data from a cost center into a competitive advantage.
We help you clean, govern, and optimize your digital foundation to fuel the future of petrochemical intelligence.
