A Fortune Global 500, one of the largest chemical companies in the world. This $47 billion multinational chemical company employs around 19,000 people and is a global leader in innovation, consistently developing high-quality chemicals, polymers, fuels, and technologies.

CHALLENGE

‍

A leading chemical manufacturer was operating with limited visibility into one of its most critical cost drivers: vendor invoices.

Invoice data was stored as image files within SAP, while purchase order (PO) line items existed in inconsistent, free-form text formats. This created a fragmented data environment where meaningful analysis was nearly impossible.

As a result, procurement teams were left working reactively, without the insight needed to identify cost-saving opportunities or enforce pricing consistency.

• Limited visibility into invoice and PO data
• Missed opportunities for cost optimization
• Manual, time-intensive audit processes
• High risk of errors and inconsistencies

‍

SOLUTIONS

‍

Aligned Automation designed and deployed an intelligent invoice processing and analytics solution powered by Machine Learning (ML) and Intelligent Character Recognition (ICR).

The solution transformed unstructured invoice images and free-form PO data into a unified, structured data model that could be analyzed in real time.

By standardizing and enriching procurement data, the system enabled teams to move beyond manual audits and into proactive, insight-driven decision-making.

Key capabilities included:

• Automated extraction of invoice data from diverse image formats
• Normalization and structuring of free-form PO line items
• Creation of an integrated, analytics-ready procurement data model
• Identification of pricing discrepancies and optimization opportunities
• Actionable insights to improve FFT-based procurement processes

‍

What Changed

‍

With structured, reliable data now at their fingertips, procurement teams gained the ability to continuously monitor vendor pricing, identify anomalies, and take action before costs escalated.

What was once a fragmented, error-prone process became a scalable, intelligence-driven function aligned to business outcomes.