Business Challenge
A leading Oil & Gas company, based in USA, faced significant inefficiencies in managing non-PO invoices, which accounted for a substantial portion of their accounts payable transactions. Their finance teams struggled with:
- Assigning GL Accounts and Cost Centers: Non-PO invoices required manual classification, leading to errors and inconsistencies, unlike standard invoices linked to purchase orders.
- Time-Taking and Manual AP Processes: Manually searching for relevant data, validating entries, and assigning the correct financial codes delayed invoice processing and increased workload.
- Limited Financial Reporting Accuracy: Consolidating multiple line items into reports made it difficult to track expenses and make informed financial decisions.
Owing to these inefficiencies, the finance team faced delays in invoice processing, compliance risks due to potential errors, and increased operational costs.
Solution
Integritty implemented SAP Datasphere and SAP AI Core within the company’s SAP Business Technology Platform (BTP) landscape, which focused on automating the invoice processing workflow while ensuring accuracy in financial data classification.
Document Information Extraction:
- Implemented AI-based document processing to extract structured data from unstructured invoice documents.
- Automated the retrieval of essential details such as invoice numbers, vendor information, amounts, and line items.
Supplier and Employee Data Enhancement:
- Integrated external data sources to validate supplier details and match invoices with the correct cost center or GL account.
- Reduced manual verification efforts by enabling intelligent data matching.
Invoice Object Recommendation:
- Used machine learning to predict the correct GL accounts and cost object assignments based on historical data.
- Provided accurate recommendation model to minimize misclassifications.
Automated Reporting:
- Implemented real-time data processing to ensure non-PO invoices were assigned accurately and processed without manual intervention.
- Enabled integration with SAP Analytics Cloud for real-time financial reporting and dashboards.
Business Impact
The implementation of SAP Datasphere and AI-driven automation led to:
- 65-70% Reduction in Manual Work: Automation drastically cut down manual processing time.
- Elimination of Data Inconsistencies: AI-powered enrichment and validation ensured accurate GL and cost center assignments.
- Improved Financial Reporting: Faster and more precise data consolidation enabled real-time insights into spending patterns and budget tracking.
- Enhanced Compliance and Audit Readiness: Reduced errors and provided a clear audit trail for invoice processing, minimizing regulatory risks.
- Optimized Payment Strategy: With automated categorization and approval, the finance team could focus on strategic financial management rather than manual data entry.
With SAP Datasphere and SAP AI Core, the Oil & Gas company successfully improved accuracy and efficiency, and freed up valuable time for finance teams to focus on higher-value financial planning and strategy.
