Automating Purchase Invoice Matching
How Process Automation Transformed Invoice Management for a High-Volume Operation
Discuss a Similar ProjectExecutive Summary
A logistics client, dealing with hundreds of purchase invoices weekly, was constrained by a manual, time-consuming invoice-matching process that required multiple operators and presented frequent errors. By implementing a custom automation solution using Microsoft Power Automate, AI Builder, and SQL Server, the client achieved substantial efficiency gains, reduced staffing requirements, and improved data accuracy. This case study highlights the measurable impact of automation on cost savings and operational excellence, demonstrating the transformative power of process optimisation.
Challenges: High-Volume, Manual Invoice Processing
Client Persona: High-volume logistics operations managing complex purchase invoices with specific requirements for each supplier and depot.
The client handled 400-500 purchase invoices each week, each requiring manual entry and verification against detailed goods receipt notes (GRNs). This process presented several critical challenges:
Metric | Before Automation | After Automation |
---|---|---|
Operators Required | 4 | 1 |
Time per 100 Invoices | ~8 Hours | 10 minutes |
Automated Processing Rate | 0% | 90-95% |
Error Rate | Frequent Duplications, incorrect values | Minimised, flagged clearly |
Resource-Intensive:
Four full-time operators were required to manage invoice processing.
Error-Prone:
Duplicate entries and manual errors were frequent, impacting data accuracy.
Time-Consuming:
Identifying and correcting errors took significant time, delaying the process and increasing operational costs.
Solution: Tailored Automation with Microsoft Power Platform and SQL Server
The solution was designed to streamline the entire purchase invoice process, incorporating tailored automation tools that adapted to the client's unique business rules. The approach consisted of three core stages:
Invoice Ingestion (Power Automate)
Using Microsoft Power Automate, incoming invoices were automatically routed to an AI processing hub (AI Builder by Microsoft) where they were standardized and converted into structured text files.
Standardisation and Matching (AI Builder and SQL Server)
Processed invoices were transferred to the client's server, where SQL Server procedures matched them against corresponding GRNs based on unique criteria like invoice number, supplier reference, and values. The solution adapted to specific matching rules for each supplier and handled invoices with multi-GRN and depot-specific ledger postings.
Auto-authorization and Error Flagging
Custom rules were set to automatically authorise invoices within accepted variances and flag discrepancies. This allowed the system to auto-approve or hold invoices based on predetermined conditions, significantly reducing manual intervention.
Technologies Used:
- Microsoft Power Automate
- Microsoft AI Builder
- SQL Server (Procedures and Agent Jobs)
Results: Enhanced Efficiency, Cost Savings, and Accuracy
Key Outcomes
Reduced Staffing Requirements
Staffing was reduced from four full-time operators to just one, redirecting resources to other high-value tasks.
Accelerated Processing Time
Processing time for 100 invoices was cut to approximately 10 minutes.
Automated Invoice Matching
90-95% of invoices were processed automatically, with the remaining invoices flagged for manual review with clear, actionable reasons.
Operational Cost Savings
With reduced labor needs and faster processing times, the client experienced a substantial decrease in operational costs.
Processing Breakdown
Manual Review Reasons:
- GRN not recorded in system
- Quantity mismatch beyond threshold
- Price variance exceeding allowed limit
- New supplier or product requiring setup
Client Impact Statement:
"The automation has become an essential part of our operations, yielding substantial time and cost savings. It's hard to imagine our workflows without it."
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