Introduction
In the manufacturing sector, where every minute is precious, manual management of delivery notes (DDT) can become an obstacle. In many companies, data entry requires time, resources, and constant attention, with the risk of errors that accumulate every day.
This is the case of a plant engineering and industrial automation company, about 20 million in revenue, which every year found itself managing 80,000 delivery note lines. Each document required an average of five minutes of manual work: a repetitive and slow activity.
The results we present come from this specific context: high volumes, clear processes, and targeted integrations. In different scenarios, for numbers, data quality, or work organization, the impact can change, but the goal remains the same: reduce times and errors, increasing control and traceability.
Note: every reality is different. The results described in this case study depend on volumes, data quality, process rules, and integrations. The reported numbers are specific to the analyzed case and don't constitute a guarantee of identical results in your context.
The AI breakthrough
The turning point came with the introduction of an AI-powered solution for automatic delivery note reading and extraction. The system, based on machine learning models, is capable of:
- Reading documents in different formats (PDF, images, scans)
- Recognizing key data (customer, items, quantities, dates)
- Validating extracted information against business rules
- Automatically inserting data into the ERP system
Implementation didn't require replacing the existing ERP or complex infrastructure changes. The AI solution integrated with existing systems through APIs, working as a "smart layer" between documents and management software.
The implementation process
The project was divided into three phases:
- Analysis and training (4 weeks): The AI model was trained on a sample of historical delivery notes to learn document structure and data extraction patterns.
- Pilot (6 weeks): The system was tested on a subset of suppliers, with parallel manual verification to validate accuracy.
- Gradual rollout (3 months): Progressive extension to all suppliers, with continuous monitoring and optimization.
Concrete efficiency: the benefits
After full implementation, the company measured these results:
Time reduction
- Before: 5 minutes average per delivery note
- After: 1 minute average (only for exception validation)
- Reduction: 80%
- Annual savings: over 1,100 hours
Error reduction
- Before: 12% error rate in manual data entry
- After: less than 2% error rate
- Improvement: 83%
Operational capacity
- Same team can handle 3x volume without additional hiring
- Freed up resources reallocated to higher-value activities (supplier management, exception resolution)
- Reduced processing backlog from 3-4 days to same-day
Financial impact
- ROI achieved in: 8 months
- Annual cost savings: approximately €35,000 in direct labor
- Indirect savings: fewer errors, faster payments, better supplier relationships
Why AI is strategic
This case study demonstrates how AI isn't just automation technology, but a strategic enabler for businesses that want to:
1. Scale without proportionally increasing costs
The company can now handle volume growth (new customers, new suppliers, seasonal peaks) without needing to immediately hire additional staff.
2. Improve data quality
Fewer errors mean better traceability, fewer disputes with suppliers, and more accurate inventory.
3. Free up human resources for strategic activities
The team shifted from "data entry" to "process control," with time to focus on exception management, supplier relationship improvement, and process optimization.
4. Create foundation for further automation
Once the delivery note flow is automated, the company can extend automation to other documents (invoices, orders, contracts) using the same infrastructure.
Key lessons
- AI doesn't replace people, but frees them from repetitive activities
- ROI is measurable and achievable in the short term (6-12 months)
- Implementation doesn't require disrupting existing infrastructure
- Benefits extend beyond simple time savings: better quality, scalability, strategic flexibility
Want to discover how AI can transform your document processes? Contact us for a personalized assessment.