Executive Summary

A Chicago-area precision manufacturing company with 85 employees was processing 400+ supplier invoices monthly using manual data entry. This resulted in:

40+ hours weekly spent on invoice processing
12% error rate requiring costly corrections
7-10 day payment cycles straining vendor relationships
$58,000 annual labor costs for invoice processing

In 90 days, Dooder Digital implemented an AI-powered invoice automation solution that:

✅ Reduced processing time from 40 hours/week to 6 hours/week (85% reduction)
✅ Improved accuracy from 88% to 99.8%
✅ Cut payment cycles from 7-10 days to 2-3 days
✅ Saved $47,000 annually in labor costs
✅ Achieved 320% ROI in first year

The Challenge

Business Context

This precision manufacturing company specializes in machined components for aerospace and medical device manufacturers. As the business grew from $12M to $22M in revenue over three years, invoice volume increased from 180 to 400+ monthly invoices.

Pain Points

Manual Data Entry Bottleneck

AP team manually entered data from PDF invoices into QuickBooks
40+ hours weekly spent on data entry
Process couldn't scale with business growth

High Error Rate

12% of invoices contained data entry errors
Errors caused payment delays, duplicate payments, and vendor disputes
8-10 hours weekly spent on error correction

Cash Flow Impact

7-10 day invoice processing cycle
Missed early payment discounts (2% net 10)
Strained relationships with key suppliers

Staff Burnout

AP team overwhelmed during month-end
High turnover in AP clerk position
Limited time for strategic financial analysis

Technical Environment

Accounting: QuickBooks Desktop
Invoice receipt: Email (PDF attachments)
ERP: Epicor Prophet 21
Volume: 400-450 invoices/month
Supplier diversity: 200+ active vendors

Our Solution

Discovery & Assessment (Week 1-2)

Process Mapping

Shadowed AP team for 3 days
Documented current invoice workflow
Identified 12 distinct process steps
Analyzed error patterns and root causes

Requirements Gathering

Interviewed AP manager, CFO, and procurement
Reviewed sample invoices from top 50 suppliers
Assessed QuickBooks integration requirements
Defined success metrics and acceptance criteria

Solution Design (Week 2-3)

Technology Selection

AI Platform: UiPath Document Understanding with custom ML model
OCR Engine: UiPath Intelligence OCR + Google Cloud Vision API
Integration: QuickBooks Desktop API via Web Connector
Validation: Custom business rules engine
Workflow: UiPath Studio for exception handling

Architecture

Email → UiPath Orchestrator → Document Understanding →
Validation Rules → QuickBooks API → Exception Queue →
Human Review (if needed) → Approval → Posting

Implementation (Week 4-10)

Phase 1: ML Model Training (Week 4-6)

Collected 800 historical invoices across 50 suppliers
Trained custom ML model for data extraction
Achieved 94% field accuracy on test set
Fine-tuned for client-specific invoice formats

Phase 2: Business Rules Development (Week 6-8)

Built validation rules:
- PO matching (3-way match)
- Duplicate detection
- GL coding logic
- Approval routing based on amount
Created exception handling workflows
Developed reporting dashboards

Phase 3: Integration & Testing (Week 8-10)

Connected to QuickBooks Desktop via API
Built secure email monitoring workflow
Tested with 100 sample invoices
Conducted UAT with AP team
Refined exception handling based on feedback

Phase 4: Training & Go-Live (Week 11-12)

Trained AP team on exception handling
Implemented parallel processing (bot + manual)
Monitored accuracy for 2 weeks
Transitioned to full automation
Documented standard operating procedures

Change Management

Team Enablement

6 hours of hands-on training for AP team
Created video tutorials for common scenarios
Established weekly check-ins for first month
Repositioned AP clerk role to focus on vendor relationships

Stakeholder Communication

Monthly steering committee updates
Vendor notification of faster payment processing
Finance team training on new reporting dashboards

Results & Impact

Quantitative Outcomes

Efficiency Gains

Metric	Before	After	Improvement
Weekly processing hours	40 hrs	6 hrs	85% reduction
Avg. time per invoice	6 minutes	0.9 minutes	85% reduction
Human touch rate	100%	15%	85% automated
Invoices processed/day	20-25	120+	4.8x increase

Quality Improvements

Metric	Before	After	Improvement
Data accuracy	88%	99.8%	11.8 point increase
Duplicate payments	2-3/month	0	100% elimination
Missing PO tags	18%	0.5%	97% reduction
Exception rate	N/A	15%	Trackable & managed

Financial Impact

Category	Annual Savings
Labor cost reduction	$38,000
Duplicate payment prevention	$5,400
Early payment discounts captured	$3,600
Total Annual Savings	$47,000

Investment & ROI

Implementation cost: $14,700
Annual licensing: $4,200
First-year ROI: 320%
Payback period: 4.5 months

Qualitative Benefits

Operational

AP team refocused on strategic vendor management
Ability to scale invoice processing without headcount
Real-time visibility into AP aging and cash flow
Reduced month-end crunch and overtime

Strategic

Faster payment cycles improved vendor relationships
CFO gained confidence in AP data accuracy
Created foundation for automated spend analytics
Positioned company for future AI initiatives

Employee Satisfaction

AP clerk role elevated to AP Specialist
Eliminated repetitive, error-prone work
Team engagement scores increased
Zero turnover since implementation

Client Testimonial

"Dooder Digital transformed our accounts payable process in just 90 days. We went from drowning in invoices to processing everything automatically with incredible accuracy. Our AP team loves the change—they're no longer doing mind-numbing data entry and can focus on building vendor relationships and strategic analysis. The $47,000 in annual savings is great, but the time savings and accuracy improvements are game-changing for our growth plans."

— CFO, Chicago Manufacturing Company

Key Success Factors

What Made This Project Successful

Executive Sponsorship: CFO prioritized project and allocated AP team time
Process-First Approach: We optimized the workflow before automating
Realistic Expectations: Planned for 15% exception rate requiring human review
Change Management: Positioned automation as empowering, not replacing staff
Iterative Refinement: Monitored accuracy weekly and continuously improved ML model

Lessons Learned

Challenge: Initial ML model struggled with handwritten notes on invoices Solution: Added OCR confidence scoring; routes low-confidence items to human review

Challenge: AP team anxious about job security Solution: Reframed as "augmentation," created new AP Specialist role with better responsibilities

Challenge: Integration with legacy QuickBooks Desktop required custom API work Solution: Built middleware layer; now reusable for other clients

Next Steps for the Client

Following the success of invoice automation, the client is now exploring:

Purchase Order Automation: Automate PO creation from approved requisitions
Spend Analytics: AI-powered insights into spending patterns and cost-saving opportunities
Vendor Management: Automated vendor onboarding and performance tracking
Predictive Cash Flow: ML models for cash flow forecasting

How Dooder Digital Can Help Your Business

Is your organization struggling with manual invoice processing or other repetitive financial workflows?

We can help you achieve similar results:

✅ Free 30-minute assessment of your AP process
✅ ROI projection specific to your invoice volume
✅ 90-day implementation timeline
✅ Training and change management included

📞 Contact us today:

Phone: +1 (224) 585-9126
Email: info@dooderdigital.com
Schedule: Book a free consultation

About This Case Study

Industry: Manufacturing (Precision Machining) Company Size: 75-100 employees, $15M-$25M revenue Location: Greater Chicago Area Project Duration: 90 days (discovery to go-live) Technologies Used: UiPath, Google Cloud Vision API, QuickBooks Desktop API Services Provided: Process Automation, AI Implementation, Change Management

Case Study: How a Chicago Manufacturer Reduced Invoice Processing Time by 85%