The Challenge
One of the world's largest beverage companies was running a critical back-office operation almost entirely by hand. Staff spent their days logging into legacy financial systems and booking platforms—systems with no APIs, no integrations, and no way to extract data programmatically.
The manual work included:
- Booking management — Logging into legacy systems to manage capacity and reservations
- Financial data entry — Copying records from legacy platforms into spreadsheets
- Reporting — Manually pulling data from multiple sources and building Excel reports
- Data collection — Extracting confirmations, transaction details, and financial records one screen at a time
The team was spending 120 hours per week on repetitive data entry and extraction. They regularly needed temporary staff to handle volume spikes. The work was tedious, error-prone, and kept skilled employees from higher-value projects.
Our Approach
We started with a comprehensive assessment of every manual workflow. For each process, we mapped the steps, identified the systems involved, and determined the best automation approach.
Some platforms could be automated with RPA. Others had partial Microsoft 365 integration we could leverage. A few required custom scripts. The solution would need to orchestrate across all of them.
The Solution
We built an integrated automation platform combining multiple technologies:
UiPath RPA Bots
- Hosted UiPath Orchestrator for centralized bot management
- Built attended and unattended bots for different workflow types
- Automated login sequences for legacy financial systems
- Created screen-scraping routines for platforms with no API access
- Handled airline portal navigation and capacity booking workflows
Power Automate Integration
- Leveraged Microsoft 365 Power Automate for workflows within the Microsoft ecosystem
- Connected Excel, SharePoint, and email-based processes
- Filled integration gaps between RPA bots and cloud systems
Custom Scripting
- PowerShell commands for Windows-based automation tasks
- Python functions for data transformation and validation
- Orchestration layer connecting all automation components
Data Infrastructure
- Migrated extracted data from scattered spreadsheets to SQL Server instances
- Integrated with existing data lake for centralized, secure storage
- Structured data properly for reporting and analytics
The Results
The impact was immediate and substantial.
Time Savings:
- 120 hours per week of manual work fully automated
- 6-8 full-time employees redirected to high-impact projects
- Temporary staffing for volume spikes eliminated entirely
Operational Improvements:
- Bots run 24/7—no more waiting for business hours to process transactions
- Data extraction happens in minutes instead of hours
- Consistent, error-free execution every time
Data Quality:
- Structured data in SQL replaces scattered Excel files
- Single source of truth for financial and operational records
- Audit trail for every automated transaction
Strategic Value:
- Skilled employees now work on projects that move the business forward
- Scalable capacity—bots handle volume spikes without additional headcount
- Foundation for further automation across other departments
The employees who had been doing this work for years weren't replaced—they were finally freed up to do work that matters. The repetitive tasks that consumed their weeks are now handled by bots that never take breaks and never make typos.