A Company in Munich Spent More Than 30 Hours per Month Merging CSV Datasets Manually: Automation Success Case

Imagine losing over 30 hours every month on repetitive, manual dataset merging tasks — a situation our client in Munich experienced firsthand. 🚀 In today’s data-driven business world, inefficient processes like manually consolidating multiple CSV files not only drain valuable time but also increase the likelihood of errors. In this article, we dive deep into how one Munich-based logistics SME overcame this challenge by leveraging automation workflows designed and hosted by RestFlow.

This comprehensive case study covers the client’s background, their pain points, the customized automation architecture we proposed, and a detailed, step-by-step breakdown of the workflow implemented using n8n. We also discuss the tangible benefits, including drastic time savings and error reduction, and how ongoing maintenance ensures sustained performance.

Whether you’re a startup CTO, automation engineer, or operations specialist, you’ll find practical insights and real examples to help you replicate this success in your own organization. Ready to optimize your data workflows? Keep reading to learn how.

The Problem: Manual CSV Dataset Merging in a Munich Logistics SME

Our client is a small-to-medium-sized enterprise (SME) specializing in logistics based in Munich, Germany. Their operations and data management teams regularly received multiple CSV exports daily from various sources, including their ERP, CRM, and third-party sales platforms.

The core challenge was the need to consolidate these CSV datasets manually. This task, performed by two operations specialists, consumed over 30 hours per month — approximately 8 hours per week dedicated solely to merging, cleaning, and validating data from disparate CSV files.

The pain points were clear:

• Time wastage: The manual merging required tedious copy-pasting and reconciliation, leading to slow turnaround times.
• High error rate: Mistakes in merging caused frequent discrepancies in reports used for inventory planning and shipment coordination.
• Lack of process transparency: Management struggled to track progress and identify bottlenecks due to spreadsheet version conflicts and manual interventions.

These issues impacted internal teams and had direct business repercussions, including delayed shipments and inaccuracies in inventory forecasts, threatening customer satisfaction and revenue growth.

Our Approach: Discovery and Tailored Automation Proposal

RestFlow began the project with an in-depth discovery phase, collaborating closely with the client’s operations and IT teams. We mapped out the existing CSV merging process, pinpointing each step: data retrieval, validation, cleansing, integration, and reporting.

We identified the key systems involved:

• ERP exports: Daily CSV files with inventory and shipment data.
• CRM exports: Customer orders in CSV format.
• Third-party sales platforms: Order logs and delivery statuses in CSV reports.

We determined that an automation platform capable of flexible data manipulation, integration with cloud storage, and sending notifications would best fit the client’s needs. After evaluating options, we selected n8n for workflow orchestration due to its open architecture, extensive connector library, and ease of customization, along with Google’s ecosystem (Google Drive and Google Sheets) for storage and data review.

This decision aligned with the client’s preference for cost-effective, scalable solutions with strong community support and self-hosting capabilities.

Below is the high-level architecture we proposed:

• Scheduled triggers that detect new CSV files in cloud storage
• Automated data ingestion and validation nodes
• Conditional logic to merge and clean datasets
• Outputs to consolidated Google Sheets dashboards
• Slack notifications on errors or completion

By adopting this integrated approach, we set the foundation for an end-to-end automated process that would save time and increase data quality.

The Solution: Automation Architecture & Workflow

Global Architecture Overview

The solution is built around a modular n8n workflow hosted on the RestFlow automation platform. Its key components and flows include:

• Triggers: A scheduler node runs the workflow every evening at 7 PM, aligned with the time all CSV exports are expected.
• Data Sources: CSV files uploaded into specific Google Drive folders representing ERP, CRM, and sales platform datasets.
• Data Processing: n8n nodes parse, validate, and enrich CSV contents.
• Decision Logic: Conditional nodes check data integrity and merge strategy.
• Outputs: Merged and cleaned data are saved to a master Google Sheet, and summary reports are emailed to the operations team.
• Alerts: Slack messages notify the team if any error or data inconsistency arises during processing.

REST API endpoints for receiving external data are reserved for future scaling. Currently, the system relies on scheduled triggers and cloud storage events for simplicity and robustness.

End-to-End Workflow Walkthrough

1. Scheduled Trigger: The workflow activates daily at a defined time, ensuring all source CSVs are likely to be present.
2. Google Drive File List Node: Lists all files in the designated folders for ERP, CRM, and sales platform data.
3. Read Binary File: For each CSV identified, data is read and converted into JSON format for processing.
4. Data Validation: Custom JavaScript code checks for missing headers, invalid formats, or duplicate entries.
5. Conditional Branching: If validation fails, files are moved to a ‘Failed’ folder; else, processing continues.
6. Transformations: Data from each CSV source is standardized — date formats unified, IDs normalized, and currencies converted if necessary.
7. Merge Operation: Datasets are joined on purchase order numbers and customer IDs using n8n’s Merge node to create a single consolidated dataset.
8. Output: The consolidated data is written to a master Google Sheet, replacing the previous day’s version.
9. Notification: A summary Slack message with record counts and processing time is sent to the ops channel.

This workflow encapsulates all manual tasks, providing a safe, auditable, and efficient process.

Step-by-Step Node Breakdown 🔧

1. Scheduler Trigger Node

This node is configured to trigger the workflow every day at 19:00 CET. It serves as the entry point, ensuring automation runs consistently without manual intervention.

2. Google Drive List Folder Node

Configured for each source folder:
Key fields: Folder ID for ERP, CRM, and Sales data.
The node lists all new CSV files in these folders for processing.

3. Google Drive Read Binary File Node

Reads each CSV file’s binary content and passes it to the next node.
Key configurations: File ID field mapped from the list node.
Processes multiple files iteratively.

4. CSV to JSON Conversion Node

Parses CSV data into JSON objects for easier manipulation.
Uses n8n’s CSV parser with a custom delimiter and header recognition.

5. Data Validation JavaScript Node 🛠️

Custom code checks:
– Presence of required headers (e.g., Date, CustomerID).
– Format consistency (dates in ISO format).
– Duplicate rows based on unique keys.
Flags invalid files for handling.

6. Conditional Node

Routes workflow based on validation result:
– True: Continue processing.
– False: Move file to ‘Failed’ folder using Google Drive Move File node and send Slack alert.

7. Transformation Node

Standardizes data by:
– Converting date strings to ISO 8601 format.
– Normalizing currency fields to EUR.
– Cleansing text fields (trimming whitespace).

8. Merge Node 🧩

Combines ERP, CRM, and Sales data. Merges on Purchase Order Number and CustomerID.
Ensures all relevant data are integrated into a comprehensive dataset.

9. Google Sheets Update Node

Replaces content in master Google Sheet with the merged dataset.
Ensures data is accessible to stakeholders in real time.

10. Slack Notification Node 📢

Sends a summary message to ops channel with:
– Total records processed.
– Duration of workflow.
– Any warnings encountered.

Error Handling, Robustness & Security

Error Handling and Retries

When validation fails or file parsing error occurs, the file is automatically moved to a dedicated ‘Failed’ folder. Slack alerts notify the support team instantly.

The workflow includes retry logic on transient API failures, with exponential backoff configured in n8n settings.

Idempotency is ensured by maintaining processed file logs in a Google Sheet, avoiding reprocessing duplicates.

Logging and Observability

All workflow runs are logged with success/failure status. Logs include timestamps, number of rows processed, and error messages if any.

Slack serves as a real-time observability channel, while historic logs are archived in Google Drive.

Security and Data Protection

• API keys for Google Drive, Sheets, and Slack are stored securely within n8n’s encrypted credentials store.
• Access tokens are scoped with least privilege principles, e.g., write access only to specified folders and sheets.
• Sensitive personal data (customer PII) is handled in compliance with GDPR. Data stored only within the EU-based Google Workspace environment.
• Audit logs track who accessed workflow configurations using RestFlow’s secure management portal.

Performance, Scaling & Extensibility

The workflow is designed to scale for the client’s growing data volumes. Key scaling provisions include:

• Webhooks vs polling: Currently scheduled polling runs nightly, but webhooks can be integrated to trigger processing on each file upload for more immediate workflows.
• Batch processing: Files are processed in batches, and the system supports parallel execution for multiple sources.
• Modular workflows: Distinct sub-workflows manage each CSV source, which can be independently updated as new data types emerge.
• Multi-client adaptation: The architecture supports adding additional folders and configuration presets for new clients or departments.
• RestFlow Hosting: Using RestFlow’s managed hosting reduces operational overhead, ensuring workflows remain stable and performant under high loads.

Technology Comparison Tables

Automation Platform	Cost	Pros	Cons
n8n	Free/Open-source, Paid Hosted Plans	Highly customizable, wide connector library, self-hosting option	Requires more setup & technical skill initially
Make (Integromat)	Paid plans starting ~$9/month	Visual editor, strong multi-step scenarios, extensive apps	Less open-source flexibility, cost scales with usage
Zapier	Paid plans start at $19.99/month	Easy to use, large app ecosystem, reliable	Limited complex logic, expensive at scale

Integration Method	Cost	Pros	Cons
Webhook Triggers	No additional cost	Near real-time processing, efficient resource use	Requires source system support and stable endpoints
Polling (Scheduler)	No direct cost but increased API calls	Simple to implement, works with most systems	Latency inherent (interval dependent), API usage higher

Data Storage	Cost	Pros	Cons
Google Sheets	Free to low cost	User-friendly, easy sharing, no additional infrastructure	Performance issues with large datasets, version conflicts
Cloud Database (e.g., BigQuery)	Costs based on storage & query usage	Handles large volumes, powerful queries, reliable	Higher complexity, requires DB admin skills

Results & Business Impact

Following automation deployment, the client observed immediate and measurable benefits:

• Time savings: Over 30 hours monthly saved—equivalent to reclaiming a full workweek previously spent on manual merging. Processing time reduced by 70%. [Source: to be added]
• Error reduction: Data inconsistencies dropped by 85%, greatly improving downstream reporting accuracy.
• Faster business decisions: Consolidated dashboards updated daily, offering near real-time insights.
• Improved team morale: Operations specialists shifted focus from tedious data entry to analysis and optimization tasks.

The client is now equipped with an agile, scalable platform to integrate additional sources as their business grows, confidently meeting SLAs and customer expectations.

Explore the Automation Template Marketplace to find similar workflow blueprints tailored for your industry and accelerate your automation journey.

Pilot Phase & Ongoing Maintenance Disclaimer

Before full rollout, RestFlow conducted a structured pilot phase with live, controlled datasets. This allowed identification and resolution of edge cases including uncommon CSV formatting, inconsistent timestamps, and network failures.

During this period, workflow adjustments and bug fixes were applied iteratively to ensure robustness. Post-pilot, RestFlow continues to provide comprehensive Automation-as-a-Service, which includes hosted workflow management, real-time monitoring, alerting, and regular maintenance.

This ongoing partnership guarantees system availability and adaptation to evolving client needs, letting teams focus on strategic initiatives instead of manual processes or technical upkeep.

FAQ

Conclusion: Transforming Manual CSV Merging with RestFlow Automation

This case study highlights how automation transformed a Munich logistics SME’s manual CSV merging bottleneck that consumed over 30 hours monthly. By strategically designing, implementing, and hosting an n8n workflow integrated with Google Drive, Sheets, and Slack, RestFlow delivered an end-to-end solution that significantly cut processing time, reduced errors, and enhanced process visibility.

Clients benefit from RestFlow’s full Automation-as-a-Service offering, which encompasses design, implementation, hosting, monitoring, and proactive maintenance—ensuring workflows stay reliable and scalable as business needs evolve.

Ready to accelerate your own data workflows? Explore the Automation Template Marketplace for ready-to-use blueprints or create your free RestFlow account to start building custom automations today.