Evaluating Workflow Automation Efficiency Using n8n: A Small-Scale Business Case Study
Abstract
Workflow automation has become increasingly accessible through low-code platforms, enabling individuals and small organizations to improve operational efficiency without extensive software development expertise. This study evaluates the performance impact of workflow automation using n8n through a small-scale business case study. A representative lead-processing workflow was implemented to automatically store data, send email confirmations, and generate real-time notifications. Experimental benchmarking compared 20 manual executions with 25 automated executions under controlled conditions. Results show a reduction in average execution time from 185.35 seconds (manual) to 1.23 seconds (automated), representing an approximately 151× improvement. Manual execution exhibited a 5% error rate, while automated execution showed no observed errors. Findings demonstrate that low-code workflow automation significantly improves efficiency, reliability, and execution stability in lightweight operational environments. This study provides empirical evidence supporting the practical adoption of automation technologies by small-scale users and early-stage practitioners.
Fields of Study & Subjects
Scientific Computing and Data Management
Business Process Modeling and Analysis
Software System Performance and Reliability
Publication details
- Publisher
- ScienceOpen
- Publication date
- 30 January 2026
- Document type
- Preprint