Evaluating Workflow Automation Efficiency Using n8n: A Small-Scale Business Case Study
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arXiv
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| Hauptverfasser: | , |
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| Format: | Preprint |
| Veröffentlicht: |
2026
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| _version_ | 1866914299756150784 |
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| author | Amir, Ahmed Raza Atif, Syed Muhammad |
| author_facet | Amir, Ahmed Raza Atif, Syed Muhammad |
| contents | Workflow automation has become increasingly accessible through low-code platforms, enabling small organizations and individuals 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 was conducted by comparing 20 manual executions with 25 automated executions under controlled conditions. The results demonstrate a significant reduction in the average execution time from 185.35 seconds (manual) to 1.23 seconds (automated), corresponding to an approximately 151 times reduction in execution time. Additionally, manual execution exhibited an error rate of 5%, while automated execution achieved zero observed errors. The findings highlight the effectiveness of low-code automation in improving efficiency, reliability, and operational consistency for small-scale workflows. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_01311 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Evaluating Workflow Automation Efficiency Using n8n: A Small-Scale Business Case Study Amir, Ahmed Raza Atif, Syed Muhammad Software Engineering Workflow automation has become increasingly accessible through low-code platforms, enabling small organizations and individuals 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 was conducted by comparing 20 manual executions with 25 automated executions under controlled conditions. The results demonstrate a significant reduction in the average execution time from 185.35 seconds (manual) to 1.23 seconds (automated), corresponding to an approximately 151 times reduction in execution time. Additionally, manual execution exhibited an error rate of 5%, while automated execution achieved zero observed errors. The findings highlight the effectiveness of low-code automation in improving efficiency, reliability, and operational consistency for small-scale workflows. |
| title | Evaluating Workflow Automation Efficiency Using n8n: A Small-Scale Business Case Study |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2602.01311 |