How Leave Request Automation Saves HR Teams 60% of Their Time

BLOG Nodify Team
2 min read

One of the most time-consuming tasks for HR departments is still managing leave requests manually. Excel sheets, endless email chains, waiting for managerial approvals – all these make the process inefficient and frustrating for both HR and employees.

But is it possible to digitize this process and eliminate hours of manual work?

The answer is YES — with Business Process Management (BPM) platforms.

The Problem:

- Employees submit leave requests via email or Excel.

- Managers take days to approve them.

- HR manually tracks remaining leave balances.

- Reporting and preparing audit-ready records is time-consuming.

Result: Errors increase, efficiency drops, and employee satisfaction declines.

 

The Solution:

Leave Request Automation with BPM
Low-code BPM platforms like Nodify allow HR teams to quickly digitize and automate their leave workflows.

How it works:
- Employees submit requests via web or mobile.
- Notifications are automatically sent to approvers.
- Leave days are calculated and updated instantly.
- HR accesses all leave balances from a central dashboard.
- Historical data can be exported in one click (PDF/Excel).

Real-World Example:
In a mid-size tech company, a Nodify-based leave automation process went live in just two weeks. As a result:
- Average approval time dropped from 3.5 days to 4 hours.
- HR’s manual workload was reduced by 60%.
- Complete historical records were securely archived and audit-ready.

Why Now?
As of 2025, over 70% of companies prioritize digital transformation in HR. If your organization is still tracking leave manually, you may be missing out on major efficiency gains.

Ready to digitize your HR processes with Nodify? Save hours – even months – of effort with a smart, low-code platform.
Request a free demo now: info@nodify.com

 

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Nodify Team

Nodify Team

The entire team are experts, with their technical and management experience in deploying simple and complex solutions, combining people, processes and data.

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