Interview with an Employee on Leave

Streamline return-to-work support with psychologically safe AI dialogue

Background and Challenges

Care information before and after leave, as well as handover items, are scattered across multiple locations, making the support status unclear

Individual return-to-work support is left to the discretion of the 담당者, and understanding workplace issues and structuring accommodation items is insufficient

Follow-up after returning to work is also person-dependent, making it easy to miss early signs of the risk of another leave

AS-IS (Current)

・Support information is fragmented and unclear

・Person-dependent plan creation

・Risk of missing signs of another leave

TO-BE (After Implementation)

・Centralized information collection and management

・Automatic structuring of accommodation items

・Early sign detection through continuous follow-up

Operational Flow

1. The system sends a questionnaire to the target employee

2. Based on the responses, accommodation items and issues are structured

3. A return-to-work support plan is automatically generated and reviewed

4. Post-return periodic status checks are also automated

Information Available

・List of accommodation points

・Draft return-to-work plan

・Workplace environment issue report

Implementation Benefits (KPI)

・Releave rate: Decrease

・Return-to-work rate: Improvement

・Support plan creation: Faster