인사 데이터 및 분석 • 6 최소 읽기 시간
결근 데이터를 사용하여 결근율을 줄이는 방법
MAY 12, 2026
결근 데이터는 HR이 활용할 수 있는 가장 풍부하고 가장 덜 활용되는 통찰의 원천 중 하나입니다. 이를 행동으로 전환하는 방법은 다음과 같습니다.
결근 데이터가 말해 주는 것
Absence data contains multiple diagnostic signals that HR rarely reads systematically. High overall absence rates signal a general wellbeing or management problem. High rates of short-term absence (one to three days) with frequent occurrences per individual signal the Bradford Factor problem: employees who are frequently absent in short bursts have a disproportionate operational impact compared to employees with the same total days absent in fewer, longer episodes. Clusters of absence on Mondays and Fridays signal presenteeism followed by avoidance, often associated with burnout or work-related stress.
분석에 대한 대응
Once you have identified the patterns, the intervention is typically at the manager level. High absence in a specific team, particularly short-term and Monday-Friday-clustered absence, is almost always partly explainable by management quality. Require managers of high-absence teams to review the absence data with HR and identify the root causes. Implement structured return-to-work conversations after every absence, regardless of length: they are the most effective single intervention for reducing short-term absence rates because they signal that absence is noticed and that manager support is available.
