ESRS S1-9 Working Time

What ESRS S1-9 requires

ESRS S1-9 requires disclosure of: the number of employees working part-time and the percentage this represents of total employees; and information about working time arrangements — particularly overtime hours and excessive working time where material.

Part-time employees: The number and percentage of employees working part-time (as defined in S1-6 methodology — below standard full-time hours for the jurisdiction). Breakdown by gender is expected — the gender split in part-time work is a key indicator of work-life balance equity between male and female employees.

Overtime: Where overtime is material — either financially significant or a wellbeing risk — disclose average overtime hours per employee and the percentage of employees working overtime above a defined threshold (for example, more than 10% above contracted hours regularly).

EU Working Time Directive compliance: For EU operations, the Working Time Directive (2003/88/EC) sets a 48-hour maximum average working week (including overtime), a minimum 11-hour daily rest period, and a minimum 4 weeks paid annual leave. Disclose whether all operations comply with these minimum standards — non-compliance is a material legal risk.

Flexible working arrangements: As hybrid and remote working become standard, disclose the prevalence of flexible working — percentage of employees with access to remote working, flexible hours arrangements, compressed working weeks, or other non-standard arrangements. This is not yet a mandatory S1-9 metric but is increasingly expected as context.

Part-time work and gender equity

The gender distribution of part-time work is one of the most revealing indicators of workplace gender equity — and S1-9 part-time data combined with S1-12 gender pay gap data tells a powerful story about structural equality.

The structural connection: In most European economies, women are significantly overrepresented in part-time employment — typically comprising 70-80% of part-time workers. Part-time work reduces career progression speed, limits access to bonuses and promotion cycles, and creates pension gaps (lower lifetime contributions). This structural concentration of women in part-time roles is a primary driver of the gender pay gap and the gender pension gap.

For S1-9 gender breakdown: disclose part-time employees by gender — the ratio of female to male part-time workers reveals whether part-time work is distributed equitably or concentrated among female employees. A company with 30% female employees overall but where 90% of part-time workers are female has a significant gender equity issue embedded in its working time structure.

Policy responses: Companies with equity ambitions address this through: flexible working rights for all employees regardless of caring responsibilities; active promotion of male part-time working and shared parental leave; career development pathways for part-time employees equivalent to full-time; and line manager training on equitable treatment of part-time staff.

For S1-9 and S1-12 integration: when disclosing the gender pay gap (S1-12), reference the part-time gender distribution (S1-9) as a structural factor. This demonstrates awareness of the root cause — not just the surface metric — and provides investors with the context to assess whether gender pay gap remediation is addressing causes or symptoms.

Overtime and worker wellbeing

Excessive overtime is a material workforce sustainability issue — connected to burnout, mental health deterioration, H&S incident risk, and long-term workforce capability degradation. S1-9 overtime disclosure makes this risk visible.

Where overtime is particularly material: call centres and customer service operations during peak periods; manufacturing with seasonal or project-driven demand spikes; professional services with deadline-intensive project work; healthcare with staff shortages requiring extended shifts; and retail during holiday trading periods.

Measuring overtime: Average overtime hours per employee provides a basic measure. Distribution matters more than average — a population where most employees work moderate overtime differs from one where a small percentage works extreme overtime while others work none. Disclose the percentage of employees regularly working more than a defined overtime threshold.

EU Working Time Directive opt-out: The Directive allows individual employees to opt out of the 48-hour maximum by signing an individual agreement. Disclose whether opt-out agreements are used, the percentage of employees who have signed them, and the average working hours of opt-out employees. Widespread opt-out usage in professional services and some healthcare roles is common — but high opt-out rates in manual or operational roles may indicate systematic Working Time Directive avoidance.

Wellbeing connection: Link S1-9 overtime data to your wellbeing programme disclosures. Where high overtime is identified as a material issue — through S1-9 data or employee survey feedback — what targeted interventions are being deployed? Workforce planning, productivity investment, and wellbeing support are the primary levers.

Frequently asked questions