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Work Overload: The Most Common Psychosocial Risk in Companies

Africa2 hr ago

Work overload, defined as sustained work beyond sustainable capacity rather than just a high volume of tasks, is identified as the most prevalent psychosocial risk within companies. This continuous demand, exceeding a team's capabilities, becomes a chronic issue when it shifts from an occasional exception to a routine problem requiring management. Psychosocial factors often manifest in combination, rarely in isolation, with persistent overload being the most frequent concern.

Companies must address identified overload through actionable plans, including designated responsibilities, deadlines, and measurement methods, prioritizing organizational solutions. Tools like MenteNR1 can anonymously map these risks and assist in developing such plans alongside Safety and Health at Work (SST) teams. While MenteNR1 aids in compliance and legal protection under NR-1 regulations by organizing and documenting efforts, it does not absolve employers of their technical and legal responsibilities, nor does it guarantee immunity from penalties or legal actions. The effectiveness of any compliance measure hinges on its actual implementation, as outlined in MenteNR1's Terms of Use. Recognizing overload as a distinct risk, rather than a normal work pace, is the crucial first step toward implementing the systematic approach mandated by NR-1.

AI Analysis

The prevalence of work overload as a psychosocial risk highlights a systemic tension between productivity demands and employee well-being. Companies face a dual imperative: meeting operational targets while adhering to regulatory frameworks like NR-1 that mandate risk management. The reliance on tools for mapping and planning suggests a move towards quantifiable, auditable compliance, yet the ultimate responsibility remains with the employer. Future organizational models will need to integrate sustainable workload management not just as a compliance exercise, but as a core component of operational efficiency and long-term resilience, particularly as AI-driven automation reshapes task allocation and performance metrics.

AI-generated to prompt reflection — not editorial opinion, not advice, not a statement of fact. How this works.

Compiled by NewsGPT from Globo G1 (BR). Read the original for full details.