Long working hours are now considered by the WHO/ILO to be the occupational risk factor with the largest attributable disease burden. WHO/ILO advise, “Protecting and promoting occupational and workers’ safety and health requires interventions to reduce hazardous long working hours.”
So, what is data accuracy? Data accuracy is one of the “six dimensions” of data quality and it can be defined as the “degree to which the data correctly describes the ‘real world’ objects being described.” This definition makes it easy to see how poor data accuracy could greatly impact your ability to use your data effectively.
Being a safety and occupational health leader is not easy. In many cases, the position requires enormous responsibility and accountability with little or no authority or resources.
Incident investigations are a critical part of your safety program and safety culture. When an incident occurs, when and how you address it is equally as important as what you address and why.
CEOs Action for Diversity & Inclusion (1) state that “… diversity and inclusion are multifaceted issues and that we need to tackle these subjects holistically to better engage and support all underrepresented groups within business.”
With the announcement last week that ASSP has opened up registration for their conference in Austin this September, they announced the safety precautions they are taking to ensure everyone who is attending is comfortable.
There are only two programs that I believe require repeated discussions because failure to do things right in either of them can lead to death. Those programs are LOTO and Confined Space Entry.
“First do no harm” is a fundamental ethical principle practiced among physicians and related healthcare professions throughout the world. OHS pros should be aware of its concepts.
Many companies starting their data analytics journey make the mistake of skipping the data cleaning process all together. None of us want to see how the sausage is made, we just want the bratwurst to magically appear. But as we have seen over, and over, insightful analytics cannot be achieved with poor data quality.