Human Problems Require a Human Approach.
Human behaviour is inherently variable and uncertain, and any approach to understanding a person’s behavioural impact on their exposure to health and safety risks must take these factors into account.
When it comes to assessing a person’s exposure to Hand Arm Vibration (HAV), a reliable metric is one that provides insight into the way that a person actually uses a tool, which includes frequency of use, operator competency, tool condition, and myriad of other – often unpredictable – factors. The traditional method for determining the risk posed to workers by exposure to vibration provides unrealistic, unrepresentative information because it relies on data from one person’s use of one tool during one activity at one point in time. Said otherwise: it doesn’t account for the variability or unpredictability that most certainly influences an individual’s actual, long-term exposure to vibration. This limited data is used to predict a person’s exposure moving forward, but the reality is that such restricted information is essentially useless for ascertaining a worker’s actual exposure to HAV over time. It’s simply impossible to utilise such finite data to make informed predictions about long-term exposure to unsafe conditions.
The foundation for this logic, that reliable, repeatable, reproducible information – information that is not collected in a vacuum – is the most representative and trustworthy available, underpins the field of predictive analytics (measuring behaviour to determine a future course of action), and it’s the bedrock of any calculation as to whether results you’ve gathered are meaningful and, most crucially, useful. Information need not be perfect – in most cases perfection isn’t possible – but any effort to collect sufficient data must attempt to ascertain the most accurate, most reliable, most robust results available. One person’s use of one tool during one activity at one point in time falls well short of this universally accepted standard.
It’s a bit like training for a marathon without an exercise monitor: if you embark on a training plan to run 26.2 miles but you have no data to inform how far you’re running or how fast, your assessment of your own progress will be incomplete, inaccurate, and strictly retrospective. If you wear an exercise monitor, however, you’ll be able to view your running stats over time and better understand – and refine – your training behaviours. If, for example, you learn that your pace is consistently slower on warmer days, you could reasonably assess that your body performs better in cooler temperatures. From this information, you could make simple changes to increase your performance and avoid unnecessarily draining workouts: You could work out in the early morning or later at night when the weather is cooler, you could plan fewer challenging workouts on warmer days, and you could plan future races around cooler training times and seasons.
Similarly, this type of approach – a human approach – can be applied to assessing a workers’ exposure to HAV by evaluating real use data for individual workers using specific tools: It uses personalised, real-time monitoring to collect and collate information over time. This provides valuable insights for workers and duty holders to act upon when it comes to reducing exposure to HAV. As such it offers more adequate, more representative information than traditional methods for evaluating the risk of specific tasks. This kind of information – information that is most approximately right – is the key to guiding process refinement and driving down your employees’ exposure to HAV. In so doing you will not only make your workplace a safer place for your employees, but you will also more readily meet your legal obligations to reduce risk as low as reasonably practicable.
The only way to make sure your employees and business are exposed to less risk of HAV is to invest in tools that give you the actual knowledge you need to understand and address the issue – tools that take a human approach to assessing exposure to HAV.
For more information on HAVS prevention visit https://bit.ly/2VHw9ml