No 3 – Sensor + Observational Data Collection
“Remote data collection via multi-sensor technologies can enable an assessor to collect tremendous amounts of quantitative data,” Join LifeBooster’s Program Manager & Ergonomist, William Thomas, as we discuss the benefits and differences between sensor and observational data collection.
Modern wearables technologies and traditional observational approaches to ergonomics are not in competition with one another—they are perfect compliments for achieving better holistic insights and for collecting the right information to drive the best ergonomic program outcomes.
When comparing more traditional observational approaches to ergonomics versus using sensor technologies to collect ergonomic data virtually, it’s important to understand that there are relative merits to each and that they can work in tandem to achieve better results. Observational methods afford a practitioner the opportunity to engage with a workforce and understand the work context. These methods can provide powerful insights into organizational and psychosocial risk factors. However, these methods present challenges in collecting a wide variety of quantitative data in a timely and resource-efficient manner and are potentially limited by assessor bias and data validity challenges.
On the flip side of this, remote data collection via wearable sensor technologies is well suited to collecting quantitative data and can enable an assessor to collect tremendous amounts of data while affording an opportunity to account for worker and temporal variability by devising an effective data sampling strategy to generate a representative sample of the workforce. These benefits enable an assessor to take a data-driven approach to ergonomics risk management, whereby this data can then be enriched and informed through employing more targeted qualitative and observational techniques as a subsequent tool. The result is not only more accurate and comprehensive data insights but an enrichment of this data through a focused application of supporting qualitative methods.
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