01/20/2020 | News release | Distributed by Public on 01/20/2020 10:57
The field of analytics can be complex and daunting, especially for smaller firms that may not have in-house analytics teams to guide the implementation process. While there is a plethora of foreign and confusing terminology, EHS programmes and Initiatives typically rely on three categories of analytics:
Descriptive analytics is the most prevalent and traditional category in EHS, which analyses past performance and generates lagging indicators-such as Lost Time Injury Frequency Rate-that can be used to improve future performance.
Predictive analytics has been used in the financial industry for over a decade but is just now gaining a foothold in the EHS landscape. This category uses statistical techniques to make predictions about future performance.
Prescriptive analytics provides recommendations on actions or decisions to take and can be based on indicators from both descriptive and predictive analytics.
So why are we seeing an increasing focus on analytics across the EHS landscape? Firms in the modern operating environment face intense reputational risks from both the consumer and investor stakeholder groups. This is especially true for the EHS practice where internal processes are intensely investigated following a worker incident and the associated sentencing guidelines and fines are increasingly hard-hitting. Firms are leveraging the enhanced tools available to improve risk visibility through data collection and interrogation and alleviate the resource constraints exacerbated by ever-increasing regulatory and reporting requirements (see Figure 1).
Working in parallel with the organizational demand drivers, we also are seeing the value proposition and business case of analytics projects strengthen due to strong technological enablers (see Figure 2). The proliferation of mobile applications, wearable devices and IoT sensors-which have become more affordable and fit for various EHS use cases-have increased the volume and ease of data collection dramatically. In conjunction with mobile capability and IoT advancements, data quality also has improved, which improves the accuracy and reliability of the derived insights. The reduction of silos through expansive business and EHS software solutions are enabling firms to build holistic, enterprise-wide pictures of their risk landscape and share key learnings across business units, sites and geographies. The higher acceptance of SaaS and cloud-based infrastructure also is allowing a higher degree of real-time monitoring, which facilitates the shift from reactive to proactive risk management. Lastly, the visualization of key indicators is a huge priority for firms. As such, out-the-box forms, reports and visualization capabilities are fast becoming a standard feature of EHS software solutions, which adds new power to analytics activities.
These organizational and technological enablers left their definitive mark on the EHS landscape in 2019, and signal a transformative year ahead for risk, safety and process management.
Stay tuned for Part II of this blog post, where we shine a spotlight on the tangible benefits of EHS analytics and highlight the initial predictive and prescriptive analytics use cases that have emerged.