Part II: From Lagging To Leading Indicators: The Use Cases For Predictive And Prescriptive Analytics Expands

The year 2019 saw significant momentum in the digitization efforts of firms, facilitated by strong internal and external enablers (see Verdantix Organizational And Technological Enablers Are Enhancing The Value Of EHS Analytics). With the EHS industry experiencing a shift from reactive to proactive risk management, the use cases for predictive and prescriptive analytics are being increasingly scrutinized. Previously, EHS professionals could access only descriptive data on past events. While this data remains valuable, the growth of IoT and Industry 4.0 technologies, which allows deeper analysis and real-time monitoring, has improved the impact of data collected for EHS management objectives (see Verdantix Smart Innovators: EHS Analytics In The Age Of IoT). Vendors are providing EHS practitioners of varying levels of analytical experience with insight to make smarter safety decisions while also removing the complexity often associated with advanced analytics through platforms tailored to customer personas (see Figure 1).

EHS Part II Figure 1

So, what innovative use cases are emerging for those firms looking to generate greater business value from their traditional and new data streams? In a new approach to safety and risk management, EHS managers are leveraging cross-functional data for behaviour-based safety initiatives. This is evident in Cority’s real-time safety culture score as well as the proliferation of tailored microlearning instruments. Witness Parker Hannifin, which has deployed the VelocityEHS Humantech System to manage workplace ergonomics among 2,000 team members across 400 global facilities. The modular curriculum structure of the Humantech System enabled Parker Hannifin to provide role-specific training and create cross-functional ergonomics teams. Since implementing the system in 2017, over 1,000 employees have completed online training modules, more than 2,000 users have conducted over 5,500 ergonomics and the firm has implemented over 1,200 workplace improvements.

The depth of analytics is intensifying. Firms are using predictive analytics, machine learning and leading-edge graph database architecture to model dynamic connections among historical and real-time data points to help firms prioritize their risks, identify unsafe situations, intervene pre-emptively and improve the efficiency and accuracy of root cause analyses by leveraging enterprise-wide insights. The granularity achieved through extensive data collection also has benefits at the macro-level. For example, Gensuite and consulting firm Bowers Management Analytics are experimenting with applying machine learning to a combined 1.3 million anonymized data records from six participating clients. The experiment will explore whether the application of AI to this volume of data can yield new insights, trends and early warnings from quantitative and text-based data that will further increase the value of data collection and analytics for their clients.

Undoubtedly, 2019 was a transformative year for analytics in the EHS sphere. As corporates continue to see the value of increasingly complex data analysis and vendors continue developing new data-driven solutions, the use cases for prescriptive and predictive analytics will continue to expand… into 2020 and beyond.

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