Best Practices For EHS Analytics

Published 4 September 2018 by Rachel Umunna & David Metcalfe &

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Executive Summary

This report provides EHS decision-makers with advice on how to succeed with a digital analytics project. The EHS community has utilized data management and analytics techniques for decades. In the last five years the rise of Internet of Things data collection, the impact of generational changes on the use of digital technology, and the arrival of more robust EHS analytics offerings has pushed the idea of digital analytics up the agenda. Despite the promise of digital analytics, most EHS decision-makers have barely moved off the starting grid due to dirty data, a lack of expertise and resistance to new ways of making decisions. To improve the success of EHS digital analytics efforts, firms need to adopt a project management approach which integrates learnings from other data science projects. By doing so they can benefit from predictive analytics models, intra-day analysis of environmental compliance data, new insights from collaborative safe operations analysis, IoT sensor networks, geo-spatial enhancements to existing data and improved leading indicators.   

Table of contents

Digital Analytics Engage And Confuse EHS Decision-Makers
Analytical Techniques Are Old Hat For EHS Professionals
Digital Data Collection Opens Up A Brave New World Of Analytics
Getting Started With The New Breed Of Digital Analytics Is A Big Challenge

Succeeding With Digital Analytics Requires An Innovation Mindset 
Embrace An Innovation Mindset Before Trying To Upgrade Analytics
Clean Up The Dirty Data Lake Before Playing With Shiny Analytic Motorboats
Hire, Borrow And Poach Data Scientists To Improve Project Success
Share Analytics Successes With The EHS Community To Speed Up Adoption

Table of figures

Figure 1. Five Analytics Concepts Used By EHS Professionals 
Figure 2. Four Drivers Increase Adoption Of Digital Analytics 
Figure 3. Data Management And Analytics Terminology  
Figure 4. Data Science Flow Chart For Digital Analytics Projects  
Figure 5. Business Intelligence Functionality Is An Important Purchase Criterion 
Figure 6. In-House Software Is Used Most Frequently For EHS Analytics  
Figure 7. Value Of Analytics For Different EHS Usage Scenarios 

About the authors

Rachel Umunna


Rachel is a technology analyst in the Verdantix Operational Excellence Practice. Her research agenda explores the value of technologies for investors, service providers and corporates. Prior to joining Verdantix Rachel worked for the CDP. Rachel holds an MSc Environmental Technology from Imperial College London.

David Metcalfe


David is the CEO of Verdantix and co-founded the firm in 2008. Based on his 20 years of experience in technology strategy and research roles he provides guidance on digital strategies to C-level executives at technology providers, partners at private equity firms and function heads at large corporations. His current focus is on helping clients understand their market opportunity tied to ESG investment trends and their impact on corporate sustainability strategies. During his 12 years running Verdantix – including 4 leading the New York office – he has helped dozens of clients grow their businesses through fund raising, acquisitions and international growth. David was previously SVP Research at Forrester and Head of Analysis & Forecasting at BT. He holds a PhD from Cambridge University and also worked as a Research Associate at the Harvard Business School.

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