Guest Post: Digital Transformation of EHS & ESG Promises Clarity, Consensus, and Direction
By: Donavan Hornsby, Chief Strategy Officer at Benchmark Digital
Clarity and consensus are fundamental to effective risk management and mitigation. Global events over the last few years have revealed corporate resiliency gaps and demonstrated the importance of those fundamentals.
It’s time that business leaders see their legacy risk management frameworks and mitigation protocols for what they are: exceedingly reactive and, as a result, increasingly ineffective. While reactive approaches have a role to play in value preservation, they don’t lend themselves to true enterprise resilience, leaving opportunities for value creation on the table.
What’s missing is direction. Fortunately, business leaders need not reinvent the wheel to find it.
Building the kind of enterprise resilience capable of cultivating value is a matter of improved planning and preparation. To do this, business leaders will first need more granular insight into the nature, severity, and probability of event occurrence for the unique hazards they face. Relatedly, they will need to leverage this information to ensure they are combatting the biggest threats to their business first, a process that can only be achieved with continuous insight into the accuracy of their risk evaluations, as well as the life cycle outcomes of whatever corrective actions are deployed.
Accurate, timely, complete, and retrievable data is the centerpiece. Yet, collecting data from across all reaches of a company and using it to inform decision-making requires an amount of time and energy that may undercut any value created. More still, if these processes are operationalized via manual, spreadsheet-driven workflows, the inevitable human error and delay in data entry, analysis, and reporting risks incurring new costs of their own.
Business leaders can circumvent these limitations and graduate from reactive risk management and mitigation to a proactive approach with the right technological foundations.
Cloud-based platforms are uniquely positioned to bring the necessary efficiency and rigor to operational data collection and management. Dedicated, digital channels for cross-functional communications will support improved workflows. And AI-powered descriptive, predictive, and prescriptive analytics will bring certainty to risk evaluation, prioritization, and mitigation selection.
For evidence, consider the case of the Environment, Health, and Safety (EHS) leader. These professionals are among the first line of defense against the sort of risks intensified during the pandemic era, including those pertaining to employee health and wellbeing, workplace safety, and other Environmental, Social, and Governance (ESG) matters.
Without adequate data collection, management, analysis, and internal reporting systems in place, accurate measurement of these non-financial risks, let alone effective management of them, would be all but mission impossible for the EHS leader or their counterparts. Yet cloud-based systems can automate data collection from siloed systems, lessening the burdens of dispatching, responding to, and confirming the accuracy of performance data queries.
This much, at least, is confirmed by the findings of a recent survey of U.S. business leaders commissioned by my organization, Benchmark Digital®. In brief, our survey results suggest that companies who use cloud-based data management and reporting software provided by a vendor to drive their ESG programs—as opposed to those developed in-house—are more likely (+15%) to report complete interoperability with their legacy, often siloed data management systems.
Among other advantages, this functionality facilitates a more decentralized, cross-functional approach to measuring, managing, and reporting ESG risk management outcomes. As a result, these respondents reported outperformance in real-time data updates (+8%), data observability (+12%), and performance evaluation (+4%).
Business leaders can trust that, with these competencies, they will have a degree of clarity and consensus over the hazards and risks they face that would otherwise be unattainable. Especially when equipped with the descriptive and predictive analytics capabilities of artificial intelligence, the operationalization of these systems empowers their users with forward-looking insight into the provenance, nature, severity, durability, and yes, even resolvability of the sustainability risks they face.
These are the makings of more proactive risk management and mitigation, the centerpiece of enterprise resilience.
Yet, with an eye to value creation, it’s the capacity of artificial intelligence (AI) to generate prescriptive analytics that matters most. Specifically, these systems can analyze the troves of operational data stored in a cloud-based system, from records of workplace safety incidents to the outcomes of corrective actions deployed. In short, with AI-equipped cloud-based data management and reporting systems, users will not only have a better understanding of the efficacy of today’s risk management interventions, but also be better able to select the optimal risk mitigation measure tomorrow across a range of metrics, inclusive of financial and sustainability performance ROI.
The value of equipping cross-functional teams with deep, continuous insight into the successes and failures of their organization’s sustainability risk management and mitigation processes cannot be overstated. Empowering them with the resources they need to perform, and see the fruits of their labor, is the key to programmatic success.