Organizations today are challenged with improving EHS performance with fewer financial and human resources. A current trend in the professional EHS community is to focus on using data in advanced analytic models to gain meaningful insight that drives change and performance improvements. The issue with this approach, however, lies in the barriers to performing advanced analytics successfully—such as the methods in which data is captured, and its structure, type, and quality. EHS consultancies are experiencing a transformational change towards the digitization of their value propositions. Virtually all EHS services firms have broadened their use of digital tools from environmental data management (EDM) software and EHS software implementation, to mobile apps, business intelligence tools, and IoT sensors. To produce sustainable improvement, Accenture recommends implementing a Digital Strategy for EHS Performance. This structured collection of high-quality data and advanced analysis can help companies produce actionable EHS insights in real-time.
It is imperative that companies move beyond traditional EHS data reporting. Which for many, consists of monitoring key performance indicators. But monitoring leading and lagging performance metrics does not provide an understanding of true operational risks or the insights to improve performance.
The initial step toward a Digital Strategy is to review available data and determine its capability to be used in an advanced analytics model. A specific opportunity to improve data quality and structure can be found in the outfitting of Digital Workers with new technology that automates and streamlines data capture. Workers are provided with sensory equipment, interactive hardware, and mobile applications that allow for real time data collection and decision-making.
Examples of new automated technologies are:
- Mobile apps that can be run simultaneously on tablets in the field, allowing for multiple data streams to be collected at the time and location of generation. The data capture process is streamlined with benefits for multiple business functions.
- Sensory equipment to read worker location and concentrations of oxygen, hydrogen sulfide and the lower explosive limits of chemicals in atmosphere. Location sensors can also provide data to prevent access to unauthorized work areas for workers and equipment, and data can be used to validate worker productivity, equipment use and associated costs.
- Pervasive wireless is another solution that enables the collection of high quality data. In fixed facilities with complex infrastructures, such as manufacturing plants and production facilities, the ability to remain connected to digitally equipped workers and equipment is hindered by the structure itself. Installation of a local and secure pervasive wireless mesh network can overcome this critical barrier and support the real-time collection, storage, and analysis of data. By improving the processes for data capture and underlying data structure, a higher quality data set enables advanced analytics. These analytic models produce relevant information, provide operational insight, and are scalable for broader enterprise analysis or deeper individual business unit analysis. Advanced analytics can be applied to EHS data to identify operational risks for targeted action and improvement. However, care must be taken when developing an analytic model. This is, in a manner of speaking, a predictive capability and trying to predict an EHS incident with specificity can be a difficult and risky task of its own. For example, changes in leadership and company priorities can impact the type of data being generated. Thus, an analytic model’s ability to reliably and consistently assess and identify operational risks is therefore impacted, and the analytic model will need to be recalibrated as the EHS culture evolves.
All in all, EH&S is more of a convention of the present day and age that isn’t just a dire necessity for your organization but is also something that needs to evolve with time. This is why EH&S needs to be digitalized, but more importantly, it has to become mainstream so that we can ensure the safety of our resources and to be able to make the overall environment more connected.
