we are witnessing how organizations, which are in the field of e-commerce, social networking, video streaming and collaboration tools are performing, one thing is clear that data driven decision and big data is here to stay. It would be a new normal for organizations to use big data and data driven analytics to operate on a day to day basis. If you notice the amount of data consumed and generated in past few months post pandemic is phenomenally large. You would not be surprised to if research finds out that the amount of information consumed or generated in current year surpassed the all previous years by an incremental fold. Visualize if we could analyse and process such data for deriving insights, data is not worth if we are not able to derive insights.

To carry out such analysis we have tools available be it big data technology like Hadoop, Data lakes etc. or data analytics tools with latest and sophisticated algorithms which emerge each passing day. The data insights and analytics for the areas of Environment, health and safety is an exciting area which has a potential to help organizations benefit a lot. In my previous blogs I have wrote in detail analytics opportunities for Product Safety Stewardship, Health and Safety and Environmental Monitoring. In this blog I would like to summarize the key big data and data analytics opportunities for meeting EHS requirements in current scenario.

There are already several research articles are published which highlight how disease prevalence and population characteristics can be used to derive insights around pandemic. Such analysis of disease prevalence, treatment patterns, patient key attributes, location and air quality or meteorological patterns can help organizations in understanding the situation. The simulations of fluid dynamics also referenced in literature which are being used in conjunction with analytics to derive insights.

Other similar use of big data and data analytics for human health management is around analysis of workplace sampling data and employee physiological pattern which is being used in many organizations to understand the risk. In this scenario a series of IoT devices are coupled with environmental monitoring to understand the risk and suggest in real time. Though it needs a set of wearables to carry out the monitoring there are also efforts of real time monitoring via fixed sampling devices and their analysis.  

The significance of material procurement can not be ignored. A careful analysis of social media analysis can reveal the risk an organization facing with their current suppliers. A detailed assessment of media posts can help understand the locations where the impact is severe and how the chosen organization is performing and the associated risk it poses to the supply chain. There are many organizations which are dynamically in and out of the business overnight. The analysis of media posts can help plan better.

The other topic of big data and data analytics is assessing the impact of the pandemic on organizations in terms of their direct and indirect costs. There is a need for churning multiple documents, scattered data records of varied forms to derive insights. A careful assessment strategy of data and deriving impacts in-terms of regulatory cost is a huge benefit for the organizations.

Like the workplace analysis, there are also huge efforts underway in many organizations to analyse the proximity and scanner studies. A real time collection of people proximity violations and thermal scanners with employee in question is also gaining popularity. There are various devices available which when integrated with big data and data analytics can identify the anomalies in real time. Like a sensor to sensor proximity study or even real time video streaming and flagging of proximity risk can also be carried out.  

Other areas where big data and analytics can be used is around identification of operational risk of restarting the equipment. Many plants and their machinery have been put under hibernation and when they are restarted for use there is a likely hood of failures. A careful collection of data from such systems for various attributes and analysis of fault or failure can help a lot for organizations. Though many such equipment are not coupled with sensors systems, but a similarity approach can be adopted to analyse such impacts. Impacts like risk while operating refrigeration system or operation of equipment or valves or pressure gauges etc can be analysed for potential failure so that necessary precautions can be taken.

Transportation of supplies and impact of storage conditions is also another impact study in the current scenario. Due to blocks and hinderances transportation needed to be tracked carefully to derive insights.

Other analytic use which is not related to industrial operations but for communities in general is around assessment of global environmental patterns because of the pandemic and how various parameters like GHG, Ambient Air quality or Air Pollutant related disease prevalence, meteorological changes due to changes in transportation or similar studies like sustainability related can be performed. Though it is with individual expertise in performing the analysis multi year analysis and comparing with single year monitoring database.

The other area though which can derive lot of benefit to organizational in the field of Agriculture is around assessment of impact on the yield in various countries and how likely they are in the verge of facing food scarcity or issues due to food supply chain disruptions.

To conclude we have been witnessing many cases studies of big data and data analytics in the field of retail business, oil & gas, chemical, supply chain, health, entertainment but the scope of using the technologies for EHS is huge. The success of the analysis lies in identifying the right set of data or munging of data or choosing right set of big data or analytics to derive insights. The domain specific expertise can not be ignored either. So before wrapping what are the EHS areas which you think are relevant in the current scenario where use of big data and analytics will help you staying ahead.



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