Organizations have been implementing robust guidelines to ensure minimal health and safety (H&S) incidents in manufacturing for decades now. More recently, these H&S guidelines have been integrated with their corporate business strategies, with the goal being ‘zero fatalities’ and ‘injury-free facilities’ among others. With COVID-19, when most organizations have experienced slowdown or complete shutdown based on respective industry dynamics, supply and demand situation, and regulatory approvals, their employees have been transitioned into a remote working model. However, with little adoption of remote operations – particularly in asset-intensive industries – enhancing manufacturing capacity to revive the global economy will require the physical presence of the workforce.
In this climate, an organization must ensure employee safety and take appropriate and responsible measures on the field to contain the disease spread effectively. Hence, an H&S agenda assumes a much larger role for manufacturers now. It calls for a re-emphasized responsibility for chief sustainability officers (CSOs) to develop a resilient H&S capability to support full-throttle operations. A robust H&S policy in manufacturing and technology-enabled implementation will ensure business continuity with limited or no unsafe incidents.
According to TCS’ Neural Manufacturing framework, manufacturing firms can use networked technologies to identify non-compliance of pandemic-specific and organization-level H&S practices. Firms can use machine learning to identify corrective actions and enact strategies using automation to avoid COVID-19 transmission and any H&S mishaps within organizational premises. Organizations can benefit from an intelligent and connected H&S management capability within manufacturing premises by using offerings based on internet of things and analytics.
Below are a few recommended practices for CSOs and H&S managers to ensure a more comprehensive H&S function management. It is important to note that the implementation of one policy naturally demands dependency on other practices to ensure full-fledged employee safety.
1. Data acquisition: Managers must assess the non-compliance to social distancing guidelines and safety measures, presence of COVID-19 symptoms, safety incidents, accidents on the field, and record for analysis and insights. Technologies such as Lidar, bluetooth, immersive, and computer vision can be applied in these areas. Such recorded H&S data ranges from linear information to video streams. The major challenge is sorting out this massive and varied data set appropriately to draw meaningful insights. With big data and data science technologies, analyzing H&S events becomes easier; this also presents a cognitive capability to slice and dice the data effectively and efficiently. The richer this database, the more effective will be the prognostic capability built atop it.
2. Intelligence: Based on the information collected, managers must react in near real time to potential hazardous events to eliminate H&S risks. This is possible only when adequate information reaches the H&S taskforce on the ground before the detected event leads to an accident, which would mean managers must have the capability to:
- Understand the data point received.
- Derive root causes for the event and generate insights.
- Predict the time and intensity of a potential H&S hazard.
- Provide this prediction to H&S stakeholders to trigger action.
In some cases, the action itself can be automated using an AI agent. Managers must also consider probable areas for deploying AI and automation for statistical analysis of data and subsequently convert insights into prescriptive action, which will optimize the H&S function.
3. Holistic H&S capability: With time, managers can introduce a more holistic H&S capability to generate deep insights into worker behavior and ensure adherence to H&S guidelines, leading to preventive and prescriptive actions. Similarly, a more intricate understanding of unsafe and hazardous zones within sites can help with a comprehensive H&S management plan. Multiple layers can be woven – from personnel behavior and hazardous elements – into this tech-enabled renewed H&S capability. This single-pane-of-glass view can provide visibility into mental and physical employee health, and product, asset, process, and employee safety. However, care must be taken to abide by data privacy protocols while handling such intricate information. For example, Lidar devices can be used to detect non-compliance of social distancing norms instead of sensors or wearables worn by employees. Even if employees sign in to use wearables or sensors, it is important for organizations to limit the distribution of employee H&S data with only concerned stakeholders for appropriate actions.
4. Role-based data governance: As employee safety demands colossal amounts of data to be collected and distributed, firms must set up appropriate usage policies. Role-based consumption of H&S data, insights, and prediction is important, not only for timely action but also for better governance purposes. Different stakeholders would use their piece of data to integrate insights and evolve the existing H&S policy and procedures to eliminate potential risks.
As manufacturing organizations and other asset-intensive shop floors resume operations, employee H&S will top the agenda to ensure smoother operations. COVID-19 or not, it is time for the H&S function to evolve multifold and assume its rightful order in the boardroom’s priority list – it cannot be just a reporting KPI anymore.