Working from home has become the “New Normal” since March 2020, when COVID-19 forced employers to move employees out of physical offices for health and safety reasons. Now, states across the U.S. are slowly emerging from stay-at-home orders and businesses are looking to resume activities within both essential and non-essential business sectors.
But with this shift comes concern. Will returning to physical workspaces create a resurgence of the virus? According to global consultants at McKinsey, simply mapping out new cleaning schedules and adjusting workspaces and walking paths to allow for social distancing may not be enough to provide a safe and healthy workspace. A McKinsey COVID-19 briefing note suggests organizations ramp up their skills in analytics to help manage the complex problem-solving and data crunching that creating a safe and healthy workspace may require.
But using analytics technology to manage health and safety risks has not been a regular part of most human resources, financial, legal or management team roles in the past. It’s less tangible than guidelines set by OSHA and the application of worker’s compensation is murky at best, according to the National Council on Compensation Insurance (NCCI). A glimmer of hope may come in the form of new software solutions, leveraging critical pieces of data, automation and analytics that can alert to increased risk of COVID-19 for employees and businesses.
The Challenge of Data
Employees returning to work outside their home have an increased risk of contracting coronavirus. There’s simply no way to avoid exposure without complete isolation. Since isolation is incompatible with the infrastructure of returning to work, we must find a way to make the risk more manageable. One way to do this is through the collection and analysis of data as it relates to risk.
For example, employees can use an app on their phones to self-monitor their health and record any changes in temperature, COVID-like symptoms or general well-being. They can also self-monitor their interactions such as close contact with other individuals that later tested positive for coronavirus or indicated symptoms. In addition, technology such as Bluetooth and radio-frequency can monitor proximity information and locations using smartphones.
Aggregating data from all employees returning to physical areas allows us to gain a bigger picture of health and activity. The data begins to tell a story – it gives us a baseline for risk and allows us to identify if and when the risk level elevates.
One challenge though, is collecting and analyzing these large volumes of data in a way that creates useful insights. Another challenge is accomplishing it in a way that supports data privacy for employees and their information.
One path to a solution that manages collective employee data, safeguards privacy and alerts to risk factors is to leverage AI and machine learning-driven technology. Since the pandemic, enterprise SaaS platforms have begun to emerge that provide location and proximity monitoring, contact tracing advanced privacy and notifications of risk. Combined with an employee mobile app, this type of solution enables full enterprise risk management.
It’s important to note that these are different from large-scale government contact tracing programs or apps. Unlike those broad solutions, business-focused risk mitigation solutions are designed to be used within a business with one or more locations and are restricted to employees or third parties who opt-in. Similarly, contact tracing and location data can be limited to areas within the office, campus, manufacturing facility, cafeteria or other workplace locations, ensuring that locations visited outside of work are not tracked.
An effective approach to creating a risk assessment dashboard must use anonymized and secured employee data. A platform or dashboard should not collect and store data in a centralized database. Instead, contact tracing data should remain with the employee on their device, unless the employee explicitly shares the data with the employer. This allows for collection of important data but safeguards employee privacy.
Only if the risk factors indicate concern, would an employee share their data with their employer. With the data, an employer would then have clear direction on areas of the workplace that may require further sanitization and would be able to notify employees within the radius of the employee in question that the risk has been elevated. An effective platform would support this action without sharing the identity or status of the original at-risk employee with any employees outside of the HR function.
Risk Monitoring, Risk Mitigation
In theory, simply having an employee wellness and risk monitoring platform in place can reduce an organization’s liability. It indicates a proactive effort to manage wellness and safeguard employees if risks are elevated.
But organizations must also have the processes in place to support such as platform as well. For example, organizations must have the proper employee training and education in place. A new role for HR may now be to help employees understand the benefits of an employee wellness system and ensuring its proper use. Employees must be comfortable with a system in order to accept and use it properly, otherwise the resulting data could have less impact on potential risk scores.
For employees to feel secure in their data, it’s also important for them to understand that Bluetooth, rolling proximity identifiers (RPIDs), encryption, and tokens are designed to maintain privacy and security at the highest level for any system that asks for employee health data.
For managers, having a dedicated leader to oversee and engage with the platform is also key. In many cases, an employee wellness and risk monitoring platform is integrated with other enterprise software systems such as human capital management, risk and liability, CRM platforms and more. Having a plan to deploy, maintain, train and manage oversight of a platform and disseminate information in a respectful and risk-mitigating way is key to success.
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About The Authors
Mike Magnifico is a partner and CTO at Liberty Advisor Group. Mike has 19 years of consulting and operations experience with an emphasis on digital transformation strategies, supply chain optimization, ERP readiness, and M&A divestitures and integrations. Mike joined Liberty to be an advisor to senior executives and their organizations by applying his expertise and insight to assist them in making the best informed strategic decisions.
Gopal Parvathaneni is CEO of EPSoft Technologies, a global software company that leverages intelligent AI, machine learning, automation, and big data to optimize critical business processes. He is co-founder of Virtual PPE, an employee wellness and risk mitigation platform to help businesses during the pandemic.