The return to the office is fraught with many challenges for employers. Unlike the NBA or NHL, the vast majority of offices cannot isolate within a “bubble,” so companies must plan for the new normal of working around COVID-19. The most effective way for employers to avoid a breakout is by utilizing effective PPE and social distancing measures. These measures include mandatory mask use in the office, increased desk separation, and rotational in-office schedules.

Beyond PPE and social distancing, there will be a demand for health testing and contact tracing. Both of these preventative measures will require robust data capabilities in order to process the massive influx of employee data. In addition, companies will need to focus on data governance to properly manage the sensitive health information that is collected.

As the country moves back into the office, employers must strike a delicate balance between staying informed of health risks and maintaining employee privacy. Let’s first dive into the need for and benefits of employee testing and how data analytics can improve office safety.

What can be gained?

The success of employee diagnostic testing in the office will require a robust data strategy to rapidly and accurately process the influx of new information. Data analytics will be necessary to intake employee data and return the results in a clear, understandable manner.

The gains from these insights are invaluable due to the speed of transmission of COVID-19. If an employee is showing symptoms of the virus, it is necessary to identify the sick individual as fast and as accurately as possible to maintain a safe work environment.

At a higher level than diagnostic testing, contact tracing can identify possibly infected employees before they show symptoms. Through geolocation data, contact tracing analysis can follow an infected individual’s path outside of the office and determine who they may have infected. Conversely, contact tracing from another firm can inform an employer whether their staff has been exposed to the virus.

Geolocation through cellular data dramatically increases the amount of information that needs to be processed in order to maintain a safe working environment. The vast web of human interaction is extremely challenging to accurately map. Millions of data points must be synthesized to assess whether an employee has been exposed to the virus. Again, the necessity for speed of reporting is vital because an employee could unwittingly be spreading COVID-19 around the workplace in a matter of days after being exposed.

With these higher-level data challenges comes higher-level data insights and safety precautions. Because COVID-19 is able to be passed through asymptomatic transmission, temperature and other diagnostic checks are unable to catch a large number of cases that could possibly infect a workforce. So being able to identify employees who have come in contact with the virus is incredibly effective in proactively limiting risk. By tracking diagnostic and geolocation data, companies will be able to transition to in-office work in a relatively safe manner, but the entire process relies on robust data capabilities.

Counterbalance of data governance

While acquiring worker diagnostic and geolocation data can help maintain a safe work environment, the process is also extremely invasive of individual privacy. Data governance is a key counterbalance that must be employed by companies to ensure a successful transition back to the office.

Here are the key factors that companies must focus on to strike a balance between strong data usage and responsible data governance:

  • Clear communication: A basic channel of communication is important at every step in this process but establishing a discourse early is just as vital. There needs to be a clear understanding from employees on what specific data is being collected and why it is being gathered. Releasing health and geolocation data with an employer cannot be blindly accepted in a “Terms & Conditions” page but rather with full transparency.
  • Positive framing: In addition to a basic knowledge of the data being gathered, employers should also clearly spell out the costs and benefits of the program. As has been seen with mask adoption, the more a non-adopter feels talked-down-to the more entrenched in their beliefs they become. An implementation process that focuses on positive benefits rather than sacrifices or personal responsibility is key to avoiding issues.
  • Security: The large influx of health and geolocation data could become overwhelming and rife for exploitation. A reliable data analytics package is key to safe intake and encryption of data throughout the reporting process. This step seems the most basic and likely the most salient form of data governance but presents the most technically demanding challenge.
  • Data retention schedules: To proactively avoid data theft and put employees’ minds at ease, a company should state a clear time period after which the information will be destroyed. The length of time needs to take into account the incubation and infectious periods, which could range anywhere from 24-34 days. This estimate, however rough, is indicative of the need to develop a robust data security program. The data on employees’ health and location remains insightful for more than a month.

 

In order to effectively manage the transition back into the workplace, employers must find an equilibrium between strong data capabilities and trustworthy data governance. A successful dance between these two factors must utilize strong data analytics to increase safety and peace of mind in the office.

 

Teddy Craven