When office closures began in March, the crisis management team at Austin-based software engineering company, National Instruments now known as NI, huddled to create a COVID-19 crisis response team with one key objective: ensuring the safety of its 7,000+ employees.
For months, this meant helping employees adjust to their new remote-work reality. Now, with employees settled in, NI’s crisis team is looking ahead to determine when—and how—its employees can safely return to the office.
The answer is complex. NI’s employees reside all over the world. Every nation – and every state—has different restrictions. Case counts are changing daily. This all adds up to a lot of data to be considered to execute a safe, efficient return to site. For the past 18 months, NI had been exploring ways to streamline HR data.
With the new COVID-19 environment and the high stakes associated with re-opening offices, NI leadership knew it was more critical than ever to lean on a data-driven approach as the foundation for its future plans.
To assist NI’s COVID-19 crisis team in making decisions about facilities re-opening and employee safety protocols, the company is leveraging Oracle Fusion HCM Analytics to create visualizations monitoring case count and case increase percentages for critical locations.
The visualization leverages data from The New York Times and Johns Hopkins and provides easy-to-understand insights, helping HR executives determine when and how to re-open their facilities.
Workforce risk based on employee location
Now, NI’s executives and HR teams can access the solution to collaborate and make informed decisions as circumstances continue to change each day. The management team is pleased with the insights unlocked so far and they are working towards making the solution available to all managers.
Although it’s nearly impossible to predict what the world will look like even next week, NI uses Oracle Fusion HCM Analytics along with other outside factors to help make things clearer and enable its executives to make decisions based on crucial real-world data.
