Many companies are moving towards hiring practices that reduce bias. This is a trend moving in the right direction, as companies need to find who is the right fit for a job, not just who appears to be the right fit.

But what happens after the employee is hired? Unconscious bias is not limited to the hiring process.

If an employee walks into the office with a huge smile on her face and strikes up pleasant conversations at the water cooler, it is easy to perceive her as being a highly motivated and productive employee. This may lead to managers rewarding her disproportionately compared to her coworkers, leaving her coworkers dejected and disengaged.

Oli loves data, and she collects the same data for every employee of the same job type. This ensures that employees are being encouraged and rewarded in real-time in a way that does not leave it up to a manager to decide who is being truly productive and who has room for improvement.

Process mining discovers the most efficient way to do a particular task. This does not rely on the perception of individuals to fuel the insights. Oli ignores what is superficial and get straight to the heart of the matter.

The solution to bias is data. Collecting data and reporting on what is and not what appears is the first step to unraveling misconceptions regarding work, employees, and best practices.