Employee Tracking: Bank of America case
Before going to this case, I am a huge fan of well-illustrated science-fiction films. What I could not imagine, it was I will end up providing creative ideas to a big corporation, helping them grow ethically (of course). So let's start with a little bit of context.
Employee Monitoring & Bank of America
Employee Monitoring has been around even before Snowden was born. Today we went from simple cameras to real IoT sensor data insights. It might sound privacy-intrusive, but with the Internet of Things era it can evolve from people surveillance to business and workspaces enablement.
Hold on! Why? I tell you why: because of productivity and efficacy. It is well known, maybe not in your company yet, we are changing the way we work and interact with our peers. We are moving from pressure methodology work environment to a self-motivation and team-building culture. Companies today are looking to open unprecedented technology capabilities allowing people managers & individual contributors to thriving in their workspace.
From an experiment to real application
Let me start with a short story. In 2013, A company specialized in sociometry solutions (same name Sociometric Solutions no creativity at all) created tracking sensors for one of the most important banks in the world: Bank of America. This tracking tech company based this model in a previous experiment where they studied students from the Massachusetts Institute of Technology — collecting real-time data from students speaking speed, tone of voice, volume, gestures, and body posture... How is this applicable to a work environment? Where were they going to track this data for our lovely bank? From IoT sensors built-in employees’ IDs.
The objective was clear, boost efficiency. Analyzing when productivity reaches high peak levels to enable future strategies and plans. Plans that could allow them to maximize or keep high-performance employee levels. IoT employee tracking could be done in a way that brings valuable insights to people leaders. We do not need to use hard unfashioned control measures that can bring employee discomfort or lack of trust — no need to record conversations or associate any metadata with employees. Consequently, they could make this process fully legit.
Sociometric sensors were composed of a microphone, a motion sensor, an infrared beam, and a Bluetooth device. They allowed measuring the amount of emotion in the conversation due to voice pitch and speed. They identified other IDs and body posture of speakers to gather communication-related insights from infrared beams. An excellent example of it was when listeners were following the speaker while he was dominating the conversation, speakers mirroring each other or they were on equal terms.
Even if it looks like a chapter of Black Mirror, the idea behind was not the control of the population it was to help to map our socializing patterns and connect them to unlock and enable productivity.