Electronic Performance Monitoring: When Good Intentions Turn to Digital Hammers
Electronic performance monitoring tools (let’s call them EPMs) are becoming more prevalent in the workplace. The transportation sector seems to be leading the pack at the moment. Dr. Ron Knipling and I discussed these tools several years ago in a PM e-zine article. In the last year alone I have encountered these systems in railroads, trucking and bus transit companies. They range from blackbox technologies storing several parameters of performance, to devices that store GPS and performance data, and record photographs or videos of operators engaged in work tasks when some pre-designated trigger occurs (such as hard braking by a vehicle driver).
Positive improvements to driver behavior are often touted as one of the benefits, as in this quote from a vendor website describing one such system: “Improved driver behavior can be immediate, as the system emits an audio beep to alert the operator of a harsh braking or rapid acceleration event.” At first glance, it seems to be great news to all of us interested in shaping behaviors key to business safety and success, particularly given that so much performance data can be stored or even examined in real-time. But there is a huge caveat: how are the data used? Here are two contrasting examples based on what I have witnessed as well as experienced:
Example 1: An EPM in a transportation company was established to record driver behaviors when driver errors occur, such as harsh acceleration, high-G turns and hard stops. Digital data on the event as well as video of the event are captured and sent for scoring for the severity of the error. Reports are then sent to the manager of the offending drivers who in turn is required to meet with the driver and give feedback to them regarding the offense. How do the drivers feel about the EPM and its use? Here’s how: A maintenance manager at one location told me that 90% of the EPMs were rendered inoperable through driver sabotage! The system designed to report offending drivers is so offending to the drivers themselves that they attack the monitoring devices.
Example 2: I recently rented a Ford Fusion Hybrid (gasoline/electric) to get around town at a client site. I had never driven a hybrid and knew little about their operation. This car recorded data on my braking and fed it back to me via a digital dial and score on the dashboard called brake coach. Being new to the vehicle, I had no clue how the brake coach worked at first, but within 2 days of driving it became clear that if I braked more smoothly, I got a higher score on the brake coach indicator. And it seemed to be suggesting that such a braking pattern returned electricity to the battery, thus reducing my gasoline consumption. It quickly became reinforcing as I tried to brake more smoothly to beat my previous score. It was fun, and I used very little gas that week. I came away wishing that my personal car had this system to help me drive safer and more efficiently, not to mention save on fuel and wear and tear. In both of the above examples, the EPMs recorded driver behavior, so why would one inspire hatred and sabotage, and the other is seen as helpful and fun? Because in Example 1, the data was only used to point out what you did wrong—even if 99.9% of the time your driving was acceptable: all punishment and no opportunity for positive reinforcement. In Example 2, you could see when you scored low and when you scored high, providing valuable feedback that would likely lead you to try to beat your best score: plenty of opportunity for positive reinforcement. Example 2 provided positive reinforcement in multiple forms—seeing a high score immediately, which led to spending less money on gasoline. I didn’t even need a manager there to give me feedback. Right now, as more EPMs are coming online, employers have a choice in how to use them—as digital hammers to beat up your employees, or as tools for optimizing desired behavior that includes engaging your employees. If you’re interested in the former, expect disengagement, disgruntlement or even sabotage. If you’re interested in the latter, you must tie the systems to positive reinforcement. Be sure to use the data for positive and constructive feedback, pointing out when the operator is doing something right and providing feedback when something is wrong. Since most of the time operators are performing correctly, more of the feedback will be on what’s right, and they will see the systems as fair and helpful. They will be interested in the data, stay engaged, and work towards improving their scores. Isn’t that what you’re looking for?