I wish more managers would be clear with themselves about what they’re trying to achieve with monitoring. A clear and defendable goal is identifying employees who barely work in hard-to-monitor roles. For example, I’ve seen cases where giving salespeople company cars equipped with GPS reveals a handful who are working multiple jobs or just mailing it in. I’ve also gotten very crude application usage data to confirm or refute an instinct that a remote worker isn’t fully engaged.
More often, though, I’ve seen the goal as addressing an executive’s fear that “we’re getting screwed by remote workers who aren’t fully engaged.” If the goal was more positive and precise — can we find a way to boost productivity of a critical role by 5%, for example — maybe it’s worth analyzing meeting data to find and release unproductive meeting time. But when it’s to prevent fear of loss, the tendency is to grab for activity data like the Wells Fargo example that don’t actually predict productivity.
I just think that using many of these tools to find employees that are not productive is a losing proposition. You will find one or two that are not productive, but you will more likely than not alienate those who are productive, and now divert the attention of everyone to "hack" the one metric you measure.
I wish more managers would be clear with themselves about what they’re trying to achieve with monitoring. A clear and defendable goal is identifying employees who barely work in hard-to-monitor roles. For example, I’ve seen cases where giving salespeople company cars equipped with GPS reveals a handful who are working multiple jobs or just mailing it in. I’ve also gotten very crude application usage data to confirm or refute an instinct that a remote worker isn’t fully engaged.
More often, though, I’ve seen the goal as addressing an executive’s fear that “we’re getting screwed by remote workers who aren’t fully engaged.” If the goal was more positive and precise — can we find a way to boost productivity of a critical role by 5%, for example — maybe it’s worth analyzing meeting data to find and release unproductive meeting time. But when it’s to prevent fear of loss, the tendency is to grab for activity data like the Wells Fargo example that don’t actually predict productivity.
I just think that using many of these tools to find employees that are not productive is a losing proposition. You will find one or two that are not productive, but you will more likely than not alienate those who are productive, and now divert the attention of everyone to "hack" the one metric you measure.