In the time spent diving into performance measures recently, I’ve learned that what you don’t count is as impactful as what you do. The cool kids are often overheard saying, “you get what you measure.” And, it’s so true!
We all live with—often subconsciously—this powerful behavioral driver that is rooted in key performance measures. We adjust our priorities, actions, and attitudes to align with what we think management wants (as interpreted by preparing their monthly reports). This is the whole point of performance measures, right? Organizations clearly articulate what’s important and, in turn, staff gradually align their behaviors over time to create those outcomes. Perfect symmetry.
Unfortunately, many organizations have learned too late that there are unintended consequences associated with certain measures. For example, a focus on reducing processing time can drive down customer service, an emphasis on entering volumes of data can lead to entry errors, or INSERT YOUR OWN ORGANIZATION'S INTENDED VS. ACTUAL OUTCOME HERE.
In fact, I read an article earlier today highlighting some best practices at Zappos. As many of you know, I'm a fan and all too frequent customer. (On a related note, I'll share more next week on my much-needed efforts to streamline my closet.) Anyhoo, Zappos is well regarded for their commitment and success in customer service. As someone who's logged some time chatting with their reps at 11pm, I can attest personally to their fantastic-ness. So, it surprised me a little—mostly because I’d never thought about it before-- that Zappos doesn't measure call volume or duration for their customer service reps. In fact, they do the opposite. Their stated goal is to increase positive customer contact. They actually reward staff for having meaningful exchanges with customers-- regardless of how long the call took. Huh. More expensive but worth it.
All of this is a long way of saying, when you look at your measures-- think through the likely behavioral impacts then weed out the ones that you think could result in short changing customers (in the name of greater productivity) or data errors (in the name of faster data entry).