Does Your Employee Survey Measure Symptoms or Causes?
By now you should be aware that I’m kind of outraged that collectively we’ve spent billions of dollars on engagement surveys over the last several years, yet we haven’t improved our engagement scores. I think the metrics are a big piece of the problem. This whole time, we’ve been gathering extensive and detailed data—but on the wrong things.
Every engagement survey I’ve seen measures symptoms or results. The answers are always rated on a scale of unfavorable to favorable. So when you’re done, you have a lot of data about what people like or don’t like about your organization, or you have data that the survey authors are telling you correlate with high engagement (favorable) or low engagement (unfavorable). Fine. There’s nothing wrong with having some data.
But here’s the deal: those data are the equivalent of taking your body temperature. A temperature of 98.6 degrees Farenheit is “favorable,” and 101 is “unfavorable.” But in what universe do we think it’s a good idea to ONLY measure the symptom, and then spend billions trying to change the symptom metrics? If you have a temperature of 101, that’s definitely unfavorable, but I’m not going to stick you in an ice bath to fix it, am I?! I’m going to gather some other data, and connect some dots, and try to identify the root cause of the problematic symptom, and then my intervention is going to focus on addressing the cause, knowing that the symptom will return to normal on its own.
We should be doing the same when it comes to engagement. Chapter 2 in our new book, the Non-Obvious Guide to Employee Engagement, is titled “How to Start Measuring the Right Things.” We give you guidance on how to start measuring the root causes of disengagement (which is more connected to patterns inside your culture than whether or not people are happy), and we even help you think through how to measure your change efforts along the way. We also talk about the dangers of benchmarking your culture and engagement data against other organizations.