Our family recently came across the book The Life-Changing Magic of Tidying Up by Marie Kondo, a best-selling life-changing book about simplifying and organizing the items in your life and physical space. Within days we discovered that many of our friends and colleagues own this book. I’d consider it a cult classic, had it not been published only 14 months ago. One key idea is that any item that doesn’t spark joy in your life should be considered clutter.
Kondo’s “joy” is a simple metric for driving your behavior, and I’m going to make the bold statement that a similar metric is needed to govern business outcomes. In more constrained contexts like “creating quality content” and “finding something with a search engine,” the concept of joy is similarly constrained, but that makes it no less important.
Here is what I propose. Instead of getting bogged down in the operational statistics—and you know what I mean: click counts, visitor engagement, download speed, screen time—we need to elevate governance initiatives by using grand subjective measures of business satisfaction. We can use surveys to collect how people are feeling about their interactions (and the systems where these interactions take place). We can ask questions like, How much of your workday is spent writing new material? How long does it take to find the appropriate template? On a scale of 0 to 10, how good is search? How confident are you that the data are 100% accurate and timely? In other words, by asking questions that might uncover pain in the business, we are actually looking for joy: joy in the process, joy in the results. I call these subjective measures joy metrics.
Before I say more, let me point out that joy metrics really do matter. They are qualitative and opinionated, but we love them, talk about them, and even assign credit or blame for them. Even if we do absolutely nothing to improve them, improvements in our “joy” numbers is a business success. After all, we are always pleased to see positive culture change, improved morale, higher engagement, and honed skills. Joy is critical.
Joy metrics are not a fantasy. They are real because they represent clearly and in human terms the kinds of business efficiencies that we are always trying to achieve. Practically, however, we need to tie them to objective measurements. Survey results are notoriously influenced by external factors, and so we need additional more-granular measures that we can calculate objectively and trust.
From our subjective joy metrics, then, we choose our most meaningful objective statistics. Here is where the operational statistics like click counts and fill rates once again matter. Take any one survey question, like How confident are you that the data are 100% accurate and timely?, and ask why the result is less than perfect. For data quality, there could be many reasons: I don’t know if the report I’m reading is the most recent. I don’t know why the report contains the numbers that it does. I’ve seen errors in past reports. The report author is inexperienced. And, I’ve never had to do this before and don’t trust myself not to make mistakes.
By understanding why we don’t have perfect business joy, we discover precisely which measurements we need to be taking. Out of context these metrics are just numbers, but when we take the time to correlate them to the features of a great business environment, they become warning signs that something is wrong.
I don’t know if the report I’m reading is the most recent. Measure how many outdated documents appear among your search results. Measure the latency of publishing process. Check the quality of your date-related metadata.
I don’t know why the report contains the numbers that it does. Calculate how many processes are properly audited. Measure the comprehensiveness of the research process. Rank the quality of data sources.
I’ve seen errors in past reports. Count errors. Identify which documents are the most error-prone. Figure out where errors come from, and track improvements.
The report author is inexperienced. Publish track records. Correlate quality with various author attributes and make that information available.
I don’t trust myself not to make mistakes. Keep score.
Our approach to governance is distinctly metrics-driven. Making decisions based on numbers are easier to support, removing the guesswork and politics out of maintenance and governance processes. Numbers are interesting, after all. But the only way to know which metrics matter is to associate them with the aspects of the business that are most important.