The President’s (not too) recent State of the Union Address finally has me thinking, so a post. The crux of his narrative was about the state of the U.S. economy and what needs to be done. Part of the issue, or course, is the ever-lingering problem we all face regarding high unemployment.

Statistics are the “science” of what I do for a living. Some revere the practice, others abhor its positivistic tenets, and others just scratch their heads and nod.  

When speaking about out-of-work Americans, both we the people and the President zero in on statistics as a quick benchmark to gauge how bad (or good) things are nowadays. Specifically, that statistic is the percent of Americans unemployed within a particular period of time. This is the heuristic we all use: Obama, economists, cab drivers, Oprah. Yet, we all mutter under our breath that it’s not a “true measure” of those unemployed, and underneath we’ve been taught since our youth that “statistics lie” and “can be manipulated.” Maybe so.

Yet, often when my clients, the President and the rest of us focus on unemployment, we commit a classic boo-boo in the realm of statistics, by focusing on the  incorrect statistic when explaining a phenomena. Statistics don’t “lie,” they can’t, they’re just dumb numbers. It’s people’s misperception and subsequent misinterpretation of their respective findings that are off the mark. For example, what matters when speaking about those out of work is to in fact assess those that are employed.

The employed-to-population number is a ratio, or statistic, of those in the U.S. over 16 years of age or older who are not in the Armed Forces, or in institutions (e.g. VA, nursing homes, prisons). That statistic now stands at 58.3%. Hence, just a bit more than half of us are working. That’s it! The interpretation of 58.3% working is a heck of a lot different that an unemployment rate of about nine percent. Neither number lies. And theoretically, they’re examining the same phenomena.

The moral of this rant: don’t obsess about the statistic presented to you. Instead, ask first what you want to measure. Or as Chuck D. say’s: “don’t believe the hype!”

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