Everywhere I look, there are numbers, and pressure to provide numbers. Fill out this survey. Fill out another for a chance to win $1000 worth of groceries. Tell us how you liked this book. Tell us how you liked your flight. Tell us how the service was at the bank. Rate your purchase.
And that’s just the beginning. The President’s popularity is down – or up. This television program will return next season because the numerical ratings are up, that other one… so long. Advertising rates are tied to ratings as well, and because the attention spans of Americans are down, negative sensational news or quick laugh or quick action entertainment get higher numbers, and higher numbers mean higher profits.
All the stock-tracking systems show continuous numbers on public companies, the stock price by the minute, the latest P/E ratio, ratings by up to a dozen or so different services. The state of the economy is measured by the numbers of GDP or inflation by the CPI numbers [or some variant thereof] or the unemployment rate… always the numbers.
Why numbers? Because for the data to be effectively aggregated and analyzed, it has to first be quantified numerically.
All these numbers convey a sense of accuracy and authenticity, but how accurate are they? And even when they are “accurate” in their own terms, do they really convey a “true” picture?
I have grave doubts. As an author, I have access to Bookscan numbers about my sales, and, according to Bookscan, their data are 75-80% accurate. According to Bookscan, I’m only making about 25-30% of what my publisher is paying me. Now, my publisher is a good publisher, with good people, but Macmillan isn’t going to pay me for books it doesn’t sell. That, I can guarantee, and a number of other authors have made the same point. For one thing, Bookscan data represents print sales in bookstores and other venues that are point of sale outlets, which Walmart and Costco aren’t. Nor are F&SF convention booksellers, and ebook data isn’t factored in. So those “authoritative” numbers aren’t nearly as accurate as Bookscan would have one believe.
Similar problems arise in education. My wife the professor also feels inundated by numbers. There’s the pressure to retain students, because the retention and graduation numbers are “solid,” but there’s no real way to measure in terms of numbers the expertise of a singer or the ability of a music teacher to teach. And the numbers from student evaluations [as shown by more than a few studies] track more closely to a professor’s likeability and easy grading than the professor’s ability to teach singing, teaching, and actual thinking. A student switches majors because they’re not suited, and even if that student graduates in another field, the major/department in which the student began is penalized with lower “retention” numbers, which, in effect, penalizes the most demanding fields, especially demanding fields that don’t reward graduates with high paying jobs.
Yet, the more I look around, the more people seem to be relying on numbers, often without understanding what those numbers represent, or don’t represent. And there’s a real problem when decisions are made by executives or administrators or politicians who don’t understand the numbers, and from what I’ve seen, all too many of them don’t understand those numbers. We see this in the environmental field, where politicians bring snowballs into Congress and claim that there can’t be global warming, or suggest that a mere one degree rise in overall world ambient temperature is insignificant [it’s anything but insignificant, but the data and the math are too detailed for a blog post].
The unemployment numbers are another good example. The latest U.S. unemployment rate is listed at 4.5%, down from 10% in October of 2009. Supposedly, a five percent unemployment rate signifies full employment. Except… this number doesn’t include the 20% of white males aged 25-54 who’ve dropped out of the labor force. Why not? Because they’re not looking for work. If you included them, the unemployment rate would be around 17%.
Yet, as a nation, in all fields, we’re relying more and more on numbers that all too many decision-makers don’t understand… and people wonder why things don’t turn out the way they thought.
Numbers are wonderful… until they’re not.