“Measure to manage” is a favorite refrain of one of the editors of the health trade publication where I work. We write about the business side of health-care practices, and what he means by that is if you don’t keep track of how you’re doing in, say, the number of new patients per month, the cost of overhead in office space and staff payroll, and the amount you’re spending on marketing, and what you’re getting in return, you won’t succeed.
Profit-and-loss statements are essential to the running of businesses, as is tracking how much new endeavors, such as new products, cost to create and sell, compared to how much you make off of the investment, but can the same be said of human “capital”?
A recent article in The Sydney Morning Herald, out of Australia, notes a trend some companies there—and undoubtedly here—are leaning toward: the tracking and predicting of employee success according to numbers. Or as the article, “Is Big Data Leading Workplace Managers Down the Wrong Path?” puts it: “Thousands of Australian companies are measuring the performance of workers in real time and relying less and less on human intuition to make decisions about who to hire and fire.”
For some job roles, such sales, a numbers-based guide to who to hire and fire might not be such a bad idea. A role like that is easily quantifiable because its main objective is to sell as much product as possible. If one salesperson consistently misses his quota, or the goal set by his managers, while the other reps consistently exceed the quota, you obviously would have reason to let the under-selling rep go.
But for other positions, such as my own, as an editor, can performance be quantified, with future success accurately predicted? On the one hand, maybe. It’s my job to get an issue of our online-only publication published once a week, on time and in good condition (meaning articles of high interest to readers, written well, and with few typos or other flaws). You could, in theory, quantify all those things. When I was in graduate school, we learned that you can assign numbers to anything in the world, and then calculate outcomes. I don’t know whether it’s still the reigning philosophy in academia, but when I was in graduate school in the late 1990s, the quantitative model was all the rage. I even did a project for a class in which I assigned numbers to responses to measure the level of religious prejudice in part of the student population.
In the case of my workplace performance, you might not even need to assign numbers—the numbers in the age of online publication are readily available. You could judge my performance by the number of clicks my articles get, the number of typos, or other errors, per page, how often I miss my publication deadline (I never have in five-and-half years, incidentally), or how many reader comments per article we get. I similarly could be judged like a TV show—how well is the product consumed, and as a result, how well can the company sell advertising against it? A minimum amount of advertising has to be sold, of course, but beyond that, how good a measure of workplace performance would those metrics be? If I wasn’t meeting my target numbers for readership and reader interaction, would it be cause to reflexively fire me, assuming the problem was me? What happens if you get rid of me, and then find the numbers stay the same, or get even worse?
What numbers don’t tell you is why they are what they are, and what you should do about it. The article notes some of the metrics companies are starting to track: word combinations used on social media, images clicked, and time spent on LinkedIn (with managers presuming the employees are job-seeking on the site). Aside from the creepiness of managers tracking where you go online—that feeling of electronic eyes looking over your shoulder—I have to question what good that information is. It’s supposed to show the employee is focused on things other than his or her work. That could be true, but it just as easily could be untrue. All those sites the employee is visiting could be tied to his or her job. You could be looking up a contact on LinkedIn you think could help with a work challenge, maybe someone you know who can answer a question none of your co-workers can answer—or time spent on social media could be for both socializing, as well as gauging the reaction of friends to a potential advertising campaign the company is considering rolling out.
Tracking numbers related to daily routine, like the number of times an employee comes in late, or how often his or her work is turned in late, or the number of times an overhaul of the work is needed, also can lead to the management equivalent of false positives. What if the employee is coming in late because she stayed up late working on a work-related project, or because she was meeting with a business contact who could help her do their job better? Or what if she just needed extra rest that morning, but because of the extra rest, will be more productive and focused later in the day?
The question of what data can tell us has come into question over the last year with the unexpected election results in the U.S. Despite all of our sophisticated numbers-based modeling, the seeming under-dog won the presidency. Similarly, the candidate famous for intuitive, rather than numbers-based, decision-making, won. So we got an unexpected result, and the “job” candidate who was “hired” was the one who appears to be less attuned to a numbers-based approach.
When making management decisions on whom to hire and fire, what role do numbers play? What numbers do you pay attention to, and how much of an intuitive approach to management is a good thing?
