Not all of us may have seen the movie Moneyball, and probably fewer of us have read the book. But if you ask anybody, they’ve most likely at least heard of Oakland A’s general manager Billy Beane’s theory that things like on-base percentage and run productivity are valued over factors like speed and ball contact. He found that traditional baseball valuing measurements to draft and trade for players were highly subjective in nature, and that there had to be a more objective way of assessing a ball player’s current and future value to a team. It’s begun to slowly change the game of baseball, and now we’re seeing it creep into the general world of employment, too. How? Read on to find out what it looks like, and how you can bend it to suit you.
People Analytics: Going Back Decades
The essential concept of Moneyball isn’t a particularly new one, as employers have previously tried to ascertain which of their employees are going to be reliably bright and well-performing in the long run, and tried to come up with ways to predict this behavior. Typically, they would start with their already stellar employees and analyze them. They’d aggregate important information from this cream of the crop by looking at patterns in biographical data, working history, and how the employees answered computerized personality and intelligence tests. From there, they’d use these scores as a sort of benchmark for future employees, The employees that would make it onto the next level would be the ones whose scores mostly closely matched the already-employed “stars”.
It sounds like a fairly logical and efficient system. And it would be, if not for the fact that these computerized personality and intelligence tests aren’t the most accurate way of measuring a person’s intelligence, drive and performance. Like standardized IQ tests, the tests administered by these companies had one major flaw: they scored how cleverly employees could take the tests, and cleverness isn’t always or necessarily an indication of intelligence or performance. Further, these tests had a large degree of subjectivity attached to them, as the results were reliant on how the managers rated their employees’ results, instead of an objective system that could classify everyone equally.
Something else was needed.
Moneyball for the Workforce
Like Beane’s preference for using objective stats like on-base percentage and run productivity, employers have begun doing the same, adopting their own objective metrics that can predict which prospective employees can shine better than the rest. Some of the points they measure include:
How long they’ve been on the job
How many calls they process
How many sales they close
One of the most important things to keep in mind about the employee version of Moneyball
is that it doesn’t so matter what employees answer, but how
they answer. Plus, employers also look at the following on the tests they give their employees:
How long it takes them to answer each question
If their answers are fairly in line with the answers they’ve given before, or if there’s a big variation.
The vocabulary they display when it comes to answering open-ended questions.
Companies have also found that one set of answers doesn’t necessarily equate to the same predictive results across jobs, such as leadership in community groups being a good sign for acute nursing positions but not nearly the case for nursing home employees. Another example, something that may seem completely innocuous and unrelated to the job at hand, is the internet browser someone uses: an employee-screening company called Evolv takes into account factors that look at creativity versus persuasiveness, using data points like these:
The distance of someone’s commute.
The choice of their internet browser, such as opting for the factory-installed browser or upgrading to a better one like Chrome or Firefox.
What social media sites they use, and how many of the sites they frequent.
How they rank rapport with customers, and what that means to them.
Has This Actually Been Successful?
It’s a bit difficult to answer this question, as it really depends on what your definition of success entails. If it’s first-year employee turnover, then adapting Moneyball to your business or yourself most definitely works. Pegged Software, a program available to businesses to measure their employees’ value, has found that their clients have cut first-year employee turnover by at least 50%, which is a huge financial savings for them. When you factor in places like hospitals or banks, workplaces where employees require a high level of education and training, the savings from not replacing employees after the first year run $15,000 to $50,000 each. This is a resounding yes to the question of whether or not Moneyball-style metrics works.
However, critics of this way of evaluating performance say that it can lead to cookie-cutter employees where one type of personality is seen throughout. While it’s okay at jobs where only one kind of performance result is needed — such as at call centers — this works splendidly. But at workforces where individual personalities and quirts are needed, such as those requiring teamwork, creativity and judgment, this has the potential to backfire. It can be fairly difficult to get stellar results when most or all employees think and work the same way, displaying the same strengths and weaknesses.
But if you’re looking to impress your prospective manager, then bring these points up in the interview. Talk about yourself in ways that are directly related to the job you’re applying for, such as mentioning how you increased the number of sales you closed within a six-month period, or the number of sales you closed in relation to others. Because employers are human, it’ll be hard — if not impossible — to ignore that “gut feeling”, but it’ll also be difficult to ignore hard facts and data that point to you making a tangible and positive difference in the workplace.