If you haven't liked the monitoring and measurements to say nothing of the resulting coaching sessions, better brace yourself. It's all going to get much worse thanks to a set of technologies collectively called Big Data. Companies are trying to massage buckets of information to find out how to operate more effectively, efficiently and cheaply. And the data mining and number crunching probably have you in the crosshairs. Fortunately, time may be on your side.
As The Atlantic points out, a great analogy is the book "Moneyball" that describes how the Oakland Athletics under general manager Billy Beane and Harvard economics grad Paul DePodesta used statistics to pick its ball players. The team's record was matched only by the Yankees, which had spent three times as much on talent.
What made the numerical approach work so effectively is that few had paid attention to the mass of player data available in baseball. Scouts and managers who traditionally chose team rosters based decisions on gut feelings and assumptions they had learned as they came up in the game. But close analysis showed that certain types of traits and skills ignored by the "experts" better predicted who would win.
It was an early example of so-called Big Data, which allows organizations and PhDs in math to rummage through mountains of information. They look for patterns that help in making decisions and possibly predict what the outcomes of particular actions and choices would be. The techniques have been put to use in picking stocks and better targeting online ads to your browsing habits.
Now Big Data is being turned to such questions as who are the best people to hire for particular positions and how much should they be paid. As the Atlantic says, it's in part a reaction to the seat-of-the-pants approach to hiring that so many companies have developed when it turned out that "scientific" psychological testing used for years was ultimately useless.
Like baseball, companies don't know why some people do better than others or what a business can do to improve staff performance, as consultant Josh Bersin wrote at Forbes.com. As an example, one of his clients in financial services thought the best performers were those people who got good grades at well-known schools.
After analyzing performance and turnover, the company found a number of factors that did correlate to good performers, including getting some degree from college, experience in selling cars or real-estate, time management skills, and no typos or grammatical errors on their resumes. What didn't matter? Good grades or the school they went to.
That's why many companies have decided to use that data to build profiles of what people work best for them, signs that someone will be a superior employee versus an ordinary one, models of how to structure compensation to get the best performance at the lowest cost, and so on.
For the last 30 years we have captured demographic information, performance information, educational history, job location, and many other factors about our employees. Are we using this data scientifically to make people decisions? Not yet.
As Outsource Magazine wrote: "We are coming into a dream world where ... HR data can now join the big league of information that has the ability to enable true innovation in business."
The danger, according to candidate selection expert Dr. Wendell Williams in an interview with the Chicago Tribune, is that past performance can be an unreliable tease. There is often no way to tell exactly what caused improved performance. "Somewhat like discovering shark attacks are correlated with ice-cream sales at a beach, they both might happen in the same season, but one does not cause the other," Williams said. Job seekers and employees could find themselves embraced or written off because they were in the right or wrong place.
But don't despair, because it's unclear how long it might take before companies actually implement these techniques. As Bersin also wrote, a study his firm did on 480 large companies found that only 4 percent can perform the analytics necessary to make Big Data work in hiring. By the time most get around to it, you might find you've already retired.