The Moneyball Approach to Hiring

The 2003 Michael Lewis book, Moneyball—and the 2011 film of the same name—demonstrated a unique approach to hiring: using data to build a team. When it comes to hiring the right people, the Moneyball approach requires more legwork, but it can pay off handsomely in the long run. But before you implement the strategy in your business, it is important to understand the risks and benefits.

In Moneyball, the manager of the Oakland Athletics baseball team turns the traditional baseball hiring strategy on its head. Instead of using subjective information like personality and sportsmanship, he uses the players' stats to build a well-rounded, high-performing team. By focusing on the objective data, he all but removed the human element from the process.

For human resources professionals, hiring the right people is a constant challenge. By using a Moneyball-style hiring strategy, you can use predictive data to find people who will help your team perform to the best of its ability. In doing so, you can remove or reduce the impact of the natural biases and patterns embedded in your organization.

In many companies, hiring has been done the same way for years. If your company has not experienced significant growth or performance improvement, your hiring methods may be flawed. In many cases, the problem lies in the human element of the hiring process. A CEO who makes hiring decisions based on intuition or an existing belief system, for example, may not realize that her gut feeling is not leading the company in the right direction.

By using a data-driven approach to hiring the right people, a company can use predictors of high performance to find candidates who will best complement the existing team. The specific predictors will vary by company and industry; in many cases, you will need to make an initial investment to hire a data-analysis service to make statistical correlations between the behaviors, traits, and experience of your current employees and their performance on the job.

Some predictors may be surprising. According to a recent story from Harvard Business Review, predictors involved in hiring the right people may include the applicant's preferred Internet browser and the distance between home and the office. Though it may seem impersonal and counterintuitive, numerous companies, including Apple and Google, have jumped on the data-driven hiring bandwagon, indicating that it may be the way of the future.

Once you have established statistical predictors, you can apply them to the hiring process. Instead of using a rigorous interview process as a part of hiring the right people, you would collect data on each candidate based on public records, application information, and pre-employment screening tests. Using that data will help you predict which applicants will best fit in with your team.

Although data-based hiring is currently most cost-effective in large companies, signs indicate that it is likely to grow in popularity. By keeping an eye on data-analysis prices, you can adopt big-data strategies when the time is right for your company and make hiring the right people easier and more effective.

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