Are you collecting the data you need to make good and informed hiring decisions? Often organizations think HR is people driven rather than data driven – for instance, you may have a gut decision about whether a potential candidate will fit with your culture or possesses the personality your customers will want to work with. I recently attended a SHRM workshop that supports how important it is to develop a data collection and analysis plan to ensure organizations are hiring the talent (and skills) truly needed to succeed.
The movie Moneyball provides a telling anecdote. The general manager for the Oakland A’s decides the best way to assemble a winning team is to do tons of data analysis on players in order to identify which characteristics are needed to get them to the world series when put all together. He analyzed all players, including players in the minor leagues to determine which skills were undervalued, what skills were complimentary to others and what salary ranges would be competitive for their ball team. He recognized that other teams were hiring elite players and offering huge salaries, thinking that a team comprised of individual “star” players would lead them to win. The result was a lot of stars being paid a ton of money with no guarantee of the team working together. The moral of the story is that if you analyze what you need over the long term and hire talent based on those results that truly complement each other, you can have a winning team that is cost effective for the organization.
At the SHRM workshop I learned how large corporations, such as Target and Enterprise Rental Car are using data mining to tailor their customer service and hiring practices. The lessons learned reminded me how all organizations can utilize their data collection and analysis efforts to be super competitive in their field (bioscience, technology, manufacturing, etc.).
The important thing is to plan, start small, and collect, collect, collect. It may take a year to determine a pattern but having a plan in place earlier rather than later will put an organization ahead of the curve quicker. Some things to take into consideration is the type of employee characteristics that succeed in your organization, why employees have exited your organization, which skill sets are resonating with serving your customers, which factors contribute to above average performance, and what above average performance means (greater sales, team collaboration, innovative ideas and contributions, excellent customer interaction). Your data needs to be as quantifiable and descriptive as possible.
As you write job descriptions, source candidates or work to motivate existing employees, you may have a cursory view of what makes for a successful employee – the important thing is to collect your own data and relate it back to your company culture, industry needs and market context.