Are You Recruiting for Data Analytics Correctly?
A report by the professional services firm Deloitte indicates probably not. It says, “Companies are struggling at almost every level of analytics recruiting today. The team approach makes sense, but it assumes there are enough people to hire in a wide range of analytics-related roles.
“That’s not the case. Even as universities create many more analysts, it will be years before they enter the labor force and become effective. Great data scientists also rely on their past experience, and getting these new graduates to that point will take some time.”
Deloitte offers this advice, “When you’re recruiting analytical people, be clear what your needs are. Just saying you need a data scientist is like advertising a slot for a smart person who’s good with numbers.”
Wantedanalytics.com reports that the demand in Connecticut and the New York metropolitan region is among the highest in the country for these positions. The U.S. Bureau of Labor Statistics lists salaries for management analysts at an average of $87,250 in its most recent report, which is from 2011.
Also Deloitte advises against over hiring in the employment market for the position. “Some of the current talent crunch is a function of hoarding, not real demand. In response to predictions about impending shortages of qualified analysts, companies scrambled to recruit talent beyond what they actually needed. This led to experienced people being asked to carry out activities like straightforward reporting that could have been done with lower-level talent. It also led to lower-level talent doing busywork—e.g., cleaning data—that is better done by machines.”
Human resources professionals with data analytic skills may be important to recruit, too, in the opinion of Alec Levenson, senior research scientist at the Center for Effective Organizations at University of Southern California’s Marshall School of Business. He said in an interview posted on the school’s website, “The basic problem in organizations today is that companies make HR decisions—work design, training programs, skill development, compensation design—that involve hundreds of millions of dollars of expenditure that often have no scientific basis behind them.”
Levenson added, “There is growing interest in evidence-based management—making decisions about people and processes based on scientific evidence, not heuristics. The problem is that talk is cheap and evidence is hard to come by. Careful scientific evaluation can be expensive and time consuming to gather, so in the vast majority of cases HR decisions are based on common practices—what other companies are doing—and/or the gut feel of senior executives.
“Yet when companies do take the time to carefully evaluate their HR decisions, they often find that the factors impacting employee motivation and productivity are different than key stakeholders often assume is the case.”
The researcher said companies are doing these evaluations in-house by building dedicated HR analytics groups. “They are staffing them with combinations of HR professionals who are more analytically inclined and business savvy, and with people who have advanced analytical training,” he said.
Levenson conceded that this isn’t always going to be possible for organizations to do. “Not all companies can afford to build big analytics groups – and even the ones that do cannot staff so deeply that they can address all topics that come up. So there is a growing demand for external experts to provide analytics help on people and process issues,” he said.