It’s no secret that we are a society that is obsessed with numbers. From the best-selling Freakonomics to the popular New York Times blog of Nate Silver (who first achieved prominence by employing polling data and voting behavior to interpret the nation’s political climate), there is an ever-increasing focus on using quantitative tools to try to make sense of our world.
In the business arena, metrics have been employed since the advent of the factory, as engineers have long sought to improve operational efficiency in tasks geared around machines. “It’s about getting the product out the door and making sure quality is good, unit cost is low, rework is low — all non-human issues,” says Dr. Jack Fitz-Enz, a pioneer in the world of human resources metrics. “Only recently do they see that people are a critical element in the process. People are the critical variables because people make every decision and people take every action; even if it’s turning on or off a critical valve. It’s a human decision that takes place. Keep in mind that capital-intensive businesses are principally run by engineers. What is the value system of an engineer? It’s not human value.”
Even so, the engineering community has traditionally been at the vanguard of using metrics to evaluate performance, owing to its mathematical background and education. In contrast, human resource managers have historically been far more reluctant to employ quantitative tools to assess the performance of clerical staff and other white-collar workers.
However, that stance is evolving out of necessity, according to Vincent Suppa, instructor for NYU’s Leadership and Human Capital Management graduate program. “In the past, many people went into HR specifically because they had the soft skills that they felt would make them successful.” Often, these people had no statistical background and some even feared trying to develop those skill sets. “I still get students telling me that they went into HR because they like people, and while that is important, frankly, it's not enough to stay relevant in the marketplace,” Suppa continues.
Being good with people was never the best approach to HR, Suppa says. “You cannot manage what you cannot measure,” he says. “People have fought against metrics in the past because quite frankly, it brings failure to the light of day. It is only with benchmarking that we can measure our performance against our competitors and even ourselves over time. Without quantitative measurements, not only do the qualitative decisions HR makes become less relevant, but it's nearly impossible to articulate to the C-suite why they should even care about what we are doing. At the academic level, there has been a lot of catch-up as institutions have been very reactive in trying to meet these needs.”
How has this shift impacted the contingent labor market? Joan Davison, president and chief operating officer of Staff Management/SMX, believes the industry is poised to take advantage of the findings that metrics can offer, saying contingent workforce managers continue to become more sophisticated as the contingent workforce management space matures. “Given the variety and shorter duration and lead time for contingent assignments, we must track and analyze workforce statistics frequently,” Davison says. “A contingent worker can be placed on multiple assignments in a year, so we need to understand their performance and qualifications in real time to make effective reassignment decisions.”
Davison says Staff Management monitors forecasts and key statistics by client — everything from time to hire, to hiring manager satisfaction, to training certification and safety records. Such access to data can enable companies to identify and correct problems proactively, she says. “For instance, in the past when a supplier had high turnover in a particular position or department, they were deemed a failure. Today, with the data available, we may find that there is an environmental issue in the department that needs to be addressed or that the job description needs refinement.”
However, Davison adds that for larger firms like hers, it’s not absolutely imperative that each HR manager be well-versed in the application of quantitative tools. “Providing central support for specialized functions such as analytics, candidate sourcing, project management and training is more effective than trying to hire one person to wear all of those hats. So, while analytical thinking is a key dimension for many of our positions, we leave the in-depth financial, market and trend analysis to our centralized analyst team.”
Certainly, the next generation of HR managers in the staffing world won’t be required to re-invent the wheel when it comes to data analysis. But it’s clear that the bar for quantitative skills has certainly been raised, and that the ability to interpret and apply the findings of metrics will become increasingly invaluable as time progresses.
KJ Fullam is a freelance writer based in Chicago.