With the rise of big data and HR analytics, the demand for analytical skills in the workforce has increased substantially. According to a 2013 global study by the American Management Association and the Institute for Corporate Productivity, 58 percent of business leaders say analytics is a vital part of their organization today, and 82 percent of business leaders say they expect analytics to be a big part of their organization in five years.
While the era of big data may have arrived, the analytical skills that organizations need to interpret and use complex data have not kept pace, the research suggests. It is no longer enough for an organization to have a few experts able to analyze data. Ultimately, to take advantage of the vast potential of people analytics, organizations have to become data smart.
The challenge is pressing. Much like financiers and marketers use data to forecast future earnings and measure consumer habits, talent leaders can now use people analytics as an important driver of corporate decision-making. Like other functions’ use of data, people analytics improves an organization’s ability to predict risks, adapt to change, make informed decisions and compete in today’s business environment.
As a result, the skills needed to understand data are not just quantitative; they must also enable employees to gather and analyze information, formulate plans and solve complex issues. In essence, employees need fact-based analytical skills such as critical thinking, problem-solving and decision-making.
Lack of resources and corporate culture are the biggest impediments to an organization’s ability to build analytical capacity, according to the 2013 i4cp study, “Conquering Big Data — A Study of Analytical Skills in the Workforce” (Figure 1).
Jay Jamrog, vice president of research at i4cp, said many companies are producing and collecting data, but they lack the skills to turn it into actionable information. “A good predictor of whether employees will be able to leverage data is the organization’s analytical culture,” Jamrog said.
To achieve peak performance in data analytics, organizations would be wise to devote more resources to creating an analytical culture. For many companies, this is not so much a question of skills as it is an across-the-board culture change. This kind of change can be created by investing in training and development to build analytics skills, but there are also other tools companies can use that stretch beyond skill building to help create an analytics culture.
Storytelling, for instance, can play a role in influencing cultural shift. “While not everyone is comfortable crunching numbers, most employees can relate to a good story,” Jamrog said. He recommends organizations identify and use situations in which a department has gathered and analyzed data properly, asked the right questions and formulated an action plan. Leaders can then share the positive effect the plan had on the organization through internal communication channels such as town hall meetings, employee newsletters and blogs. They can also be used as case studies in employee training programs.
“Sharing these success stories can help managers get over the fear of big data and can do more to change the culture than only developing the analytical skills,” Jamrog said.
Talent Segments to Develop
Midlevel managers: Efforts to build analytical skills will pay off when development focuses on the midlevels of management, both in the short term and as managers advance in the organization.
The AMA/i4cp study probed the perceived skills of different management cohorts and found that senior executives and functional experts are thought to have the most highly developed analytical skills. At the same time, the broad midlevels of today’s organizations still have way to go (Figure 2).
The need to build analytics skills in middle management is further supported by a June 2011 McKinsey Global Institute paper. It predicts “a need for 1.5 million additional managers and analysts in the U.S. who can ask the right questions and consume the results of the analysis of big data effectively.”
The paper continued: “This gap cannot be filled by simply changing graduate requirements and waiting for people to graduate with more skills or by importing talent. It will be necessary to retrain a significant amount of the talent in place; fortunately, this level of training does not require years of dedicated study.”
Millennials: When assessed by generation, the i4cp/AMA study found that millennials are the least analytically equipped. In fact, according to the study, nearly 20 percent of millennials are perceived to lack analytical skills. Meanwhile, 58 percent of Gen X is perceived as advanced in analytical skills, as are 41 percent of baby boomers. Just 35 percent of millennials are perceived as advanced in analytical skills, according to the study (Figure 3).
Despite their familiarity with technology, millennials are not seen as having adequate analytics skills. As i4cp research suggests, what is really at issue is an analytical mindset, which includes both quantitative and qualitative ability. In other words, employees need to know what to look for, what questions to ask and how to make inferences to draw conclusions based on data.
HR and sales professionals: Analytical capability by job function was also addressed in the study (Figure 4). It showed that HR and sales were perceived as the functions lagging the most in the skill area. On the other hand, 58 percent of employees in finance were perceived as advanced in analytical skills, followed by the executive team, at 51 percent.
According to Jamrog, one of the issues facing HR is that data may not be readily accessible in one place because of disparate systems. “Some data may be in the compensation or finance department; other data may be in an HR system or a performance management system,” he said.
Additionally, HR may not have adequate resources or as much experience in data analysis as other departments.
“HR has had a hard time telling a story with data,” Jamrog said. “They haven’t really learned that discipline to the same degree that marketing and finance has. They are proficient at reporting efficiency data, but it’s a shift for many of them to tell a story with data around effectiveness and impact.”
For talent management professionals, Jamrog suggests exploring the data surrounding just one talent segment core to the organization. “I would first want to know who are my current high performers,” he said. “Then, I would conduct research to answer some key questions: Why are they high performers? Where did I recruit them? How were they onboarded? What training did we provide them? What kind of supervisor do they have? Start by collecting the different data points and see if they tell a story.”
Strategies to Build Analytical Acumen
Despite the need for employees with high analytical capabilities, the i4cp/AMA study found that only 26 percent of organizations said they had the ability to meet their analytics needs, while another 17 percent plan additional hiring to do so. The majority of respondents (47 percent) plan to invest in training current staff to meet their capabilities gaps.
Although there’s evidence that organizations have awakened to their shortcomings when it comes to data analytics, for HR and talent managers a steep road is ahead. In light of this, many organizations are creating strategies in an effort to identify the key skills and competencies needed to properly apply data analysis to the HR function.
As a result, HR and talent managers have begun to ramp up training and development investments to meet that demand. Among the strategies being used: They’re imparting data analytics skills through formal training programs and informal peer-to-peer exchanges, and they’re using cross-functional projects and job-rotation programs that allow less-experienced employees to work alongside colleagues who are proficient in the subject area.
Of course, to conquer big data, organizations must first learn to embrace it. If they are to maximize its full potential, the immediate task is to figure out what questions to ask, what skills their employees need to learn and how to provide them with those skills to meet the demands of the fast-moving, information-heavy business environment.
Once these critical data analytics skills are mastered, organizations will wonder why they ever made decisions without them.
To learn more about the obstacles to the effective usage of big data, read the sidebar to this feature here.