People Power Through Predictive Analytics

Predictive Analytics Screen

 

In this guest column, Cecile Alper-Leroux, vice president of HCM Innovation at Ultimate Software, discusses how by working together, HR and IT can use predictive analytics to create a new workplace paradigm that recognizes people as a company’s most important asset.

By suggesting a probable future for your employees, predictive analytics gives senior executives greater confidence that their organization is headed in the appropriate direction. While many companies have incorporated predictive models in sales, finance and marketing, very few have applied the statistical techniques to their most important asset: People.

Why is this? One can surmise that HR doesn’t have the information it needs to assert a need for talent-focused analytics or IT doesn’t perceive the value of the tools. This is unfortunate, since data analytics offer the means to distinguish an organization’s high performers, analyze their and other employees’ flight risks and prescribe actions to thwart their departure.

Some HR leaders have told us they’re concerned they don’t have the technological knowledge and expertise to effectively implement, understand and use predictive models. A few have confided their worries that technology may somehow replace them in their role as the overseer of strategic talent management.

Ultimate Software's Cecile-Alper Leroux
Ultimate Software’s
Cecile-Alper Leroux

Information technology isn’t the foe of HR, however. The automation of mundane administrative tasks like payroll, performance review distribution and follow-up, and health and benefits administration has liberated HR to focus more strategically on better understanding what motivates and drives employees, and how to recruit and retain the best talent. Predictive data analytics is another positive iteration in HR’s transformation, helping HR to become more of a strategic resource to senior leaders in assessing workforce-related challenges and opportunities.

Bear in mind that there is a war for talent in the resurgent employment marketplace. Some businesses will recruit and retain the best of the best. Others will fail in this regard. Predictive data analytics vastly improves the odds of winning.

HR must convey to senior executives the need for a deeper understanding of workforce talent to shape a “people-first” culture. Predictive metrics can provide this understanding on an employee-by-employee basis. They can identify who among these employees will be tomorrow’s top performers, determine their levels of engagement and take action to ensure they remain energized by their work and the company’s mission.

It’s also up to CIOs and CTOs to argue the importance of implementing predictive talent analytics to remove subjectivity from the process of identifying and retaining high performing employees. At the same time, they must assure HR that its concerns over the use of the technology will be addressed and alleviated.

Together, HR and IT can be allies in creating a new workforce paradigm, one that perceives people as a company’s most important business asset–the nucleus of its ingenuity, innovation and competitive differentiation.

The New Workforce Paradigm

One of the greatest risks a business confronts is employee retention. Conversely, having the right people in place helps ensure their job satisfaction and productivity. The problem is ascertaining who these people are.

Employee engagement surveys snap a picture of overall engagement and employee performance reviews are frequently subjected to the capriciousness that arises when one human being assesses another. Predictive data analytics, on the other hand, offers a statistically valid means of identifying high performers driving the business forward and discerning their respective flight risks.

In making these predictions, the tools draw on an abundance of historical data and real-time information, as many as 16 million workforce-related data points, according to a study by Bersin by Deloitte. Yet, only 4 percent of companies have the ability to “predict” or “model” their workforce.

Given that emotions play a role when evaluating employee performance, it’s not uncommon for predictive modeling to be more precise than human assessment of talent risks. A case in point is a client that recently conducted a one-year comparison of the findings of our predictive models with its managers’ talent assessments. The tools suggested fewer people as high performers, predicted three times as many employees to be flight risks and identified specific high performers whom managers had not considered to be at risk of leaving the organization. Looking back over the one-year period, the analytics proved more accurate.

No one argues that predictive talent analytics replace the assessments made by managers, who are in close daily proximity to the activities of colleagues and direct reports. Predictive models are an adjunct that helps managers do their jobs better, mathematically pinpointing tomorrow’s top performers and more quickly recognizing if the business is at risk of losing this talent.

The aforementioned client is doing just that. Learning from the talent analytics, its managers now engage in deeper discussions with employees about their job satisfaction, and its leaders have undertaken a more intensive analysis of the pay-for-performance alignment.

The Final Frontier of Data Analytics

Superior talent management–promoting positive organizational culture–involves a life cycle of employee experiences with leaders, managers and colleagues. This cycle begins with the recruitment of individuals, followed by ongoing assessment of employees’ engagement in their work and concluding with decisions to enhance their job satisfaction and engagement.

The last arc of this virtuous cycle, prescriptive data analytics–often referred to as the final frontier of data analytics–automatically synthesizes arrays of data sets to make predictions, then suggests specific actions over these predictions.

For example, a model may suggest that a manager hold a team lunch at each employee’s three-month tenure, at which the person’s impact on the team is discussed. At the six-month point, the model may suggest that the manager publicly recognize the employee’s achievement.

Together, these analytical solutions help managers quickly spot who has the potential to become a high performer, determine if he or she poses a flight risk, and prescribe specific actions designed to retain the employee. The people most important to the organization’s success remain in place, generating productive business results well into the future.

To achieve this state of superior workforce performance, IT and HR must partner to dynamically transform talent management, incorporating technology to the betterment of human resources.

Cecile Alper-Leroux is vice president of Human Capital Management Innovation at Ultimate Software, a leading cloud provider of HCM solutions. Based in Weston, Fla., Ultimate Software is a sponsor of the HCM Technology Report.

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