People Power Through Predictive Analytics

Cecile Alper-Leroux, VP of HCM Innovation, Ultimate Software

Cecile Alper-Leroux, VP of HCM Innovation, Ultimate Software

By suggesting a probable future for your employees, predictive analytics gives senior executive leaders greater confidence that the 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.

"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"

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

As a vendor of HCM (Human Capital Management) systems, 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.

Information technology is not the foe of HR, however. The automation of mundane manual 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 executive leaders 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 is tomorrow’s top performers, determine their levels of engagement, and take actions to ensure they remain energized by their work and the company’s mission.

It is 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 their 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 workforce engagement and employee performance reviews frequently subjected to the caprices that arise when one human being assesses another. Predictive data analytics, on the other hand, offers a statistically valid means of identifying high performing employees driving the business forward and discerning their respective flight risks.

In making these predictions, the tools draw from 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, Deloitte Consulting LLP. Yet, only 4 percent of companies have the ability to “predict” or “model” their workforce.

Ultimate Software has launched two predictive talent analytics—the UltiPro Retention Predictor™ and the UltiPro High Performer Predictor™— that sift through millions of data points. Based on a proprietary algorithm, the tools identify tomorrow’s top performers and forecast employees’ intent to stay or leave an organization within the next 12 months.

It is not uncommon for predictive modeling to be more precise than human assessments of talent risks, given that emotions play a role when evaluating the performance of a colleague or a direct report. 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 data analytics proved more accurate.

No one is arguing that predictive talent analytics replace the assessments made by managers, who are in close proximity on a daily basis to the activities of colleagues and direct reports. Predictive models are an adjunct for managers to 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 senior leaders have undertaken a more intensive analysis of the pay-for-performance alignment.

The Final Frontier

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, and then suggests specific actions over these predictions.

Ultimate Software recently introduced a prescriptive framework called UltiPro My Leadership Actions™. The tool provides more than 70 recommended leadership actions that are linked to 16 different drivers of employee engagement. Say a manager discerns team conflict—one of the 16 engagement drivers—the model will recommend a series of actions to address this behavior.

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

Together, these analytical solutions can help managers quickly spot who has the potential to become a high performer, determine if he 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.