Big data for financial leaders is more important than ever. When it comes to your organization's most valuable asset — people — big data can tell you what you need to know to engage talent and get the most out of it. Employee turnover, for example, may be among your highest costs. But by investing in big data and then using that intelligence to predict which employees are most likely to jump ship, finance leaders can enable their HR department to keep their best and brightest and stave off the high costs that come with talent attrition.

Using Big Data for Retention

Whether you are using it to its full potential or not, your organization likely collects a wide array of actionable HCM data on your employees, from performance to pay to promotion history and more. With predictive analytics, you can use this information to detect flight risks and take action to keep talent. Underlying reasons for churn include dissatisfaction with the organization, geographic location (commute time), compensation, performance standards and relationships with managers and teammates. The difficulty for most businesses is collecting data on these drivers and then measuring which are most connected to turnover.

In the case of leveraging predictive analytics, a number of algorithms can be utilized to anticipate churn. Your HCM data — when used to its full capabilities — can be your best tool against turnover. HCM data can be used to construct a model that identifies turnover drivers, and these models can then help you determine the likelihood of an employee leaving your business and indicate what factors led to the decision to go. Once these factors are identified, businesses can work to forestall churn. This can lead to substantial savings, engaged employees (who recognize efforts to retain them) and increased productivity.

Using Big Data to Benchmark

Age and retirement data collected from HCM systems offer insight about hiring needs, benefits administration and more. If you know, for example, that a large percentage of employees will soon be eligible for retirement, you can work harder in recruiting and succession planning.

Another example is wage garnishment. More than 10 percent of employees ages 35-44 may be subject to wage garnishment, per a white paper from the ADP Research Institute®. As financial stress can lead to employee disengagement and a downturn in productivity, you can employ predictive analytics to identify trouble spots and then implement measures to support those affected employees. "By offering financial counsel, budget education and preventive financial wellness training to employees, employers may minimize the destructive impact of wage garnishment and help employees manage their debt," the report states. Big Data makes all this possible.

Talent Matters

Your employees are your most valuable asset. This is not some tired trope that no longer applies in today's more complicated and technologically integrated business world. Talent still matters to both manage bottom lines and retain your competitive advantage. But understanding that talent through data can be a challenge for businesses with too many information silos and not enough integration to support big data. The average global business oversees a dizzying 33 payroll systems and 31 HR systems, according to research from the ADP Research Institute®. To take advantage of the benefits big data offers, you must first streamline your siloed infrastructures to gain clear visibility to your organization's data. Then you need access to accurate, up-to-date benchmarks to truly understand how your organization compares to others in your industry or location so you and your HR leaders can take action to improve your competitive position in the talent market.

Finance leaders should support their HR departments by empowering them to better manage systems and workforce data, and by extension better manage talent. As the report indicates, "having all the workforce data in one place globally takes Human Capital Management to entirely new levels." The power comes from the insights you glean from the data, enabling your organization to make better people and business decisions.

Tags: predictive analytics big data