Using Data Analysis For Employee Retention
By Riley Hayward
In a previous TalenTeam overview, we tackled the overall role of big data and data-driven insights in streamlining the improvement of your HR processes. We’re not alone in seeing data analytics as a primary driver in the digital transformation of HR. One report via Global News Wire reveals that the HR analytics market is headed towards an 11% worldwide growth, translating to an estimated net worth of $3.6 billion (£2.9 billion) by 2025. This means that more and more businesses are finding out how to use data analytics to build employee loyalty and lower their attrition rates to more competitive levels.
And it’s about time. HR analytics has been in the developmental stages for years —and it has resulted in lots of improvement in terms of addressing alarming attrition rates and improving HR work in general. “Our research shows that the financial costs associated with attrition can range anywhere between 13% and 23% of annual compensation depending on the function/level of the employees under the scope of the study,” explains Willis Towers Watson workforce analytics and planning director Neeraj Tandon. “In our experience, a focused attrition analytics predictive model can help lower this risk by 5% to 8% annually.”
This is possible because data analytics in HR combines traditional HR analytics with big data-enabled predictive models. This simply means that on top of your company’s typical HR metrics, your insights can be enhanced by feeding your business’ data into an artificial intelligence (AI)-enabled system. This will then reveal patterns and factors that would otherwise be undetectable to humans alone. This enables HR personnel to see hidden connections between key factors in employee engagement, attrition, and turnover, opening the doors for creative and actionable insights towards improved retention strategies. For instance, SuccessFactors Workforce Analytics enlists a comprehensive library of 2,000 standard metrics and parameters to provide direct, concrete, and actionable improvement points for your HR team to work towards. This type of software enables analysts, business partners, and HR professionals to more accurately steer the workforce towards specific goals, as well as quickly answer sensitive or significant questions from clients and candidates alike.
While everyone from startups to multinationals can benefit from predictive HR analytics, industries that generate the most work process data stand to benefit the most. This is why the global supply chain has become a big player in the digital, data-driven transformation of HR. In terms of improving employee retention, HR data analytics can be leveraged to optimise remuneration processes for both fairness and efficiency, which is particularly helpful in the hectic world of global logistics. Designed for cargo lorry companies, the fleet tracking system developed by Verizon Connect lays the foundation for an automated way of recording payroll data and other vital aspects of remuneration. With human error taken out of the picture, verifiable and automated timesheets can lessen if not fully eliminate payroll discrepancies and other major pain points. More importantly, this type of fleet and timesheet tracking system generates tons of daily business process data, which can then be processed by backend HR analytics software to find and solve any more pain points in the remuneration process.
Like the global supply chain, the call centre industry is another environment that’s similarly large, complex, and ripe for data mining by HR analytics software. Today, Intelligent CIO explains how predictive processing enables contact centre employees to respond as efficiently as possible to any customer queries and concerns – greatly reducing the need to deal with increasingly irate clients on the other end of the phones. This is accomplished through a model of data analytics that’s geared towards determining as much data as possible on the person that’s calling and arming the responsible agent with the information that’s most salient to the client’s concerns. On top of that, the collected data can then be processed into objective insights for addressing major pain points in the day-to-day lives of stressed call centre employees. This type of predictive data analytics has done a lot to improve employee retention in an industry that’s notorious for its high turnover rate.
Where there’s data, there’s insight. And in the competitive, headhunting world where modern businesses consistently vie for the best talents, HR data analytics-driven improved employee retention can help you keep your best employees and survive.