The U.S. Bureau of Labor Statistics reports that in 2018:

• The median employee tenure among workers in the United States is 4.2 years.
• The median employee tenure for workers aged 55 to 64 is 10.1 years. For those aged 25 to 34, it’s 2.8 years.

Similarly, the Society for Human Resources Management 2016 Effective Workplace Index found that 77% of employees in highly effective workplaces are “not at all likely” to leave, compared with 30% of employees whose workplaces were considered less effective. The index further identified the top three contributors to greater probability of Employee retention:

1. Satisfaction with wages, benefits and advancement opportunities
2. Work/Life fit
3. Autonomy (Commensurate with role)

While age and tenure seem to correlate directly, the Millennials and GenZ’ers who are spending less than three years at a job comprise a “churn” that is costly for any company – and should be predicted and subsequently mitigated.

But it’s a two-way street as the SHRM Index shows. Companies are just as complicit in retention outcomes.

Where’s Everybody Going?

These statistics are symptomatic of a larger issue when the labor market tightens: the failure of companies to take measures to retain qualified and trained talent. Add in an expanding dose of Millennial and Generation Z workers who seem to indulge in job-hopping, and the entire concept of retention seems antiquated at best.

Companies that fail to address high turnover proceed down a perilous path. The significant expense associated with on-boarding and training a new hire make it essential that good talent is rewarded, promoted and retained. Who wants to watch that investment in time and skills – and possibly outstanding productivity – walk out the door?

Why Retention Matters

Empirical evidence demonstrates that annual reviews, peer references, latte machines and Starbucks breaks do little to dissuade leavers. And when they go, thousands of dollars in on-boarding and training costs go with them.

A report from the Center for American Progress found that replacing an employee can cost 16% to 21% of a position’s salary. Multiply this percentage anywhere from a few to dozens of employees leaving over a designated time period (say, a year?) and the losses – in money and personnel – mount.

So, how do you manage to keep personnel around? Do you add a bubble hockey game to the rec room? Keep increasing salaries 10% to make it “worth” everyone’s while to stay? Mandate non-compete agreements?

It depends, of course, on what the Analytics say. Because as Peter Drucker famously declared, “If you can measure it, you can manage it.” To consider rectifying an employee retention plan without first looking over aggregated data will ultimately deliver the same results. So, let’s label the data as “workforce analytics” and see how BI can help mitigate employee turnover.

Workforce Analytics – What Is It?

The art – and science – behind connecting raw labor pool data to disclose and share insights that will lead to better business decisions – improving employee retention, in particular – is what workforce analytics is all about. It is a way not just to see what happened with personnel, but to understand why it happened, what will happen next, and ultimately how to adapt a workforce strategy that aligns with company objectives and culture and keeps personnel on board.

Just about any datum dealing with employee lifecycle can be measured: cost per hire, hiring source, promotion rate, resignation rate, cost of turnover, workforce turnover rate and even yield ratios. Combining these individual figures into analytics, companies can explore resignation drivers and correlations; the impact of attrition on business metrics; and, the impact of training on promotions, retention, and retirement trends.

These insights permit C-suiters to make shrewder decisions on cost management and personnel retention issues. Employee analytics show that the way a company manages its employees can be the biggest cause of staff attrition or retention.

In order to reduce employee churn, however, HR teams need to become more data-driven, looking past simple descriptive analytics (demographics) and toward more exploratory analytics (why so many 31-year-olds have left lately). Even better, they should look at Predictive Analytics (these data indicate this trend will continue, so we’ve got to address it and resolve it.)

Predictive Analytics – What Can It Do?

Predictive analytics and other data-based technologies can help streamline the hiring process while identifying the best possible talent and – more importantly – a solid cultural fit. Predictive analytics parses historical data to predict future outcomes.

Using predictive analytics, an employer gets deeper analysis of potential causes to employee turnover. This drill down enables managers to quickly adapt programs, policies and workplace conditions that should inhibit, if not altogether prevent, staff churn. In fact, research shows that hiring the “right fit” vis-a-vis skills, culture, role preference, etc. advances the onboarding and assimilation of those employees who stay long and perform well.

For example, data on employee performance and learning input can predict long-term learning and growth potential of workforce members. This can suggest HR interventions, whereby the individual can be supported by special training, mentoring, coaching, etc., to achieve goals. Shrewd adoption of such “intelligence” can satisfy individual employee needs and requisites, which leads to a culture of trust and transparency, ultimately fostering greater retention.

Predictive Analytics – What Can’t It Do?

Results from other recent workforce analytics studies demonstrate a critical factor about turnover: people will job hop until they find a position where both a company’s manager and processes are commensurate with the employee’s skills and expectations.

Therefore, it is incumbent upon the company to have measured, monitored and massed those qualifications and characteristics of an ideal employee, so when a candidate is recruited, the match between individual and company is a fait accompli.

After all, it’s cheaper to keep an employee than it is to find and train a new one. What shouldn’t be a surprise is that adopting workforce analytics today can positively affect an organization’s bottom line more than ever.

Author Bio:

Keith Craig is Content Marketing Manager for Better Buys. He has more than a decade of experience using, researching and writing about business software and hardware. He can be found on Twitter and LinkedIn.

The post Predictive Analytics and How BI can help HR improve employee retention appeared first on BI Blog | Data Visualization & Analytics Blog | datapine.