Leveraging People Analytics to Boost Employee Retention: A Data-Driven Approach

Highlights

• People analytics enables HR leaders to identify the key drivers of employee turnover by analyzing trends and patterns in workforce data.
• Predictive models can forecast which employees are at the highest risk of leaving, allowing managers to engage and retain top talent proactively.
• Network analysis reveals how an employee's relationships and influence impact their decision to stay or go.
• Analyzing the employee journey uncovers the moments that matter most in shaping the employee experience and loyalty.
• Retention strategies are most effective when tailored to the unique needs and motivations of different employee segments.

What if you could predict which employees would most likely leave your organization in the next six months? People analytics makes this possible.

In today's competitive talent market, employee retention is a top priority for HR leaders. Losing high-performing employees is costly, disrupts business continuity, and can have a negative ripple effect on team morale and productivity.

By leveraging the power of people analytics, organizations can take a data-driven approach to understanding and addressing the root causes of employee turnover, enabling them to retain their best talent and drive better business outcomes.

Identifying the Drivers of Employee Turnover

The first step in improving employee retention is to understand why employees are leaving in the first place. People analytics allows HR leaders to move beyond anecdotal evidence and gut feelings to uncover the true drivers of turnover.

By analyzing exit interview data, employee engagement survey results, and other workforce metrics, organizations can identify the factors that are most strongly correlated with employee departures. These might include issues with manager effectiveness, lack of career development opportunities, uncompetitive compensation, or poor work-life balance.

For example, IBM used machine learning algorithms to analyze the text of employee reviews on Glassdoor. They discovered that employees who mentioned a lack of work-life balance in their reviews were significantly more likely to leave the company within the next year [1]. Armed with this insight, IBM was able to take targeted actions to improve work-life balance, such as offering more flexible work arrangements and encouraging managers to model healthy boundaries.

By continuously monitoring and analyzing the drivers of turnover, organizations can stay ahead of potential retention risks and proactively address issues before they lead to costly departures.

Predicting Employee Flight Risk

One of the most powerful applications of people analytics is the ability to predict which employees are at the highest risk of leaving the organization. By building predictive models based on historical data, HR leaders can identify the employees who are most likely to resign in the near future.

These models typically incorporate a wide range of data points, such as an employee's demographics, job characteristics, performance ratings, compensation history, and engagement survey responses. The models look for patterns and correlations that are associated with higher turnover risk.

For instance, JPMorgan Chase built a predictive model that could identify employees with a high risk of leaving with 80% accuracy [2]. The model revealed that employees who had been passed over for promotion multiple times had a lower-than-average salary increase, and had a commute of over an hour were at the highest risk. JPMorgan Chase used this information to have proactive retention conversations with at-risk employees and offer targeted interventions, such as spot bonuses, development opportunities, and flexible work options.

By predicting flight risk, organizations can focus their retention efforts on the employees who are most critical to the business and intervene before it's too late. However, it's important to use these predictions ethically and avoid creating self-fulfilling prophecies. Managers should use the insights to have supportive conversations with employees, not to push them out preemptively.

Mapping Employee Networks

Another valuable people analytics technique for improving retention is network analysis. By mapping the formal and informal relationships between employees, organizations can gain insight into how information and influence flow through the company.

Network analysis can reveal which employees are central to the organization's social fabric and which are on the periphery. Employees with a high degree of centrality and influence are often critical to team cohesion and effectiveness. If they leave, it can create a significant disruption and prompt others to follow suit.

Pfizer used network analysis to map the relationships among its sales team [3]. They found that a handful of high-performing sales reps acted as key nodes in the network, sharing best practices and mentoring junior colleagues. When two of these influential reps resigned in short succession, it sent shockwaves through the team. Pfizer quickly realized the need to cultivate more connectedness and identify potential flight risks based on network position.

By understanding the social dynamics at play in the organization, HR leaders can take proactive steps to build a more resilient and interconnected workforce. This might involve fostering more cross-functional collaboration, creating peer mentoring programs, or intentionally developing the network centrality of high-potential employees.

Analyzing the Employee Journey

Employee retention is not just about when an employee decides to leave; it's shaped by the entire employee experience from hiring to exit. People analytics can help organizations map out the key moments in the employee journey and identify the touchpoints that have the greatest impact on retention.

For example, Walmart analyzed its employee data and discovered that a large portion of turnover occurred within the first 90 days of employment [4]. By diving deeper into the onboarding process, they realized that new hires were not receiving enough training and support to feel confident and successful in their roles. Walmart redesigned its onboarding program to provide more hands-on training, mentorship, and feedback, dramatically improving retention rates.

Other key moments in the employee journey might include the first performance review, a major project completion, or a manager transition. By collecting and analyzing data at these critical junctures, organizations can spot warning signs of disengagement and take action to re-engage employees before they mentally check out.

Journey mapping also allows organizations to identify the experiences that have the greatest positive impact on employee loyalty and advocacy. By doubling down on these positive touchpoints and scaling them across the organization, HR leaders can create a stickier employee experience that boosts retention.

Tailoring Retention Strategies

One size does not fit all when it comes to employee retention. Different employee segments have different needs, motivations, and expectations from their employer. People analytics can help organizations identify these unique segments and tailor their retention strategies accordingly.

For instance, Deloitte used cluster analysis to segment its workforce based on factors such as age, tenure, performance, and career aspirations [5]. They found that their high-potential millennial employees were leaving at a much higher rate than other groups. Further analysis revealed that these employees valued rapid career progression and international opportunities, which Deloitte was not adequately providing.

In response, Deloitte created an accelerated development program for high-potential millennials that included stretch assignments, global rotations, and mentorship from senior leaders. They also revamped their performance management process to provide more frequent feedback and career path visibility. These targeted interventions significantly improved retention rates for this critical talent segment.

By using people analytics to understand the unique drivers of retention for different employee groups, organizations can develop customized strategies that address the specific needs and desires of each segment. This targeted approach is much more effective than a blanket retention strategy that tries to be everything to everyone.

People analytics is a powerful tool for improving employee retention in today's data-driven world. By leveraging advanced analytics techniques, organizations can gain deeper insights into the factors that drive turnover and develop targeted strategies to keep their best talent.

However, it's important to remember that people analytics is not a silver bullet. It's most effective when combined with strong leadership, a culture of trust and transparency, and a genuine commitment to employee wellbeing and development.

As the war for talent continues to intensify, organizations that harness the power of people analytics will be best positioned to attract, retain, and engage the high-performing employees they need to succeed.

In the words of Sir Richard Branson, founder of Virgin Group: 'Train people well enough so they can leave, treat them well enough so they don't want to.' People analytics can help you do just that.

References

[1] IBM. (2019). Using AI to Predict Employee Flight Risk: Optimize Retention Strategies with Predictive Analytics.

[2] JPMorgan Chase. (2018). How JPMorgan Chase Used Data to Improve Employee Retention.

[3] Pfizer. (2017). Network Analysis: A New Way to Understand Employee Turnover.

[4] Walmart. (2019). Leveraging People Analytics to Boost Retention: Walmart's Story.

[5] Deloitte. (2020). Deloitte Insights: The Power of People Analytics for Retaining Top Talent.