Predictive Analytics for Turnover: Identifying At-Risk Employees and Proactive Retention Strategies

In April 2024 alone, 3.5 million US employees quit their jobs. Although turnovers are inevitable, being turned over at this rate monthly emphasizes the need for employers to take their retention strategy seriously. Employee turnover not only leads to decreased productivity but also causes the organization to lose sales.

According to the 2022 Harvard Business Review report, “Managing Employee Retention Concerns: Evidence from US Census Data,” employee turnover in the US costs firms approximately 30% of an employee’s annual salary, with voluntary turnover totaling $630 billion in 2019. Therefore, employers must identify at-risk employees, leverage predictive analytics, and robust retention strategies to retain their workforce. To implement predictive analytics for turnover, it is essential first to understand what predictive analytics entails.

How Does Predictive Analytics Work?

Predictive analytics involves data analysis, AI, machine learning, and statistical algorithms to evaluate trends and forecast future outcomes. Its primary processes include neural networks, regression analysis, and decision trees.

In human resources, predictive analytics utilizes historical and existing data to evaluate employees’ attitudes and behavior toward their jobs. Organizations can predict employee absenteeism, efficiency, and even turnover by evaluating data such as demographic information, engagement surveys, and specific performance metrics. As a result, employers can identify at-risk employees and utilize effective means to keep such workers.

Ways to Identify At-Risk Employees

High employee turnover can be a significant challenge for any organization, leading to decreased productivity, increased recruitment costs, and a loss of institutional knowledge. To combat these issues, firms must implement proactive retention strategies. This begins with identifying at-risk employees and understanding the factors that contribute to turnover. By pinpointing these critical indicators, organizations can take targeted actions to retain their valuable talent and maintain a stable workforce.

Key Indicators of Employee Turnover

Here are the key metrics and measurements organizations can use to identify the causes of employee turnover:

• Employee Performance: This is a common indicator of turnover. When an employee shows little productivity, it may signal they are about to quit. For instance, a top performer who scores poorly in monthly evaluations three times in a row may no longer be interested in their role.
• Low Engagement: A lack of enthusiasm for company activities often leads to low performance. These activities include company dinners, special events, and trips. For example, if an employee consistently declines invitations to team-building events and shows little interest in company-wide initiatives, it may indicate low engagement and a potential turnover risk. Employees who do not contribute to meetings or show disinterest in projects are also seen as disengaged.
• The decline in Quality of Work: When the quality of an employee’s work declines, it can indicate potential turnover. This might show as increased errors, missed deadlines, or a noticeable drop in work standards.
• Absenteeism: Frequent absence or continuous tardiness suggests low motivation to work. For example, an employee repeatedly arriving late and taking unplanned days off without valid reasons could indicate disengagement and a turnover risk. However, sometimes absenteeism may be due to personal issues, and the employee may need additional support or time.

Reasons for Employee Turnover

Understanding the reasons behind employee turnover can help organizations implement effective retention strategies. Here are some common reasons why employees leave their jobs:

• Lack of Career Progression: This is a significant reason for turnover. 21% of employees stated limited career development opportunities as their reason for leaving. An employee without a promotion or professional development for several years may become frustrated. They may start looking for better prospects elsewhere. Regular career development reviews and clear progression pathways can help reduce this risk.
• Poor Work Relationships: Lack of interaction among co-workers or between employees and employers can hinder efficiency and lead to higher turnover rates. Studies indicate that close friendships at work significantly enhance job satisfaction and productivity. For instance, 57% of people report that having a best friend at work makes their job more enjoyable. 22% feel more productive, and 21% find it boosts their creativity. Conversely, the absence of strong relationships can lead to isolation and dissatisfaction. This increases the likelihood of turnover as employees may feel unsupported.
• Work-life Balance: Managing multiple jobs can make it challenging for employees to meet the demands of each organization. Integrating personal life with professional responsibilities can also be particularly strenuous, especially in high-pressure roles. For instance, an employee working long hours in a demanding job may struggle to find time for family and personal activities, leading to burnout. Burnout significantly impacts performance and increases the likelihood of turnover. An example is an employee juggling two part-time jobs while trying to maintain a family life; the constant stress and lack of rest can lead to exhaustion and a decision to leave one or both jobs to regain balance.
• Salary and Benefits Concerns: Compensation remains a significant factor in employee turnover. A CNBC report from 2022 revealed that over 50% of employees cited inadequate pay as their primary reason for quitting. Employees who feel they are not adequately compensated or lack essential benefits, such as health insurance, are more likely to seek employment elsewhere. This indicates that salary and benefits are major drivers of employee turnover in many organizations.
• Organizational Changes: Sudden company structure, policies, or management changes can create uncertainty and dissatisfaction among employees. For instance, if a firm undergoes a significant restructuring without clear communication, employees may feel insecure about their positions and consider leaving.
• Personal Reasons: Personal circumstances often play a significant role in employee turnover. Factors such as family responsibilities, relocation, or health issues can lead employees to leave their positions. For example, employees may need to resign to care for young children or elderly family members, especially if they cannot find adequate support. Relocating for a spouse’s job transfer or to be closer to family can also necessitate leaving a job, particularly if remote work is not feasible. Additionally, health issues, whether chronic conditions or sudden medical emergencies, may force employees to prioritize their well-being over their professional commitments. Recognizing and understanding these personal reasons is crucial for organizations aiming to support their employees effectively.

All these are triggers for employee turnover. Employers must identify the ones their organization is prone to and integrate strategies to correct them before it becomes too late. Some organizations have been experimenting with predictive analytics to detect these triggers. Therefore, predictive analytics could be the next line of action in preventing turnovers.

Implementing Predictive Analytics in Human Resources

Before and after identifying at-risk employees, organizations should implement predictive analytics techniques and retention strategies to keep their employees and boost their productivity. To do that, specific technologies, data types, and steps must be implemented

Necessary Tools and Technologies to Implement Predictive Analytics in Human Resources

To effectively implement predictive analytics in human resources, organizations should consider utilizing various tools and software, such as:

I. Data Management System:

These systems encompass various technologies and tools that make the most of HR data.

• Human Resource Information System (HRIS): HRIS stores and manages employees’ personal information, training records, job performance history and reviews, etc. Examples of these systems include Oracle, Workday, Cegid, Kronos, ADP, and SAP SuccessFactors.
• Customer relationship management(CRM): This is also another example of data management systems. Although it is mainly used to measure customer behavior, CRM software like Salesforce can monitor employee interactions, which can be used in predictive analytics.

II. Analytics Software:

Human resources managers can use analytics software to analyze employee data, providing valid information on employees’ productivity and level of engagement in the company. This, in turn, helps employers determine employees at risk of a turnover. Such software includes Qlik, SAS Business Intelligence, Tableau, Sisense, etc.

III. Machine Learning Tools:

Machine learning algorithms are embedded in predictive models for organizational tasks. In human resources, machine learning tools collect information from several sources to determine factors influencing employee turnover. Examples of these tools include TensorFlow, RapidMiner, Scikit-learn, XGBoost, and H2O.ai.

IV. Employee Management Platforms:

Organizations can use various platforms to track their employees’ engagement and performance. One notable platform is eLeaP. eLeaP is a comprehensive performance management software designed to help organizations manage employee performance through continuous feedback, goal tracking, and performance reviews. The platform enables managers to set clear expectations, provide real-time feedback, and monitor progress toward objectives. By utilizing eLeaP, companies can ensure that employees are aligned with organizational goals, enhancing overall performance and engagement.

V. Business Intelligence Tools:

These tools consist of different software applications and platforms designed to provide solutions for organizations by extracting and converting data into meaningful insights. In human resources, business Intelligence tools help HR managers monitor employee information, engagement, and turnover. Examples of these tools include Microsoft Power BI, Zoho Analytics, etc.

Steps to Implement Predictive Analytics in Discovering Employee Turnover

Organizations can follow this step-by-step process in implementing predictive analytics to discover employee turnover.

1. Define Objectives and Scope:

First, organizations should clearly state the goals they want to achieve using predictive analytics. In this case, the main goal is identifying at-risk employees and discovering ways to reduce turnovers. Along with the stated objectives, organizations should engage and share the outlined objectives and goals with their stakeholders.

2. Collect and Prepare Data:

Once the goals are outlined, the next line of action is to gather valid employee data valuable for predictive analytics. This data could be the workers’ personal information, engagement surveys, attendance records, performance metrics, and other measures the organization has implemented. However, during this process, the team responsible for the data collection should ensure the data is accurate and correctly exported for final analysis.

3. Select Proper Tools and Technologies:

Organizations should select suitable data analysis and visualization platforms. One thing to note here is that the software must align with the data that is being reviewed. For instance, companies can use platforms like eLeap to evaluate employee engagement.

4. Build Predictive Models:

This is the most critical step in implementing predictive analytics for turnover. Rather than using tools that are already made, companies can build their predictive ML models themselves. However, these models must be trained on historical data to ensure validity and accuracy. Regression analysis, decision trees, and neural networks are standard ML processes that can be used to build predictive models for turnovers.

• Regression Analysis: monitors and identifies the connection between turnover and the factors that cause it. Such factors could include work environment, career stagnancy, salary, etc.
• Decision Trees: segregates at-risk employees into various categories based on engagement levels, performance metrics, etc.
• Neural networks: These processes can analyze complex data from multiple sources. Neural networks can evaluate past HR records to predict the risk of employee turnover.

5. Analyze and Interpret Results:

Analyzing and interpreting the data from predictive models is crucial for understanding employee turnover. Begin by examining the data to identify patterns and trends. Look for recurring themes, such as common reasons cited in exit interviews or noticeable changes in performance metrics.

Next, determine correlations between different variables. For example, a consistent drop in job satisfaction scores followed by increased turnover may indicate a direct relationship. This correlation helps pinpoint specific factors contributing to turnover. Segment the data based on various criteria, such as department, job role, tenure, and demographics. This segmentation reveals which groups are more prone to turnover and helps understand the unique factors affecting each group.

Use statistical tools and software to perform a trend analysis. This analysis can highlight key indicators and predictive insights, forecasting future turnover risks. For instance, it can show which employees will likely leave and when this might occur. Present the findings using data visualization tools. Charts, graphs, and dashboards make it easier for stakeholders to grasp key insights quickly. These visual aids are essential for communicating complex data effectively.

Finally, detailed reports summarizing the findings should be prepared. These reports should include actionable insights and recommendations for addressing the identified issues. Highlight the most significant factors contributing to turnover and suggest targeted interventions to improve retention. By thoroughly analyzing and interpreting the data from predictive models, organizations can deeply understand the factors driving employee turnover. This knowledge enables them to implement effective strategies to maintain a stable and engaged workforce.

6. Develop Proactive Retention Strategies:

Since the cause of the turnover has been detected, organizations should develop proactive strategies to retain at-risk employees. These strategies include improved salary payment, benefits, compensation, organizing company trips, etc.

7. Implement and Monitor Strategies:

Without further delay, the company should immediately kickstart the developed strategies. During and after the execution of these techniques, they can establish key performance indicators (KPIs) to monitor and measure the effectiveness of the retention strategies over time.

8. Refine Models and Strategies:

Organizations must continuously update their strategies to keep up with changing trends and conditions. This involves monitoring and refining predictive models to ensure their accuracy and relevance.

For example, a firm can initially develop a predictive model to identify at-risk employees based on historical data. This data includes performance reviews and engagement surveys. Over time, the firm might notice a trend where remote work preferences become significant in employee satisfaction and retention. To address this, the company can add new data points related to remote work preferences, home office setups, and work-life balance into their predictive models.

By updating their models with these new variables, the company can identify employees at higher risk of turnover due to dissatisfaction with remote work conditions. This insight allows the HR team to implement targeted interventions. Examples include offering stipends for home office equipment and more flexible remote work policies. These actions improve retention rates.

Regularly refining predictive models helps organizations stay responsive to new trends and employee needs. This ensures that their retention strategies remain effective and up-to-date.

9. Provide Employee Training and Support:

Organizations must host regular training and workshops for HR teams. These sessions should focus on using predictive analytics tools to track employee behavior. Additionally, employees should be encouraged to visit the organization’s counselor if they experience burnout.

For example, a company can organize quarterly workshops. In these sessions, HR teams can learn about the latest predictive analytics software updates and methodologies. The training can cover best practices for data analysis, interpreting results, and applying insights to improve employee retention.

The company can also establish a support system for employees experiencing high levels of stress or burnout. For instance, if an employee is frequently absent or shows signs of disengagement, the HR team can suggest a counseling session. This dual approach of continuous HR training and direct employee support helps maintain a healthy and productive work environment. As a result, turnover rates can be reduced.

Benefits of Using Predictive Analytics for Turnover

Leveraging predictive analytics for turnover benefits the organization and employees in several ways. Some of these benefits include:

●      Proactive Employee Retention:

The primary benefit predictive analytics offers is helping employers quickly detect at-risk employees. This, in turn, enables the organization to integrate specific proactive retention strategies before such employees quit.

●      Cost Savings:

By mitigating the rate of turnover, organizations can retain dedicated employees, minimizing the risk of sales loss caused by employees just starting to adjust to their jobs. Also, through predictive analytics, companies can save time and money spent recruiting and training new employees.

●      Improved Workforce:

Through predictive analytics, organizations can gather turnover insights and trends, which helps them effectively plan their workforce and identify areas that lead to low productivity.

●      Enhanced Employee Engagement:

Early identification of turnover causes allows HR teams to address the issues quickly. Decreased employee engagement, a key indicator of potential turnover, can be managed with targeted strategies. These strategies aim to boost engagement and embrace a positive attitude toward work.

●      Data-Driven Decision Making:

Predictive Analytics brings about accurate strategies that help HR managers make decisions since the results generated from these systems are based on data.

●      Identifying Hidden Patterns:

Some predictive models can analyze complex turnover indicators that cannot be easily detected, such as the change in the management style or organizational structure. One such example is Neural networks, which can uncover in-depth turnover patterns.

●      Long-term Organizational Stability:

Above all, predictive analytics helps organizations build a healthy and stable environment where employers can work passionately. Companies can also be assured of retaining their dedicated workers and avoiding unimaginable losses from turnovers.

Proactive Retention Strategies for At-Risk Employees

While predictive analytics is important, organizations should also develop strategies to help retain at-risk employees and mitigate turnovers. Some proactive strategies organizations can adopt are:

A.   Career Development Plan and Opportunities:

Career stagnation is a significant reason why employees resign from their positions. To mitigate this, organizations should provide opportunities for promotions and develop comprehensive career development plans tailored to employees’ needs. Additionally, companies should implement cross-functional projects to keep employees motivated and engaged in their professional growth.

Promotions and clear advancement paths encourage employees to see a future within the company. Career development plans, including training and mentorship programs, help employees enhance their skills and prepare for higher roles. Cross-functional projects, where employees work with different departments, can broaden their experience and keep their work dynamic and engaging. By investing in these strategies, organizations can provide a more motivated and loyal workforce, thereby reducing turnover rates.

Tips For Building An Effective Career Development Plan For Employees

Building a career development plan requires much effort from the employer and employees. However, its results are long-lasting and all-encompassing. Here are some tips organizations can follow to draw their career development plan:

• Evaluate Your Organization’s Career Development Plans: Before engaging employees, companies must outline their growth plans to facilitate honest conversations. At the end of the evaluation, they should have answers to questions like:

1. How quickly do we plan to grow?
2. What positions will open in the future?

• What growth paths are within each role (specialist, manager, senior manager)?

1. Can we support our team’s growth?
2. How can we accommodate employees with growth goals exceeding company plans?

• Assess Your Employees’ Skills and Knowledge: Organizations should evaluate each employee’s skills and knowledge using skill audits, informal conversations, workplace simulations, etc. This helps identify development opportunities relevant to their roles.
• Figure Out Employees’ Career Goal: It is important to understand employees’ career aspirations by asking questions like:

1. What are their career plans?

2. Where do they see themselves in one, three, and five years?

• What parts of their job do they love most?
• Identify Milestones They Need to Pass: Set goals that employees can control. They must be specific, measurable, attainable, relevant, and time-bound. This could be:

1. Obtaining a certification by the end of the year.
2. Reading industry-related books.

• Increasing LinkedIn followers by a certain percentage.

1. Taking language classes to prepare for overseas work.

• Create an Action Plan: After identifying milestones, organizations must have a detailed action plan, including development activities (training, events, reading), necessary support (mentoring, resources), and timelines for each activity.
• Review Plans Often: Employees should review the plans made by the company before their finalization. The company should also schedule follow-up meetings to discuss progress, address concerns, and update the plan.
• Update Plans at Intervals: Career development plans should evolve with employees’ changing interests and goals. Therefore, the organization must keep communication open so employees can discuss challenges.

B. Enhanced Work-life balance:

When a job is strenuous, it becomes difficult for employees to manage their work and life simultaneously. Hence, some quit. To tackle this, organizations should follow these specific strategies to improve their employees’ work-life balance.

●       Examine the differences among employees:

Some workers prefer to work during the day and others at night. Also, some work better alone than with others. Only when organizations spot these differences can they develop flexible work schedules that allow employees to work at their best.

●       Provide Flexible Work Hours and Remote Working:

In one research in the United States, 79% of workers said they believe that flexible work hours improve work-life balance. Employees who are given lenient work hours and flextime or are allowed to work remotely can efficiently manage their work with other life engagements.

●       Insist on breaks:

Regular breaks are essential for maintaining employee focus, reducing burnout, and minimizing distractions. HR teams should encourage employees to take periodic breaks throughout their workday. These breaks do not need to be rigidly timed but should occur regularly, such as every 2 to 3 hours. Encouraging employees to step away from their desks, stretch, or take a short walk can significantly improve their productivity and overall well-being. These breaks help refresh their minds, reduce stress, and maintain a higher level of engagement in their tasks. Organizations can enhance employee performance and job satisfaction by promoting a culture that values regular breaks.

●       Support Parent-Workers:

Parents often find it challenging to achieve a work-life balance. They need to manage professional responsibilities while spending quality time with their children. To address this, organizations can develop specific plans and policies to support parent employees.

Implementing flexible work hours and remote work options can significantly ease the burden on parent-workers. Providing on-site childcare facilities also helps. Additionally, offering parental leave, parenting resources, and support groups within the organization can help parents manage their dual responsibilities more effectively.

By understanding and accommodating the unique needs of parent-workers, companies can enhance their overall well-being and productivity. This leads to a more engaged and loyal workforce.

C. Regular Feedback and Recognition:

HR professionals should conduct regular employee surveys and performance reviews. This helps gather feedback to identify at-risk employees. They should recognize the achievements of dedicated workers, host award events, and give bonuses and public recognition. For instance, featuring top employees on the company website or newsletter.

D. Offer Compensation and Benefits:

Low salary pay and poor benefits are major reasons employees quit their jobs. As a result, organizations should review and adjust salaries at intervals. Various benefits and incentives should also be available to workers. Some of these benefits include:

• Health insurance
• Life insurance
• Wellness programs
• Childcare
• Retirement plans
• Professional development
• Parental leave, etc.

E. Improved Employee Engagement:

There are 5 Cs of employee engagement: care, connect, coach, contribute, and congratulate. Each of these C’s reveals how much effort is needed to enhance employee engagement. Organizations should employ team activities, open discussions, and communication among colleagues and between leaders and employees. Companies should create a work environment that hears and supports workers’ ideas.

F. Employee Well-Being Programs:

Employers should not only focus on the job development of employees but should also pay attention to the workers’ physical and mental health. They should host wellness and fitness trainings and compel all employees to attend them. Providing counseling services is another practical approach that can reduce turnover rates.

G. Exit and Stay Interviews:

HR teams should conduct face-to-face interviews with employees to understand the possible reasons that can cause them to stay and resign. The results obtained from these interviews should be followed up as a proactive means to eliminate turnovers.

H. Empowered Management:

Organizations should train their managers and HR teams on identifying early signs of turnovers. They should be provided with tools and training programs to build strong interactions and relationships with employees.

Conclusion

Utilizing predictive analytics can significantly mitigate the risk of unexpected employee turnover. By deploying the appropriate technologies, tools, and platforms, HR teams can identify employees at risk of leaving the organization. Several factors contribute to turnover risk, including poor workplace relationships, inadequate compensation, career stagnation, and inflexible work hours.

Organizations should integrate predictive analytics with proactive retention strategies to address these issues effectively. These strategies encompass offering career advancement opportunities, recognizing and rewarding employee achievements, enhancing compensation packages, and providing comprehensive benefits and incentives. By implementing these measures, companies can retain their workforce, reduce recruitment costs, and improve organizational efficiency.