Tue, Jan 21 2025 | Sports and Recreation 7 Ways to Use Predictive HR Analytics (w/ Real Examples)

Predictive HR analytics lets you pull back the curtain on the inner workings of your organization. This data gives you all the necessary info to run a better business, inside and out.

Once you have this data, here are just a few things you can do:

• Improve recruitment practices
• Reduce turnover rates
• Achieve optimal performance
• Cut costs related to turnover and new hires
• Create an employee profile that’ll show you have the potential to thrive in your company

But don’t take our word for it.

In 2019, the HR analytics market was already worth $1.9 billion with predictions to grow to $3.6 billion by 2024.

Not sure where to start or how to use people analytics for HR?

We’ll show you 7 companies killing it with predictive analytics and how you can do the same.

• 1. Use Predictive Analytics to Boost Retention and Bank Some Cash
• 2. People Analytics can Increase Collaboration & Engagement
• 3. Predictive Analysis Upgrades Workforce Planning
• 4. People Analytics Can Personalize Employee Experience
• 5. Crush Myths with Real Data
• 6. Boost Productivity Through Employee Engagement
• 7. Get a Handle on Absenteeism
• MakeShift Offers High-Level Workforce Forecasting

1. Use Predictive Analytics to Boost Retention and Bank Some Cash

Credit Suisse used a people analytics strategy to predict employee turnover, saving enormous costs associated with recruitment and training. To be honest, “enormous” is an understatement.

(Photo credit: SiyueSteuber)

The whole program saved them roughly $70 million a year.

They used machine learning algorithms to comb through data points related to employee behavior, performance, and engagement. Factors like:

• Work hours
• Compensation
• Tenure
• Promotion history
• Replies to internal surveys & communications

By identifying patterns and trends, Credit Suisse could accurately predict which employees would most likely leave the company.

They sprung into action to head off potential turnover. The data was anonymously given to managers to reduce turnover risk factors and keep top talent.

They tailored retention strategies to meet at-risk employees' specific needs and concerns.

For example, they offered career development opportunities, personalized compensation options, and improved work-life balance efforts. This helped retain high-value talent and enhanced employee satisfaction and engagement.

Credit Suisse reduced turnover rates, which saved big-time costs associated with hiring and onboarding new employees.

The power of predictive analytics can boost retention 💥

Credit Suisse's success in reducing employee turnover and saving a cool $70 million a year highlights the power of predictive analytics. Use that power with these tips:

1. Gather & analyze data — Start by collecting comprehensive data on your employees. The more data points you have, the more accurate your predictions will be.
2. Leverage machine learning tools — Analyze the collected data using machine learning algorithms. These tools can identify less apparent patterns and trends, helping you predict which employees are at risk of quitting. A tool like Shiftmate AI’s fatigue warning automatically monitors for you.
3. Get proactive — Once you've identified at-risk employees, roll out a targeted retention strategy. The key is to address potential issues before they lead to turnover.
4. Empower managers — Give your managers anonymous, data-driven insights about their teams. This will help them determine which proactive measures could address turnover risks.

2. People Analytics can Increase Collaboration & Engagement

Google’s most famous example of data analysis and predictive analytics is Project Aristotle, which helped identify the elements of an effective team.

(photo credit Arthur Osipyan)

To do this, Google researchers reviewed over 250 points from an annual engagement survey to determine variables (e.g., group dynamics, skill sets, or personality) that highly impact team effectiveness.

Google found that the key to killer team collaboration was based more on team interactions than individual skills. They found psychological safety is the top characteristic of successful teams.

Teams where members felt safe to take risks and be vulnerable with each other outperformed others.

This insight led Google to cultivate a work environment full of empathy, mutual respect, and open communication. This encouraged employees to share ideas and collaborate more freely, helping boost innovation and productivity company-wide.

People analytics can encourage cohesiveness & engagement 🤝

Google’s Project Aristotle illustrates how data-driven insights can significantly improve team collaboration and engagement. Here’s how you can apply similar people analytics strategies:

1. Do a deep dive with surveys — Gather data through employee engagement surveys. Focus on understanding aspects of team dynamics like:

• Communication patterns
• Interpersonal relationships
• Overall work environment

Pro tip: The more detailed your survey, the better insights you’ll get.

2. Dissect team dynamics — Use data analytics tools to identify key factors contributing to team success in your organization. Use these dynamics to guide your efforts to improve collaboration.

3. Foster a safe & open vibe — Develop a culture that prioritizes psychological safety. You want team members to feel comfortable taking risks and expressing their ideas without fear of judgment. Innovation thrives on collaboration and employee engagement.

4. Support collaboration with structure — Introduce practices like regular check-ins, structured meetings, and feedback channels to ensure all team members feel included and heard. This type of structure helps create a more inclusive and collaborative environment.

3. Predictive Analysis Upgrades Workforce Planning

Cisco upgraded its workforce planning using predictive models to foresee talent gaps and workforce trends. This allowed them to proactively address potential shortages in critical skills and plan for future hiring needs.

(photo credit: JasonDoiy)

They collected and analyzed data from HR systems, employee surveys, performance metrics, and other sources. Advanced analytics and machine learning algorithms helped them identify trends, predict future workforce needs, and make informed decisions about talent management.

They also found where they should reskill and upskill.

Cisco uses Degreed as a learning experience platform (LXP) to support this. It offers a user-friendly gateway to learning content where employees can choose content and training opportunities related to specific skills.

Transform workforce planning with predictive analytics 🔮

Cisco's approach to workforce planning demonstrates the value of predictive analytics in anticipating and addressing talent gaps. Use these strategies to up your workforce planning game:

1. Collect & analyze data — Gather data from HR systems, employee surveys, and performance metrics. Use this info to understand your current workforce dynamics, including skill levels, role requirements, and employee performance.
2. Spin data into foresight — Use advanced analytics and machine learning algorithms to identify trends and predict future workforce needs. By understanding potential talent gaps and workforce trends, you can proactively plan for hiring, reskilling, and upskilling efforts.
3. Assess roles & skills — Analyze the roles and skills within your organization to find which ones are critical. Identify transferable skills and assess whether specific roles can be filled internally through reskilling or upskilling.
4. Cultivate a culture of learning — Adopt a learning experience platform (LXP) like Cisco’s use of Degreed. This can help you curate learning content and offer employees personalized training opportunities, ensuring they’re equipped with skills needed for future roles.
5. Refine talent acquisition — Use the insights gained from your predictive models to refine your talent acquisition strategies. Focus on filling critical skill gaps and ensuring your hiring efforts align with future business needs.

Note: Hiring for skills is 5 times more predictive of job performance than hiring for education and over twice as predictive as hiring for work experience.

4. People Analytics Can Personalize Employee Experience

Apparel manufacturer and brand licenser Fam Brands used people analytics to improve employee experience. Since adopting a workforce analytics platform for visibility into employee performance and engagement, they’ve made huge strides in several areas.

(photo credit: gorodenkoff)

For example, rather than mindlessly tossing out a hybrid work policy, HR analyzed location insights to see where people do their best work. They found employees who work from home are more productive than those who don’t.

Thanks to people analytics dashboards, they also identified needs related to training, hiring, and communication that would’ve otherwise gone unnoticed.

Improve employee well-being by getting to know your employees 👥

Fam Brands' success in using people analytics to improve employee well-being through flexible work options can be a model for your organization. Try these strategies:

1. Analyze location & productivity data — Gather and analyze data on where your employees are most productive, whether in the office, at home, or in a hybrid setting. Understanding these trends allows you to tailor your work schedule options to maximize productivity and employee satisfaction.
2. Embrace flexibility — Based on your data analysis, introduce flexible work options that align with your employees’ preferences and productivity levels. Consider offering hybrid work models or fully remote options for roles that benefit from more flexibility.
3. Address training & communication needs — Identify any gaps in training, hiring, or communication that impact your employees. Use the data to implement targeted solutions to address these issues, further enhancing the employee experience.

When employees get the training they need, they’re 17% more productive, and 59% of employees feel training directly improves their performance.

5. Crush Myths with Real Data

Johnson & Johnson put employee data to work when the people analytics team tested a hypothesis among recruiters — that years of experience trump talent for specific roles.

(Photo credit: Sundry Photography)

The company noticed a dip in college graduate hires, and leadership wanted to know if more experienced candidates performed better on the job.

They analyzed data points on nearly 47,000 employees to compare performance, promotions, and attrition rates.

They found recent graduates performed as well as their more experienced colleagues and stayed with the company longer — much longer. That data sent recruiters back to college campuses and led HR to invest in leadership development and mentorship programs.

Use insight to refine (or rethink 💡) your hiring strategy

Johnson & Johnson’s use of people analytics to squash hiring myths is a valuable lesson for refining your hiring strategies. Challenge the status quo with these steps:

1. Test assumptions with data — Analyze data on current and past employees to test your hiring assumptions. Use performance, promotion, and attrition rates to compare myth to facts.
2. Adjust based on your findings — Once you’ve got solid data, tweak your hiring criteria to fit your findings.
3. Revisit recruitment strategies — Based on your findings, adjust your recruitment efforts.

6. Boost Productivity Through Employee Engagement

Shoe retailer Clarks investigated the relationship between engagement and financial performance to find out if there’s a connection.

(photo credit: J2R)

Clarks is already known for above-average employee engagement. However, they were interested in the returns on engagement. Their study analyzed 450 business performance data points.

The results showed every 1% improvement in engagement led to a 0.4% bump in business performance.

To investigate further, the team also analyzed the 100 top-performing stores. They found optimal team size and a store manager's tenure length were predictors of performance.

Using these insights, the team created a blueprint from high-performing stores and an engagement toolkit that managers use to improve store performance.

Use engagement insights to boost ⬆️ your productivity

Clarks' use of people analytics to link employee engagement with productivity provides a roadmap for enhancing business performance. Try these strategies for yourself:

1. Measure engagement & performance — Collect employee engagement levels and business performance data. Then, use predictive analysis to determine whether there’s a connection between the two.
2. Identify engagement drivers — Analyze the characteristics of your top-performing teams or locations. Look for patterns that appear to contribute to high engagement and performance.
3. Create an engagement blueprint — Use your findings to develop a blueprint for high-performing teams. This might include guidelines on team dynamics, leadership practices, and engagement strategies that have been effective.
4. Develop an engagement toolkit — Provide managers with tools and resources to enhance team engagement. Think in terms of structured feedback channels, recognition programs, and other creative ways to boost morale and productivity.

7. Get a Handle on Absenteeism

When absenteeism jumped over the acceptable benchmark set by its HR department, E.On, an electric company, used predictive analytics to find the factors driving more unscheduled time off.

(photo credit: Teka77)

They found that vacation duration and timing had the biggest impact on the frequency of unplanned absences during the rest of the year.

The company used this data to implement policy changes that encouraged managers to accommodate employees' scheduling of time off.

Now, employees are encouraged to schedule multiple small breaks throughout the year with at least one larger vacation — this combo has reduced absenteeism.

Absenteeism costs roughly $3,600 annually for each hourly worker and $2,660 yearly for salaried employees.

Use people analytics to get to the root of absenteeism ⛏️

E.On’s use of people analytics to tackle absenteeism offers a practical approach to reducing unplanned time off in your company. Give their strategy a shot:

1. Analyze absenteeism data — Round up data on employee absenteeism, including timing, duration, and reasons for unplanned time off. Analyze this data to identify patterns and potential factors contributing to higher absenteeism rates.
2. Identify critical drivers — Look for correlations between absenteeism and factors like vacation timing, workload, and employee demographics. Decide which factors have the most impact on your absenteeism rate.
3. Implement change — Based on your findings, adjust your time-off policies. For example, encourage employees to schedule multiple long weekends throughout the year, with at least one extended vacation. This will reduce the potential for burnout and absenteeism.
4. Educate managers — Train your managers to accommodate employees’ time-off requests and promote a healthy work-life balance. Empower them to be flexible with scheduling, reducing the stress that can lead to unplanned absences.

MakeShift Offers Advanced Workforce Forecasting

MakeShift Scheduling offers predictive workforce planning using advanced analytics and machine learning to forecast staffing needs and optimize scheduling.

Here’s how it works:

• Data integration & analysis — MakeShift’s AI-powered platform collects and analyzes data, including historical scheduling patterns, employee availability, and workload demands. By integrating this data, MakeShift can identify trends and patterns that impact your workforce requirements.

• Predictive algorithms — ShiftMate AI uses sophisticated predictive algorithms to forecast future staffing needs. These algorithms consider factors like seasonal fluctuations, upcoming events, budgetary limitations, and historical demand trends. By anticipating these changes, you can rest easy knowing you’ll have the right number of staff with the necessary skills at the right times.

• Real-time adjustments — Our system provides real-time insights and alerts for deviations from the predicted patterns, enabling managers to make on-the-fly adjustments. This flexibility ensures that staffing levels are continually optimized, reducing the risk of overstaffing or understaffing.

People Analytics is a Trend You Should Follow

More and more companies use predictive analytics in their HR departments to run better organizations.

Using analytics can help you become more productive, offer more support to your employees, and prepare for the future.

At MakeShift, we believe in the people-first approach. We’d love to show you how our predictive analytics transform entire organizations with smarter scheduling.

Schedule a FREE demo today.

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