Predictive HR analytics is a tech tool that HR uses to analyze past and present data to forecast future outcomes. Predictive HR analytics digitally digs through data to extract, dissect, and categorize information and then identify patterns, irregularities, and correlations. Through statistical analysis and predictive modeling, analytics enables data-driven decisions regarding HR functions. 

Predictive HR analytics systems are reminiscent of the earthworm. The worm ingests natural waste material and residue and excretes nutrient-rich, fertile soil. Predictive analytics, too, intakes unused, raw data and transforms it into applicable information that supports wiser business decisions.

Predictive HR analytics examples 

Here are some examples of how organizations today apply human capital predictive analytics:

  • Recruitment. Predictive analytics helps HR professionals identify the most effective sources of top talent. By analyzing historical data on successful hires, organizations can focus their recruitment efforts on the platforms and channels that yield the best results.
  • Employee retention. Predictive models can analyze employee data, such as performance reviews, absenteeism, and tenure, to identify people at risk of leaving the company. This allows HR to take proactive measures, such as offering career development opportunities or addressing workplace concerns, to retain valuable talent.
  • Workforce planning. Predictive analytics can forecast future skill gaps within a company by considering factors like retirement rates, turnover, and emerging industry trends. HR can then develop training and development programs to fill these gaps and ensure the workforce remains competitive.
  • Employee performance management. Predictive HR analytics can forecast a team member’s future performance based on historical performance data. This helps the HR team identify high-performing people who could be potential successors for critical roles, and can help them discover why others may be lagging behind. 
  • Employee engagement and wellbeing. Predictive analytics has the ability to uncover issues that affect employee engagement. HR professionals can identify people who may be at risk of burnout or other mental health issues by monitoring factors like workload and working hours. HR can then provide targeted support and resources to those in need.

How does predictive analytics help human resources?

Predictive HR analytics assists organizations in anticipating challenges so they can:

  • Avoid risk
  • Reduce human error
  • Forecast the typical employee profile that’ll thrive in the organization 
  • Enhance recruitment practices
  • Encourage optimal work performance

Ultimately, predictive HR analytics helps HR leaders make crystal-clear decisions that can increase overall profit and nurture employee motivation, retention, engagement, and productivity.

What is the difference between predictive and descriptive HR analytics?

Descriptive HR analytics involves examining historical HR data to get a thorough understanding of what has happened within an organization and why.  

Predictive HR analytics, on the other hand, goes beyond this and analyzes historical data and past trends to predict what will happen in the future—giving an organization the chance to take preventive measures or to seize opportunities as they arise. Organizations that use both predictive and descriptive forms of people analytics set themselves up to achieve the greatest impact.

How do you implement a successful predictive HR analytics system?

HR leaders can spearhead effective predictive HR analytics using the following tips:

  • Define business objectives. HR leaders can collaborate with their teams to identify long-term company goals, with team members also helping determine the relevant metrics that support the achievement of these objectives.
  • Ensure a thorough understanding. Predictive HR analytics is a complex field, and HR professionals unfamiliar with data science can feel intimidated by it. However, providing consistent and diverse learning options for your entire HR team can mitigate their discomfort with the subject, elevate understanding, and encourage continual employee development. One way to do this is to encourage your HR team to familiarize themselves with the fundamental reasoning driving each analytics algorithm. HR can also involve a data scientist or bring an HR data analyst on board to ensure optimal functioning of the predictive analytics process. 
  • Address ethical considerations. To avoid unfair discriminatory treatment of employees, predictive analytics teams can pre-empt possible ethical issues that may arise. Companies could intentionally or unintentionally mistreat specific demographics within the workforce or perhaps show favoritism to certain team members due to illegitimate data-driven reasoning. Thus, transparently adhering to the company’s code of conduct and the HR code of ethics is paramount. People need to know that their employers are treating them fairly to feel engaged and motivated to thrive. 
  • Harness the power of predictive analytics. HR leaders can maximize predictive analytics by applying it to specific objectives. For example, HR leaders can incorporate predictive analytics to design an effective career development program that addresses competency gaps and future competency needs, allowing them to train people in their desired learning trajectory. 
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How can predictive HR analytics improve company culture?

Predictive HR analytics offers a way to help leaders make informed decisions that nurture an enthusiastic and high-performing workforce. Effective and ethical use of HR analytics can empower companies to identify, hire, engage, and retain quality professionals who align with the company culture and are excited to contribute to its growth.

Choosing the right predictive HR analytics tool for your business

Selecting the right people analytics software is a crucial step for HR professionals and organizations to take, so that they’re able to reap all the rewards of HR predictive analytics. 

The choice of tool should align with specific business needs, resources, and objectives. There are a few key things to keep in mind to be able to make an informed decision:

  1. Integration. Can the tool seamlessly integrate with your existing HR systems? Compatibility and ease of data transfer are essential for accurate predictive modeling.
  2. Scalability. The right tool will be able to expand your predictive HR analytics efforts as your organization expands.
  3. User-friendly interface. Look for tools that offer intuitive dashboards, visualizations, and reporting features, making it easy for HR professionals to access and interpret insights.
  4. Explainability. Ensure that the tool provides explanations for its predictions. That way, your HR team can understand why certain predictions are made and take appropriate actions.
  5. Data security and compliance. HR data often includes sensitive and confidential information. Make sure the tool adheres to data privacy regulations and has security measures to protect your data.
  6. Support and training. Consider the level of support and training provided by the tool’s vendor. Adequate training and ongoing support are essential for HR teams to effectively use the tool and maximize its benefits.
  7. Cost and ROI. Evaluate the total cost of ownership, including licensing fees, implementation costs, and ongoing maintenance expenses. Calculate the potential return on investment by estimating how the tool’s insights can positively impact HR outcomes and organizational performance.
  8. User feedback and reviews. Seek feedback from HR professionals who have used the tool and read reviews from other organizations in your industry. Their experiences can provide valuable insights into the tool’s strengths and weaknesses.

By carefully considering these factors, you can empower your HR team with a predictive workforce analytics tool that enhances decision-making, drives HR strategies, and contributes to overall business success.