Originally published on HR.com, the foremost, trusted industry resource for education, career development, networking, and compliance.

Tools that leverage artificial intelligence (AI) have come a long way with regard to workforce analytics. When integrated, combining AI with workforce analytics allows businesses to integrate disparate data systems and use predictive data to make business decisions based on their greatest asset: their people.

Many HR Departments are managing numerous disparate talent-related systems that require separate logins, data management processes, and reporting tools. Gathering this information for executive management to make strategic business decisions is nearly impossible and prone to human error. More than 70% of companies now say they consider people analytics to be a high priority.

Given the costs of sourcing, hiring, onboarding, managing, and replacing employees, executives need accurate analytics often. The key to solving this data issue or lack thereof is by using workforce analytics software powered by artificial intelligence. These combined, give businesses a data-driven approach to people analytics allowing them to make important financial decisions.

Let’s dive into a few additional ways AI can help power workforce analytics and how it benefits organizations.

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AI Powers Workforce Analytics

Sourcing, hiring, onboarding, managing, and replacing employees is challenging and costly. Given the steep costs in each scenario, the executive suite is in desperate need of one system that automatically finds the important data that truly matters and allows them to make impacting decisions that benefit the business. As data-driven HR practices are becoming common among business leaders, it’s important to understand the impact these tools can truly have.

Using a workforce analytics tool which leverages AI gives the ability to:

  1. Address workforce productivity changes with workforce analytics.
  2. Aid proactive HR strategy and organization.
  3. Understand the performance, demographics, retention rates, payroll gaps, etc. of your current employees allowing you to make more informed business decisions.
  4. Source areas where efficiency can be improved with automation. While workers are an asset to a company, sometimes the tasks they do can provide minimal returns.
  5. Improve employee’s engagement by understanding their needs and satisfaction. The tool will pull data from every interaction with employees from the time they started to present day and will help create a better picture for retaining them.
  6. Create better criteria for HR and hiring managers to provide a better hiring process overall.

People Analytics Powered by AI Allows Business to Lower Turnover Rates

Human Resources is uniquely positioned in the organization to ensure the workforce is aligned with the needs of the business and at an optimal cost. Now, more than ever, business leaders need strategic insight and the ability to model how turnover trends impact revenue and profits. And, they need this information to be accurate and in real-time.

Traditional HR analytics examine employee data across different dimensions such as department and demographics to identify similar patterns within metrics like turnover and retention. Conclusions are then used to formulate decisions that affect the business.

Predictive workforce analytics does this by going a step further with artificial intelligence and using the evidence from traditional analytics as inputs for advanced techniques like machine learning. This data provides forward-looking measures such as a “flight risk,” which quantifies the likelihood of an employee’s leaving an organization within a certain period of time and the potential causes.

Predictive workforce analytics also identifies hidden connections between key factors contributing to employee turnover. The main variables the systems look into include pay, promotions, performance reviews, hours of work, commute distance, and relationship with a manager. Businesses also use external data such as labor market indicators, social media, and current economic scenarios as data variables while formulating a hypothesis and building models for retention. HR teams and managers use these findings from the report to ensure actions are taken to help retain employees.

Automatically Identify Internal Candidates Based on Workforce Analytics

Predictive workforce analytics powered by AI allows businesses to indicate the top talent to fill the open positions, making sure the HR department has the data they need to promote the right talent. Not only are you filling those vacancies faster, but you’re doing so effectively and at a lower cost. Breaking it down further, these tools aren’t helping the HR department performs “talent rediscovery” searches on previously known candidates – it’s compiling data from internal candidates to rank them based on their aptitude, experience, and other indicators which help predict if they would make a good fit in the open position or not.

AI ensures this process is accurate and compiled faster by integrating with every system and showing you the data that really matters to ensure you’re making the most informed people decisions. Who’s performing the best, what’s their performance been like the last three years, how many raises have they received, and ensuring this data is used to make better hiring decisions are just a few features on how this can be applied to internal hiring.

Analytics is not a thing of the future – they are adapting, changing, growing, developing, and strengthening companies across industries. And while some companies may not be applying them yet, those companies that want to make an impact on retention and maximizing talent management will implement workforce analytics into their company structure to gain a competitive advantage within their industry sooner rather than later.