What is Predictive Analytics in HR?

Definition and examples of Predictive Analytics in HR
By Abhishek Kathpal Updated 03 August, 2022

Predictive analytics is not exactly a new concept. It gained prominence when a certain baseball team applied it to create a history in sports. Afterward, predictive analytics saw a wide adoption rate in the sporting world; however, it didn't stop there. Data analytics has left a mark on how organizations make decisions in the business world. Therefore, it is only fitting that HR employs predictive analytics to drive decision-making. So far, this has been a game changer in organizational growth.

What is Predictive Analytics in HR

Predictive Analytics in HR meaning and definition

Predictive analytics is a rising technological solution that HR leaders and managers use to forecast future outcomes by analyzing past and present data. It involves the use of data mining techniques to predict specific outcomes that empowers HR with the ability to make data-driven decisions. Using predictive analytics tools and software, HR leaders can take historical data in raw form and transform them into valuable information.

How Does Predictive Analytics Work?

Predictive analytics functions digitally, probing data to organize, analyze, and extract information to identify correlations and patterns. It transforms raw data into interpretable information that enhances decision-making.

Why Companies Should Care About Predictive Analytics in HR

Risk and uncertainties are at the core of all businesses and organizations. To reduce these uncertainties, organizations try to predict and anticipate challenges. Predictive analytics aids in anticipating these challenges so companies can:

  1. Set down a more equitable reward system. Using predictive analytics, companies can forecast potential skill gaps. Putting in place a fair reward system can reduce the employee turnover rate as employees feel valued. Hence the desire to quit is diminished.

  2. Improve decision-making. Using predictive analytics, companies make more accurate data-driven decisions that increase productivity, save cost, and boost employee satisfaction.

  3. Put in place a solid strategy for talent identification and retention. By forecasting future vacancies, HR heads can establish systems to recruit quality workers and retain outstanding ones.

  4. Avoid risks regarding recruiting the right talent for the company.

  5. Minimize error.

  6. Forecast future skill gaps and lay down strategies through them.

  7. Improve productivity.

Implementing a Successful Predictive Analytics in HR

Establishing effective predictive analytics in HR is not an easy task. However, it is not impossible too. HR heads can initiate functional predictive analytics through these tips:

  1. Define business targets: HR members should work closely with their teams to set long-term SMART company goals. In addition, relevant metrics through which these goals are measured should be put in place.

  2. Address Ethical Issues: Knowingly or unknowingly, organizations could show favoritism or treat certain demographics of employees in the workplace unfairly. Predictive analytic teams should not use discrimination-building data to avoid discrimination and unfair treatment. Employees need to feel a sense of acceptance to feel valued and motivated.

  3. Capitalize on the power of predictive analysis. HR heads can harness their full power by applying predictive analysis to specific goals. For instance, HR heads can incorporate predictive analytics to measure employee output against the level required, allowing them to have an insight into workforce productivity. They can then make decisions and establish strategies based on this information.

Maintaining Company's Culture Using Predictive Analytics in HR

Predictive analytics drives organization leaders to make evidence-based, accurate decisions that foster employee growth and productivity. Using predictive analytics ethically and effectively, companies can outsource, acquire, and retain the right workforce that aligns with the company's culture. A culturally homogeneous workforce can be a game-changer in ensuring a near-perfect working environment. In addition, HR-management discussion regarding employees shifts from cost-based to investment-based as they have a long-term overview of what they need.

The Other Side

Many analytics systems measure specific characteristics that are irrelevant to individual job performance. Keeping data on aspects of employees' life and lifestyle and using them to drive decisions could lead to unethical decision-making.

Employees may be asked, "What type of pets do you like? What is your favorite food?" Sometimes, employees' hometowns are used to predict specific outcomes. For example, employees raised in urban areas are more likely to quit their job or roles than employees from rural or suburban areas. Although not against any laws, judging people over data points they have little or no control over is unethical.

Such toxic situations are avoidable by ensuring that only ethical information influences the data-driven decisions of predictive analytics. Therefore, to ensure predictive analytics is efficient, it has to eliminate bias by considering ethics.

Practical Case Study of Predictive Analysis in HR

AMC theatre recognized the importance of employees as the face of a brand in customer service. The company used analytics and profiling to identify candidates to get more qualified and high-performing customer-service representatives. Ultimately, they experienced a reduced turnover rate, better customer satisfaction, and higher employee engagement. May other companies and employers employ predictive analytics in in-house decision making, brand building, etc.

About the Author

Abhishek Kathpal

Abhi is the co-founder at Longlist.io. Funded by US based OnDeck, Longlist is currently enabling 50+ businesses to increase their candidate and client reach outs, automating the workflow across stages.

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