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How to Use Predictive Analytics Tools for HR

Read Time: 3 minutes

In recent years, human resource teams have begun leveraging predictive analytics (PA) to automate certain tasks while helping employees complete their work at a higher level. From improving recruitment to helping companies overcome bias, predictive analytics tools for HR are playing an integral role in creating more balanced work environments far and wide. Today, we’re taking a look at several key ways businesses are using PA to improve their HR operations.

Improving the Recruitment Process

Some major players in the tech world have adopted predictive analytics to bolster their recruiting efforts. For instance, Google’s computers generate questions for prospective employees with the goal of finding candidates who will fit the organization’s culture. Then, candidates are asked these automated questions during interviews. An algorithm analyzes the answers to these questions and measures their likelihood of succeeding as a Google employee.

Microsoft has adopted a similar approach to examine how likely it is that a current employee might quit. In this case, a marketing professional leverages predictive analytics to determine who may be on their way out, considering factors such as their length of time with the company, performance reviews and more. If a good worker looks like they may leave the company soon, then the company can focus their retainment efforts by sweetening their employment package or offering them different responsibilities.

Using Social Media to Determine Competency

While a candidate’s professional skills are important, their social persona matters, too. A 2012 study used PA to garner an idea of how well a person would do at an organization and how likely the company is to hire them based on their Facebook profile. The PA model was able to predict 8% of the ways in which managers rated the job performance of these workers. While 8% may not seem like that large of a number, the system is still effective in examining an underrated part of a worker—the way they relate to co-workers and what they add to the company socially.

More HR departments are taking note of such technology, using predictive models that consider personality traits in addition to IQ tests and structured interviews. Social media platforms help with this because they provide a wealth of information about what matters to a person. As social media becomes a larger part of our lives, predictive analytics can use this information to help businesses find the right candidates.  

Eliminating Bias in the Workplace

Predictive analytics engines can also strengthen a company’s culture by reducing bias during the interview and vetting process. Financial giant Morgan Stanley is using a PA system that scans a candidate’s resume and cover letter to identify their strengths. Then it creates targeted interview questions based on these qualities. When people create interview questions, they may be swayed by personal bias—whether conscious or unconscious—to ask questions that lead in a certain direction or fail to accurately account for a candidate’s real strengths.

In fact, the Social Mobility Commission has discovered that multiple industries often don’t hire talented, young workers who hail from “less advantaged backgrounds.” Instead, some of these companies only hire graduates from a selection of top universities, usually middle- and higher-income candidates. A PA program, however, doesn’t care who your parents are. By considering candidates from a neutral perspective, the technology ensures that everyone is assessed based on their merits rather than their status. And because PA encourages companies to consider a range of potential employees, it tends to create a more diverse workplace.

This approach also helps to ensure that candidates are accurately representing themselves. Potential hires may be tempted to present themselves as more experienced or skilled than they really are, but PA algorithms can use data to accurately sort fact from fiction.

Predictive Analytics Tools for HR

Thanks to predictive analytics tools, HR departments are able to better assess whether a candidate is the right person for the job. Plus, current and future generations of workers are more likely to be hired at a place that truly values them. These systems are recognizing the unique strengths linked with a person’s social prowess, discipline, cultural background and drive. With this technology, more people will find their right match in the professional world as HR teams around the country adapt to a new future.

Is your HR team ready to take advantage of predictive analytics technology? If so, then reach out to the team at 7T. Our data governance platform, Sertics, enables data lake creation and integrates with leading data visualization and analytics tools. We also specialize in a host of other cutting-edge technologies, including augmented reality, virtual reality, Internet of Things, machine learning, artificial intelligence and natural language processing.

7T is headquartered in Dallas, but we are also happy to serve clients in Austin, Houston, and beyond. To discuss your PA project, contact us today.

Reach out to our team today!

Shane Long

As COO and President of 7T, Shane Long brings experience in mobility that pre-dates the term “smartphone” and the release of the first iPhone. His work has helped revolutionize the growth of mobility by bringing to market one of the first graphics processors used in mobile phones, technology that after being acquired by Qualcomm lived well into the 4th generation of smartphones, as well as helped pioneer the first GPS implementations in the segment. With a strong engineering and business background, Shane understands how the rise of mobility and Predictive Analytics is crucial to greater business strategies geared toward attaining competitive advantage, accelerating revenue, and realizing new efficiencies. As the leader of a B2B mobility solutions provider, he partners with business leaders including marketers and product developers to leverage enterprise mobile applications, big data and analytics, and mobile strategy.

Shane earned a B.S. at Texas A&M (whoop!) and studied mathematics as a graduate student at Southern Methodist University.


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