Talent Analytics demands good data quality

Hiring decisions are about to become more high tech, according to Forbes. While human resources professionals previously deemed reading through resumes and selecting the most qualified candidates good enough , the rise of big data is challenging the reliability of individuals' gut instincts. Some firms are instead turning to the new tactic called talent analytics; and for good reason, Forbes points out, explaining that in some cases, the data quality and metrics HR teams use may be off the mark. 

Qualifications that don't actually matter that much
For instance, when one financial services firm was deciding which sales professionals to hire or promote to advanced roles, they considered the following criteria - college GPA, reference quality and school ranking, the source adds. But, it turns out that while these factors may look good on paper, they weren't actually the best indicators of superior performance on-the-job. 

The company performed a statistical analysis and found that people who deliver a resume that is free of errors and grammatical mistakes, have successfully completed university studies and obtained a degree, boast previous experience in high-ticket sales positions and advanced in roles that required them to juggle multiple tasks with limited guidance were stronger signals of success, Forbes adds. After implementing the new considerations in recruiting processes, the firm saw revenue jump $4 million. 

Identifying more effective metrics
More HR departments will need to start leveraging big data if they want to keep up with other teams and demonstrate value to decision makers, according to Resource Nation. This is especially the case with companies that are looking to fill highly selective roles. 

To develop better metrics that indicate success, HR can implement assessments before hiring decisions are made and after new employees are on-boarded, the source adds. With benchmarks in place, companies can identify which traits, special skills or background experience are tied to long-term success in various roles. Ultimately, these can be used to spot the best prospects during screening processes to ensure positions are always filled with the best candidates. 

However, businesses must also pay attention to data quality if they want their talent analytics programs to be successful. If information collected and compiled is incorrect, HR departments might mistakenly consider only individuals who possess certain accolades that do not actually amplify their ability to get the job done, and exclude other talented prospects from their pool of applications.