As the era of technology continues to advance, data analytics have taken the forefront of the recruitment process by storm. Modern companies use data at every stage of the talent lifecycle to strengthen the decision-making process—and companies who don’t are getting left behind. In recent years, data analytics, sometimes called predictive analytics, have occupied a perpetual spot in the limelight of the HR news world. We hear about it all the time in the development of artificial intelligence, in the application of cognitive and behavioural aptitude tests, and so on. But how exactly is data employed in the practical setting? How often is it used and why is it used? This question can be explored by interpreting how successful corporations are integrating the use of data in extraordinary ways.
Using Data to Identify the Key to Employee Retention
According to a LinkedIn Talent Solutions Report, 69% of talent professionals believe using data can elevate their careers. This is why Nielsen Holdings, a global information, data and measurement company, believes it can use people data to reduce turnover. By analyzing attrition data from the past five years, Nielsen’s People Analytics teams discovered that employees with a change in job responsibilities due to promotion or lateral movement within the past two years were much less likely to leave. Acting on this information, Nielsen’s leadership focused on presenting high-performers and “at-risk” employees with ample opportunity to pursue new positions internally. This emphasis on presenting the opportunity for corporate movement helped Nielsen realize a 5-10% increase in annual retention of their at-risk employees.
Data Leads to Jumps in Hiring Quality
Every year, JetBlue Airways evaluates over 125,000 applicants for flight attendant roles by using psychological assessments, structured interviews, video interviews and work samples against eight target traits. Being “nice” was one of those traits. It made intuitive sense to JetBlue leadership that flight attendants should be kind to passengers. But by analyzing customer feedback data, it was brought to JetBlue’s attention that “nice” took a strong backseat to “helpful”. Customers far preferred a helpful attendant to one that was nice, allowing JetBlue to cater its employees’ traits to the needs of its customers. In fact, being helpful can balance out the effect of a flight attendant who is not nice. The results of this small change to recruitment criteria were astonishing. A rise in employee engagement and retention meant that employee absences decreased by 12%, an important factor in preventing delays and cancellations of flights. JetBlue also reported a small increase in customer satisfaction, a win-win situation for all.
Knowing Exactly Where to Recruit Talent
The employee recruiting process has come a long way since the early days of gut-based decision making. As more companies are using data analytics to their advantage, hiring is becoming increasingly scientific. But that does not mean those who do not have a propensity for numbers should be intimidated. At the end of the day, behind all the numbers and the spreadsheets, recruiting talent is still about the people. It is people who drive the hiring process, not numbers. But data-driven recruiting, if used the right way, can amplify the results of even the most robust recruiting processes. By taking the generated data and asking relevant questions based on the needs of the business, people talent teams can push their hiring systems to a new standard. Managers should not be afraid of implementing data analytics into their businesses. Data is becoming a top tool that is affecting the way thousands of businesses hire employees. This is because data drives results in a concrete, factual manner. Take the Predictive Index System® for example. At Predictive Success, we pride ourselves in offering behavioural and cognitive assessments that are driven by years of scientifically validated data and research. To find out how you can employ our solutions in your employee recruitment efforts, click here.
Matthias is a social media intern at Predictive Success. He is currently a second-year student pursuing a Bachelor of Commerce at Queen's University. He spends his mornings brewing the perfect cup of coffee... or cups of coffee. Is there such thing as too much coffee?