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10 Big Data Trends You Should Know About For 2022
Rick Whiting
From predictive analytics and data fabric architecture to data observability and data governance software, here’s a look at 10 big data trends and technologies that solution and service providers need to be aware of in the new year.
Expanded Use Of Predictive Analytics To Overcome “The Great Resignation”
Just as the COVID-19 pandemic has created supply chain problems for businesses, it also triggered what has become known as “The Great Resignation” where millions of people have quit their jobs to retire, change their life direction – or because they were dissatisfied with where they were working and felt they could do better elsewhere.
Data analytics has traditionally been applied to human resource management for basic reporting tasks such as compiling employment data for tax purposes. But some forward-thinking businesses and organizations have begun applying the same kind of predictive technologies used to monitor customer churn to identifying key employees that may be on the verge of quitting by analyzing data around compensation, job satisfaction, productivity and other metrics.
Look for that trend to accelerate in 2022. “As organizations grapple with employee turnover amidst the ‘Great Resignation,’ they will increasingly look to predictive analytics to help save the day,” says Nick Curcuru, vice president of advisory services at Privitar, a developer of data privacy management software.
“By embracing predictive analytics, organizations can identify key trends in employee engagement and key moments in time to intervene, enabling them to take action and possibly save relationships that might be on the brink. It can cost as much as four times an employee salary to replace someone as it does to keep them, so being able to prevent churn can provide a huge value to an organization,” Curcuru said in an email.
But Curcuru cautions that HR analytics efforts must include safeguards for both employees and their personal data and management must be transparent about policies to protect data and its ethical use.
