Data-Driven Methods Can Help to Address the Issues of the Great Resignation

    Wide-scale job losses were one of the most devastating blows of the Covid19 pandemic on the economy. Overnight, the job market and the industry plunged into deep uncertainty that resulted in mass layoffs, millions of job losses, and those who could save their jobs clung to their roles for survival. No one knew the way forward, and it appeared as if people would be too happy to regain employment after the revival of the economy. However, as the economy opens up gradually and the signs of recovery give hope of regaining normalcy, a peculiar phenomenon is taking place in the job market. Many people are now leaving their jobs, which experts term as the great resignation. Learning lessons from the prolonged detachment, employees are –re-thinking their careers which seems to be one of the most significant ripple effects of the pandemic

    What the Numbers Say About the Great Resignation?

    Here are some numbers that should help teach the extent of the mass resignations that resembles an exodus. Based on the data-driven method of analyzing the phenomenon, the US Bureau of Labor Statistics revealed that the resignations were at their peak in April 2021 when the economy started recovering. In July 2021, the resignation figure of the US employees touched 4 million. The high rate of resignation continued through the following months, and as of the end of July, there were 10.9 million open jobs. Employers have a torrid time retaining employees.


    How does the Picture Look Like?

    The phenomenon of people re-thinking their careers at a mass scale is not only unprecedented but contrary to our expectations. The pandemic-induced job losses made us believe that those affected would be keen to retain their jobs when the opportunity comes. On the contrary, now that the economic revival has begun and jobs are back again, it is not attracting employees as expected. Instead, most people are looking forward to changing their jobs that triggered large-scale resignations that indicate a significant shift. A record number of open positions across companies have given experts enough reason to explore the cause for the change. Various teams of experts are turning to data-driven techniques to analyze the cause and understand the problem, 

    What is Driving the Shift?

    A research team led by Ian Cook collected and analyzed data from 4000 global companies employing 9 million employees to gather insights about the trend of resignation. The study revealed two broad trends – healthcare and technology industries experienced the highest number of resignations, and those in the middle of their career are mostly leaving their jobs.

    What can Employers do to Arrest the Trend?

    To address the issue while trying to reduce the rate of turnover, employers must use data-driven techniques that provide valuable insights. It can point to the high-risk group of employees most prone to resigning, reasons for quitting, and actions o take to retain them. Although the details will differ by organization, the following measures should help all organizations address the problem effectively. 

    Ascertain how big the problem is – Before looking for solutions, you must first determine the scope and impact of the problem. First, ascertain the retention rate or the turnover rate by dividing the number of resignations in a year by the average number of employees during the period. You can use the same formula to understand how many of the voluntary resignations are due to firings and layoffs.

    Next, evaluate the impact of the resignations on the critical business metrics. Resignations result in losing skill sets that can adversely affect the quality of work, turnaround times, and deadlines, which can impact the bottom line. Similarly, determine the impact of increased turnover on other key business metrics.

    Identify the Root Causes.

    Next, doing some data analysis will help understand what is causing employees to leave the organization. Metrics like compensation, size of pay increases, the time between promotions, training opportunities, performance, and tenure can help identify blind spots and trends within the organization. Further segmentation into demographics, location, and function will provide more insights.

    Organizations can develop tailor-made employee retention programs to know the causes of the great resignation.

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