The global COVID-19 pandemic ushered in many structural changes within our society, chief among them being the Great Resignation. A survey conducted by the Pew Research Center found that the main reasons why employees have quit during the pandemic include low pay, a lack of opportunities for advancement and feeling disrespected. The worker shortage has been felt everywhere from the gas station to the airport, and also exposed painful truths about worker inequality.
But the Great Resignation didn’t start with the pandemic. Rather, it’s the continuation of a trend in rising quit rates that began more than a decade ago. There are five factors at play that have contributed toward rising quit rates in the US: retirement, relocation, reconsideration, reshuffling, and reluctance.
“Reshuffling” is the notion that not all workers who quit are leaving the labor market; some are moving among different jobs in the same sector, or even between sectors. And many are quitting for new and better jobs in a phenomenon known as the Great Upgrade.
As people move toward more skilled jobs, they need to ensure they can keep up with expectations. A study by Tableau and Forrester found that 82% of decision-makers expect their employees to have basic data literacy. And organizations that commit to data literacy efforts see wide-ranging benefits like enhanced innovation, greater customer experiences, better decision-making, reduced costs, improved retention, and increased revenues. But how can employers and employees alike ensure that they have the chops to do the job, and do it well?
(Rafal Olechowski/Shutterstock)
Investing in Data Skills: It’s Worth It
One step that can help set a company up for success with respect to data literacy programming is to recognize that data proficiency levels depend on an employee’s role (e.g., a sales representative does not need to know as much as a data scientist). While in-house training can be an effective way to cut costs, such programs may not be comprehensive enough. Outsourcing this training to consulting partners, technology vendors, data literacy specialists, and others can supply a wide variety of programming for a variety of different roles and business needs.
Strengthening hard skills is an important way to close the data literacy gap, and the effects benefit more than just companies: becoming more data literate can create upward mobility and career advancements and add 11% to an employee’s salary.
Last year we conducted a survey with ESG about how advanced data skills affect Splunk practitioners’ career prospects. The survey revealed that companies continue to value employees that can use data to answer business questions. Below we’ll outline how data skills positively impact employee compensation, job security, and preparation for a cloud-first future.
The Impact of Data Skills
1. Compensation
Salary has overtaken work/life balance as the top determining factor of job satisfaction. This is unsurprising, as financial security allows employees to save, enjoy leisure activities, plan for the future, and comfortably meet financial obligations like mortgages and rent. Employees that learn how to use analytics tools, ask questions about their data, and get actionable answers from their data will be more valuable to their employers and command higher salaries.
(Na_Studio/Shutterstock)
2. Portability of Skills = Increased Job Security
The most frequently reported benefits related to job security in the survey are the respondents’ effectiveness and portable skills. Given that COVID-19 is here to stay, the importance of having in-demand, portable skills in an uncertain world and volatile job market can’t be understated. But the importance of the portability of skills was on the rise before COVID-19. Gone are the days when employees used to pledge loyalty to a company for decades. The International Labor Organization (ILO) estimated that workers between the ages of 18 and 38 changed jobs ten times in 2010. With more widely relevant and recognized skills, workers can improve their employability and adaptability, but the benefits don’t stop there: portable skills contribute to human development by empowering people to make full use of their skills and talents. This is particularly impactful for women, who tend to be employed below their skill level.
3. Preparing for a Cloud-First Future
COVID-19 has rapidly accelerated digital transformation across the enterprise, and one key driver of digital transformation is the increasing use of cloud services. Data practitioners helped accelerate cloud service adoption as companies found new ways to support the increasing number of remote workers, the continued, exponential growth of data, and finding new channels and ways of engaging with customers during a global pandemic – all skills that go across data vendors and have a longer shelf life than deep data skills related to a single platform. This is especially important as 90% of large organizations are opting for a multi-cloud approach.
The proliferation of data has allowed businesses to become more strategic and improve revenue and operational efficiencies. Learning technical skills (like SPL) can improve a company’s bottom line while simultaneously creating economic gain and advancement for employees. As workers build more portable skills, they not only help themselves and their employers, they also improve labor market efficiency by lowering transaction costs in job search and recruitment, as the ILO study showed. However, it’s important to note that training employees with hard skills is not a panacea; there are many soft skills that are important to help people realize the full value of working with data, like collaboration, curiosity, critical thinking, and storytelling.
About the author: Brittany Coppola is a Product Marketing Manager on the Platform team at Splunk, where she focuses on pricing and the admin experience. She’s passionate about harnessing the power of data to help organizations solve their most pressing problems. Prior to joining Splunk she worked in edtech and fintech.
This article originally appeared in Datanami.
