Why big salaries alone won’t close the analytics talent gap
A recent article in Information Management shared March 2018 data from Salary.com ranking the 25 highest-paying jobs in IT, software development and data management.
All positions on the list, ranging from Chief Information Officer (CIO) to IT Quality Assurance Director, are in the management ranks, with most holding the title of director or above and earning, on average, more than $150,000 a year.
These numbers validate the predictions of many 2018 forecasts that IT and data professionals would earn more than their peers in other areas of business. While compensation rates vary by region and industry, the trend is clear that working with technology garners a hefty paycheck.
Moreover, among tech jobs, data analytics is at the very top. Glassdoor's annual "50 Best Jobs in America" survey ranks Data Scientist as No. 1 for the third consecutive year.
Yet, in the face of these enticing trend, the U.S. may soon confront an analytics talent crisis. Management firm McKinsey predicts a 50 to 60 percent gap between the supply and demand of analytics talent within the year.
Signs are this situation will worsen. Per a 2017 report by Forrester Research, the future workforce will require fewer IT workers and more data analysts. But, according to the study’s author, many officers believe their staffs lack sufficient skills in the areas of analytics and data management.
If McKinsey doesn’t expect data science talent to come from outside organizations, and Forrester doesn’t see talent developing inside existing enterprises, then how will we cultivate analytics talent for tomorrow’s business needs? Here’s how: By working to attract more teens to data science careers today.
"Tweens and teens" are the solution. The cohort currently ascending from middle school through high school already makes up a quarter of the U.S. population and will account for more than 20 percent of the workforce by the middle of the next decade.
What’s more, research suggests that many in this group have the temperament to become more than technicians; they show the foundational character of true technologists; they have an optimal mix of hard technical skills and relationship “soft skills” acumen.
We expect that workers with a technologist’s mentality will be the vanguard of digital business evolution for companies of all shapes and sizes across the country along a broad spectrum of industries for decades to come.
We do not expect, however, that these young people will adhere to one of the greatest myths about technology careers, which is that money is the main benefit of a tech job.
We know money isn’t the biggest driver for teens choosing a career, because we asked them. In our 2015 Teen Views on Tech Careers survey, teens ranked having a job they love and helping other people as their prime career motivators. Like scientists, mathematicians and engineers, people working with business data like to solve problems. Driven by curiosity and empathy, they want to use big data to alleviate homelessness, for example, or deliver analytics to people seeking greater economic opportunities.
But imagining how their work can have an impact on society is tricky for young people to visualize. That’s why data-science role models are critical to shrinking the analytics talent gap – and my organization is dedicated to facilitating and amplifying their influence on teenagers.
Through curricula, projects, partnerships and mentorship, CompTIA’s NextUp initiative aims to tap into the passion today’s teens have for technology, spark their curiosity and build a generation of technologists for tomorrow.
Our research shows most of today’s teens want a job they love—and money isn’t the biggest driver for them. Working in a tech career -- especially one working in field like analytics that gleans new insights into persistent social problems – has the promise of so much more than a good salary. It has potential to make a lasting difference. And we believe the best way to demonstrate that fact is for data scientists to let young people sample the work of data science—and see how they can not only change a business, but a world.