Whatever Happened to the Workforce of Tomorrow?
Coding boot camps, engineering campuses, and online tech courses have been available for years, yet the struggle to match tech jobs with candidates continues.
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When industries began to go digital and turn data into gold, the need arose for more than just a tech savvy workforce.
Data scientists, software engineers, and a host of other IT professionals were needed to build up infrastructure and drive the next innovations. In response, high school and college curriculum, trade schools, STEM and STEAM programs, coding boot camps, and private academies ramped up the training of the theoretical workforce of tomorrow.
New campuses were planned, online courses surged, and many career changers and new job seekers were presented with the possibility of big salaries -- if they learned how to work with 0s and 1s.
After reporting on such efforts for more than a decade, writing stories about multiple campaigns to train up potential tech employees, it is easy to wonder why there is a hiring crisis now.
With respect to Alan Moore’s acclaimed Superman story “Whatever Happened to the Man of Tomorrow?” about the disappearance of the titular superhero, what became of the tech workforce of the future?
It may seem a smug oversimplification, but with so much attention focused on seeding the employment pool with skills for the digital age, how can there be a tech hiring crisis? There should be a vast tech workforce by now, ready to push industry and commerce to new heights, right?
Reality is more complicated than well-intentioned plans.
Is it possible to teach everyone in the country how to code by the time they graduate high school? Perhaps, with concerted, consistent effort, but that alone is not enough to maintain a tech career. The needs of many employers can shift dramatically, which naturally can create gaps between classroom-based career expectations and real-world demand.
Looking back to 2012, New York City was trying to build momentum as an emerging tech hub. That was the year the Cornell Tech applied science and engineering school set up shop in temporary space at Google’s New York headquarters in the Chelsea neighborhood. A few years later, the permanent campus on Roosevelt Island would open its first buildings with the entire project expected to be complete by 2037.
Cornell Tech is one of numerous efforts to train or skill up the workforce for this era where “software is eating the world” -- as Marc Andreesen once said. That was a popular mindset until the next paradigm shift. AI, data analytics, edge computing, privacy management, energy consumption, and the possibilities of quantum computing have evolved the tech scene.
And that is the challenge of trying to keep tech career curriculum abreast of technology movements. As fast as organizations such as the Flatiron School, Stiegler EdTech, Girls Who Code, Tech Elevator, General Assembly, and Black Girls Code adapt education to the market, the goal posts can move. Then there is the possibility of companies holding out for “rockstar” candidates with experience from major tech companies rather than give up-and-comers a chance.
In the slides that follow, experts that include tech developers, educators, consultants, and investors discuss how tech hiring compares with the training of the workforce -- and what might be done to address some of the disparity.
“A decade ago, tech skills would probably be synonymous with software development -- programming,” says Brock Solano, managing director with the human capital advisory of KPMG professional services firm. “Today, that’s the vernacular that perhaps we’re getting tripped up on when we say there’s a tech crisis.”
There is no shortage of developers and programmers, he says, but tech skills in such areas as cybersecurity, data science, machine learning, virtual reality, and blockchain are often thought of when discussing a limited supply of talent. There are opportunities for professional development within associations, universities, or outside training sources, Solano says. What companies want is a combination of technical understanding, such as cybersecurity, in the context of industry, business, and production. “That is, I believe, what we mean when we say there’s a dearth of individuals that can pair the two,” he says.
Companies should embrace the idea that they will build such talent internally, Solano says. That could lead to data scientists in the finance segment of an organization or an understanding of how to incorporate AI and machine learning in procurement. “Being able to build that talent from within is going to be crucial,” he says.
Demand in recent years for data scientists set off an eagerness to enter the field, says Moses Guttmann, CEO of ClearML, a developer of a MLOps (machine learning operations) platform.
“A lot of people started calling themselves data scientists,” he says. “We even saw a bunch of Medium posts on how to get into data science.” This led to a rush of junior data scientists emerging in the market, Guttmann says, but that abundance could also make them fodder for layoffs from tech giants. Laid off data scientists might trickle down to businesses that wanted personnel with such skills, he says, but found it hard to compete previously with tech giants on salary.
During the recovery years after the Great Recession of 2008, numerous courses emerged for people to change careers to get into tech, Guttmann says. Since those days though, certain types of technical proficiency have cooled while others have grown white-hot. For example, expectations were high for Java as a language, he says, with its proliferation in the backend yet demand declined within the past 10 years. “We see Python and Go really taking over that entire field,” Guttmann says. “They’re relatively different from Java.”
He believes more consistency is coming, possibly within the next year, in terms of technology used by industry and related skillsets sought. “We are seeing some kind of maturity in the market,” Guttmann says. “Everyone kind of stabilized themselves on very specific frameworks and sets of ways to work.”
“The demand for talent, in general, for the last half a decade has outpaced the development of the talent,” says Sachin Gupta, CEO of HackerEarth. The rise of MOOCs (massive open online courses) and coding bootcamps led to a buildup of talent that can perform rapid application development, he says. While that specialty is vital to traditional transformation, other areas of technology have increasing needs for scarce talent.
“Maybe every business is becoming a data-driven business, so everybody now needs data scientists and machine learning engineers in their team,” Gupta says. But some training courses may fall short meeting that demand.
“It’s not something that one can learn in a bootcamp or in a period of six to nine months,” he says. “These skills develop over a period of time. We would like to be able to compress them, but truth be told it develops over a period of time through education and working in the industry.”
Cybersecurity and AI, Gupta says, are also areas with a limited supply of skilled professionals despite significant investments in talent development.
There were two types of hiring big tech companies tended to pursue, he says. “One is they resorted to hiring really smart people and then training them internally but not through formal training programs.”
Looking at Meta, Google, Amazon, Gupta says the rigors of their processes are so strong, and the exposure to scale is so wide, that anyone of keen mind would develop useful skillsets. He says abbreviated courses and programs can give tech careers a jumpstart, however practical on-the-job training remains crucial. “To be able to write code that scales across hundreds of thousands of users requires exposure to those kinds of systems,” Gupta says.
The other type of hiring he saw from Big Tech was for experienced people already armed with skills. “While a Big Tech company can afford to hire a lot of people at the junior level, and then skill them up, they also need a strong middle layer,” Gupta says. “That’s where everybody has struggled.”
When on-premise IT began the transition in the early 2000s to the cloud, the job market and skills changed as well, says Mark Angle, chief cloud operations officer with OneStream Software. He expects such change to continue with the growing need for cloud native technologies. “Technology is one of those fields I feel is available to almost anyone who has the initiative,” Angle says.
While training and experience remain essential, he says it is important for new hires to be excited to learn more on the job. “If you can get someone with the right technology mindset who is interested broadly in technology, then you are going to be much further ahead than getting someone who went through a specific program,” Angle says, referring to someone focused on just fulfilling a specific task to the minimum of what is needed.
Exploring partnerships between companies and education programs to provide real-life experience can help further develop tech talent, Angle says. “You can put something in the lab and make it work, but that doesn’t necessarily mean you understand how to make it work for hundreds of thousands of people in the real world.”
“The focus on technology within the cybersecurity industry is one of the key enablers of its success and that has also been one of the reasons why it struggles,” says Jack Danahy, vice president of product and engineering with NuHarbor Security.
Cybersecurity skills can be perishable, he says, because the technology that supports cybersecurity must also support rapidly changing environments in terms of infrastructure and application technology. In effect, the target is always in motion. “The threat landscape changes because the attack community changes what they’re doing all the time,” Danahy says.
There can also be issues of matching the security knowledge with operational needs. “The focus on understanding technology to solve cybersecurity problems has created a group of practitioners who are focused on the tech but don’t understand the problem they’re trying to solve,” he says.
Training people just to get up to speed on technology does not always translate into a security advantage for the companies they work for, Danahy says. Instead, training should aim to better connect with real world application. “Security is never an absolute,” he says. “That’s one of the places where educationally sometimes as an industry we fall down.”
For instance, security personnel might not understand why other people do not patch software immediately, Danahy says, or why they do not enforce hard password requirements and other stringent security measures. This can stem from a lack of awareness of healthy business activity that intense security could interrupt in the process.
Cybersecurity rockstars of tomorrow, he says, should understand the healthy state of the businesses and organizations they work in, then slide in appropriate security without disrupting business.
“A lot of the genesis of the technology that we built here is really because there’s such a major skills gap,” says Raj Datta, CEO of oak9, a developer of a security as code platform for cloud. Developers are not expected to keep up trends and technology in security and vice versa, he says. This has also meant there is a shortage of available security engineers, who can be rather expensive to hire.
“There will always be some type of technical gap,” Datta says, between curriculum that tech talent is taught and real-world needs. As new languages and new ways to code continue to emerge, he says it can help to hire individuals with the aptitude to keep learning -- not just the skills sought at the moment. Datta says oak9 hired some of its staff from tech bootcamp programs and those hires were able get rolling quickly. This benefitted his startup at times when it did not have much funding and leeway to chase down experienced, and more expensive, IT talent.
The mercurial nature of tech development and deployment makes it a hard target to teach for, says Pasha Maher, COO of Stiegler EdTech. “It becomes really challenging for traditional education systems to meet the rigor and demand.” One of the dilemmas he faces is when heads of departments ask how they can find tenured professors in blockchain or Web 3.0 -- areas of technology that are still rather new. “It’s almost an oxymoron to even try and pursue,” Maher says.
He sees employers becoming increasingly involved in the curriculum conversation as well with Google certifications and Microsoft’s ownership of LinkedIn and LinkedIn Learning. Maher says Stiegler EdTech has a partnership with AWS as part of Amazon’s plan to train 29 million people in cloud computing by 2025.
Despite such efforts and intentions, a disparity seems to persist in the supply of tech talent and jobs waiting to be filled. In North Carolina, where Maher is based, there are 20,000 jobs openings annually in technology and just 2,500 computer science graduates. “That’s not to say every single one of these jobs is an entry level job,” he says, “but you can imagine how year-over-year, over a 10-year horizon, that issue becomes really exacerbated. Businesses need to get invested in solving this delta.”
Maher would like to see organizations become more receptive to nontraditional candidates and remove their college degree requirements for potential hires. “You’ve already seen that with -- name your favorite Fortune 100 company: Apple, JPMorgan, Microsoft, Amazon, Bank of America,” he says.
Tastes in career paths are changing, says Suresh Sambandam, CEO of Kissflow, as creative fields and the arts gain in popularity at some colleges. “Previously people thought to land a high-paying job, you need to be a computer science engineer,” he says. “That is changing.” His company is a developer of a low-code, no-code platform.
Expectations to land a job with major tech product companies such as Microsoft and Facebook is steep, Sambandam says, with such companies eager for engineers for product development. “That’s the real fight for talent that happens in the valley,” he says. Such companies are likely to look for rockstar engineers to work on what could be the next game-changing product or platform.
In general, industry can be anxious to meet expectations being set upon their shoulders, with Sambandam citing an assumed flood of applications to be built in the near future.
A few years ago, International Data Corp. (IDC) laid out a prediction that by 2023, more than 500 million digital apps and services would be developed and deployed via cloud-native, which would match the number of apps developed during the prior 40 years. The trouble is, there might not be enough available tech talent to manifest that digital tsunami.
“We don’t have so many people who can build 500 million applications,” Sambandam says. If that is to be realized, he says there needs to be away to bridge the gap of the talent shortage. Sambandam believes low-code, no-code platforms might help address that gap.
Anthony Hughes, CEO of Tech Elevator coding bootcamp, which graduates some 1,500 students annually, says he approached this scene from a tech-based economic development background, having previously worked for a nonprofit in Cleveland, Ohio. He worked with local entrepreneurs but realized their plans were bound to stall. “I saw that these tech startups that we were helping launch had no fuel in the form of people,” Hughes says.
Building up that supply of tech talent can be hard in areas faced with brain drain. Cleveland annually sees a total of 280 computer scientists graduate from all the four-year institutions in the region, Hughes says, with 50% of those graduates often relocating to other cities. Meanwhile 8,000 software developer positions are advertised in the Cleveland area, he says.
Training more people through technology bootcamps does not mean much though if companies are not receptive to nontraditional hires. Upping digital literacy through coding bootcamps is a way to develop local tech talent, but Hughes says many differ in focus and types of training. Moreover, he says there are cynical jokes in the industry about companies seeking hires required to have years upon years of experience in technologies that are relatively new.
There has also been the boom and bust of venture-backed efforts, Hughes says, where investors push companies to go fast and gain market share by throwing money at the best engineers because there was no time for people to learn on the job. That can leave tech talent from bootcamps out in the cold. “You’ve seen a massive inflation of salaries in technology and there is the inferred credibility that comes with Stamford, MIT, Carnegie-Mellon, and technical excellence,” he says.
It could be in the best interests of companies to change how they assess potential tech hires. “There are companies out there that are getting in their own way,” Hughes says. For example, they might insist on graduate degrees in computer science to consider candidates. “No one is graduating from Carnegie-Mellon or MIT and saying, ‘I’d really like to work for an old school manufacturing company,’” he says. “They want to go work for Google. These people are putting up barriers.”
Hughes’s frustration is evident when talking about companies that would consider candidates who lacked computer science degrees -- but only if they had seven years of professional coding experience.
“It’s something in the region of 25,000 hours of practical coding experience is the equivalent of a computer science degree,” he says. “That is f------ b-------. It’s the stupidest thing ever.”
Too often the tech scene is equated strictly with apps, software, cloud infrastructure, and AI. Such innovations still require devices of some sort, even if it is a handheld on the edge, to make anything happen.
It can be a challenge communicating to newer generations of the workforce of the impact of the semiconductor industry, says Tony Chan Carusone, CTO of Alphawave IP, which creates wired connectivity solutions and custom silicon chips.
He says there is a perception problem that semiconductors represent a staid industry, a perception that is not aided by media depictions of people working in enclosed “bunny suits.”
Younger students may be more receptive to lessons about software and coding, Carusone says, which can seem more accessible to them, compared with semiconductors, which may be more mysterious. He wants to see such perceptions change.
“Semiconductor design is all about writing code,” Carusone says. Furthermore, semiconductors are part of infrastructure, consumer electronics, and the applications that ride on top of all that. He sees this as a chance for new hires to be part of the technology scene. “There’s an opportunity right out of undergrad education to hit the ground running and have an impact.”
Some aspects of engineering programs in college can run astray of real-world design practices and design skills, he says. That energy and time could be devoted to more practical applications. “I wish that universities would focus on making sure students pick up some specific engineering skills and tools before they turn to learning design practices that use those tools,” Carusone says.
Industry specific design practices, he says, can be learned along the way on the job. “The unique things that can be learned in the university environment are more analytical tools -- those are things that are very hard to make time to pick up once you’re in the workforce,” Carusone says.
The push to train tech talent to chase popular trends can lead to overlooked opportunities such as the hardware scene. “There’s a very natural tendency among everyone -- parents, teachers, politicians, companies -- to encourage training to focus on immediate, short-term needs, but there’s just a long-time constant associated with training fundamentally,” he says.
The decade-old ambitions of creating a tech workforce may need a bit of reset, and even then, there might not be an easy answer to match demand for talent with the skilled professionals in the pool.
The market just might be stuck going in different directions in some instances.
“The talent that was getting developed, 10 to 15 years ago in engineering was for a completely different dynamic of engineer, for a different code base,” says Arjun Kapur, managing partner with Forecast Labs, a startup studio established by Comcast Ventures.
He says a lot of work was done over the years to bring people to engineering and technical fields across multiple disciplines. That includes product management and data scientists. Companies that sought to hire developers to build on code bases such Mason will not find many people in the field now who want to follow that path. Kapur says even if they do have skills with legacy code, many tech professionals have reskilled themselves to remain relevant in the forward-looking market.
Companies that work with monolithic databases that lack services-oriented architecture or cloud-heavy architecture, will have a hard time finding hires unless they are anxious for work.
“They’re not actually looking for those kinds of opportunities,” he says. “They are looking for opportunities where they can work on the next generation of tech architecture.” The market has reached a period, Kapur says, with waning interest in helping a company transition of off a monolithic architecture to microservices. “They are looking to work on newer code bases.”
This can lead to a hiring impasse as there is a desire among potential new tech talent, he says, to work with open-source code but massive enterprises have limited work where open source is permitted. Banks, for example, are not likely to go open source with their core product innovation. “They’re not building core products on it because there’s IP and security issues,” Kapur says.
The decade-old ambitions of creating a tech workforce may need a bit of reset, and even then, there might not be an easy answer to match demand for talent with the skilled professionals in the pool.
The market just might be stuck going in different directions in some instances.
“The talent that was getting developed, 10 to 15 years ago in engineering was for a completely different dynamic of engineer, for a different code base,” says Arjun Kapur, managing partner with Forecast Labs, a startup studio established by Comcast Ventures.
He says a lot of work was done over the years to bring people to engineering and technical fields across multiple disciplines. That includes product management and data scientists. Companies that sought to hire developers to build on code bases such Mason will not find many people in the field now who want to follow that path. Kapur says even if they do have skills with legacy code, many tech professionals have reskilled themselves to remain relevant in the forward-looking market.
Companies that work with monolithic databases that lack services-oriented architecture or cloud-heavy architecture, will have a hard time finding hires unless they are anxious for work.
“They’re not actually looking for those kinds of opportunities,” he says. “They are looking for opportunities where they can work on the next generation of tech architecture.” The market has reached a period, Kapur says, with waning interest in helping a company transition of off a monolithic architecture to microservices. “They are looking to work on newer code bases.”
This can lead to a hiring impasse as there is a desire among potential new tech talent, he says, to work with open-source code but massive enterprises have limited work where open source is permitted. Banks, for example, are not likely to go open source with their core product innovation. “They’re not building core products on it because there’s IP and security issues,” Kapur says.
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