How CIOs/CTOs Should Strategize their Hiring Plans in 2023

Here’s how desperately companies need tech talent: Scrolling LinkedIn recently, I came across a CTO bemoaning his company’s shortage of tech professionals. Pessimistic about finding the experienced professionals he needed, the CTO said he’d asked the local high school’s technology department to train 11th and 12th graders to do the jobs he couldn’t fill.

While nurturing budding talent is the right idea for the future, it doesn’t solve the challenges CTOs and CIOs are facing in the here and now.

Despite layoffs at some technology companies – though rarely among core tech workers – and the ominous possibility of recession, in the vast majority of organizations tech talent remains in painfully short supply, and the future looks worse. The market for tech workers companies need most remains “red hot,” according to CNBC

Nearly 70 percent of managers surveyed for an August “Future of Workforce Report” by Upwork say they’ll continue to hire workers in the toughest jobs to fill: data science, analytics, software architecture, IT, and networking.

HRTech News: Lattice Powers More Effective Compensation Practices and Pay Transparency for Businesses with Mercer Alliance

A recent Pulse Survey of 700 company executives by PwC ranked tech talent acquisition as the second-biggest risk to their business (behind cyberattacks).

So What’s the Solution? 

I could pile on scary stats all day, but every CTO/CIO already knows the problem. The important question is how to solve it without busting tight budgets.

The most promising solution with the richest potential ROI is to recruit tech workers organizations need from the existing employee population. Just going out and hiring them – even if they could be found – is too expensive: it costs six times as much to hire an external candidate than to reskill an existing employee for the most in-demand tech jobs.

One powerful new CIO/CTO tool is the Talent Intelligence Cloud (IC), an AI/ML-based brain with knowledge of all an organization’s multiple HR solutions that adds the power of analytic insights drawn from deep wells of real-world data to solve multiple HR, staffing, and career-navigation challenges.

Success Profiles Give a Seemingly Sprawling Problem Tighter Definition 

Defining the problem is Step 1, but as CIOs and CTOs know, this is harder than it sounds. Any tech organization would seem to have too many jobs to approach upskilling systematically. This is where Tech Success Profiles help define the precise universe of tech jobs in a structured manner that makes grappling with the challenge not exactly easy, but not impossible, either.

Tech Success Profiles create distinct portraits of a job with such elements as precise functions, levels, responsibilities, skills, competencies, traits and drivers clearly defined to show clearly what jobs actually look like in a data-based way. Tech Success Profiles create some breathing space by showing there are actually fewer distinct tech jobs in organizations than one would imagine.

An example: I was part of a 300-person team with 200 different listed jobs. Through applying Success Profile analytics to the fundamental architectures and functions of different positions, it turned out there were actually fewer than 50 distinct jobs, not 200. That not only makes it easier to understand the nature of our work, it’s more feasible to build rewarding career paths for 50 jobs than for 200.

In fact, across all of tech, there are essentially 350 distinct jobs, Korn Ferry found. That’s not a small set, but still more bounded that the 60,000+ different job titles we looked at initially when mining the jobs data. This narrowed structure enables leaders to both manage strategically and create future career moves for their teams.

Training Tech Talent for the Top 10 Most In-Demand Jobs 

The next step is defining the tech skills each organization will need, and who among the current workforce has the drive and capability to fill those slots. Across thousands of companies, here are the near future’s Top 10 most in-demand jobs, we found:

  1. Machine Learning Engineer
  2. Data Scientist
  3. Cybersecurity Specialist
  4. Application Security engineer
  5. Cloud Architect
  6. Data Engineer
  7. Mobile App Developer
  8. Front-end Software Developer
  9. DevOps Engineer
  10. Network Systems Engineer

The most important current and future technical jobs in your organization may be different, but the core concept remains the same: once a company knows what it needs, how do you get it? Importantly, how do you also provide satisfying career paths to become an employer of choice?

Top HR News: Workhuman Announces Expansion in Dublin to Meet Demand for Employee Engagement Solution

Intelligence Cloud Success Profiles make it possible by revealing clear learning paths from a current job to a destination job. Once skill and competency gaps are identified, an organization can develop a powerful and efficient learning journey to a more business-critical role, or to one the employee desires for their personal sense of purpose.

Intelligence Cloud Success Profile Navigation Solves the ‘Problem of Plenty’

In practical terms, we’ve found, software developers are both more plentiful inside organizations and more interested in upskilling themselves with the right training to fill the most in-demand jobs.

“The right training” is a loaded term. If anything, there’s too much training available to employees eager to upskill themselves. One leading researcher found the average company uses 22 different learning and development solutions and platforms. To any company’s official L&D channels add multiple self-education options, from Udacity and Udemy to YouTube to old-fashioned books.

The Problem of Plenty offers even highly motivated would-be learners so many unfocused choices they end up bewildered. It’s established science: too many choices paralyze decision-making.

Let’s take the example of Python, a basic skill for data scientists. Google “Python training courses,” and you get 334 million results. Where should one start? Python also has multiple skill elements such as deep learning, strings, classes, neural networks, etc. So how can someone know they’ve truly “learned” Python?

Compounding the confusion, even if an aspiring data scientist learns Python, they won’t necessarily learn the specific skill elements nor the right mindset that makes “knowing Python” important to data scientists.

Intelligence Cloud Success Profiles, though, clearly show not only what about Python data scientists must know, but the most effective way to learn Python in the exact context of becoming a data scientist.

Putting the employee and their organization equally at the center, Intelligence Cloud Success Profiles create an illuminated path, guiding the development of focused, personalized, purpose-driven, curated journeys for each employee, with specific goals and outcomes and clearly defined routes to achieving them.

These journeys are composed of bite-sized pieces of training employees accomplish on their own schedules, or, even better, as part of their existing workflow – the more organic and convenient, the better.

Internal recruiting/upskilling is the only way CTOs and CIOs will fill critical tech jobs without spending an organization into oblivion with no guarantee of success – or looking in desperation to the local high school to fill skilled tech professional roles today. Intelligence cloud platforms are fairly new, but they are enormously promising in empowering CTOs and CIOs to do just that.

Equally beneficial in the long term, employees upskilling to more rewarding career tracks will value the chance to advance without having to leave their current employer.