Where Skills Data Falls Short

You can’t have a conversation about the workforce and labor market these days without it immediately going to skills—skills mapping, skills-based hiring, skills transformation. Every company is focused there.

In many ways, that’s great. The new obsession with skills is much better than the old obsession with degrees—which are all too often exclusionary and aren’t that great at telling you whether someone is qualified for a job. Businesses will need a better way of understanding what their employees know and can do, and how they might move from one job to another.

Skills are a useful—even essential—starting point, but they aren’t sufficient on their own. And many skills-mapping efforts are especially destined to fall short when it comes to frontline workers.

The reasons are two-fold:

#1 To start, the skills data for frontline workers just isn’t very good. Frontline workers’ job descriptions are perhaps the least important descriptor of their talents. And many don’t have LinkedIn profiles or formal credentials that show up on resumes or job applications. They do, however, have skills that were developed on the job or raising a family, managing a side hustle, or working in their community that don’t show up in today’s data.

Think about your own experience in hourly jobs: Managing irate and unreasonable customers, taking on additional work when a coworker didn’t show up for a shift, and making sure you’re not the one who is juggling too much and misses work. Or think about all the financial, logistical, and emotional issues you have to manage to keep your home and your family humming along. Or maybe you have a hobby that you’re more passionate about than your job—and that may require more skill too.

That’s a lot of problem-solving, creativity, time management, and financial acumen that will never show up in a job description. In other words, companies are awash in talents they can’t see in their data.

A number of savvy employers are trying to change that—thinking about how to build systems that capture their employees’ skills and interests that fall outside of their job descriptions. And some data platforms, like Arena Analytics and Pymetrics, are using personality-focused assessments to match candidates with roles, while de-biasing their data to ensure that successful matches aren’t skewed towards any particular race, ethnicity, or gender. Those kinds of efforts are in their early days, but hold promise.

#2 Beyond data quality, skills aren’t the only factor that makes someone a great candidate for a new role or a career switch down the road. Skills are a foundational building block, but values, interests, and personalities matter too. For many frontline workers, the skills they have today may actually be the least important factor for determining the career they want and could have tomorrow.

Taking a wide view of qualifications—values, interests, personalities, and yes, skills—can greatly increase the pool of internal candidates for high-demand roles. It also improves match quality, ensuring people are in roles that actually align with their career goals and making them more likely to succeed and to stay.

Take Staci Werner: She has a deep passion for what she sees as the lost art of cooking and food preparation. You might get some sense of that from the official description of her job as a food unit lead. But you wouldn’t know that she also spends her free time teaching friends and family to cook—or that she’s drawn to cooking because it provides a practical application for math.

Staci loves math. She also has strong math skills, but her passion is what made her an ideal candidate to grow into a role more focused on food science. And her company would have no way of knowing about that passion, or her skills for that matter, if Staci hadn’t talked to her manager about it and her desire to pursue additional education with her company’s benefits.

That’s how she ended up working towards a Microsoft Excel certificate from Penn Foster that will enable her to translate her interest in math to the technology her company uses.

Staci’s story is a success story. But the way she found her path was far from systematic.

As companies move away from credentials as the sole proxy for talent—a laudable move—and toward skills-based hiring and promotion, they need to make sure they aren’t swapping one narrow measure for another. They run a real risk of doing just that if they confuse their employees’ existing data with what those people actually can—and want—to do.

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