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Best fit: A leader’s guide to matching jobs to skills

Harmony Internal - McKinsey

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ESSENTIALS FOR LEADERS AND THOSE THEY LEAD

Brought to you by Liz Hilton Segel & Homayoun Hatami
Global leaders, Industry & Capabilities Practices

Economists generally define a job mismatch as a disconnect between open jobs and people looking for work. This is usually because potential candidates don’t have the skills employers need, but mismatches can also happen for other reasons . For example, the people who already work for you may be under- or overqualified for their jobs or may have lost some skills over time. With the competition for talent remaining fierce, leaders may want to pay closer attention to skill mismatches . Most companies know that they have talent gaps, but relatively few are prepared to respond appropriately, according to research by McKinsey senior partner Aaron De Smet and colleagues. Some actions can address common talent disparities.

AN IDEA

A variety of metal scrap pieces, representing different kinds of worker skills and competencies

Look for skills, not degrees

“Degree inflation” became prevalent about 20 years ago when companies began adding a college degree as a requirement for jobs that hadn’t called for one previously. Now the pendulum is swinging the other way. As talent becomes scarce, many employers are turning to skills-based hiring practices, which select candidates based on their skills and competencies rather than academic degrees. This approach can create a more resilient and inclusive workforce, but merely removing formal educational requirements doesn’t guarantee success. Results from a McKinsey survey show that nearly half of companies struggle to validate candidates’ competencies and references and to source job seekers with the right skills. Employers “should keep an eye on a long-term plan,” suggest McKinsey’s Bryan Hancock , Jonathan Law , and other experts. The impact of skills-based practices is maximized when they’re implemented across the whole talent journey, including in sourcing, hiring, and career development.

A BIG NUMBER

50%

That’s the projected increase in the amount of time spent using advanced technological skills in the United States by 2030; in Europe, that figure is 41 percent. McKinsey senior partners Eric Hazan and Peter Dahlström and their colleagues report that the largest skill mismatches are likely to be in functions that are already the most automated, such as data analytics, web design, and R&D. Leaders should anticipate severe talent shortages in the rapidly growing field of quantum computing —but watch out for mismatches in filling those vacancies. McKinsey’s Niko Mohr , Rodney Zemmel , and other experts cite the case of a company that hired nearly 1,000 data scientists in the early days of AI but did not realize the expected outcomes: “Just 100 true data scientists placed in the right roles would have been sufficient,” they say.

A QUOTE

“It is difficult to teach what is not well defined.”

That’s McKinsey partners Julia Klier and Jörg Schubert and their coauthors, who were after more precise definitions when they set out to explore the adult training and education that governments will need to provide to citizens in the future. The research they conducted identifies 56 distinct elements of talent (DELTAs) distributed across 13 skill groups and four categories of skills (cognitive, digital, interpersonal, and self-leadership). For example, understanding one’s own strengths is a talent element in the self-awareness and self-management group, which falls under the self-leadership category. Such detailed definitions may spur governments “to ensure that curricula include the DELTAs that will future-proof citizens’ skills in the world of work,” the authors suggest.

A SPOTLIGHT INTERVIEW

Image of four people working on computers

‘Before you can talk about what makes the individual successful, you have to be able to answer the question, “For what job?”’ says McKinsey senior partner Bill Schaninger in a podcast on how advanced analytics can help leaders make critical talent decisions. Evidence-based data derived from people analytics—which pulls data from various HR and business systems into a unified view—can offer insights into the attributes, experiences, knowledge, and skills that organizations need, enabling leaders to match those capabilities with roles to improve business outcomes. “If you’re about to make a choice about a person, you can probably do it better with some data,” says Schaninger. “It is really that simple.”

CAN’T BUY ME LOVE

Image of post-it notes with faces drawn on them

You’ve gone all out to find the right candidate—but failed. Now what? A useful first step may be to understand why. The reasons are complex and not necessarily ones that organizations can solve quickly. For example, COVID-19-related health risks, care duties, burnout, and early retirement are among the reasons people may not want to work. Also pay attention to why employees quit en masse in 2021: low pay, no advancement opportunities, feeling disrespected at work, childcare issues, and lack of flexibility were just a few of the reasons, according to a study. No single organization can resolve all of these concerns, but using them as a springboard to improve working conditions would be a good place to start.

Lead by matching well.

— Edited by Rama Ramaswami, senior editor, New York

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by "McKinsey Leading Off" <publishing@email.mckinsey.com> - 02:46 - 9 Jan 2023

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Best fit: A leader’s guide to matching jobs to skills

Look for skills, not degrees

“It is difficult to teach what is not well defined.”