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As many as 375 million workers across the globe — that’s 14% of the entire world’s workforce — may need to switch occupational categories by 2030 as the rising tide of digitization, automation, and AI disrupts many of the jobs and tasks carried out today.
McKinsey’s report into the future of work found that two-thirds of executives believe they will need to provide new training or replace upwards of a quarter of their workforce by 2023 as they seek to address potential skills gaps related to automation and digitization.
The key question here is whether employees will be retrained or if they’ll be replaced. While managers are traditionally wary of training costs, they can pale in comparison to the costs involved in replacing an employee. A CAP Study found that average replacement costs range from 20% of annual salary for mid-range positions to 213% of annual salary for executive positions. These costs can be sorted into three broad categories:
- Separation costs — immediate costs incurred when an employee leaves (such as severance pay).
- Recruitment costs — money and time spent looking for someone to fill the position or hiring a third-party recruitment firm to provide candidates. All new employees, no matter how experienced, will also require some form of training.
- Productivity costs — lost hours of productivity while the position is unfilled, time spent by other employees on doing those tasks in the meantime, and the length of time it will take for the new employee to get up to the speed of the previous employee.
The other factor to take into account is that skilled workers with niche technical skills are in high demand, leading to higher recruitment costs and longer times to fill a position. In most organizations it would therefore be more cost-effective to upskill existing staff, assuming they have the talent, capability, and willingness to learn.
Reskilling in Manufacturing
A 2018 report from the World Economic Forum (WEF) found that manufacturing is projected to “suffer a net decline in overall numbers of jobs between now and 2026.” This means that optimistic predictions of new jobs emerging at the same rate that other jobs are replaced will not apply in manufacturing. That being said, the increase in advanced manufacturing technology will increase the need for skilled technicians.
Writing for Forbes, Jim Vinoski points out that a decline in U.S. manufacturing employment driven by automation is nothing new, with a general fall in jobs since the late 1970s. But Industry 4.0 is expected to speed this decline in employment as AI vastly increases the number of factory tasks that can be automated.
The main concern in terms of employment is that sweeping automation means displaced workers will be unable to find a job that was similar to their previous work and must therefore reskill and transition to new types of employment. Even workers who are fortunate enough to keep their current jobs will find that the nature of those jobs changes dramatically in an AI-boosted environment, and they are likely to require training alongside their colleagues who are transitioning to completely new roles.
Companies that no longer need workers for tasks that have been automated should consider:
- partnering with companies in economic sectors that are expecting growth as part of an outplacement service
- building a workforce strategy around new job pathways
- identifying low-skilled workers with the potential to be reskilled and transitioned to technical jobs internally.
Keep in mind, however, that some elements of highly skilled and technical jobs cannot be simply trained for in a single-day workshop or through on-the-job training. Workers may need to attend lengthy — and expensive — courses, and a culture of continuous learning may need to be developed to keep up with ever-evolving technological disruption. Again, it’s up to the organization to compare these training costs against the high costs associated with replacing staff.
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