Manufacturing and the Great Resignation


Whether you call it the Great Resignation, the Great Reshuffle, or any of the other labels currently being bandied about, the immense pace of personnel changes in the manufacturing sector for the past half-decade is no anomaly. It is just one of the many new normals and companies need to come to grips with it if they are to have any hope of maintaining competitiveness. 

Forty-three million Americans left their jobs voluntarily this past year, with the departure rate hitting its peak in November 2021. Much attention has been paid to restaurant and hospitality workers who have left their typically low-paying positions in droves, frequently finding, with relative ease, new, better-paying positions with more predictable hours as the industry struggles for survival. Health care workers as well, pummeled by the work demands and health risks of the two-year-old COVID-19 pandemic, are actively seeking alternative positions. 

The exodus in manufacturing

The manufacturing industry has not received nearly the same level of publicity and scrutiny, despite the sector’s rate of departure having risen by nearly 60% versus pre-pandemic levels, a departure rate increase unrivaled by any other vertical. In addition to COVID-19, numerous other systemic factors have driven this trend in recent years, including the sharp drop in unionization rates versus decades ago, and the slow but inexorable encroachment of two-tier compensation systems, in which temporary workers make dramatically less in salary and benefits than their full-time colleagues. The Washington Post (see figure below) estimates that the industry as a whole is down nearly a quarter of a million workers versus pre-pandemic levels, this despite the large percentage of workers who have simply left one position and taken a new better-paying one elsewhere. The National Institute of Standards and Technology says there are currently 900,000 unfilled job openings in American manufacturing. 

With an overall strong manufacturing sector (driven in part by the ironically positive effect of COVID-19 on demand for manufactured goods) and a significant gap between employment levels and required labor, workers have awakened in the past 24 months to the realization that at long last they are the ones with the leverage, a power they have opted to act upon in the millions. 

This has left the industry scrambling to find qualified replacements, a challenge arguably even more daunting than that faced by the hospitality industry, given the relatively high skill levels required to perform many manufacturing jobs. A recent big driver of this phenomenon is, of course, the COVID-19 pandemic. While many white-collar jobs have migrated to dining room tables over the past two years, manufacturing offers no such respite from the daily risks of the pandemic. And the high departure rate has caused those left behind to work even more grueling schedules than normal, simply to keep up with demand. In addition to the pandemic, departure rates have been exacerbated by the failure of compensation rates to keep up with the historical norms typically associated with this industry, a situation made even more tenuous by recent inflationary trends. 

What does this mean for the industry?

Increasing difficulties achieving safety, productivity, and product quality goals mean that industry leaders are now obliged to look in previously unexplored directions for solutions. The primary challenge for manufacturers will be that of doing more with less, a challenge that inevitably points in the direction of technology. And a rapidly evolving component of that technology will be artificial intelligence (AI). 

Achieving performance goals requires greater flexibility (of staff and systems), more efficient use of data, and embracing the automation that comes from AI-based solutions like machine learning (ML), natural language processing (NLP), and predictive equipment maintenance, all areas in which SparkCognition has tested and proven experience, and a wide range of product offerings. 

NLP directly addresses the conundrum of too much data and too little insight. By ingesting and analyzing the vast quantities of performance and status information contained in unstructured sources like technical manuals, emails, and handwritten reports—and doing so without the need for manual labor—equipment can be operated more efficiently and its lifetime increased. 

Similarly, predictive and prescriptive maintenance solutions aggregate and analyze real-time performance data from the multitude of sensors already installed on equipment throughout factories and assembly lines. Alerts are then provided that indicate imminent failures or required maintenance which, if left unaddressed, could result in breakdowns, increased operational and capital costs, productivity losses, and compromises to worker safety.  

AI: the key to adapting to the new normal

Whether you believe worker empowerment is a passing fad or is here to stay, one lesson from the past few years is undeniable. Manufacturers will be required, more than ever, to identify ways of extracting more meaningful, more productive work from their teams. And that means embracing the benefits that AI delivers every day at the world’s leading firms—firms that have made a conscious decision to stay ahead of what looks, by any objective measure, to be the new normal for the manufacturing industry.

To learn more about how SparkCognition solutions can help you address the growing skills gap, contact us at

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