The wave of tech company layoffs and social contagion
12 January 2023
I’ve worked in a number of organisations in the past that have been subject to rounds of staff layoffs or redundancies. In most cases the prime motivation was cost cutting, and the decision to proceed was usually made by a senior executive who would not have to deal directly with the subsequent fallout. For anyone not familiar with the process, it was not pleasant. Stress, anxiety, baseless rumours, and misinformation, were all in abundance.
Despite noises made to the contrary by management, the negative impact on workers — both those departing, and those staying behind — was seldom given thought. In one situation, a former colleague made what is probably a common observation: there’ll still be the same amount of work to do. New work processes and technologies might reduce some of the load, but likely not markedly.
Like many people, the recent wave of layoffs in the tech sector has puzzled me. One company announced a round of redundancies, and the next thing other tech companies are following suit. But why? Surely all these companies, Meta (the Facebook owner), Linkedin, Twitter, Tesla, Netflix, and Salesforce — who are but a handful of organisations to send employees home in recent months — cannot all be struggling financially.
This make the staff cuts all the more baffling. But as Jeffrey Pfeffer, a professor at the Stanford Graduate School of Business explains, the layoffs are a case of social contagion. In other words, because one or two tech companies have been shedding staff, everyone else feels they must do the same. Long story short, there is no real reason for the redundancies, and the turmoil they create for workers, and the organisations themselves:
The tech industry layoffs are basically an instance of social contagion, in which companies imitate what others are doing. If you look for reasons for why companies do layoffs, the reason is that everybody else is doing it. Layoffs are the result of imitative behavior and are not particularly evidence-based.