Machine learning can help both recruiters and job seekers meet the challenges of these industry-wide layoffs.
by Gergo Vari
January 19, 2023
Twitter has made headlines recently, announcing nearly 4,000 layoffs – almost half of their workforce. But Twitter is not the only tech company undergoing a massive reduction in staff. The problem is so widespread we can now qualify it as a veritable layoff wave (depending on your outlook, bordering on a tsunami).
To extend the water analogy, these layoffs will undoubtedly have a ripple effect throughout the industry. What does this mean for HR managers and recruiters? What new challenges are they facing and what steps are they taking to meet these challenges?
Let’s look at what impact the current wave of layoffs in the tech industry is having, the reasons behind the layoffs and what it means for the near future of HR in the tech industry.
The current state of affairs
Are we really in the midst of a tech layoff, or are we making a mountain out of our virtual molehill? Well, the numbers don’t lie. Major companies, considered pillars of the tech industry, are reporting record job cuts, with Meta leading the way at approximately 11,000 layoffs (a number which corresponds to roughly 13 percent of its staff).
In the U.S. alone, it is estimated nearly 75,000 tech employees have been laid off in 2022. Surprisingly, this comes after a banner year in 2021.
What’s behind the massive tech layoffs?
Unsurprisingly, several factors can be cited for causing the current wave of layoffs in the tech industry. While there is some consensus as to what factors have led to this problem, the experts are not all in agreement as to which factors have played the largest role.
It’s worth bearing in mind that we are coming out of a period that saw a particularly unusual set of circumstances stemming from the COVID-19 pandemic. The subsequent worldwide lockdowns saw an increase in consumer reliance on technology which fuelled spending in the industry in a way that was simply not sustainable (thankfully).
Coming out of the pandemic, we have seen high rates of inflation which have negatively impacted consumer spending. Consequently, companies across all sectors of activity (including tech) are scaling back on investments, which translates to a scale back in hiring.
With the threat of a global recession looming, the current layoffs in the tech industry can be seen as preventative measures as companies brace themselves for a financial hit and are taking actions to help weather the storm.
Industry-wide layoffs are nothing new. And tech has been far from impervious to this phenomenon. Past recessions and industry-wide layoffs have proven to be trying for HR. It is during these times that their decisions and actions have the greatest impact on their organizations.
Amid layoffs, employees are especially vulnerable to dissatisfaction or a loss of faith in their employers. HR managers must be vigilant for signs of quiet quitting and general employee disengagement.
Traditionally, during times of economic downturn, the focus of HR has been aimed at cutting costs while retaining current top talent and keeping them engaged. Easier said than done. Industry experts frequently cite two main factors that determine their success in these challenging endeavours:
- Transparency: While being open and honest with employees is always a staple of HR best practices, amidst massive layoffs when there is a risk of paranoia and panic spreading through the company, transparency takes on an even greater role.
- Employee experience: This incorporates the employee’s well-being and work-life balance. When retention and engagement become all the more critical, a concentrated effort into reshaping the employee experience to retain talent is a high priority.
Difficult times call for a shift in priorities
A greater emphasis is placed on transparency and less emphasis is placed on recruiting new talent. And while HR managers still need to do some recruiting as companies brace for an impending recession, the emphasis is placed on smart hiring rather than on high-risk or growth-anticipation hiring.
The role of HR is heightened during tough economic times. And the call is to put the “human” back into human resources.
- Minimize losses
- Minimize the amount of or the effects of potentially disgruntled workers
- Help recently laid-off workers with their next career move
Machine learning may help
More HR managers are soliciting technological advancements to help them face the challenges of their roles. One may argue that in stressful times, such as during a wave of layoffs, what’s needed above all is the human touch. But that’s precisely what some technological advancements, such as AI, can offer.
Artificial intelligence, when used correctly, can take over the more time-consuming menial tasks of the recruitment manager, leaving him or her, thus, free to spend more time and energy on sensitive tasks where “the human touch” is needed more. AI can help with time-consuming tasks such as:
- Filtering out applicants who are clearly not suited for the position
- Sending out initial messages confirming the receipt of a resume
- Sending out politely worded rejection letters
- Engaging candidates in assessment tests or skill evaluation exams
- Scheduling follow-up interviews
- Answering questions frequently asked by applicants
Machine learning – in popular parlance, often used interchangeably with AI – analyzes millions of resumes and job offers. From this analysis of big data, machine learning can then identify patterns and match applicants with positions they are most suited for. The idea is to steer job seekers toward jobs they are more likely to excel in and help them along their respective career paths.
Since HR managers are being tasked with helping recently laid-off workers, it is only fitting that technological advancements such as machine learning are being tasked with the same.
Machine learning can help recently laid-off workers find their next job in the ways explained above. But it can also do much more in AI-powered out skilling.
- Identifying weaknesses in the resume: Since machine learning analyzes millions of resumes and job offers in real-time, it can identify weaknesses – skills, qualifications, or credentials that may be lacking – in the resume of a recently laid-off worker.
- Creating a career roadmap: Some workers are laid off because their jobs have ceased to be relevant or market demands have shifted away from their role. In these cases, machine learning can identify specific career resources, such as additional training, that will steer the recently laid-off worker toward a more viable career path.
- Job market forecasts – Machine learning can spot and predict trends in the labor market that can prove to be valuable in the decision-making process of a recently laid-off worker.