Data Science Hiring Freezes — Convincing Management That’s a Bad Idea
It’s common in the wake of global disruptions to implement hiring freezes until surer times come, and the recent COVID-19 pandemic has been no different. According to a Fortune survey, 59% of CEOS have used hiring freezes as a way to save money and shore up company finances, but at what long term cost?
Data science and related positions were caught up in the hiring freeze. Spring is normally one of the busiest periods for hiring. As you can see in the chart above the hiring freezes began to kick in late February 2020 and peaked towards the end of April 2020. All roles were equally affected including data scientists, machine learning engineers, data analysts, and others.
Not unlike hiring freezes in other departments, freezing new hires in data and AI could have long term negative consequences for businesses not only struggling with COVID disruption but also looking to survive the longer-term disruption of the newest digital age.
It may feel counterintuitive, but hiring — and hiring more — during a disruption could help companies’ chances of survival once the dust settles. Here’s why management must reconsider hiring freezes in data science departments, and how to convince them to see the truth.
Rethinking the wisdom of hiring freezes
A substantial long term consequence of a hiring freeze is losing valuable ground to big companies already leading the way in data and AI. FAANG hasn’t stopped hiring despite the disruption. With less competition for talent during COVID, even more, data science and AI gets concentrated even more closely with these already competitive companies.
When we take a step back from long-held beliefs about hiring freezes saving money and restoring order, we begin to see a different reality. Companies that are hiring aggressively are also the companies that are seeing increases in revenue despite, and even because of, the pandemic.
For example, Instacart, an online grocery leader, greatly expanded operations to meet the sudden demand for at-home shopping during quarantine orders, but it wasn’t just for delivery. They invested heavily in engineering talent designed to streamline the process and allow Instacart to scale to meet the need.
Peloton is another story in hiring and scale. The company faced past backlash for its controversial commercials and its hefty product price tag, but that’s changing with 2020’s disruption to the gym scene.
Sales surged an estimated 66% from last year, and the company’s reliance on AI-driven workout models along with increased hiring to accommodate the new reality of its customers. While some people still question the sustainability of the company’s growth, Peloton is backing an aggressive hiring strategy to prove them wrong.
Telehealth startups are closing serious funding rounds as a response to changes in the way people seek healthcare due to disruption, a trend experts predict will continue long after COVID comes under control. These startups are hiring aggressively as a tactic to gain long term footing in a historically difficult industry.
The benefits of hiring aggressively during disruption
When management is considering a freeze, convince them to go a different direction by highlighting the long-term benefits of investing in the data science department.
Less employee turnover
Data scientists have an extremely high turnover rate, and the field of tech has the highest turnover rate of other industries. Companies have struggled to compete with the likes of Google and Facebook and then struggled again to retain the talent they do attract.
Hiring during disruption could make people less likely to move jobs, giving smaller companies the chance to hire and retain valuable data scientists. While the presence of a pandemic isn’t enough to keep a data science team happy, it could buy an organization some time to build a robust and thriving department.
Data science talent isn’t going to get easier to fill. Viewing through a long-term lens, companies who remain committed to attracting and retaining top talent despite global crisis have the best chance of coming out of that crisis prepared for the new working landscape.
Continued commitment to innovation: why data science hiring is key
The world is changing. Shutting down during disruption doesn’t save organizations — it only makes it less likely that they won’t survive. During past crises, companies like Airbnb arose from the financial crisis, leaving towering hospitality giants in its dust.
Pursuing data science talent despite black swan events like COVID helps ensure that companies can pivot to data-driven decisions that can bring them out of the crisis stronger, restructuring from the ground up and arriving more disruption-resistant with every event.
Amazon, for example, hires aggressively and continues to come out of global crashes, pandemics, and uncertainty stronger and more necessary for day to day society.
Even where innovation fails, such as the original dot com bubble, the tracks laid by these failures lead the way to real change. Using data science and AI, companies could begin making decisions that turn real value.
Not artificial — augmented intelligence
The biggest draw to aggressive hiring in the data science arena is the emergence of this decision intelligence. Companies deploying AI and data infrastructure will be the ones to survive disruption — any disruption. This is a game of early adoption, and management can’t afford to miss out even during a crisis.
Companies that are surviving and thriving have already invested heavily in data, and a global crisis is precisely the time companies should be investing in that restructuring. The long term ROI of becoming data-driven is enormous.
Evaluating a hiring freeze the right way
Before implementing the hiring freeze, management should carefully explore the reasoning behind it and look to long term benefits or consequences, asking:
- What’s our budgetary consideration? — If management is bankrupting the company for hiring, a freeze could be valid. However, if it’s merely a perceived loss, look to the long term ROI of investing in data science. It could help retain and grow market share, uncover new opportunities, and put companies ahead of trends.
- Are we able to find the talent we need? — If an organization is lucky to have more applications than openings, a freeze may not hurt. If it’s already a struggle to fill positions and find talent, it’s not going to get better.
- Is there an end date to budget freezes? — If management knows the date budgets open back up, getting a head start on the search process will make the transition back to normal operations much much easier.
- How will remote work expand operations? — The current crisis has warmed both organizations and employees to the idea of remote work. Expanding your talent search during the crisis takes full advantage of the uptick in remote options. Your best candidates may not be close to you, and that’s a good thing.
Hiring for data science is worth it
Investing in data science during a crisis builds the foundations for long term survival. As AI becomes a more significant part of what drives organizations, take advantage of these times to shore up your talent and pivot to find new markets. When the next crisis comes, you’ll be ready.
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