To continue their hypergrowth trajectory, hypergrowth tech companies need to attract and hire top talent — fast. Employing artificial intelligence in talent acquisition can help.
More and more tech startups the world over are reaching unicorn status – meaning they’re valued at more than $1 billion. In 2021 alone, Europe launched 72 unicorn companies, according to Sifted, making it the fastest-growing venture capital region across the globe.
As is typical, growing pains accompany any rapid growth. And that’s certainly the case for hypergrowth tech companies. The biggest pain is in the area of talent acquisition. Rapid growth requires rapid talent acquisition. Scaling the workforce isn’t always easy, especially given the highly competitive talent landscape.
With the proliferation of digital transformation, companies across industries around the world are vying for the same candidates, such as data scientists, software engineers, web developers, information security analysts and commercial account executives.
The need for better talent acquisition
Adding to the challenge, “only about 30% of European startups have located their headquarters in a tech superhub — where they might have an easier time attracting talent and funding — versus almost half of U.S. startups,” explains McKinsey research.
“Although London, Paris, Berlin, and Stockholm can be considered the leading hubs in Europe, they have not achieved the same concentration in terms of capital, knowledge and talent,”
Many European hypergrowth tech companies lack the tools to attract top talent, such as stock options, and have a smaller pool of talent experienced in building initial public offering companies.
Those companies that succeed in attracting talent lack follow-through in responding to and nurturing applicants. Research from talent cloud company iCIMS found that “more than 50% of the largest European companies do not reply to a candidate within two weeks of receiving an application, and the majority of responses are from a generic email address.”
When candidates finally hear from a company, they may be turned off or already lured away to a competitor that offered a personalized experience. There’s clearly room for improvement in talent acquisition at hypergrowth tech companies.
How 2 European companies transitioned
Spotify succeeded in quickly ramping up its workforce by solidifying a strong relationship between its talent acquisition and human resources teams. With that relationship established, the company encouraged employees to help recruit talent with the requisite skills, a move that continues to be fruitful.
Europe’s fashion technology company Zalando is on a quest to become the “Netflix or Spotify of the fashion world,” according to Manjuri Sinha, the company’s former global lead of tech talent acquisition. To work toward that goal, Zalando took a hard look at the data and analytics surrounding its talent acquisition practices and quickly saw the need for an overhaul. So, the company set out to improve the quality of candidates, the time to hire and the candidate experience in general.
Zalando realized its applicant tracking system filtered out 88% of all applications. Many of those that did make it through were subsequently filtered out by recruiters based on job descriptions. The company took measures to fine-tune its job descriptions by creating talented personas, as well as reduce its times to offer and hire.
The key to the company’s successful talent acquisition transformation was artificial intelligence (AI). Using AI-based scheduling automation helped Zalando reduce its time to schedule a first interview from 22 minutes to 44 seconds.
In addition, AI helped the company reduce its days to offer from 52 to 32 and its candidate filter-out ratio from 88% to 71%. Zalando’s candidate Net Promoter Score increased from -7 to +33, and its offer acceptance rose by 30%.
It all comes down to data
Zalando is only one example of how hypergrowth tech companies can use data and AI to turn their talent acquisition process around. Taking a data-driven AI approach can help you realize positive results as well. But to get the results you want, you must first determine the outcomes you want to achieve. Only then will you be ready to put AI to work for your organization.
Implementing an AI-driven talent lifecycle management strategy can help you transition your talent acquisition practices from reactive to proactive. Because hypergrowth companies move so quickly, they need to attract and hire candidates just as quickly. Data can make all the difference, as it did for Zalando.
To get the most out of your talent data, it needs to be pooled in a single repository, cleaned and maintained. Using a centralized talent data platform can eliminate data silos and streamline the talent acquisition process across departments and locations.
In this way, talent teams can get conclusive insight into in-house skills and discover where skills gaps lie. Powered by AI, a talent data platform can connect the dots between candidates’ previous experience and needed skills at your organization — even if the two use different nomenclature. That’s a task that’s not easy for humans to master but is imperative in order to quickly find and hire the quality talent your company needs.
Learn how Beamery can help hypergrowth tech companies hire quality talent.