Why Data & Analytics Teams Lose Out on Top Candidates: 7 Things to Avoid
As the data & analytics job market becomes increasingly competitive with highly sought after niche skills in demand like AI & ML Engineering, companies need to step up their recruitment game to attract top talent. However, even with the best intentions, companies can sometimes lose out on the best candidates. In this article, we will explore the seven reasons why companies lose out on top candidates and what they can do to avoid making these mistakes.
1. Lengthy Application Process
LinkedIn reports that the best candidates are often hired within 10 days
One of the biggest reasons companies lose out on top candidates is due to a lengthy and complicated application process. More than two technical components and multiple interviews decreases the likelihood of a great candidate proceeding. Companies need to streamline their application process, making it easy and efficient for candidates to apply. This may look like:
Video Meet -> Technical (1 week case study) -> F2F -> Offer
F2F -> Technical (in person) -> Offer
2. Lack of Outreach & Awareness
Another reason why companies lose out on top candidates is the lack of outreach. Companies need to actively reach out to top candidates, even if they aren't actively looking for a job. This can be achieved through networking events, social media, and professional development opportunities. Industry User Groups such as AWS, Azure, Databricks and Data Engineer Meetup are great for data professionals.
3. Only Posting a Job Advert on Seek
Relying solely on Seek or other job boards is a common mistake that companies make. While job boards are a great tool, they should not be the only avenue for recruitment. Top candidates may not actively search for jobs on job boards, so companies need to explore other avenues such as LinkedIn or industry-specific job boards.
4. Poor Employee Offerings
Companies that don't offer competitive salaries, benefits, or professional development opportunities are at risk of losing top candidates to companies that do. In Data & Analytics this often means providing upskilling opportunity with modern tools and the relevant certification avenues to suit. Companies need to have a comprehensive employee value proposition (EVP) that includes competitive salaries, flexible work arrangements, and professional development opportunities.
5. Not Knowing the Employer Market
Not knowing the employer market is another reason why companies lose out on top candidates. Companies need to be aware of the trends and demands of the employer market. This includes understanding what top candidates are looking for in a company and adapting to these demands.
6. Poor Response Rates
Companies that don't respond to candidates in a timely manner or provide feedback on their application are at risk of losing top candidates. Candidates value feedback and communication, so it's essential for companies to provide this throughout the recruitment process.
7. Bad Internal Culture
Finally, companies with a toxic or negative internal culture are at risk of losing top candidates. Candidates are looking for a positive and inclusive work environment that fosters growth and development. Companies need to create a positive work culture that attracts and retains top talent.
In conclusion, data & analytics companies need to avoid these seven common mistakes to attract and retain top talent. By streamlining their application process, actively reaching out to top candidates, exploring various avenues for recruitment, offering a competitive employee value proposition, understanding the employer market, providing timely feedback, and creating a positive work culture, companies can avoid losing out on top candidates.
I'm Douglas Robertson, Founder of DR Analytics Recruitment - a former data analyst now analytics recruiter. I've done the job and now I recruit for it. We
Partner with Australian based data consultancies
Support acquisition growth with a low-risk revenue share fee model
Provide ongoing business development training for staff
Our goal is to invest in the success of the candidates we place and help build businesses for the long-term.
