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Optimize hiring for speed and scale to outpace the competition

The hiring landscape has changed dramatically this year, but moving fast can create a huge competitive advantage when vying for top software engineering talent.
October 09, 2023

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The hiring landscape has changed dramatically this year, but moving fast can create a huge competitive advantage when vying for top software engineering talent.

The continued uncertainty around the global economy has resulted in a seismic shift in staffing for hundreds of technology companies. Layoffs.fyi reports that tech companies have cut more than 225,000 jobs in 2023. While that number is scary, many laid-off professionals are securing new employment within a matter of months, by pursuing opportunities outside of the tech industry. 

This shift is likely due to the consistent demand for tech expertise to drive forward large-scale digital transformation and modernization projects at companies in the finance, healthcare, nonprofit, and government sectors. 

Recent reports from the U.S. Bureau of Labor Statistics predict that job security for software developers will increase by 25% by 2031, and 35% for cybersecurity analysts. 

As companies and organizations seize the moment and ramp up their tech hiring, recalibrating your hiring for speed and scale can optimize your processes, delight your candidates, limit disruptions to your engineering teams, and bring the best talent on board.

Karat

Expand the top of your hiring funnel with technical assessments

After a job has been posted, hiring managers and recruiters review candidate resumes and applications. Historically, this has meant evaluating work history, educational credentials, and other certifications before they invite a select group of applicants to interview. 

For many, especially at larger companies or during peak times like university recruiting season, the sheer volume of direct applicants means prioritizing certain candidates over others, which presents a challenge: how do you assess a large number of candidates efficiently, and fairly?

Some organizations prioritize referrals, proactively sourced candidates, and those with impressive resumes, but this approach focuses more on filtering candidates out, rather than qualifying them in. In fact, Larry Quninlan, former CIO of Deloitte, believes that expanding talent pools beyond referrals and existing networks is key to both improving the quality of engineering teams and increasing diversity. 

“Many in the industry are quick to reject candidates based on their pedigree – what companies they worked for or what schools they went to – but, all this does is reinforce the same profile of candidates that are already being hired. Breaking out of that pattern by giving more direct applicants a shot simultaneously raises the hiring bar and improves diversity numbers.”

To more directly evaluate candidates, leading organizations are turning to direct skills assessments that often take one of two forms: adaptive assessments and code tests.

Code tests present candidates with a long-form coding question. However, recent developments in generative AI have made traditional coding assessments less predictive. What’s more, long-form coding tests have very high drop-out rates – especially when it comes to senior, executive, or highly competitive candidates. 

The adaptive, multiple-choice format is often much shorter, averaging 15-30 minutes per exercise, which often makes it more convenient and accessible to candidates. Adaptive assessments achieve this by selecting which questions to ask the candidate based on their prior answers, allowing the system to narrow in on the candidate’s skill level with fewer questions than a traditional fixed-format test. Adaptive assessments have also proven to result in more predictive results and leveling insights for companies tasked with hiring tech talent. 

Once skills have been reviewed, consider conducting initial interviews with large pools of qualified candidates. The latest hiring trends research from Karat and Harris Poll shows that engineering and talent leaders who cast a wider net by interviewing more candidates are more likely to meet hiring targets and build strong engineering teams. Previously, one of the biggest barriers to expanding talent pipelines was that the tools available for vetting deep pools of candidates were designed to screen applicants out, rather than qualify them for consideration.

Design and deploy technical interviews

Once candidates have successfully passed an adaptive technical assessment, we recommend that hiring leaders design and conduct technical interviews that dig into the specifics of the role. Think about what success will look like for the person in this position when they have their first annual review. Identify the critical skills needed for that type of an evaluation. 

Once you have identified those skills, use them for more than a draft of your job description. Transform those skills into the framework for a technical interview by linking each question you ask to a specific skill needed for the role. This approach will help you accurately and consistently evaluate qualifications from candidate to candidate. What’s more, share those qualifications with candidates prior to the interview so they know how to prepare and how they will be assessed.

Finally, your framework can help architect questions for the technical interview. Refrain from asking ambiguous questions that could result in responses that don’t assess relevant skills. Draft questions that enable candidates to analyze something specific, have a limited number of possible answers, and directly measure the proficiency for which you’re hiring.

Set a straightforward and standard hiring bar

Your skills framework can also serve as your hiring bar. Discuss the skills you identified with your hiring committee and decide what level of proficiency is needed for successful on-the-job performance. How you arrived at that decision will help you develop an interview scoring rubric that can be used to consistently evaluate each candidate’s performance.

Establishing what skills you are looking for, and what traits you are observing to evaluate them, creates a clear and consistent hiring bar. This is especially important in a remote hiring environment, because it creates an established standard everyone can refer to when evaluating different candidates’ performance. 

Maintain high-quality metrics on your hiring process

Consistent, high-quality metrics are central to an equitable hiring process. Designate someone to identify the data sources you plan to track, possibly a member of your Talent Acquisition, HR Analytics, or HRIS (Human Resources Information System) team. Ensure someone routinely reviews them to maintain their consistency. 

When you verify this process is in place, your organization can compare candidates using meaningful data unavailable to competitors vying for the same high-quality talent. Your company will also be able to:

  • Identify issues in your interview and hiring processes to make continuous improvements
  • Ensure your data’s integrity and quality
  • Reduce bias, because all applicants are evaluated on the same metrics and benchmarks

Ultimately, hiring should be about finding the best possible talent and delivering an experience where candidates can showcase what they can do as the best version of themselves. Refining your hiring strategy by implementing adaptive technical assessments, conducting technical interviews, creating a consistent hiring bar, and monitoring your process through metrics helps you achieve both.

Karat