Talented software engineers are in high demand. In their rush to hire technical talent faster than the competition, recruiters and hiring managers may make hires that end up being a poor fit for the company. As a result, the tech industry experiences higher turnover rates (13.2%) than other sectors (10.5% average). Forward-thinking companies are now using the Quality of Hire (QoH) metric to evaluate the effectiveness of their hires.
According to Jobvite’s survey, improving Quality of Hire over the next 12 months is the top priority of recruiters surveyed.
In this article, we explore this crucial hiring metric, how it impacts your business, and what to do to improve it.
What is Quality of Hire?
Quality of Hire (QoH) is an important metric that indicates the value an employee adds to your organization. It also helps you examine the efficacy of your hiring process in finding, onboarding and retaining top talent.
Companies typically measure a new hire’s performance during the first year to assess QoH. Measuring your new hire’s performance during the first year (or even earlier) provides insight into their contribution to your organization’s success.
Low QoH rates indicate low-quality hires with the potential to cost your organization a significant amount of money in the long run. On the other hand, a higher QoH leads to better performance, increased revenue and higher retention rates over time.
Since various factors impact employee performance, companies use a combination of pre-hire and post-hire data and metrics like performance indicators, employee engagement and turnover to assess QoH.
Analyzing employee performance and engagement can help predict turnover, so you can proactively develop retention tactics for employees at the risk of quitting. You can also identify employees with higher engagement levels and productivity who are more likely to stay on.
But measuring the quality of hire has its own set of complexities.
Challenges in Measuring the Quality of Hire
While measuring QoH is becoming popular, it is a complex metric to track. Metrics like employee engagement and cultural fit, crucial to QoH, may be subjective, difficult to quantify and differ across organizations.
Without a universal formula or approach to measuring QoH, talent acquisition leaders struggle with optimizing talent.
So, how can you measure the quality of hire?
How To Calculate Quality of Hire
There is no one-size-fits-all approach when it comes to measuring the quality of hire. Quality and value are unique to all organizations, and they use a combination of different variables to determine value. The most common metrics organizations use include:
Pre-hire metrics include scores on skill assessments, time to hire, cost of hire and hiring budget and determine the candidate’s probability of being a quality hire. Tracking pre-hire metrics strengthens the hiring process to predict hiring quality precisely before onboarding a candidate.
Performance Metrics – One of the most popular ways to measure QoH is via employee performance reviews, the success rate in achieving set goals or targets and assessing productivity and job fit.
Employee Engagement and Satisfaction – Employees who are satisfied and engaged with their work consistently perform better, resulting in improved business outcomes.
Retention & Turnover – Early turnover amongst new hires indicates that there are issues with your hiring process and organizational structure, leading to high turnover. Consequently, better QoH improves employee retention and vice versa – employees who stay long-term bring more value to the organization.
A tried-and-tested formula is to quantify the variables and average them to get an average quality score for new hires.
How to Improve Quality of Hire
Perfect Your Job Descriptions and Ads
A job ad is the candidate’s first interaction with your brand, and it is essential to get it right if you want to attract and retain talented candidates. Creating job ads with accurate and detailed job descriptions written by subject matter experts will provide a compelling overview of the job and increase your chances of reaching the right candidates.
Unclear and vague job descriptions will confuse candidates, while on the other hand, job descriptions with unrealistic requirements may deter qualified candidates from applying.
Hiring managers will struggle to identify the candidates who fit the role, while candidates will fall short of your expectations without proper job role information. If you end up hiring an unsuitable candidate, it is an additional cost to your organization.
Focus on listing specific objectives, tasks, duties and deliverables rather than simply stating required skills and qualifications. Providing candidates with a realistic picture of what the job will look like helps candidates feel prepared and motivated to pursue the role.
This is especially true when hiring for technical positions where roles are distinctly defined.
Validated Technical Screening and Assessments
Skills-based assessments are fundamental to tech hiring as they offer insight into a candidate’s technical, programming and problem-solving skills. Technical screening and coding assessments have replaced traditional resume screenings, opening the recruitment funnel to diverse candidates and promoting skill-based hiring.
Assessing candidates for skill shifts the focus from pedigree to competency. With validated and research-backed screening tools, you can streamline the process, automate scoring and evaluation and ensure consistently higher performance from new employees.
These factors, including culture fit, personality and proficiency, impact the QoH of your candidates.
Make Recruitment a Team Effort
Often recruiters have little information about the role they are hiring for. When hiring for technical positions, designing a specific job description and ads is crucial. Work with hiring managers, subject matter experts and Industrial-Organizational Psychologists trained in job analysis to define the job role and essential skills to look for. Then, craft a compelling job description to attract candidates.
By collaborating with all stakeholders, you ensure that everyone understands the role and its demands. It also helps you define ‘quality’ and ‘value add’ for your candidates. Post-hire measuring performance and employee value will become easier with everyone on the same page about the hire.
Assess Your Current QoH
Lastly, begin by first evaluating your current quality of hire. Use your organization recruiting data and employee performance to ascertain your current QoH. It will help you define important metrics for your organization and improve the process to ensure hiring quality.
Conclusion
Quality of Hire is an important and popular metric this year for organizations to assess the effectiveness of their new hires. But, it is a complex metric to track due to the subjective nature of the variables involved.
High QoH influences employee performance, retention and business revenue. You can improve your quality of hire by optimizing your job descriptions, using validated screening and assessments and collaborating with experts to understand hiring needs.
Authors
Sophia Baik
Sophia Baik is Co-founder and VP of People, Finance, and Operations at CodeSignal, a coding skills assessment platform dedicated to helping companies #GoBeyondResumes in tech recruiting. Prior to co-founding CodeSignal, Sophia started her career in investment banking at Lehman Brothers before gaining experience in marketing and operations at tech companies such as Wayfair, Zynga, and Beepi.
Discussion
1 thought on “Understanding the Quality of Hire Metric in Tech, and 4 Ways of Improving It”
Comments are closed.
Please log in to post comments.
LoginRecruit Smarter
Weekly news and industry insights delivered straight to your inbox.
I really like the idea of creating an average quality score. Where I see companies struggling with this though is that, unless they have a very sophisticated HCM analytics function, they will be unable to produce these metrics consistently, let alone use them for strategic decision-making. This is so often the case—companies know THAT they should be measuring, they know WHAT they should be measuring, but they lack the bandwidth and/or internal capacity to actually DO the measuring consistently.