Technical interviews are a crucial part of the hiring process for software engineering and other technical roles. These interviews aim to assess a candidate's skills, knowledge, and problem-solving abilities through a series of coding, system design, and behavioral questions. One key metric used to evaluate the efficiency and effectiveness of a technical interview process is the pass-through rate. In this blog post, we will discuss pass-through rates, how to measure them, the importance of having strong pass-through rates for interviewing efficiency, and gold standard pass-through rates based on insights from industry leaders.
What are Pass-Through Rates and Why You Should Measure Them
Pass-through rates represent the percentage of candidates who successfully advance from one stage of the interview process to the next. The higher the pass-through rate, the more candidates are progressing through the interview stages, ultimately leading to an increased likelihood of filling the open positions. Conversely, a low pass-through rate may indicate that the interview process is too difficult or is not accurately evaluating candidates' skills and knowledge.
Strong pass-through rates are essential for maintaining an efficient interview process. When pass-through rates are low, it may indicate that the process is either too challenging or not effectively assessing candidates. This can result in a higher number of interviews conducted, ultimately consuming more of your engineers' time and reducing their productivity. By optimizing pass-through rates, organizations can streamline their hiring processes, minimize the time spent on interviews, and allow engineers to focus on their core responsibilities.
How to Measure Pass-Through Rates
To calculate pass-through rates, follow these steps:
- Identify the stages of your interview process: Common stages in a technical interview process include phone screens, technical assessments, on-site interviews, final hiring decisions, and offer acceptance.
- Determine the number of candidates at each stage: Track the number of candidates that enter each stage of the process and the number that advance to the subsequent stage.
- Calculate pass-through rates: Divide the number of candidates that advanced to the next stage by the total number of candidates at the current stage. Multiply the result by 100 to obtain the pass-through rate percentage for each stage.
Gold Standard Pass-Through Rates
There isn't a one-size-fits-all answer for the ideal pass-through rate, as it can vary depending on company size, industry, and specific job requirements. However, in a recent interview with Plaid's CTO and Segment's CPO which boast engineering recruitment excellence, they shared their gold standard pass-through rates as follows:
Phone Screen to Technical Assessment: 50%+
Technical Assessment to On-site Interview: 40-60%
Offer to Acceptance Rate: 70%+
These rates strike a balance between maintaining a rigorous interview process and ensuring a sufficient number of candidates make it through to the final stages. By continually monitoring and adjusting pass-through rates, organizations can optimize their hiring processes, ensuring they are both effective and efficient.
The Impact of Strong Pass-Through Rates
Let's consider two companies with different pass-through rates in their technical interview process, both needing to fill 5 positions.
Company A (low pass-through rates):
- 358 initial candidates (Phone Screen, 40% pass-through rate)
- 143 candidates (Technical Assessment, 30% pass-through rate)
- 43 candidates (On-site Interview, 30% pass-through rate)
- 13 candidates (Final Hiring Decision)
- 5 candidates (Offer Acceptance, 40% offer to acceptance rate)
Company B (optimized pass-through rates):
- 70 initial candidates (Phone Screen, 40% pass-through rate)
- 28 candidates (Technical Assessment, 50% pass-through rate)
- 14 candidates (On-site Interview, 50% pass-through rate)
- 7 candidates (Final Hiring Decision)
- 5 candidates (Offer Acceptance, 70% offer to acceptance rate)
Now, let's assume the average time spent per technical assessment is 1.5 hours, and per on-site interview is 4 hours. The total time spent on interviews for each company would be:
- Technical Assessments: 143 candidates * 1.5 hours = 214.5 hours
- On-site Interviews: 43 candidates * 4 hours = 172 hours
- Total engineering time: 386.5 hours
- Technical Assessments: 28 candidates * 1.5 hours = 42 hours
- On-site Interviews: 14 candidates * 4 hours = 56 hours
- Total engineering time: 98 hours
Assuming an average fully-loaded hourly cost of $150 per senior engineer, Company A would spend an additional $43,275 in engineering time (288.5 hours * $150) for the same number of accepted offers compared to Company B.
Additionally, low pass-through rates result in a higher workload for recruiters, as they need to screen more candidates at the top of the funnel. Assuming a recruiter gets paid $75 per hour and spends 1 hour per candidate for phone screening, the total time and cost for the recruitment process would be:
- Phone Screens: 358 candidates * 1 hour = 358 hours
- Total recruitment cost: 358 hours * $75 = $26,850
- Phone Screens: 70 candidates * 1 hour = 70 hours
- Total recruitment cost: 70 hours * $75 = $5,250
Company A would spend an additional $21,600 in recruitment costs for the same number of accepted offers compared to Company B. Overall, the cost savings of both recruiter and engineering time would amount to close to $65K by just improving the pass-through rates.
Understanding pass-through rates in a technical interview process is essential for companies looking to optimize their hiring efforts. By calculating pass-through rates, organizations can identify areas for improvement and make data-driven adjustments to their interview processes. Aiming for gold standard pass-through rates, as recommended by industry leaders, can help strike the right balance between a challenging interview process and securing the best talent for your organization. Moreover, strong pass-through rates are crucial for maintaining interviewing efficiency and minimizing the impact on your engineers' time and productivity.