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How to Calculate Your Tech Recruitment ROI

How to Calculate Your Tech Recruitment ROI

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Ruehie Jaiya Karri
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December 3, 2021
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5 min read
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The demand for technical talent is higher than ever. Our brand new edition of the State Of Developer Recruitment survey reports that over 30% of respondents are expecting to hire over 100 developers in 2022.Frantically sinking resources into hiring at scale when there are chances that several employees will quit before their first-year mark is your sign to stop and evaluate your tech recruiting ROI; especially when the cost of a bad hire is an expensive mistake to make.

The tech industry already has a high rate of attrition with costs of bad hires skyrocketing. It cannot afford any further delays due to hiring slips and misses. Keeping certain performance indicators in mind will help you assess what is working for you and what needs to be tweaked.

What is Recruitment ROI?

Recruitment ROI (Return on Investment) is a performance measure used to evaluate the efficiency of an organization’s hiring process. It helps businesses and HR professionals determine the value and effectiveness of their recruitment strategies. Simply put, Recruitment ROI gauges the benefits (qualified candidates, successful hires) against the costs (advertising expenses, recruiter salaries, interview expenses, etc.) involved in the recruitment process.

Understanding this metric helps companies allocate their resources more efficiently, ensuring that every dollar spent on hiring brings the maximum possible value to the organization.

7 metrics to monitor tech recruiting ROI

Metric to calculate your tech recruiting ROI

Time to hire

On average, it takes 42 days to fill an open position. Right from posting a new job opening to hiring a candidate for that role constitutes the time to fill metric. It takes time to complete the process right from sourcing, recruitment marketing, screening to interviewing. It is every recruiter’s goal to reduce the time to fill by as much as possible but it is increasingly difficult to do so when recruiting technical talent.

Coupled with the usual sourcing and interviewing phases, you also need to carry out skills assessments, which only prolongs the time to hire. If this area needs to be optimized, it is time to streamline your hiring processes. Cut down on the several phases of the interview; assess your candidate with a skills assessment instead of a phone interview.

Quality of hire

This recruitment metric is vital to evaluating whether the newly employed candidate is a good hire or a bad hire. You need to assess how much value the new hire contributes to the team and what is their impact on the long-term success of the company. This is subjective and varies from company to company as performance/culture fit can’t just be confined to scores or numbers.

Improving the quality of the source from where you’re hiring directly improves the quality of the candidates. Instead of relying on high-volume recruitment tactics, where you get plenty of leads of under-qualified candidates limit your talent pool. Set aside applicants that are a right fit for the role. Also, assess the ratio of passive to active candidates in your talent pool and work on improving this.

Cost per hire

The simplest way to measure return on investment for your tech recruiting is to calculate how much you’re spending for each hire. What costs are you running up for the entire talent acquisition process? Can you switch to a new tool that is not such a drain on the resources without compromising on its performance? How much are you spending on recruitment marketing?

Tracking the cost per hire helps you analyze where you’re spending more money than you should, how to reduce it, and provides an opportunity for you to spend it elsewhere.

Candidate experience

63% of job seekers will likely reject a job offer because of poor candidate experience, and you certainly don’t want that. If your hiring procedures are clunky and long, you decrease your chances of attracting top talent by a lot. Find the gaps in your tech recruitment processes to make them candidate-friendly and improve your employer brand.

Getting a candidate on board is not the end game. You have to keep an eye on how the early days of the new hire are going, ensure that they are satisfied with the job, and meet expectations of the role.

Recommended read: 5 Reasons For Bad Candidate Experience In Tech Interviews

First-year attrition

A new hire will take a minimum of one year to settle down and begin producing their best work, especially in an engineering team. If your candidates are leaving before they complete a year with you, you never have a chance of getting back what you invested in them. Talent acquisition costs will add up and affect your company’s bottom line.

Unclear expectations and poor performance lead to first-year attrition. When candidates are met with unrealistic expectations that don’t necessarily align with the job requirements, it’s more likely they’ll quit the position within a year. And when you hire an unsuitable candidate for the job, performance will suffer and you may have to let the employee go. Take care to clearly communicate what is expected out of the candidate for the position and ensure they have enough resources to maximize their performance.

Offer acceptance rate

An offer acceptance rate (OAR) determines the percentage of candidates who have accepted a formal job offer letter from your organization. This measurement ought to be vigorously depended on as a sign of a recruiter’s competence.

It is indicative of the recruiter’s ability to trace out the candidate’s priorities, needs, and major issues before an offer is extended. It is no mean feat to arrive on an offer that hits the sweet spot for both the applicant and the organization.

Application completion rate

Another important metric to track is the number of individuals who finish your application form. Low application completion rates mean that individuals drop off midway by as much as 60% according to a CareerBuilder survey — because it’s too lengthy, is tedious, or complicated.

It could also show some sort of technical issue. Investigate low application completion rates right away. Your entire hiring process is hindered until you do, especially as this is the first step in a series of rounds.

Formula for calculating Recruitment ROI

To calculate the ROI of your recruitment process, you can use the following formula:

Recruitment ROI = ((Benefits of Hiring−Cost of Recruitment)/Cost of Recruitment)×100

where,

Benefits of Hiring is the monetary value that a new hire brings to the organization. This could be measured in terms of the new hire’s revenue generation, cost savings, or any other financial metric deemed relevant,

and,

Cost of Recruitment is the cumulative of expenses associated with the recruitment process. This includes advertising costs, recruiter salaries, interview expenses, onboarding costs, training costs, and any other relevant expenses.

By calculating Recruitment ROI, you can determine the percentage return on the investments made to hire.

Challenges in measuring Recruitment ROI

Measuring Recruitment ROI is undeniably complex, but by understanding and addressing these challenges, organizations can gain a clearer picture of their hiring process‘s efficiency and effectiveness. Some of the common challenges faced while measuring this metric are listed below:

1. Quantifying intangible benefits is hard: Unlike direct costs, benefits like improved team synergy, cultural fit, or long-term potential of a recruit can be challenging to quantify.

2. Variable costs can affect standardization: Costs can vary widely between hiring campaigns, making it challenging to maintain a standard measure for ROI calculations.

3. There is usually no immediate ROI: The true ROI of a recruit might be realized only after a significant amount of time, especially if the position requires extensive training or has a longer gestation period for maximum productivity.

4.Speed of hiring can affect ROI: It’s essential to balance the quality of hires with the number of hires. An organization might make many inexpensive hires quickly, but if those hires are not a good fit, the long-term ROI may be negative.

5. Indirect costs might be hard to quantify: There are hidden costs associated with recruitment, such as the time managers spend on interviews, which might not be easily accounted for.

6. ROI can change if the business goals change: As business objectives shift, the value or “benefit” expected from a hire might change, affecting the perceived ROI.

7. External factors: Economic changes, industry trends, and labor market shifts can all impact the cost or value of a new hire, complicating ROI calculations.

How we calculate recruiting ROI at HackerEarth

HE's Tech Recruiting ROI Calculator

We designed an ROI Calculator that simulates the potential amount of time you could save if you use HackerEarth’s offerings in your tech hiring process. This would directly lead to a significant decrease in the cost per hire metric. That’s why they say, “Time is of the essence when it comes to making quality hires!”

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Author
Ruehie Jaiya Karri
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December 3, 2021
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5 min read
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Vibe Coding: Shaping the Future of Software

A New Era of CodeVibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today,...

A New Era of Code

Vibe coding is a new method of using natural language prompts and AI tools to generate code. I have seen firsthand that this change makes software more accessible to everyone. In the past, being able to produce functional code was a strong advantage for developers. Today, when code is produced quickly through AI, the true value lies in designing, refining, and optimizing systems. Our role now goes beyond writing code; we must also ensure that our systems remain efficient and reliable.

From Machine Language to Natural Language

I recall the early days when every line of code was written manually. We progressed from machine language to high-level programming, and now we are beginning to interact with our tools using natural language. This development does not only increase speed but also changes how we approach problem solving. Product managers can now create working demos in hours instead of weeks, and founders have a clearer way of pitching their ideas with functional prototypes. It is important for us to rethink our role as developers and focus on architecture and system design rather than simply on typing code.

The Promise and the Pitfalls

I have experienced both sides of vibe coding. In cases where the goal was to build a quick prototype or a simple internal tool, AI-generated code provided impressive results. Teams have been able to test new ideas and validate concepts much faster. However, when it comes to more complex systems that require careful planning and attention to detail, the output from AI can be problematic. I have seen situations where AI produces large volumes of code that become difficult to manage without significant human intervention.

AI-powered coding tools like GitHub Copilot and AWS’s Q Developer have demonstrated significant productivity gains. For instance, at the National Australia Bank, it’s reported that half of the production code is generated by Q Developer, allowing developers to focus on higher-level problem-solving . Similarly, platforms like Lovable enable non-coders to build viable tech businesses using natural language prompts, contributing to a shift where AI-generated code reduces the need for large engineering teams. However, there are challenges. AI-generated code can sometimes be verbose or lack the architectural discipline required for complex systems. While AI can rapidly produce prototypes or simple utilities, building large-scale systems still necessitates experienced engineers to refine and optimize the code.​

The Economic Impact

The democratization of code generation is altering the economic landscape of software development. As AI tools become more prevalent, the value of average coding skills may diminish, potentially affecting salaries for entry-level positions. Conversely, developers who excel in system design, architecture, and optimization are likely to see increased demand and compensation.​
Seizing the Opportunity

Vibe coding is most beneficial in areas such as rapid prototyping and building simple applications or internal tools. It frees up valuable time that we can then invest in higher-level tasks such as system architecture, security, and user experience. When used in the right context, AI becomes a helpful partner that accelerates the development process without replacing the need for skilled engineers.

This is revolutionizing our craft, much like the shift from machine language to assembly to high-level languages did in the past. AI can churn out code at lightning speed, but remember, “Any fool can write code that a computer can understand. Good programmers write code that humans can understand.” Use AI for rapid prototyping, but it’s your expertise that transforms raw output into robust, scalable software. By honing our skills in design and architecture, we ensure our work remains impactful and enduring. Let’s continue to learn, adapt, and build software that stands the test of time.​

Ready to streamline your recruitment process? Get a free demo to explore cutting-edge solutions and resources for your hiring needs.

Guide to Conducting Successful System Design Interviews in 2025

What is Systems Design?Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.Systems Design, in its...

What is Systems Design?

Systems Design is an all encompassing term which encapsulates both frontend and backend components harmonized to define the overall architecture of a product.

Designing robust and scalable systems requires a deep understanding of application, architecture and their underlying components like networks, data, interfaces and modules.

Systems Design, in its essence, is a blueprint of how software and applications should work to meet specific goals. The multi-dimensional nature of this discipline makes it open-ended – as there is no single one-size-fits-all solution to a system design problem.

What is a System Design Interview?

Conducting a System Design interview requires recruiters to take an unconventional approach and look beyond right or wrong answers. Recruiters should aim for evaluating a candidate’s ‘systemic thinking’ skills across three key aspects:

How they navigate technical complexity and navigate uncertainty
How they meet expectations of scale, security and speed
How they focus on the bigger picture without losing sight of details

This assessment of the end-to-end thought process and a holistic approach to problem-solving is what the interview should focus on.

What are some common topics for a System Design Interview

System design interview questions are free-form and exploratory in nature where there is no right or best answer to a specific problem statement. Here are some common questions:

How would you approach the design of a social media app or video app?

What are some ways to design a search engine or a ticketing system?

How would you design an API for a payment gateway?

What are some trade-offs and constraints you will consider while designing systems?

What is your rationale for taking a particular approach to problem solving?

Usually, interviewers base the questions depending on the organization, its goals, key competitors and a candidate’s experience level.

For senior roles, the questions tend to focus on assessing the computational thinking, decision making and reasoning ability of a candidate. For entry level job interviews, the questions are designed to test the hard skills required for building a system architecture.

The Difference between a System Design Interview and a Coding Interview

If a coding interview is like a map that takes you from point A to Z – a systems design interview is like a compass which gives you a sense of the right direction.

Here are three key difference between the two:

Coding challenges follow a linear interviewing experience i.e. candidates are given a problem and interaction with recruiters is limited. System design interviews are more lateral and conversational, requiring active participation from interviewers.

Coding interviews or challenges focus on evaluating the technical acumen of a candidate whereas systems design interviews are oriented to assess problem solving and interpersonal skills.

Coding interviews are based on a right/wrong approach with ideal answers to problem statements while a systems design interview focuses on assessing the thought process and the ability to reason from first principles.

How to Conduct an Effective System Design Interview

One common mistake recruiters make is that they approach a system design interview with the expectations and preparation of a typical coding interview.
Here is a four step framework technical recruiters can follow to ensure a seamless and productive interview experience:

Step 1: Understand the subject at hand

  • Develop an understanding of basics of system design and architecture
  • Familiarize yourself with commonly asked systems design interview questions
  • Read about system design case studies for popular applications
  • Structure the questions and problems by increasing magnitude of difficulty

Step 2: Prepare for the interview

  • Plan the extent of the topics and scope of discussion in advance
  • Clearly define the evaluation criteria and communicate expectations
  • Quantify constraints, inputs, boundaries and assumptions
  • Establish the broader context and a detailed scope of the exercise

Step 3: Stay actively involved

  • Ask follow-up questions to challenge a solution
  • Probe candidates to gauge real-time logical reasoning skills
  • Make it a conversation and take notes of important pointers and outcomes
  • Guide candidates with hints and suggestions to steer them in the right direction

Step 4: Be a collaborator

  • Encourage candidates to explore and consider alternative solutions
  • Work with the candidate to drill the problem into smaller tasks
  • Provide context and supporting details to help candidates stay on track
  • Ask follow-up questions to learn about the candidate’s experience

Technical recruiters and hiring managers should aim for providing an environment of positive reinforcement, actionable feedback and encouragement to candidates.

Evaluation Rubric for Candidates

Facilitate Successful System Design Interview Experiences with FaceCode

FaceCode, HackerEarth’s intuitive and secure platform, empowers recruiters to conduct system design interviews in a live coding environment with HD video chat.

FaceCode comes with an interactive diagram board which makes it easier for interviewers to assess the design thinking skills and conduct communication assessments using a built-in library of diagram based questions.

With FaceCode, you can combine your feedback points with AI-powered insights to generate accurate, data-driven assessment reports in a breeze. Plus, you can access interview recordings and transcripts anytime to recall and trace back the interview experience.

Learn how FaceCode can help you conduct system design interviews and boost your hiring efficiency.

How Candidates Use Technology to Cheat in Online Technical Assessments

Impact of Online Assessments in Technical Hiring In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers. The ease and...

Impact of Online Assessments in Technical Hiring


In a digitally-native hiring landscape, online assessments have proven to be both a boon and a bane for recruiters and employers.

The ease and efficiency of virtual interviews, take home programming tests and remote coding challenges is transformative. Around 82% of companies use pre-employment assessments as reliable indicators of a candidate's skills and potential.

Online skill assessment tests have been proven to streamline technical hiring and enable recruiters to significantly reduce the time and cost to identify and hire top talent.

In the realm of online assessments, remote assessments have transformed the hiring landscape, boosting the speed and efficiency of screening and evaluating talent. On the flip side, candidates have learned how to use creative methods and AI tools to cheat in tests.

As it turns out, technology that makes hiring easier for recruiters and managers - is also their Achilles' heel.

Cheating in Online Assessments is a High Stakes Problem



With the proliferation of AI in recruitment, the conversation around cheating has come to the forefront, putting recruiters and hiring managers in a bit of a flux.



According to research, nearly 30 to 50 percent of candidates cheat in online assessments for entry level jobs. Even 10% of senior candidates have been reportedly caught cheating.

The problem becomes twofold - if finding the right talent can be a competitive advantage, the consequences of hiring the wrong one can be equally damaging and counter-productive.

As per Forbes, a wrong hire can cost a company around 30% of an employee's salary - not to mention, loss of precious productive hours and morale disruption.

The question that arises is - "Can organizations continue to leverage AI-driven tools for online assessments without compromising on the integrity of their hiring process? "

This article will discuss the common methods candidates use to outsmart online assessments. We will also dive deep into actionable steps that you can take to prevent cheating while delivering a positive candidate experience.

Common Cheating Tactics and How You Can Combat Them


  1. Using ChatGPT and other AI tools to write code

    Copy-pasting code using AI-based platforms and online code generators is one of common cheat codes in candidates' books. For tackling technical assessments, candidates conveniently use readily available tools like ChatGPT and GitHub. Using these tools, candidates can easily generate solutions to solve common programming challenges such as:
    • Debugging code
    • Optimizing existing code
    • Writing problem-specific code from scratch
    Ways to prevent it
    • Enable full-screen mode
    • Disable copy-and-paste functionality
    • Restrict tab switching outside of code editors
    • Use AI to detect code that has been copied and pasted
  2. Enlist external help to complete the assessment


    Candidates often seek out someone else to take the assessment on their behalf. In many cases, they also use screen sharing and remote collaboration tools for real-time assistance.

    In extreme cases, some candidates might have an off-camera individual present in the same environment for help.

    Ways to prevent it
    • Verify a candidate using video authentication
    • Restrict test access from specific IP addresses
    • Use online proctoring by taking snapshots of the candidate periodically
    • Use a 360 degree environment scan to ensure no unauthorized individual is present
  3. Using multiple devices at the same time


    Candidates attempting to cheat often rely on secondary devices such as a computer, tablet, notebook or a mobile phone hidden from the line of sight of their webcam.

    By using multiple devices, candidates can look up information, search for solutions or simply augment their answers.

    Ways to prevent it
    • Track mouse exit count to detect irregularities
    • Detect when a new device or peripheral is connected
    • Use network monitoring and scanning to detect any smart devices in proximity
    • Conduct a virtual whiteboard interview to monitor movements and gestures
  4. Using remote desktop software and virtual machines


    Tech-savvy candidates go to great lengths to cheat. Using virtual machines, candidates can search for answers using a secondary OS while their primary OS is being monitored.

    Remote desktop software is another cheating technique which lets candidates give access to a third-person, allowing them to control their device.

    With remote desktops, candidates can screen share the test window and use external help.

    Ways to prevent it
    • Restrict access to virtual machines
    • AI-based proctoring for identifying malicious keystrokes
    • Use smart browsers to block candidates from using VMs

Future-proof Your Online Assessments With HackerEarth

HackerEarth's AI-powered online proctoring solution is a tested and proven way to outsmart cheating and take preventive measures at the right stage. With HackerEarth's Smart Browser, recruiters can mitigate the threat of cheating and ensure their online assessments are accurate and trustworthy.
  • Secure, sealed-off testing environment
  • AI-enabled live test monitoring
  • Enterprise-grade, industry leading compliance
  • Built-in features to track, detect and flag cheating attempts
Boost your hiring efficiency and conduct reliable online assessments confidently with HackerEarth's revolutionary Smart Browser.
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