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Identifying, attracting, and retaining great software engineering talent is a struggle that every organization faces during their recruitment process. According to the Harvard Business Review, 80% of employee turnover is a result of bad hiring decisions.

The cost of a bad hire can cost organizations at least $25,000 in monetary damages apart from the almost irrecoverable decrease in productivity and performance of teams.

Why Traditional Methods of Hiring Are Bad for Your Recruitment Process?

Traditional methods of hiring also contribute heavily to the degrading quality of hire of software engineering talents. Interviewing techniques such as administering coding tests are viewed in a negative light by the majority of job-seeking developers.

“Most engineers today hate the idea of completing a coding test, and more than 50% of the candidates straight out refuse to do status quo assessments”, says Deepti Chopra, co-founder of Adaface, in her article, Why Engineers Won’t Do Your Coding Test.

She holds the following reasons responsible for engineers to be reluctant to do traditional coding tests:

• Testing for tricky algorithmic skills rather than on-the-job skills.
• A candidate-unfriendly environment and a weak employer brand.
• Coding tests are time-consuming.

Most job-seeking developers irrespective of their level of experience have voiced their concerns with coding tests, and most of their criticisms are well-founded.

By leveraging the latest technologies in artificial intelligence in tandem with developer-first hiring practices, organizations in-turn can use their developer assessment tools for a competitive advantage.

How AI-Powered Solutions Are Changing the Candidate-Screening Market?

Automated artificial intelligence systems are transforming how recruiting managers and their teams can apply an equitable hiring process throughout the recruitment funnel while reducing the time needed to hire the best talent. One of the ways in which AI-powered solutions are effective is for the screening of potential candidates. This can be done in the following ways:

• Automated Resume Screening
  AI screening solutions can filter through resumes and CVs faster than a human can and flag the potential applicants that might be of interest. Such tools use keyword analysis to determine the best applicants from the talent pool based on the content of their resume and are usually coupled with applicant tracking systems for easier use.
• Automated Skills Screening
  Developers aren’t necessarily good at selling their skills on CVs and resumes. Automated screening based on skills, screen candidates for the required on-the-job skills using quizzes and tasks. Skill-based screening assessments have been proven to be more accurate considering other methods, with the highest success rate of finding the right candidate-job fit.
• Video Screening
  AI video screening platforms filter candidates by analyzing their answers and choice of words to interview questions. Physical cues such as eye movements, facial expressions, and other traits are also recorded and analyzed, which helps companies identify the best candidate for a job.

Benefits of using AI for screening candidates include:

• Reduction in hiring costs.
• Efficient interviews.
• Finding the best right person-job fit.

What Are Conversational Assessments?

Consider a student working with a teacher for the first time. To better understand the boundaries of the student’s knowledge, the teacher may put forward problems to solve and then review the student’s answer. If the submitted answer is incomplete, or unsatisfactory, or completely irrelevant to the question itself, the teacher may follow-up with additional questions or hints. These additional follow up questions and hints can reveal the degree of understanding of concepts by the student. Such open-ended interactive conversations reveal more diagnostic information on the student’s domain of knowledge and the ability to apply the skills.

This is the governing idea behind Conversational Assessments or Conversation-based Assessments (CBA) wherein the interaction takes place between a candidate and an AI system. Interacting with candidates using conversations as a method to accurately assess the applicant’s knowledge and skills in order to provide an adaptive response to their input. Human-to-computer and vice versa conversations are already being used in gamified educational learning and intelligent tutoring systems.

An automated conversational assessment system can be used for skill-based screening of a pool of applicants by integrating the measurement of multiple skills within a single, customizable assessment. Traditional hiring assessment platforms have a test completion rate of almost 50% due to low interactivity, whereas conversational assessments see a completion rate of almost 86% because of a higher level of interactivity with the candidates in a candidate-friendly environment. Questions and hints for CBAs are carefully designed to provide opportunities for candidates to showcase their knowledge and skills.

CBAs are powered by AI-based conversational bots or chatbot which function by gathering candidate user data, answering their queries, providing hints during the assessment as well as testing and scoring them on relevant skills. This allows HR teams to achieve a 100% screening coverage, which if done manually is unachievable.

Key benefits of using Conversational Assessments over traditional hiring assessments include:

• Reduction in the time required for hiring.
• Increase in test completion rates.
• Testing for on-the-job skills.
• Identification of the best talent.
• A positive increase in employer brand awareness.

Hiring Developers Using Conversational Assessments

41% of recruiting managers use some kind of talent assessment platform when it comes to hiring Software engineers. Choosing the right kind of pre-employment assessment platform can either make or break your hiring funnel.

It is shamefully true that software developers in general are bad at selling their talent and skills. AI-based conversational assessments help in engaging both active and passive candidates with the help of natural and dynamic conversations. Candidates are more open to CBAs because they are faster and feel like an interview with a Senior developer rather than just another test.

Through open-ended natural conversations, CBAs assess developers on programming skills with customizable questions of all difficulty levels. This allows recruiters to screen prospective candidates for on-the-job core technical skills (for example the SQL online test for SQL developers and Backend developers), basic skills (for example the excel test for assessing excel skills for all business-related roles) as well as soft skills. Conversational AI-based assessments along with machine learning and natural language processing abilities, have the capacity to assess candidates based on their conversation and can provide a pass or fail recommendations to the recruiters.

Such systems are also helpful for recruiting teams to gather extensive candidate insights along with a positive candidate engagement. Implementing CBAs also provides additional benefits of losing fewer potential candidates along the recruiting pipeline, making the entire hiring process more efficient.

Using Conversational Assessments for Remote Hiring

As more and more organizations are moving towards remote hiring practices, it is important for recruitment technologies to accommodate the same. Remote hiring practices include hiring remote employees (which further increases the talent pool) and/or hiring employees from the same location but completely or at least partially digitalizing the recruitment process.

Every conversational assessment — skill-based or behavioral — is conducted online. This means that candidates can now attempt hiring assessments from their preferred time zone at their own pace. Features such as online remote proctoring ensure the authenticity and validity of the assessment results.

Conclusion

AI-powered conversational assessment platforms have the potential to disrupt the HR marketplace and revolutionize the hiring process. All organizations can benefit from AI-powered solutions, provided they make the effort to maximize the pros and limit the cons.

Photo by ThisisEngineering RAEng on Unsplash