With hundreds of candidates applying for each job role, recruiters may often find themselves overwhelmed with a large number of essays to screen. Reading and understanding each easy takes a lot of time, leading to a higher time-to-hire and lower hiring accuracy.
Furthermore, essay evaluation is often a subjective task. There may not always be a consensus on who has written the best essay when recruiters review a pool of applicants. This is due to a lack of a concrete evaluation methodology. While recruiters may use the same metrics, for example, clarity of writing and choice of words, it is difficult to say how much weight each recruiter gives to a metric when evaluating an essay. Recruiters may also be biased towards a particular writing style or topic when examining essays. This lack of consensus makes it challenging to identify high-value candidates, adds time to the recruitment process, and may result in hiring inaccuracies.
Today, recruiters require immediate and insightful insights into a candidate’s writing proficiency with the help of consistent and well-defined metrics. Using natural language processing, essay rating can be automated to allow recruiters to easily shortlist and focus on high-value candidates who express themselves well.
Automated essay systems use natural language processing to evaluate a candidate’s writing with the help of an extensive number of metrics (read our blog detailing various metrics used in automated essay evaluation and scoring for more information). Due to their objective nature, they can provide recruiters with an unbiased score, resolving the issue of subjectivity in evaluating writing. Automated systems can also produce more reproducible results compared to traditional checking methods. They do not contain any inherent biasing metrics, which enables recruiters to conduct more accurate and fair hiring. Studies have shown that automated essay systems have been proven to be as reliable as human graders. Automation consequently enables recruiters to gain the same insights as human evaluations at a fraction of the cost, effort, and time.
The cost of scaling automation is significantly cheaper than hiring more recruiters to review essays. This translates into a substantial increase in productivity for recruiters. Natural language processing algorithms can process entire essays at once and provide instantaneous feedback. On the other hand, humans have to read essays from start to finish, often multiple times, before being able to make an informed evaluation. End-to-end recruitment platforms like impress.ai are enriched with automated essay evaluation and scoring features that provide actionable feedback for candidates to improve their writing skills, resulting in an improved candidate experience.
Automated essay rating is the perfect solution for recruiters who recognize the benefits of essay-based questions in interviews but cannot maximise their potential due to a high volume of applicants and a lack of objective evaluation criteria. They allow recruiters to quickly identify and target high-value candidates, enabling them to remain agile and competitive in the labour market. Automated essay ratings have the potential to be one of the most disruptive technologies in recruitment automation and must be considered for adoption by all recruiters who use essay-based questions in their application process.