Candidate screening is a process that an organization uses to evaluate a job applicant. Historically candidate screening has taken many forms; from the highly formalized submission of resumes sourced through recommendations to the classic nepotism of hiring your brother's step-son as a favor. A universal process to screen candidates has never and will never exist. The process will always have to be highly customized to fit the purpose of the organization and must evolve to maintain effectiveness.
The internet provides an unlimited source of candidates. Anyone can go online and apply for a job through a variety of platforms. This sounds like a good thing for employers until 10,000 candidates apply for a single open position. How do employers hire the right person out of 10,000? Employers must have consistent processes to screen candidates, but they must also be efficient.
Humans will always play a critical role in the hiring process, but the consistency vs efficiency challenge exemplifies why reviewing resumes is a task better suited for modern machines than modern humans.
Here are 4 reasons why candidate screening is no longer a human task.
1. The volume of candidates to review is too large for humans.
It is not uncommon for large companies to process over a million candidates per year. That's an incredible challenge for talent operations and if leaders are not careful, it will add up to an incredible cost. Most companies manually read each applicant's resume or profile. This means that talent acquisition professionals are asked to evaluate thousands of candidates a week.
Imagine for a moment that your job was to read 3,000 resumes a week. Assuming that you don't have any other responsibilities, that's 600 resumes a day, 60 an hour, or 1 per minute. Could you say with confidence that you can size up a candidate in under a minute? Could you guarantee that candidate #1 was evaluated the exact same way as candidate #3000? How long would it take for you get bored of screening candidates and switch your brain to autopilot?
2. Talent acquisition teams should maximize their time connecting with candidates.
Resumes and online profiles only provide a small window into a candidate. The real vetting takes place via personal interaction. Talent acquisition teams are put in place to connect with people and to use their professional judgment to evaluate fit. HR leaders should take every step possible to increase the time their talent acquisition teams are interacting with candidates. If reviewing resumes becomes hyper-efficient then the time saved can go directly towards candidate interaction.
3. Humans are biased in unpredictable ways.
If the goal of candidate screening is to deliver a consistent and repeatable outcome across thousands of data points, humans are no longer the best option. In fact, given the currently available options, humans might be the worst. There have been numerous academic studies detailing hiring bias based upon education level, name, gender, race, ethnicity, height, etc. Human brains are not able to make any judgment without some bias. Once biases are recognized in candidate screening, the only option is to limit bias wherever possible. Modern machines are the best solution for combating bias because they are more effective at reviewing resumes quickly, consistently, and accurately.
This is where people usually point out that "Machines built by humans also possess bias," and it is true. The key difference between human bias and machine bias is that machines are biased in predictable and measurable ways. Bias in machines can be carefully monitored and coached out over time. Bias free machines don't exist, but properly trained machines are objectively less biased than humans.
4. A candidate screening machine won't leave you.
25% of the millennial workforce is contemplating leaving their job by the end of this year. Tasks like reviewing resumes are usually done by entry-level employees, who tend to be millennial-aged. Entry-level churn rates are higher than senior positions, automating a low-level task like candidate screening ensures consistency and quality for the foreseeable future. Better still, the machine will become highly specialized in candidate screening and eventually surpass the quality of a single human trainer. Once a candidate screening machine is operational, it can be monitored by HR leadership and retrained to adjust course if the strategic direction changes.
The human element of candidate screening will always exist, but the digitization of the job application process has created a rapid increase in the volume of candidates that companies encounter. Talent acquisition teams must think carefully when deciding which tasks to automate and which tasks deserve their focused human brainpower.
We covered the "big data" problem in talent in more depth in our ebook: Talent Classification Guide for the AI Era of HR.
Founded in 2014 and based in Bellevue, Washington, Vettd.ai is setting the standard for AI-guided decision management. Vettd.ai uses customized deep learning AI models at the core of their advanced decision management solutions for organizations across a number of industries. These solutions help organizations make more informed decisions by quickly and comprehensively interpreting natural language data including resumes, personal essays, and more. Vettd.ai was founded to help people and organizations thrive together through better alignment with one another. For more information on how Vettd.ai is enhancing the capabilities of decision-makers, visit. http://www.vettd.ai.