Algorithms and hiring: these two factors are critical for talent acquisition, and can make all the difference to the team you hire. 55% of US organizations use algorithms and predictive analysis which contributes to their talent acquisition process.
You’ll definitely know what hiring is if you’re a recruiter, but do you know what algorithms are and how they impact the hiring process?
Knowing as much as possible about algorithms and their relationship to hiring is crucial for optimizing your recruitment process. So, read this article to learn all you need to know about algorithms and hiring.
What is meant by algorithms in hiring?
A simple definition of an algorithm is the processes, operations, calculations and analyses of statistics and information and data related to your candidates. Algorithms then produce information and data that you can use when making a hiring decision.
During the candidate evaluation stage, certain types of data are targeted by algorithms to help you assess candidates, such as their resumes, their skills and answers to skills and personality tests, and the information available to the public that can be found online.
Part of knowing what algorithms are in hiring is knowing what AI (artificial intelligence) is in the context of hiring algorithms. AI is an advanced technology that can automate hiring processes and even make predictions on how successful an applicant will be if hired.
AI can work together with algorithms to combine various data points and predict the best-fit candidate for your organization.
What is algorithm validation?
Algorithm validation is also important when using algorithms for talent acquisition. It refers to the process of ensuring that the algorithm used for screening can accurately predict a job-related quality. In other words, it involves making sure that predictive validity can be demonstrated, which can be difficult as older validation methods might be invalid now.
Why is knowing what algorithms do as a user important?
Knowing what algorithms do as a user is crucial. It’s important to know whether your algorithm is searching for the characteristics of a job applicant that predict success, or is analyzing social media data and data that’s available publicly, or has been designed to analyze the data gathered from skills assessments, because this can impact the hiring process and how you interpret the data once processed.
What are the advantages and disadvantages of using algorithms for hiring?
Let’s now analyze some of the advantages and disadvantages of using algorithms for hiring. We’ll start with the advantages.
Advantages of using algorithms for hiring
Two advantages of using algorithms for hiring include enhancing the candidate experience and boosting the efficiency of the hiring process.
How do algorithms enhance the candidate experience?
During hiring, algorithms make your decision-making process as a recruiter or hiring manager easier since they analyze the data faster, thus reducing the time it takes to select candidates for the interview stage based on their applications and data. This faster decision-making process in turn enables you to respond to candidates faster and earlier.
With faster responses to candidates, you can keep them interested in the position and enhance the candidate experience, decreasing your chances of losing exceptional talent due to lengthy decision making.
How do algorithms enhance the efficiency of the hiring process?
When used and developed correctly, algorithms and artificial intelligence enhance the efficiency of the hiring process by helping to reduce bias. The reduction of bias can produce good results for your hiring process, helping you to increase diversity and inclusion—but only when algorithms are developed the right way.
Disadvantages of using algorithms for hiring
Two disadvantages of using algorithms for hiring include that they can be biased when used incorrectly, and that it must be aligned with your hiring process.
Are algorithms biased and do they make biased decisions?
Just like human recruiters, algorithms can make biased decisions because they learn from data and are programmed by humans who might be biased when programming them. Therefore, the process of analyzing the data can be skewed towards certain candidates who might not be suitable for the role if the algorithm has not been developed the right way.
The algorithm might not be correctly aligned for your company’s hiring
It takes time to align an algorithm to your hiring process. You might need an algorithm for resume analysis, or specifically for skills test result analysis, so programming the algorithm specifically for these purposes is critical.
If your algorithm is incorrectly aligned for your company’s hiring process, you risk making the wrong hire. You risk wasting time, not only during the first development stage of the algorithm itself, but during the hiring process as well. You risk wasting money and incurring high costs that impact your recruitment budget. And you risk having to rehire candidates.
Algorithms, AI and talent acquisition: Why you should use them
Ultimately, algorithms and AI can definitely make a positive impact on your talent acquisition process. They can keep time to hire low when compared with manual and lengthy resume analysis and enhance the candidate experience.
Use algorithms in conjunction with AI to analyze data efficiently and reduce bias, and learn more about how they enhance talent acquisition at recruitmenttech.com.