How is Machine Learning Actually Impacting Hiring?
From a job board provider perspective:
There are many factors that are influencing the world of recruitment right now. From ongoing skills shortages and tackling unconscious bias, to new technologies and record employment; hiring professionals are under pressure to source the right candidates, in the right way.
Indeed, one of the key areas that’s on everyone’s lips is machine learning and AI. Ultimately, machine learning seeks to help employers automate some of the more repetitive areas of the recruitment process. And for that reason, it’s an area that many organizations are keen to explore.
But how is machine learning actually impacting (and improving) companies’ hiring practices? With promises that it can boost your hiring efforts and remove some of the more arduous tasks associated with recruitment, it’s no wonder that businesses want a piece of the pie. So, let’s discuss just some of the ways this is happening.
Improving Job Matches for Candidates
At Resume-Library, we’ve been using assisted machine learning to help improve job matches for candidates. This works by manually rating job search results against popular search terms. So, for example, if a candidate were to search ‘substitute teachers’ and the results included jobs for ‘substitute nurses’, this would receive a one star rating out of five.
Once we complete this stage, this information is fed into the ‘machine’, which goes on to identify patterns for good and bad jobs. The logic is then applied to all jobs on the site to ensure that candidates are presented with only the most relevant search results.
This approach to machine learning is helping to improve matches for candidates, while also pushing employers’ jobs in front of the right people. Ultimately, this will ensure companies receive more applications from the most relevant candidates. So, it’s worth checking in with your vendors to find out whether they’re using machine learning to improve your candidate matches.
Analyzing the Success of Job Adverts and Identifying Patterns for Future Posts
Your job advertisement is one of the most important parts of your hiring process. After all, it’s the first insight a candidate has of your company, so it’s crucial to get it right. The good news is that this is an area where machine learning is playing a key role.
Of course, AI and machine learning can never take away the entire task of writing your job adverts; this still requires a human touch. However, it can help to analyze your postings and tell you why some adverts work and others don’t. This might be down to language patterns, tone of voice and even any gender specific wordings that might be putting off applicants.
It then uses this information to make suggestions on what you should (and shouldn’t) include in future posts. For organizations that are struggling to recruit, this can provide valuable insights that make a real difference to your hiring process; so it’s definitely something to explore.
Screening Resumes and Assessing For Cultural Fit
Another key area where machine learning is impacting hiring is of course throughout the screening process. Time and money is precious and both can be lost if your screening process isn’t as efficient as possible. The good news is technology is making it easier than ever to screen resumes and assess candidates for cultural fit.
While screening candidates’ skills against a job description is nothing new, the fact that these tools are now able to assess how well a candidate will fit into the company culture is particularly impressive. After all, as it becomes harder to source top talent, companies are increasingly hiring on potential rather than experience. So, being able to assess someone on how well they’ll fit into your business, and what they can bring to the table, can be extremely beneficial.
Another key benefit of using AI and machine learning in this way is that it can help to remove human bias throughout the screening process. Whether we mean to or not, we’re all guilty of judging a book by its cover; so anything we can do to prevent this from happening can certainly help.
Managing Relations with Candidates
Candidate experience is always going to be an important part of the hiring process. As mentioned above, it’s harder than ever to recruit right now and that’s why it’s vital that companies focus on candidate engagement.
This covers each stage of the user journey. From answering candidate questions at the application stage, to staying in contact pre and post interview; keeping candidates happy and informed should be a priority.
One of the trends we’re noticing in this area is the rise in chatbots. Many organizations are using these to help interact with candidates; for example, by providing more information about a job, or even scheduling in an interview. Again, this can save massive amounts of time when recruiting, ultimately having a positive impact on your hiring efforts.
What Are You Doing to Improve Your Hiring Efforts?
Overall, it’s clear that there are a numbers of ways in which AI and machine learning are impacting hiring practises for the better. From improving job matches and job adverts, to screening candidates and managing relations with them, technology is ultimately making the process of sourcing and hiring individuals much easier.
However, it’s important to note that each area should be closely monitored to avoid any form of bias. Indeed, some organizations have hit the headlines for all the wrong reasons when it comes to using AI in their hiring process; and you don’t want to be one of them.
But that’s why it’s still important to include a human element when hiring. Who knows if it will ever be a fully automated process, but what we do know is that there are some great developments being made across the industry.
About the author.
Lee Biggins is founder and CEO of Resume-Library, the fastest growing job board in the U.S. and CV-Library, the UK’s leading independent job board. With industry experience spanning nearly 20 years, Lee is a pioneer of online recruitment and is passionate about the latest developments in the market.