All tech goes through periods of great change, and recruitment software is no different. Earlier this year Josh Bersin, a global industry analyst, released a 55-page report called the “2019 HR Technology Market.”
In this report, he identified 11 “seismic shifts” that are taking place in today’s HR sector.
Among the shifts he mentioned, Bersin cited the arrival of “innovative, creative and often AI-based” tools for talent management.
“These new talent applications,” he wrote, “are focused on improving the employee experience from top to bottom—aiding recruitment, performance and goal setting, learning, career management, rewards, well-being, and ultimately work itself.”
With the immense amount of funding coming into the recruitment space, recruitment software has helped improve a lot of admin-intensive activities of recruiting:
- Candidate screening
- Applicant Tracking Systems
- Interview scheduling automation
Technology is currently focused on improving AI in recruiting software to support recruiting’s main goal: hiring the right people. Hiring the wrong person can be detrimental and lead to astronomical losses. Zappos’ founder said bad hires have cost the company over $100M.
Other sources calculate that the cost of a bad hire is at least 30% of the employee’s salary. No matter how you slice it, it’s an unaffordable waste to hire someone that isn’t a good fit. With recruiting software, however, has come an increase in efficiency. Unfortunately, we are still somewhat antiquated in our processes.
For example, even some of the most advanced companies still rely on unstructured interviews and a hiring manager’s gut-feeling when making decisions on who should be hired. With diversity and inclusion one of the hottest topics in 2019, structured interviews with diversified panels is a big focus to remove unconscious bias. While hiring assessments are trying to eliminate this bias, the data you get out is only as good as the data you put in.
With all of this top-of-mind, we predict this year’s recruiting software will focus on:
Data & Analytics
Applicant Tracking Systems are the one-stop-shop for recruiting teams to see their entire candidate pipeline. While this data is great, in our own experience, we’ve found that an ATS doesn’t provide enough data to help organizations when it comes to forecasting.
With recruiting bringing in people from all kinds of backgrounds, data is the one thing everyone desperately wants: How many people do we need to hire? How long will it take? How many interviews do I need to get scheduled? How many interviewers do I need, and how long will they be removed from working on their key projects? How much will it cost to reach these hiring goals?
All of these questions and more are what talent leaders are faced with at every company, but very few are able to answer them. This will definitely change as the HR space has realized in order to succeed they need to start relying on data just as much as sales, marketing, and operations.
AI is not just another buzz word being thrown around – it’s the real deal. However, it may be overreported with its impact on recruiting. With Chatbots, NLP, and other items, the main focus for AI is to leverage the data all these recruiting systems are capturing and continue to optimize over time.
With advanced screening technology, organizations have made selecting candidates a lot better. Companies receive a ton of resumes/CVs from job boards, referrals, and from headhunting. Before, going through all these resumes would take recruiting teams hours on end. Now, technology is available to screen these resumes for teams to help identify which candidates should be moved forward and which should not. The issue at hand, however, is that these bots only look for specific traits, and may not accept candidates that would be a good fit but have different backgrounds.
This is similar to the current interview process, where a first impression is everything (whether in-person or virtually), is everything. A candidate’s school, previous employment, how they walk, or if they smiled all are key factors in determining future employment.
With IBM mentioning the benefits of diversity in an organization (to the sum of billions!), it’s critical for companies to minimize bias in the hiring process. Blanking out school names/employers on resumes has helped reduce bias from Hiring Managers, and it’s a good start, and as recruiting software gets better and better, bias will be even further removed.
Smarter interview panels are part of the future, one where interviewers will be selected based on personal characteristics, where an interviewer/candidate when to school, and many other factors. By using data to intelligently select interviewer, companies will be able to select candidates based on their skill sets and if they are a good match for the company values instead of gut feelings.
Self-driving cars aren’t the only actualized realities that we’ll be working with. The coming years are poised to bring a lot of exciting new technology into the world of recruiting. Still, even with all the advancements we’ve gotten since the creation of the ATS, there’s still so much work to do. From reducing the time/cost to hire by increasing recruiting efficiency to improving the quality of hire, we expect to continue to see both VCs and companies investing in these new technologies to edge out their competitors when it comes to bringing the right people into their organization.
What are some of your predictions?
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