It’s incredible to think just how much sourcing and recruitment have changed since businesses first began to invest in talent acquisition functions. I can’t imagine what it must have been like 20, even ten years ago, when conveniences like LinkedIn and even browsing the web were unheard of. Our sourcing resources have changed dramatically over time, to say the least. Upon looking at the past and how much things have changed, it makes me wonder just how much sourcing will evolve over the next 20 years. What new, disruptive technologies will once again transform the function? How will we utilize those technologies? What changes will we see in talent acquisition as a result?
Upon pondering these questions, I don’t think certain elements of the talent acquisition process will be affected as much. At its core, I firmly believe that recruitment requires a personal touch. The process isn’t always black and white, and the best candidates don’t join companies simply because one pays more than another. That’s where people come in; and from my perspective, no solution or technological advancement is going to change that in the foreseeable future. But don’t just take my word for it; industry experts seem to agree. Craig Fisher, Head of Employer Brand at CA Technologies and Allegis Global Solutions, states, “Any job that will require an element of empathy is not easily replaced by AI. The jobs that require finesse, and feeling and subtlety will still be needed long after the robots take over.” Human connection is an integral part of recruitment, making automation and AI integration difficult, especially when dealing with complex roles within organizations.
Having said that, there are parts of the process where I could see innovation, namely in sourcing. While the way we research and find candidates has improved dramatically over the years, there are still gaps that need to be filled. Despite the resources we have at our disposal, sourcing the right candidate can still take time. Ji-A Min, a data scientist, specializing in best practices in data-based recruitment, sums it up perfectly, “Up to 88% of resumes received for a role are considered unqualified. A recruiter spends on average 23 hours screening resumes for a single hire.” With the vast amount of information out there, lots of sifting is often required. What is deemed a proficient Boolean string may require going through hundreds of profiles/resumes to get the five that you want.
With advances in big data and artificial intelligence, huge improvements in getting to the right candidate pools quickly seem realistic. One innovation that I could see being useful would be the ability to drag and drop a job description and have a search system (LinkedIn, CareerBuilder, Indeed, etc.) scrub over the description, pulling candidates that match the description keywords from most relevant to least. You could do the same thing with a “bogey” resume, in the hopes of getting more similar results, in effect training the system to get smarter. I’m skeptical on how well a tool like this would work at first, and it’s not something as simple as targeting most frequently used words. (I don’t want the resume with the most uses of “the”) However, if something like this could be developed and refined to the point where meaningful results could be produced, then candidate pipelines could be created much faster, with higher quality results. With the technological advances, we’ve had to this point, “drag and drop” searches seem like a plausible possibility.
Looking at things from a different perspective, I could also see additional barriers coming into play as brands and entities look to protect their information. Take LinkedIn for example, with the highly competitive landscape for candidate information, they have stripped away features and made it harder to access LinkedIn member’s data. Firms like these are blocking emails and phone numbers behind numerous barriers and attempting to strip away the use of extensions or technologies with information scraping capabilities.
Take their ongoing lawsuit with hiQ Labs for example, where, as Alison Frenkel of Reuters reports, “LinkedIn claimed it has a right to protect the privacy of its users by blocking users that violate its terms of service, just as a public library might cut off borrowing privileges for someone who used a fake ID or refused to return a book. HiQ countered that it never trespassed but only accessed LinkedIn data available to the entire world, like any onlooker in a public square.” In the fight to maintain a competitive advantage and protect their bottom line, we have begun to see businesses like LinkedIn make an effort to tighten up their accessibility. It will be interesting to see how situations like these develop as new, disruptive technologies enter the marketplace. Recruiting is highly data-driven, and cases like the one above will shape the way we can acquire and utilize information on the Internet going forward. As such, I would anticipate the way we source today being far different than how we go about the process in the years ahead.