In competitive markets like the tech industry, finding qualified applicants is difficult. Closing the right people for the role and the company is even tougher. Since this pain is so widely felt, many technologists dream up software-enabled solutions to solve all of these problems. From automated resume screening to AI-powered video interviews, more advanced tools are built every day to find the right people to hire.
Searchlight.ai, an Accel-backed startup founded by twins with master’s degrees from Stanford and experience at Google and McKinsey, offers an interesting twist in the space. Instead of plugging resumes into a machine learning algorithm or analyzing emotions from during interviews, Searchlight uses your network to determine how well you’d fit into the hiring company. Where most companies would start with an initial phone screen for applicants, Searchlight allows applicants to give references up front which Searchlight then sends a proprietary questionnaire about the candidate. By collecting data from your previous colleagues, they are able to build a profile unbiased by resume writing skills or unconscious bias of a phone screener. The company can then use this profile to find potential matches for soft skills as well as technical abilities.
When I originally came across Searchlight, I was skeptical. Although I’ve had great experiences with previous employers and coworkers, there is an innate uncomfortability with not having the ability to represent oneself during the application process. Perhaps less obscure than many black-box algorithms used in hiring processes these days, the inability to control the narrative or even see what the references say about you still adds to the mounting feeling that applying to new jobs is increasingly a shot in the dark. And what if your colleagues only know the “work you” and not your “true self”? The data could be tainted by existing perceptions, making it very difficult to reinvent yourself as your career progresses.
After weighing the pros and cons, I’m convinced that despite the potential downsides this is actually a great way to leverage human-generated data in a non-biased, positive way. The most apparent benefit is that people are generally bad at demonstrating or judging soft skills in an interview setting. Resume writing, interviewing, and performing well in an interview are all skills that have to be trained and learned. This leads to otherwise stellar candidates regularly being passed over in the process. By aggregating analysis on a candidate from multiple people from their past, Searchlight diversifies the data sources used in support of the candidate and allows recruiters to make less biased decisions. The Searchlight system also helps companies get more serious applicants as it requires additional upfront work. If an applicant is excited about working for the company, it is a fairly low hurdle to collect the references but it is a big enough barrier to filter out unserious applicants. Also, by giving applicants the ability to retain references on the platform, it helps applicants continually add to their profile over time.
According to the article, Searchlight is starting with hiring but expects to leverage their datasets in the future for employee development. This could be particularly interesting if past or present colleagues identified soft skill opportunity areas that could then be focus areas for personal training and development programs. Also, the profiles could be used in the very first 1:1 a new hire has with their manager to bridge the person improvement gap so often felt when switching jobs. Off to a fast start, It will be exciting to keep up with Searchlight as they grow their dataset and add additional features to their platform.
Daso, F., 2020. Accel-Backed Searchlight.Ai, A B2B Hiring Software Startup, Fixes The Broken Interviewing Process. [online] Forbes. Available at: <https://www.forbes.com/sites/frederickdaso/2020/03/31/accel-backed-searchlightai-a-b2b-hiring-software-startup-fixes-the-broken-interviewing-process/#5607aed47536> [Accessed 11 April 2020].