As global economic competition grows each year, firms work tirelessly to recruit the best talent available on the market. Companies invest in university and college recruiting sessions extensively. They also incentivize their employees with cash rewards to tap their networks to fill empty positions. Many think the problem with hiring top talent is related to not reaching enough potential candidates. However, Kerry and Anna Wang viewed the problem differently and created Searchlight.ai as their solution. Searchlight.ai is a hiring software startup integrating automated reference checks to companies’ hiring processes to build in-depth profiles of prospective candidates. The startup was in Y Combinator’s Winter 2019 batch. The San Francisco-based startup raised over $2.5 million in their recent oversubscribed seed round led by Accel, with participation from Founders Fund, Soma Capital, Operator Collective, Jason Boehmig, Mathilde Collin (CEO of Front), and Amber Feng.
Accel’s Dan Levine, the firm’s partner leading the deal, says, “When backing teams, I look for four things: Do I like these people? Are the founders able to work hard? If needed, are they incredibly smart? I’d prefer it if my founders didn’t need to work or be smart, AND the company was successful, but it’s nice to have the option. Are they able to recruit other great people?
The answer to all of these questions is yes. It’s clear that Kerry and Anna work incredibly hard; they do a great job of recruiting top talent. I’m delighted I work with them and don’t have to compete against them!”
Searchlight.ai cofounders Kerry (left) and Anna Wang (right).
Acquiring the best talent out on the market is a challenge for any firm, regardless of its size or brand. Big tech companies and startups all alike face fierce competition for the best software engineers, product managers and marketers, designers, and other essential roles. However, most companies focus on expanding their search for more candidates, thinking their issue lies in not contacting a greater number of candidates. The Wang sisters realized the true nature of the problem lay in how companies interview candidates instead of the number of candidates they interviewed. Interviews are not well designed to capture a candidate’s soft skills. For example, LinkedIn discovered that the number one skill that new hires need to have is communication. The standard interview process isn’t designed to assess their communication skills separately, but as a function of their style of responding to questions asked by the interviewer. A lack of screening for soft skills specifically results in bad hires, which has a significant negative impact on a company. The unaddressed problem faced by companies all over the U.S. represents a novel and lucrative market opportunity.
Kerry states, “After talking to hundreds of people and talent leaders, we know the current interviewing process is broken. Companies need to build teams that are greater than a sum of its parts, but hiring over-indexes today on individual credentials and technical skills, rather than assess for what’s known as soft skills or behavioral fit.”
The Society for Human Resource Management (SHRM) produced a study revealing the average cost to hire an employee is $4,129. Glassdoor similarly found that a regular firm pays roughly $4,000 to fill a vacant position. Inc reports that the average number of applicants per job is 250. If one only considers the approximately 1 million open jobs in the professional business service sector having SHRM’s average cost of hiring, there’s an immediate $4 billion market. Provided there is an untapped value (assuming at least $1) produced from better collecting data on the top 10% of prospective candidates for each open position, the potential market opportunity balloons to $100 billion. The founders of Searchlight.ai have focused on building their product to deliver this unearthed value to their customers.
Collin says, “At Front, we’ve always prioritized a work environment in which employees could thrive and “Work Happier.” Paramount to that is understanding our current team profiles and who every candidate is, so that we can better hire, onboard, and build teams. In hiring top talent using traditional methods, it’s challenging to get a real sense of who an employee is without spending long periods working with them. Searchlight accelerates this timeline and illuminates how candidates would fit within existing teams. This allows companies to hire top talent faster from diverse backgrounds and set them up for success from day one.”
Searchlight’s core offering is a modern reference platform that aggregates data around the candidate’s core soft skills and team fit in the form of a profile. All of this can be done without an interview taking place prior. From their customer interviews, they understood the interviewing “best practices” and aimed to translate that into code and heuristics powering their platform. The cofounders developed Searchlight to work as a standalone product or integrate into a firm’s applicant tracking systems (ATS). In addition to automating reference data collection, Searchlight captures thousands of previously unrecorded data points on its platform to unearth valuable candidate insights and actionable analytics regarding team and behavior fit.
The startup works with customers like Udemy, TrueCar, MasterClass, and Standard Cognition. Searchlight works across all roles, from engineering to sales to operations. Customers are now using their platform at earlier stages of the hiring process. Anna claims, “We’ve accelerated time to hire by seven days on average. 80% of our customers improve the number of hires they make from underrepresented backgrounds. Overall, our customers have a much higher quality of hire.” Given that it takes on average 42 days to fill a role, according to Glassdoor, cutting the time to hire by one-sixth results in significant cost savings for Searchlight’s customers, not even counting the cost-savings from avoided mis-hires.
“One thing that came up in discussions with customers was the following: How do we know what kind of people do we want? References help uncover strengths and areas for development in candidates relative to the company. Mock references of internal folks could help companies to better understand which applicants would be a fit as compared to internal folks. Searchlight is focused on hiring now, but there are opportunities for companies to be more reflective in how they can grow and develop talent over time with the same dataset,” adds Levine.
The Wang sisters work well together in building a “consumer-first” platform for its users. The twin sisters both went to Stanford for their Bachelor’s and Master’s degrees. Both previously worked at McKinsey and Google. Beyond their extensive technical and business experience, the most significant advantage these two have is their relationship as sisters serving as the bedrock of their partnership as cofounders. Together, they can help reduce the time it takes to hire a candidate and increasing diversity across the board through Searchlight.ai.
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