An Interview with Sanjoe Jose, CEO and Cofounder of Talview
The challenges in hiring span from finding the right talent to finding the technology to help make successful hires. And we’ve seen an incredibly fast-paced phase of innovation in the field. At the forefront are leaders like Sanjoe Tom Jose, cofounder and CEO of Talview.
Sanjoe is passionate about making hiring easier with cutting-edge AI and machine learning-based technologies. He’s also likely one of the rare innovators who turned down an offer from Google to strike out on his own. Instead, he built Talview — which stands for ‘talent view.’ The firm’s Instahiring Experience platform is the first to bring the one-click consumer experience to a hiring context, radically shortening an organization’s time-to-hire.
We talked about how AI can be leveraged to transform the whole hiring journey, about his thoughts on the market, and why certain hiring teams are AI-averse — despite the fact that given today’s talent race, recruiting needs, and deserves, a real shot in the arm.
What market problems are you trying to solve in the age of the super recruiter?
In speaking with our customers, hiring lag or a long hiring process is their biggest challenge. Businesses always need talent as soon as possible. But hiring lag also impacts other key hiring metrics — such as Quality of Hire, since the best candidates are only available in the market for ten days. This is especially critical in the gig economy, where companies can’t spend 2 months to hire someone who might only be employed for 6-12 months. Long hiring processes and not being able to provide remote functions also impact the Candidate Experience: 57% of candidates drop out of the hiring funnel due to a long hiring process. Companies also need a way to showcase their culture, values, and expectations to candidates before they’re hired, as it will help new hires ramp up quicker.
In your view, how is the candidate experience broken?
The back-and-forth process between employer and employee can easily become slow and confusing due to the time it takes to screen and select the best resumes, contact the candidate, arrange an interview time that suits both parties, and organize for someone to conduct the interview. It’s not just a lack of speed that’s hurting businesses’ hiring process, either. The quality of the candidate’s experience as they go through the different stages of the funnel is also suffering at the hands of inefficient and ageing recruitment practices. Job applicants are often forced to take off work to make multiple trips to attend interviews in person, and once they’re in the final stages, an offer can take weeks. A poor candidate experience also means applicants drop out of the funnel, and they’re less likely to reapply to the same company in the future.
Let’s talk a bit about solutions. How can technology fix some of these problems?
In our own firm, we base solutions on three propellers: Remote, Automate, and Reuse. Generally, organizations need to be able to complete screening assessments and interviews online — they should not have to rely on physical face to face, especially if the best talent is remote. This can be done through live and recorded modes, saving candidates as well as recruiters immense time while both parties are still deciding if there’s a good fit.
And there are so many routine recruitment processes that are still completed by humans when they could be automated, such as screening resumes and scheduling interviews. Automating these processes frees up recruiters ’so they can spend time on far more value-adding activities,such as conducting final-stage interviews. And automation should be able to function round the clock, so candidates don’t have to wait to hear back from recruiters, and their questions can be answered immediately by a chatbot.
Finally, recruiters and candidates as well need a way of streamlining the process when this is a repeat applicant. That means recording all application and interview data — so it’s available to reuse when a candidate reapplies to work for the same organization, and they can be fast-forwarded to the relevant stage. There’s no reason they should have to go through those assessments and interviews they already completed when they applied previously. Reuse just makes it easier.
How do you leverage AI and machine learning in your platform? What phases are you using AI and ML for in terms of the hiring journey? Is it end to end?
Yes — we’ve leveraged AI and machine learning to automate and drive more insights — all the way from the top of the hiring funnel right through to the moment of hire. From the start of the process, these technologies are used to screen resumes, derive additional insights from interviews and expertly match candidates to their ideal roles. As the candidate goes through each step from the location of their choice, computer vision is leveraged to authenticate their identity and administer multiple variety of skill based assessments. During the interview process, the technology assists hiring managers in conducting an objective interview — by building a behavioral profile of the candidate that leverages speech recognition and natural language processing, and giving suggestions as to areas hiring managers should probe from a non-technical skills standpoint. With companies struggling to assess soft skills accurately, these kinds of behavioral reports help companies hone in on communication, interpersonal, and leadership skills.
Do you think organizations can benefit more from recruiting platforms that are all-in-one inclusive?
I do. While there are many pinpointed solutions that impact one or two steps in the hiring process, disparate systems can pose problems for enterprises, such as time-consuming, inefficient data entry and reconciliation processes. It’s more effective to have a seamless experience. Inefficiencies can lead to user dissatisfaction for all parties involved. And while some organizations do try to integrate disparate systems themselves, the performance is far from optimal and adds major overhead. We wanted to be enable the true digitization of hiring, and provide a platform that could be integrated with any of the leading Applicant Tracking Systems. I think that’s the kind of solution both sides want — the candidates as well as the hiring teams.
My last question: What would you say to companies that are reluctant to shift to AI and machine learning for recruiting and hiring?
AI offers significant benefits while applied in the recruiting process, and hence is bound to become a significant part of every organization’s recruiting strategy sooner or later. AI can be leveraged to automate a lot of mundane tasks recruiters today perform — like matching a resume to the job description and scheduling of an interview. It enables recruitment teams to become true strategists and candidate experience champions, and ensure the best candidates join their organizations. It would be wiser for teams to leverage the benefits of AI and become super-recruiters than to get left behind.