Last week I had the opportunity to join an old friend, William Tincup, on the Use Case Podcast. William is the President and Editor-at-Large of Recruiting Daily, and one of the most influential thought leaders in the HR industry. The Use Podcast features guests who share the business case associated with their HR technology. Its aim is to make good technology better, and more accessible. I joined William on the Podcast a few weeks ago, and here are some snippets of what we discussed.
On why I started Censia, and How it has Mission has Evolved
I had several “careers” before starting Censia, each one of them vastly different, and that really got me thinking about what talent actually means. I created and sold a number of companies, and after one exit I decided to travel around the world to figure out what the biggest pain points leaders were facing. No matter where I went in the world and who I spoke to, the answer was always the same: leaders were terrified that they would run out of good talent and wouldn’t be able to stay competitive. This got me thinking.
There are two problems when it comes to talent acquisition and talent management: one is overwhelm, and the other is lack of automatability. Overwhelm comes from constantly having to manage, upgrade and replenish your workforce. The lack of automatability comes from the fact that people data, or talent data, is inherently messy.
And that’s where the idea for Censia was born.
Censia is designed to solve talent headaches at their root. We do this by collecting and cleaning talent data, and creating ethical AI algorithms that add predictive capabilities to any human resources technology. We also designed it to plug into people’s existing ATS and HCM software suites either via integration or API. This way, companies can reap the benefits of clean data and cutting-edge AI without having to upgrade to a new platform.
I like to say that we democratize talent information and help organizations hire much better talent in a much easier way.
The AHA! Moments
Another thing we discussed on the podcast are the AHA! moments that people are having when Censia. One of the most common ones is when they first realize how fast and easy it is to find the perfect candidate or applicant using the Ideal Candidate Modeling.
So let’s say you have a star employee, and you want to hire someone just like them. Do you go to the same school? Look for the same job title? The same company?
All of the common things that recruiters look at are actually pretty ineffective because people are more than keywords and college degrees. Our skills and capabilities are born out of a wide breadth of experience, and algorithms are much better at seeing those than humans.
In Censia, you can actually take someone’s LinkedIn profile or resumé, and use it as the base for an ideal candidate model. Our technology will instantly find people whose experience and capabilities resemble that of your ideal candidate across hundreds of factors, not just basic keyword searches. It also fills in the gaps, so you never have to worry about missing another term for, let’s say B2B sales, or a junior recruiter not having enough subject matter expertise.
Our technology will instantly find people whose experience and capabilities resemble that of your ideal candidate across hundreds of factors, not just basic keyword searches.
This is also a huge boon for diversity! Our lists are inherently more diverse for a number of reasons. One is that we look past job titles, which instantly makes slates more diverse. A 2020 report found that women and minorities receive far fewer promotions than their white male counterparts. This means that if you’re only looking at previous job titles, you’re missing great candidates AND are reinforcing systemic bias.
Censia has also invested heavily in diversity filters, so you can find veterans, women, minorities, and more with the click of a button. With another button you can anonymize the slate, hiding any information that might reveal a person’s protected status, and in 5 minutes, you have a completely OFCCP-compliant list of optimal candidates.
On Solving Recruiter Pain Points
After talking about diversity and ideal candidates we started talking about pain points. Censia was created to reduce bias, but at the end of the day, if no one uses your technology, it won’t have an impact.
There are so many companies in the HR tech space. Thousands. And talent teams are constantly being bombarded with shiny new interfaces. We make the choice easy: keep your current software and integrate Censia to access powerful AI capabilities. That’s already a big relief for our customers who don’t want to migrate to another software.
The other pain point is that these softwares are still using an outdated boolean search that requires them to add the specific skills they are looking for manually, which is inefficient for two reasons. It takes time, and not everyone puts the same skills on their resume.
Our Talent Genome fixes that by clustering skills and capabilities and linking them to certain job titles. So even if we only had a job title, our software would help you look for all the skills associated with that title, and the variations of those skills. All of a sudden recruiters without any expertise can find experts in any subject matter. It’s completely revolutionary.
We talked about how searching by job titles reinforced bias, but let’s talk about another challenge: creative job titles. Did you know that IBM actually changed their title of data scientist to data poet? If you’re trying to hire that person, you won’t find them by just searching for job titles and companies.
