Joanna is an expert in all things teams and tech. Her passion for democratizing talent information in order to help organizations hire much better talent more efficiently and lucratively really comes through during the podcast.
Give the show a listen and please let me know what you think.
Welcome to RecruitingDaily Use Case podcast, a show dedicated to the storytelling that happens or should happen when practitioners purchase technology. Each episode is designed to inspire new ways and ideas to make your business better. As we speak with the brightest minds in recruitment and HR tech, that's what we do. Here's your host, William Tincup.
Ladies and gentlemen, this is William Tincup, and you are listening to RecruitingDaily podcast, specifically the Use Case podcast. We have Joanna from Censia. And we are going to be talking about her firm. Joe and I have known each other for well, more years than we probably care to admit publicly, and I love what she does more, and more I love her as a person. She's just a bright bulb and just really easy to be around and smart. So I can't wait to have this conversation. So Joe, take us into introductions first. Let's introduce yourself and introduce your firm, and it will start getting into what you all do and how you do it.
Yeah, absolutely. Well, thank you so much for having me. I love any moment I get with you. You're just fantastic. So I completely feed off of you.
It's kind of you.
Well, just to introduce myself, I am Joanna Riley. I go by Joe by those that know me well and even those that don't. I am the CEO and Co-founder of Censia and, thinking about just my own journey. It kind of connects really closely to what I do professionally. I was born and raised in San Francisco. I went to University of Virginia for college and was a horrendous athlete but an incredible rower. Rowing's one of the sports that comes after rock climbing when your parents were trying to figure out if they think you're a great athlete. Rowing was after that fact. But I absolutely fell in love with it, and it really was important for me in understanding how you build teams. And I think this really connects a lot too, in general, just the listener because that's the big challenge ahead is how do you build a great team? And in rowing everyone, I rode in eighth, and everyone had their own special seat, and you couldn't put those people in a different seat, and yet we were completely aligned.
If you've ever seen rowing, it's one of the most beautiful sports. It's completely aligned, completely in sync. And so that's something I bring along with me, but after I left UVA, actually, well while at University of Virginia, I was recruited to the FBI, worked for them for about a year and a half, loved what I did, but I really didn't love the bureaucratic structure. I was very much driven by merit, and I think this is something that we see a lot today in talent. It's just talent that is driven by the opportunity to continue to achieve and learn in ways that they have never done before.
So it actually led me into being an entrepreneur, and today Censia is actually my fourth company. My first company was in an outsource sales marketing firm. I grew the company to about 500 employees before I sold it. Then I moved to China for five years. I built a mobile e-commerce company that I joint ventured to the Chinese government there, and living in China really exposed me to the idea that... I started to travel around the world, and I really became hyper-aware that great leaders in every country I would go to. I would meet these incredible leaders, and they would share with me that... They would tell me all about how their greatest asset is their people and how important people are.
At the exact same time, they told me that their biggest problem was people, finding great talent. And what was even more amazing is the CEOs of these huge organizations. These leaders of the world were sitting there saying that their greatest fear on the planet is they know for a fact, if they can't find talent skilled enough for the future, they're not going to survive. And they were really afraid of it. And I think it's such a wonderful time right now for talent acquisition and such great time for HR because people is absolutely the greatest asset. And I think that the world has realized that in a lot of ways, and 2020 has made that even more important.
So I built my third company, I built my first HR tech company. I focused really on assessments because I kind of thought that was the problem and took that all the way through IPO and built Censia out of the understanding that truly a lot of talent... I'm a huge believer that I believe that bias and talent decisions is affecting billions of highly capable people around the world. I would watch time and time again great leaders select talent that they would always want to see more talent. They'd always want to see more capable talent. And yet they would define talent by things like where they went to school or did they work at Fortune 500 companies, or do they look like me? And in the end of the day, that's not necessarily what leads to capability.
So, of course, it would have a massive impact in the bottom line of that organization. And so, Censia, we set out to democratize talent information and help organizations hire much better talent in a much easier way. And at the same time, do it for a lot less money than they're doing it today.
I love it. Thanks. And that's a brief intro, by the way, because she's got a whole bunch of-
I know I'm sorry.
No. No, no, no. You shouldn't be sorry. There's a whole lot of other things that you've achieved in there that you had to shorten up. The firm itself. So when people, especially practitioners, when they think of categorizing you, what's the best way to categorize Censia?
Yeah. Censia is specifically a talent acquisition and talent management solution. What is interesting about us is that we looked at it and said, how can we help find great talent? So really focused on outsourcing, the screening aspect of talent. ATS is there's super-valuable data hubs, and yet they're totally unsearchable. So that's another component is being able to search ATS, and that's the rediscovery and all that's kind of focused on talent acquisition.
We also really help organizations around internal mobility because there's a ton of fantastic talent inside the organization, but the organization lacks data on their employees. At the same time, recruiters don't know all the employees of an organization that would be impossible for them to know. And so, we make that a lot easier for them to have right at their fingertips. They have internal employees that are qualified for opportunities.
We also help organizations understand on the workforce planning side and workforce intelligence side what's happening. What types of skills do we need for the future? How do we start thinking about planning? So it's really kind of across the board there, but all done directly inside of existing systems. So what's really cool about Censia is that we understood most organizations are too fatigued, so we're here to help them.
Well, it's great. It's harvesting. You already have some of this data in payroll. You already have some of this data and performance or engagement, or insourcing or in the ATS as you mentioned, you have some of this data pulling this data together to make you smarter about making other types of decisions, whether or not they're promotions or offers or whatever they are. Now, you have a talent intelligence tool. I love that. When folks demo Censia, what is that? I call it an aha moment, but what do they love? What are the two or three things when they're like, "Oh, when you get to that particular part of the demo or whatever,' they're like, 'Oh my God," like the light bulb went on? Everything changed for them. What are those moments?
Yeah. I think that the aha moment, one of the first ones, is the ability to model people. So people hiring managers talk to recruiters all the time, and they say, "You know what? I love William Tincup. He is my star, go get me more people just like him." And the recruiter's like, "Well, what makes him great? I don't know, but he's just fantastic. I just need more people like him. Okay." Now the recruiter is going to go look at your background, try and figure out what makes you great. And inevitably, it's very difficult for human to identify patterns on people. Other than detective things like, "Oh, okay, well William went to this school. Okay. He has this title. Okay. He worked at these companies," and in reality, we're all a lot more than just those things. We're a lot more than our keywords. I like to say.
So what Censia does, one of the first places that organizations love to start is that they can model people. You can put anyone's name in in the system, and it instantly will build a rank shortlist of people that capability-wise are a 95% match and above on that person.
The other aspect that they love is the DNI side, being able to target talent based on are their gender or are they underrepresented minorities, people of color. These are really important things, especially today. And I think the fact that it's all really integrated. So being able to just very quickly select on a job and see a ranked candidate slate from every source of internal, you're already looking at candidates that are inside your ATS. It automatically ranks the inbound applicants. It automatically is going to populate passive talent. So all of these places that recruiters have to go, it's all in one. So they have this, "Wow, that happens so fast." And these are so on point with what we're looking for. So it just saved hours and hours of scouring the internet trying to figure out where these people are, who they are, try to get them engaged. We make that all very, very simple.
I love that. Take us more into how your customers are using DNI because I know folks are going to be really, really interested. We're 100 years late. So we can all kind of go get there fast intellectually and emotionally. However, there is not just great words and conversation. There's some people don't really, really good work now.
Thankfully, because of applications like Censia so take us into some of the work that folks are doing. And again, anonymized, we don't need to know names. They're using the application. They are using it for good. And examples are great for people to hear.
Yeah, for sure. I think that this is something that every recruiter can resonate with, what we realized about the talent problem. A lot of technologies come out to market, and there's no shortage of recruiters getting hit with one sourcing thing after the next. And they're all pretty much they're cool interfaces, but the same problem keeps surfacing, which is that it requires the recruiters to type in countless keywords, know exactly what they're looking for. And it leaves a lot of errors because I think every recruiter is familiar with this problem. You type in a title. Let's say you type in data scientists. Well, there's lots of titles. Do you know that IBM actually changed their title of data scientist to data poet?
Oh, that's cool.
Yeah. But the best data scientists in the world called themselves Markov modelers. Well, if you don't know those things as a recruiter, you're very limited by keywords. So this is a very frustrating problem. And also, when you think about skills, women, and this goes to the diversity point, women put 40% less skills on their resumes and profiles, and they're equal counterparts men. And they don't know they're doing that. And in any keyword search system, what naturally happens is unknowing the recruiter and not at all on purpose completely by just the fact of how technology has been built in the past. Naturally, they filter out women.
So what Censia looked at, and what we focused on is the big differentiator, was that we had just start to cluster these baits. AI is really a fantastic. Machine learning and AI absolutely will dramatically continue to improve the world when used correctly, but you cannot apply... And all of that AI is, is a math equation. One plus one equals two very complex math equations, but it's looking at lots of data. Now, if there are 100 different ways to say one skill, which we all know there are. There are lots of ways that you can say B2B sales. You could say enterprise sales or corporate sales or business sales. If they're all these variations, you can't actually create a math equation. You have to standardize that first to be able to then say, "Now let's look for patterns."
So that's where Censia came into play was we started to say, we're going to standardize things like skills. We're going to standardize things like titles. We're going to standardize companies. Let's look at one company like SAP. How many acquisitions is SAP made when you're looking at, I want to find people that work at SAP? Do you have to know all the companies that they've acquired, or is there a way to be able to quickly identify that?
So we looked at saying, how can we cluster all these things together and start to build much more predictability into the way that we look for talent? What that naturally led to is when you started to create a level playing field and infer data on talent, more diverse talent came out, and that happened without organization saying, "Okay, I've got to look over here on this job board that is for people of color. I've got to look over here for this place that has women only," but rather, how do we start to create this one ranked candidate slate, but let's see it as diverse. Let's start to see talent that is completely skilled and capable. So that's kind of the first piece that it's kind of, as you said earlier, an aha moment, but an aha moment on diversity is that the talent pool is already much more diverse than they're used to seeing.
Secondly, we also allow the organization to put a threshold on talent to say. I really need to have what I love is a lot of companies today. And many of our clients are focused on, and we work with large enterprises. So our average customer is 33,000 employees. However, we also work with companies that are smaller and the 2000 size or a 1000 size and growing. And I think that what they're doing that is really working is they're starting to say that we have to see at least half of the candidates that we interview must be diverse. What happens then is the scale for when you're interviewing talent, and half that talent pool is diverse. What happens is actually the scale tips in favor of the diverse talent, because if all of them are qualified, if there's only one person out of, let's say, six people that are diverse, they have actually statistically, a 0% chance to get the job. That's a Harvard study. It's actually really, really interesting.
So you've got to shift that. And so those that put those thresholds in there are really critical. And so we allow them to actually search based on diversity too. So search based on gender, search based on, are they a person of color? Are they an underrepresented minority? Are they a veteran? And this is really helping organizations make sure that they have that even balanced when there is a shortage or when they've over-corrected too much into one category of, let's say, white males or a different category that they are now trying to even that out.
So one of the things you mentioned is you're playing upmarket A, B, which means more systems. So the larger the firm tends to be, the more systems HR and recruiting systems that they have more global company, the more systems. So we get that. And you're pulling data out of those systems. So give us some insight into kind of the integrations and what that's been like for you all and the journey that you all been on to integrate with the different systems that these folks use.
Yeah, no, it's a great question. So there's something different about Censia than a lot of talent intelligence platforms that are out there. Censia does not require organizations to give us data in order for us to deliver our solution to them. One of the things that we did ahead of time was that we contextualize people data based on all this public data that we get from vendors and all of that comes pulled together. And then, we start to build structure on that data. So all of our intelligence, all of our algorithms, we continuously build based on hundreds and hundreds of millions of people.
Then how we went to market, is we looked at it and said, we're going to go to market with most of these organizations already have HR system. Let's say applicant tracking systems. Since there's a global partner with SAP Success Factors, with Workday, with Microsoft, with ICIMs, with Jobvite, with Greenhouse, we went and built these integrations ahead of time so that we can make it very plug and play, that we could just extend and enhance the existing systems these companies already had, or let's say platforms like Phenom people, Censia's gold partner with Phenom people, with Beamery, with Bullhorn.
So we've gone ahead, and we've created these integrations so that it's really plug and play for the recruiting teams because what they can't do is stop doing what they're doing every day and learn something new. We all hate. It's not a recruiting thing. It's an everybody thing. We hate change. We hate learning new things, even if it's better for us. I always use my iPhone. When I had turned in my iPhone and get a new iPhone, which had all the cool bells and whistles, everything was much better. I hated that those first weeks of learning it. It just drove me crazy. I was like, "I just want everything to be back." And if I had my other iPhone sitting right next to me, I probably would have gone back to it. But the reality is it was taken away.
What Censia understands is how do we make that really, really easy? And so how do we do that directly inside of the systems that recruiters use every day and therefore, they can click on a button, and it will rank an inbound slate, or they can say, "Give me a passive candidate slate." It's going to automatically be populated by looking already at the job description, at the team members of that organization. We already have so much of that data. We don't need the organization to give us that information.
So because what we say in Texas is a colloquialism. This isn't your first rodeo. So one of the things I want to get your take on is buying questions from practitioners that you love and buying questions that you would rather. We just kind of sunset, if you will. What are those for you right now? Because again, we could have talked four years ago and would have probably been different things. But today, when you hear certain phrases or certain things from buyers, you're like, "Yes, great stuff." You know you're on the right path. You know you're talking to the right people. You can just tell they get it, et cetera, et cetera. And then the opposite. Let's talk about that as well.
Sure, sure. Yeah. I think that when teams really genuinely understand, they have a pain point. They know that they, for example, I love when they ask, I need to identify more diverse talent rather than I need... One of the things that I think that we need to sunset is talent technology is not responsible for a candidate's success. Talent technology is responsible to deliver qualified talent. And if, for example, we're shifting recruiting thoughts from this is a lot of time where in the past hire agencies, they make sure the candidate's successful. And that's how their business model worked. It was like three trenches. You hire them, they deliver a candidate, and you pay them a second time. And then third time you pay them is after they'd been there for a while.
In the end of the day, actually, there's a lot of data that shows that candidates are that talent is successful if they're engaged with the manager, that 90% of talent if they stay in a job is because they had an engagement with a manager. Well, talent technology is not responsible for that. So understanding, I think this is one of those things where, for example, when you're asking a talent technology, I love when they ask why are you differentiated? I love when they ask, how have you thought about making it easy for my team?
I think every, for example, every talent leader knows that adoption on technology is one of the biggest challenges. And that's not just for talent. That is for all people. So two-thirds of the digital technologies that went into enterprises in the last year failed because they didn't have skilled enough people to learn how to use them. So it's on both the technology side to make that easy. And it's on the enterprise side to make sure they give that technology a chance to be successful.
I like to say I was with a customer, huge, huge, huge staffing firm, and they said, "We want to do all these things." They're like, "We want to do this, this, this, this, this." And they said, "How do we get started? How do we start to see success?" And I was like, "Okay, well, here's my thoughts." And they're like, "Great. We're going to come back." And they said, "Hey, what if we started, a few recruiters, got seed access to one component of your system?" I said, "Well," and I'm not kidding. This is what I said. I said, "Well, that would be like testing a car based on picking out Nikes," Because everything that you have said you need is something completely different than what you just asked to test on.
So if that's a test, we need to change the actual big picture outcome. And I think sometimes... The second I said that they were like, "Oh, actually, you're very right. Why would we do that? We would never do that."
So it was just so natural. And I think this is something that talent practitioners need to kind of sunset is the idea of, "Let me try something, that's a small component of what you do as a test to see, can you do this whole other thing?" Does that make sense?
It's kind of like if you're trying to see if a sorcer's good, you wouldn't watch them in an interview.
Right. Well, it's a mitigating risk in their minds. They're mitigating some type of risks like, "I've been lied to so many times in the marketing and sales process," and so I'm reticent about going all-in but the problem is with that mentality is like, "Well, nothing ventured, nothing gained." If you find a vendor that you really think is compelling, they do solve it. You do your homework. You check references. You do all that other stuff. And then you go all in, and you make the decision. This is actually going to fix these specific problems. We're going to find some other things that it fixes as well because there's always the unintended things that we find along the way. I know people will ask questions about pricing. We don't need to get to the dollars and cents, but what shows philosophy on pricing?
Yeah. So actually, Censia has two different pricings. One, we don't love the seat model. I think the seat model is really difficult for enterprises to actually put that wrap their head around in it very quickly when you're trying to create change, and especially in hiring, hiring is happening everywhere. You've got hiring managers sourcing candidates, you've got recruiting agencies involved, you've got internal talent team members. And so the idea that you have to pay a certain amount of money for a seat it's kind of crazy to me. And especially because we're integrating systems, and everyone that has access to that system has the ability to now rank. They have the ability to source. They have the ability... I mean, so saying only these people can have access is actually really not a great one.
Yeah, that's [crosstalk 00:24:44] to the interest.
We want to see change, transformation and speed, and complete adoption. And so we actually do it based on a per employee per month price. And it's very similar to how you think about if you're trying to buy success factors. Workday's very similar. We also have an alternative, which is a consumption price. So because Censia is an API first business, which means that our whole technology is built connected to our data platform, and we allow organizations we actually help their existing technologies be a lot smarter. And so, based on how often our system is used, the price will go up. Kind of like, think about AWS. The more that you use, the more that you pay, but at the same time, the more your per-unit cost goes down.
So is that counter... I mean, I know why you have it because it creates flexibility for folks, but is that also a bit counterintuitive or a counter to their interests in so far as you want them to consume more, they should consume more. But consumption also will mean that the bill will be more.
Yes. I mean, as long as it's not really like that of a... It doesn't create. That was a really important focus for us is we don't want to create like hoarding mentality where people are like, "I'm going to use it for this." And that's super dangerous is to buy something that is that way. It's kind of like if you're going to use Marketo or if you're going to use Salesforce, it is based on the volume that goes inside of it for access because it's kind of the same thing. Whereas if an organization has they go, "Hey, we need all of the data and intelligence that you have on our existing employees." Because Censia has contextualized data for public sources, which has a lot of work data that the organizations don't already have, and they're going, "Hey, we want to start promoting our people. We want to know what skills are transferable across our organization. You guys know that, can you help us by seeing that data versus forcing our employees to fill it out again because they don't want to. And so therefore they're getting limited access on what they are purchasing." So Censia can really help that.
If it's 10,000 people, it's a different cost, if it's 100 people. I mean, that's just natural. And so that's kind of, we don't do it in the sense of like, it's more consumption that way.
Yeah, and it makes sense. It's also, again, people are also accustomed to buying the life that. I know CFOs hate variable costs, so there's probably a way to flatten that out over time. Once the organization knows what they're consuming, there's probably a way to go back to that and say, "Okay, listen, let's flatten this out. So the CFO doesn't get upset."
I actually think it's so important for, and this goes back to your question a second ago, which is around building ROI analysis. I am such a huge believer in making talent leaders look like rockstars. One of our big goals is to get talent leaders in the boardroom and get them to be able to... Everyone looks at them as going, "We're going to gain revenue. We're going to save costs." And I think there's a lot of opportunities for talent leaders to do that. And so, one of the best things to put in front of a talent technology is, "Here's what I currently spend. This is where I'm spending in. Job boards is what I'm spending in. Agencies is where I'm spending in. Professional networks, this where I'm spending in dah, dah dah. Here's how many recruiters I have. Here's how many roles they fill, how are you going to increase the performance of recruiters?"
We have one of our clients, a Fortune 500 organization. Their recruiter performance is increased five X. The work of one recruiter can now do the work of five before Censia, which is awesome. So that kind of a change. And where you go, "All right, now, I need to optimize." I only have so many recruiters. Where every organization fire their recruiters in 2020 or vast majority, not every, but vast majority of them because they froze hiring. And so now they came back overnight. "We need to hire all these people." Turnovers is getting out of control. We're predicting 40 to 60% of the workforce is going to turn over.
So talent teams are on hyper-alert of, "Wow, I might have a plan, but I need to also be prepared to go way higher, way more people than plan. We have to figure out how to get more performance out of recruiter." So I think that if we look at it and go, "Where are you going to have that effect?" Being able for the talent technology to hand that talent leader, a great ROI analysis is going to be critical. So giving them the numbers to say, "Show me where you'll save me money." And I think that's been something that's really worked for us; William is just that we are a huge ROI for an organization, and we give them that information ahead of time so they can rock right to the CFO and say, "This is where we're going to save."
I love that. The folks that you're doing last question, because I know you got to get. The folks that you love dealing with in terms of the people that interact with you, CHROs, global heads of talent, sourcers, recruiters. Who do you want in the room when you're talking about Censia?
Yeah, so I think what's been really interesting is how much airtime and focused HR has gotten in the boardroom lately. And so what's happening is you're seeing a lot of the C-levels levels go, not just to CHRO, "Hey, we need to hire this," but you've got CIO's and I can't tell you how many times, I sometimes hear sales calls and it's chief strategy officer, president of the organization, CIO, head of talent, head of people, and you're like, "Why are all these people on the call?"
Yeah it turns out people are important.
It's so important, so important. And it's so great to see because it is time. This is the biggest opportunity to generate revenue. Is your people the best way to go through transformation and technology innovation is people? And so it's fantastic because talent teams are the conduit great talent. They are the fastest way to get to revenue profitability or revenue growth and scale or innovation scale. So it's really great to see that. I think when it comes down to sourcers, for example, in the room, one thing that I think it happens in talent technology is it can very quickly be misunderstood to displace jobs. And what I've seen is that rarely does technology actually displaced jobs the way that we think it is. Technology actually increases people's value. If you're just doing something that's manual every day, all day, that organization needs to figure out how to not have you do that because you're too important.
Organizations are looking at how can we up-level our people, and Censia really looks at how can we take the mundane manual work that's not great for humans to be doing in general. They're not great at it. And on top of that, it's not good use of a human's capability. That how do we optimize or how do we drive efficiency and predictability through that and automation.
So sometimes, when you have people in there that are responsible for doing that manual work, they get really scared. And so I think it's an absolute fair question to even sometimes pull off on the side and go, "Is this going to get rid of my sourcers? Or is this going to get rid of this team member? Or should my recruiters, is my team going to get smaller? Should I be thinking about that?" Sometimes team leaders can't hire a recruiter. So they're like, "I need this to replace that headcount." Other times they're looking at it going, "I absolutely need my recruiters to be more strategic." We are completely lacking on the strategy side. People don't know how to interview. We don't know what we're doing. I hear that almost 100% of the time, they need their recruiters to be strategic, and they can't be while they're in the weeds.
So I think that's really important as far as people in the room, I think it's really important that everyone kind of shows up with, if you, every meeting you went to, you looked at and you go, "How are you going to make me 10 X better?" That's kind of the lens to evaluate through versus is this going to get rid of my job?
Right. That's defensive. First of all, it's emotional. It's very defensive, fear-based, which you can kind of understand rationally. You kind of understand, but getting past that and getting to the next thing is I need my time back. So how do I get my time back? Does Censia actually get me to a place where I'm more efficient and doing the things that the organization needs me to do? Which is a resounding yes. So we can get past the point of, "Oh my gosh, this is going to take my job." It's-
Nobody fires the person that goes from filling 100 wrecks a year to 500 racks, and the person that continues to hire rockstars that are divers, nobody fires that person ever.
Yeah. No, that person gets stuck there. That person gets promoted.
That person is totally promoted.
Yes. That's just the way that works. Joe, thank you so much for coming on the show, and thanks for breaking down Censia for us. I could spend the day talking to you, but I know that you've got 1000 other things going on, so thank you so much for carving out time for it.
This was great. Thank you so much, William. This is fantastic. And thank you everyone listening.
Thanks for everyone listening to Use Case podcast until next time.
You've been listening to RecruitingDaily Use Case podcast. Be sure to subscribe on your favorite platform and hit us up at recruitingdaily.com.