Meet Your Diversity Goals with Talent Acquisition
Mihir: Hello, and welcome to today’s webinar, “Meet Your Diversity Goals With Talent
Acquisition.” My name is Mihir Gandhi, and I’m the Head of Marketplace Operations at Eightfold.ai. As a hiring manager for nearly two decades; sourcing, hiring and retaining talent has been a central theme in my career. Managing hyper-growth companies like Lyft, where I was the first general manager for their flagship region in northern California, I’ve acutely felt the pain of hiring rapidly and hiring right.
I’m thrilled at how Eightfold is addressing these challenges and so much more. Specifically today we’re diving deep into meeting diversity goals with talent acquisition. We’re joined by our esteemed guest, Daniel Doody. Daniel is the Head of Global Talent at the AdRoll Group, and we have some interesting and robust content to cover. By way of introduction, Daniel spent over 15
years in the recruitment world.
He started an agency that supported global growth, he opened Facebook’s global office, the first engineering office outside of California; later did the same at Twitter, managing global acquisitions on the talent side; and five years ago joined the AdRoll Group, leading international recruiting and global talent acquisition. With that, I’ll kick it over to Daniel – happy to have you, and thanks for spending the time with us.
Daniel: Delighted to be here – I’m very much looking forward to the conversation.
Mihir: Great. Well, let’s go ahead and dive right in. I would love to maybe start a quick conversation around diversity. Can you help us understand a little bit more about diversity and why it’s an important goal for talent acquisition?
Daniel: Sure. So certainly from our point of view at AdRoll Group, when we think about diversity, I think it’s important to, first and foremost, understand, we’re a global organization. So diversity means different things in, obviously, different geographies. So we think about diversity in San Francisco and the Bay Area: We may have to focus on underrepresented minorities or women in engineering or women in tech; whereas in our European offices or international offices, that means something slightly different, in Tokyo, say, and in Dublin.
Why it is important: Obviously aside from research, there are well-documented benefits of having a diverse organization, I think it’s because talent acquisition has fundamentally changed over the last number of years. It has now become a strategic imperative and a core pillar of a high performing talent acquisition team. So it has to be woven into the fabric of us, literally everything that we do.
Mihir: So if you think about – you said something interesting there as you talked about talent acquisition becoming a strategic pillar of an organization. This is a hot, trendy topic today. Maybe 10 or 15 years ago it was more of a service-oriented transaction. Can you talk about that evolution a little bit? It seems like it’s been through the duration of your career. How have you seen that evolve, and what have companies that have really been pushing the envelope been doing to ensure that talent acquisition is a source of strategic advantage?
Daniel: Yes. So I’m not sure if we want to call out specific companies that have actually nailed this, although there are some that come to mind. I may have worked in one or two of those. Sometimes I think when we are talking about diversity, there’s one or two that stand out. We were lucky enough to have Candace Grey here in the office, who did a Fireside chat with our CEO, Toby Gabriner. There are some really, really interesting strategies that they’ve deployed. I think they as an organization must be called out.
In terms of the transition, in terms of how it has evolved, to your point, I think talent acquisition was a strategy and they were fillers and they had most of the successful organizations that are doing this right – there’s a seat at the table. Talent acquisition is participating in that conversation. So the guardians of human capital, that team that is responsible for going out and raising awareness, identifying talent, and engaging with that talent, it is incumbent upon us to make sure that we are thinking about this strategically and tactically.
So we think about innovation views. We think about it in terms of essentially the full funnel of the recruiting process. So if you think about writing a job description, or an intake meeting, at that very early stage, you are starting to formulate that strategy with the hiring teams in terms of how we’re going to note and identify the talent. It’s in the innovative methods within the training and education that you work with internally, and then ultimately in the strategy that you deploy in order to fulfill that.
Mihir: So you bring up something that I think a lot of folks on the line today have had experience with in terms of job descriptions. Historically – and I’ll call myself out on this – it’s been a copy and paste job, changing a few minor keywords.
Daniel: Shame on you. Yes.
Mihir: So guilty as charged, but I think as you look at job descriptions and how they evolve over time, I would love to hear a little bit about how you can use job descriptions to ensure that you’re not only attracting a diverse set of candidates, but maybe more importantly not turning off applicants of diversity through some keywords or the way the job description is structured.
Daniel: Well, this is probably a webinar in itself in terms of that content, because I think – honestly speaking I think it’s about having that conversation and bringing it all back that we’re trying to solve for here; removing the ease of falling into that trap of just copy and paste, or perhaps it’s high volume requisition where you just wash, rinse, repeat; and you do the same thing over and over; actually bringing it back down to, what is it that we’re trying to solve for here.
I think if you take it from that perspective you avoid, maybe, falling into those areas where bias can start creeping in.
Mihir: So this helps, I think, bridge us into the next question or the next pillar of questions, around misconceptions for recruiting and diversity. So I’ll leave it open ended, because I know you have some distinct thoughts about it.
Daniel: Yes. It’s not a misconception, but it is extremely hard. I think that’s the first thing to clarify. Going back to your previous question on transformation being like moving from transaction into strategic partnerships. I think a grand misconception is that talent acquisition owns this, that you can create a job description and let them go and executive on that strategy that is being fleshed out and created in order to solve for it; but there is no one silver bullet.
Talent acquisition has to partner in all levels at all stages of that process. In terms of – if you think about the various different tactics and tools that typically result in the hires, it’s referrals. It’s sourcing. It’s branding. So it is that sales and marketing funnel that we look to in terms of raising awareness, engaging the talent, and then bringing them into that process.
Talent acquisition has to be thinking about how to leverage internal employee resources. We have to be thinking about, what are the tools that we’re using, and what is the message that we are putting out there into the marketplace. It’s really, I think, a misconception that it is just going out and when actually, in reality, it is a multitude of things that you have to really tie together in order to solve for this.
Mihir: As you say that, what strikes me is the sentence is, talent acquisition doesn’t own it. The way you described it, hiring managers have a deep impact on top of funnel recruiting. The marketing team has a big impact on attracting talent and engaging talent. ERGs do. All of a sudden recruiting goes from being a function and a service to the organization to, really, a central strategic pillar. How can heads of TA and recruiting organizations begin to exert that influence on marketing, on hiring managers, on ERGs, and really pull them together to deliver a cohesive message around what it’s actually like to work at the company?
Daniel: So at AdRoll Group we’re lucky enough to have an executive team to champion this. I think that that is becoming more prevalent. I wouldn’t say that it’s commonplace, but I think it certainly helps solve the problem. It allows you then, as a TA leader, to go out and engage from top down, from the executives all the way through the organization. So I think it’s about creating a culture, and obviously, culture by definition is essentially those behaviors that are rewarded and identified as being rewarded.
So making sure that the hiring managers understand that it is actually part of their job to own this and not just talent acquisition. Obviously, we have a huge part to play in helping those that are involved in education, learning, and development. So we talked about removing bias from the process; and going back to your question, once we have that support, and once that’s part of the culture, it’s really about making sure that you’re reinforcing that through the various different parts of the process.
One of the things that we’ve done at AdRoll Group is making sure that that content and that education is becoming part of hiring manager training, interviewer training, so that each and every single touchpoint of that process targets the candidate; whether you’re reading marketing or branding material, or whether you’re coming in for your first interview; that there is a consistent experience in terms of unconscious bias or treatment of the candidate or an individual going through that process.
So I think a really core piece of it is education, making sure that people are aligned to understand the importance of it.
Mihir: As you say that, creating culture, there is a multimodal engagement with potential candidates via Twitter, Instagram, social media, professional media like LinkedIn and so on and so forth. It’s not only the company owned handles but also the executive. I think what we see is that talent picks up very quickly on discrepancies between what the company is saying, individuals, are saying, across these multiple channels.
As someone who’s deeply engaged in that, how do you think about ensuring that there’s a consistent message that’s being sent across these channels?
Daniel: It’s really, really challenging; because as an organization, AdRoll Group was founded in 2007. We’re over 10 years old. Obviously, through that,, you go through various different iterations and evolutions as a company. Unless you are super in control of such employer branding – which is separate piece altogether and quite often doesn’t sit within talent acquisition, so it really requires you to have a strong partnership there – it is constantly evolving in the same way as your organization is evolving.
So it has to be real. It has to be authentic. If you are trying to present yourself as something for a career site or an event, and then that experience that individuals have either during the process or after they’re onboard is disconnected or completely different, then you’ve got serious problems. So I guess the point that I’m making is that it’s really got to be authentic and part of your actual values.
Mihir: Yes, and I love that you bring that up; because the next question, topic, will cover best practices to recruit a diverse talent pool. You talked a little bit about what you do today at the AdRoll Group, what you’ve seen be successful in your time at Facebook and Twitter, and how that’s changing.
Daniel: Wow. Okay, there’s a lot in that. I think when we think about how to solve for this, there’s no one silver bullet. So once you have that in mind, once you understand that it is an organization-wide problem to solve, then you can start leveraging all the resources that you have at your disposal. So the things that we think about, and how we solve for it – for example, at AdRoll Group we know that 25 percent of our hires come through referrals, then we want to make sure that we are leveraging the underrepresented minorities that we have in the organization. That’s globally.
So it’s helping them understand that they have a part to play in that, organizing things like sourcing jobs; and working with various different partners. It’s being proactive about attending those events. We also organize a lot of hosted events.
So if you think about that awareness and engagement piece, we find that one of the most influential things that we have done over the last number of months is making sure that we are participating in local communities. So if we’re solving – for example here, our staff in our headquarters, we’re reaching out to various different organizations that our own employees are participating in; and making sure that we are tapping into that.
The danger with referrals is that you generate the same type of profiles. So if you’re a predominantly sales-oriented organization, you’re trying to tap into leads, you’re probably going to be creating that same cycle. So using things like Eightfold, whether it’s machine learning or whether it’s expanding social and professional networks, it’s trying to maximize all of those channels; and then making sure that that experience, as we talked about, is a really authentic, genuine one.
Mihir: Yes. So as you – we talked about these channel strategies, multichannel strategy between referrals, sourcing, local organizations; and that they relate to your overall talent acquisition mix and talent retention mix. Do you see diversity naturally channeling towards one of those channels, or do you see it more broadly across all those?
Daniel: I’m not sure – can you help me understand specifically what you mean by that?
Mihir: Yes. So referrals, as you pointed out, can be heavily biased against existing networks; whereas sourcing is getting out in the community, can maybe have a broader exposure. That helps you at top of funnel. However, after that top of funnel, when you’ve gone through the phone screen; you’re starting to get the hiring manager process, actual interview loops – I’m going to move the question in a little bit different direction – how do you help control for biases, or at least shine light on some of the unconscious bias that may preclude diverse talent making it deeper into the interview cycle?
Daniel: Yes. It’s one of the problems that we’re trying to solve for at the moment: understanding diversity in this light. So we try to surface those insights within the ATS that we use, and I think once we are able to do that, then we’ll understand where at each stage of the funnel we are seeing those signals that will flag whether or not we have a problem, or whether we’re overcompensating, for example. I think the tools that we use right now in order to solve for this are part of that education.
Really what it boils down to is ensuring that we call each other out. So things like the debriefs, having a conversation with the hiring panel after every single interview, and making sure that that is data based and fact-based rather than opinion – ironically that’s actually a good benefit that you get from diverse teams. You have that cognitive friction, which indicates our ability as a group of individuals to avoid that kind of groupthink and make sure that we’re incorporating different perspectives.
Does that –
Mihir: It does. Let’s talk about interview loops. It’s so important; not only to ensure that you have diversity in terms of the cross-functional partners that an employee or candidate would be interfacing with but then also cultural diversity across those interview loops. Can you talk about how those interview loops are set and what some best practices are?
Daniel: Yes, we think about it the beginning of the process. So going back to that intake meeting, part of our intake in terms of looking at what we are trying to identify, what business problem we’re trying to solve for, identifying the talent. We are very deliberate and intentional in making sure that those panels are diverse; not just from a functional perspective, but also from the nature of the individuals that are participating in that.
So we try to solve for it at the very beginning, and then through the analysis of looking at scorecards and various things; and we monitor that part of the interview training as well, to make sure that we are continuing to diversify the pools of interviewers that are actually participating in our process; because as we all know, if you’re scaling fast and growing organizations – which I’m sure a lot of people on the call can – one of the big risks is actually interviewer fatigue.
Once you start fatiguing, then those unconscious bias things start to creep in, where you have confirmation bias or otherwise. But it’s really about making sure that those panels are fresh, that they’re calibrated, that they are trained; and then that we are calling each other out in terms of what the feedback looks like.
Mihir: Got it. So then as you do those interview loops, if you think about the micro versus the macro when I say micro what I mean is any given manager manages between one and 10 people on average; but in aggregate, organizations are hundreds if not thousands if not hundreds of thousands of people. In the aggregate, diversity matters increasingly in terms of when you report externally, et cetera. There’s a public accountability associated with it at the AdRoll Group level.
However, at the micro level of a department or a division, let alone a singular manager, that same diversity doesn’t necessarily translate. You don’t have the breadth. So how do you integrate into the training around diversity the need for micro building to macro?
Daniel: Difficult problem to solve, because you’re working within the confines of the smaller teams.
Mihir: And the managers are optimizing for their team and the performance of their team or their goals, which ladder up to the organizational goals; but diversity may or may not be one of them.
Daniel: So I think what you solve for then is standardization. At AdRoll Group we look to structured interviews. So each person, regardless of what their role is within that team, is going into that process, into that interview, with a specific focus area. That takes away a lot of the variables that can sometimes occur, whether it’s opinion or personality; and it becomes much more data-based. So you’re going in there as a fact-finding mission, and I think once you adhere to the rigor around that process, then I think you’re on the right track in terms of making the right hiring decisions.
Mihir: Got it. When you use analytics to help understand how funnels are performing, meaning how diversity is progressing through the interview cycles, what is the feedback loop with the recruiting team on where they should be fishing for more talent, which pools they should be going to; meaning, how do you use those analytics to help drive your talent strategy at top of funnel?
Daniel: Yes. So this is where it gets tricky, I guess; because ultimately there’s got to be a change in mindset we were talking about earlier; which is, you’re not here to fill a requisition. It’s about hiring the best talent. So we think about that in terms of, where are we going in hunting for that talent. We market to different areas. So we try to solve for that at the very beginning of the process in terms of, okay, well we know that these exist in various different competitors; but are we thinking about schools, colleges, or other organizations that would present a different pool of talent, which we know to be more diverse.
So it’s making sure that it’s in there at the beginning. In terms of the analytics, we really just have to make sure that we’re looking at and understanding where those trends are when we see flags, trying to course correct. Then it becomes quite tactical in terms of making sure that, again, we’re having that conversation with the hiring manager to help them understand, what can the market provide us. There is that expanding, and where we’re going after that talent; and that changes depending on the role or depending on the job description.
Mihir: Sure. So with this increased focus and scrutiny on diversity and frankly the talent space broadly, there’s been an explosion of tools and capabilities for the talent teams and for organizations to help understand and dissect the work that they do. No longer is it simply scrolling through résumés and then profiles and then sending random emails.
So can you talk a little bit about some of the toolkits that you’ve used, but then also talk about them within the context of how goal setting has been changed, or what goals look like to our talent teams today; and how you see that evolving over time with tools helping achieve those goals?
Daniel: Yes. So I think there’s a lot of exciting developments happening and innovative products that are coming onto the market, Eightfold being one of those in terms of allowing us to leverage one of the largest assets that we have. As a 10-year-old organization we’ve grown fast globally, and we have a lot of data at our fingertips; but even two, three years ago we didn’t really tap into that; and even with a lot of ATSs that are probably industry standards that don’t allow talent acquisition teams to really interrogate in an intelligent way.
So we see things like machine learning and algorithms that are able to surface those profiles based off of successful applicants in the past of people that have recently been hired, but also those that have traveled through and that have had indicators of success. So if you think about the partnership, we can understand based off of scorecards how successful data can be.
So as we grow as an organization, the nature of the skill sets and positions that we’re looking to fill have evolved; but we can’t rely on recruiters to have intuition so we rely on tools like Eightfold to be able to surface those things, and we’ve had had some unbelievable returns with regard to its ability to – in a non-biased way, because it is an algorithm that is doing it – surface those and, to use a marketing term, as a lead or a high-intent individual that has a very high likelihood of matching some of those skills that we’re looking to bring into the organization.
There are other tools that allow us to surface some of that data as well. Textio allows us to provide and shape job description in a way that’s going to attract people as well.
Mihir: So goals have probably changed. When you started at Facebook, it likely was along the lines of so many hires or a certain fill rate. That was your top line KPI or OKR. Can you talk about how diversity is starting to creep into some of your actual goals that you report up on?
Daniel: Yes. So at AdRoll Group two or three years ago we had a natural groundswell in terms of the transformation of the company globally but also just the executives and also shaped by the marketplace. But diversity is becoming more and more important, so during those last couple of years, we’ve really fought very hard, and we’ve got some pretty aggressive goals around women in leadership being one of those.
It’s important to call out, just by solving women in leadership, you don’t solve diversity. In fact, it’s a very dangerous area to get into, but women in leadership was one of those diversity goals. Women in technology, as in engineering, is also another; and then making sure that we also have a strategy around underrepresented minorities. Thankfully we’re in a position now where we are at 53 percent women in leadership. We’re at 12 percent underrepresented minorities, and with women in tech we are probably going to increase but I think as a recruitment function, yes it, of course, has to play in, and becomes one of those things where previously it was not.
We don’t set a hiring goal around assigning that to a recruiter. What we do is, we give them accountability and ownership as part of that partnership with our hiring group to make sure that it’s built into their strategy, whether that is where they’re sourcing in terms of diverse talent pools, but also in terms of all of those things that we can leverage internally around ERGs and sourcing and so forth.
Mihir: So this is interesting. It’s actually a question that we received from an audience member. A quick note to the audience members: Feel free, please, to engage. You probably have five or 10 minutes left of Daniel’s time. I would love to ask him any questions you have. You can click the Q&A button at the bottom of the webinar.
One of the questions that’s been asked here is around global diversity. So oftentimes – what the question says is: Oftentimes articles that I’ve read deal with diversity from a very US-centric point of view. How do you think about global diversity so as not so US-centric?
Daniel: Yes, great question, diversity is definitely part of – we are starting to change how we think about it. I think by our own admission, we probably were US-centric. Thankfully in my role as global head, I operate out of Dublin; so my perspective is entirely different to the Bay Area’s where, for example, we look at it much more on a gender basis. So a lot of organizations, particularly in Europe, would be a sales and marketing culture where you have sales and account management, predominantly male-dominated.
So for our Dublin office, for example, we think about it from a gender perspective; because actually by nature, there are a lot of Europeans or multilingual people being hired into one site, and therefore you have a lot of different cultures already there. So you have that diversity built into it automatically. So it’s about making sure there’s a gender balance there.
I think the other part of that question is really about the “I” of D and I. It’s about inclusivity as well. Obviously, that can take many different forms. It could be with regard to communications. So again from a global perspective, one of the things that a lot of global organizations suffer from, or you hear that are challenging, is around global communication: How people, do people, feel like they are included in decision making; or are they influences in terms of the direction of product, various different things.
So when thinking about this, one of the pieces that AdRoll Group really does very well is making sure that we are being inclusive in those, and that requires a lot of making sure that we are including our global offices.
Mihir: Got it. Another question from the audience. This dovetails quite nicely, actually, with the – what can TA teams and all people in a company do to encourage better hiring?
Daniel: Talk about it more; get out in front.
Mihir: Let’s talk about that for a second. When you say talk about it more, I think we still don’t have the tools and the verbiage to know what to talk about or how to talk about it. Can you help us understand how the rank and file of an organization can talk about it more?
Daniel: So it goes back to the culture. If you are intentional, if you have executive sponsorship if it is truly something that your organization is trying to solve for, through whatever means those are – we’ve touched on a few of them – then I don’t see where the challenge is. I think too many times – I’ve seen it in too many organizations, where you’ve got a tech team or sales team, or perhaps it’s just by geography or logistic.
Part of solving for this is the internal brand and the internal messaging, so it’s making sure that you are front and center, that not just your executives are talking about it, or you’re talking about it in hiring teams; but actually you’re out there making sure that for people it’s part of their responsibility. Does that make sense?
Mihir: Absolutely. Part of their responsibility, I think, as increasingly people bring their personalities to work and bring their work to their personality –
Daniel: Hopefully –
Mihir: … hopefully, increasingly – one of the open questions from the audience was, any advice on how to find good local organizations to work with or how to bring local organizations into the fold –
Daniel: Yes. Ask the people that sit right beside you. This is what we were talking about a little earlier on leveraging in the ERGs or leveraging the individuals. To reinforce, this is an organizational problem that we’re trying to solve. So if you have people that you are hiring from those areas – and if you’re not, well then going back out into those communities. So at AdRoll Group, we have a program called AdRoll Gives Back, whereby people are encouraged – and I think that’s very much commonplace – to go out and dedicate some of their own time to giving back to their communities.
More specifically, I think there are colleges. There are schools well recognized, for example in the Bay Area, that would be predominantly more diverse than perhaps elsewhere where the larger population of the organization has come from. So I think it’s about really getting in and leveraging the employees that you have, because to your point here, it is about bringing you authentic self to work. In order to do that, obviously, people are passionate about things that they’re interested in.
So, in the end, you could maybe start to surface some of those things at the beginning of the process, right? It’s not just about what’s on a résumé. I think certainly when I’m interviewing individuals, one of the things I always try to do is tap into who they are. What is most important to them? What motivates them? Quite often a lot of that will come from the things that they do in their spare time.
So making sure that you’re leveraging that when you actually bring people in, you have the employees that are there day in, day out; making sure that they can actually participate.
Mihir: Yes. So as you bring those employees in, this next question – perhaps the last question we’ll have time for – wraps back around to the interview and to the specific tactics associated with interview loops. It has to do with the roles and responsibilities of different people on an interview loop. You will have technical or subject matter specific experts who are focused on X, Y, and Z. Then you’ll have, typically, one person who the culture fits interview, or the – the question here is, how do you have the interview loop all test for culture in their own unique ways?
Daniel: So at AdRoll we do break it up into focus areas. We have stopped calling it culture fit, because I think there’s an inherent bias there; and one of the things that we definitely got right early on a few years ago as we were scaling – which, by the way, is probably one of the biggest things as a growing company, that you lose touch on culture– but that identity is really important.
Also, understanding that it’s nuanced: So as a global organization with offices everywhere, you’re going to have, what it means to be at AdRoll or Eightfold, right, obviously, we have some spirit animals that we try to identify with in terms of working hard, doing right by the customers, and so forth. So what we try to do is make sure that first of all, we understand it, what those culture or values interviews mean and what are we looking for; what is a values fit.
So we think about – well, for example, thinking about diversity, we want people who are passionate about giving back to their communities or passionate – things outside of work. So it’s a difficult one to solve, because if you try to identify that values or culture fit in each of the stages, very quickly you’re going to run out of time, or you’ll be getting the same signal; and interviewing is tough enough. I’d say if you’re running a structured process it’s important to obviously have a mandate and an objective for each of the individuals then yes, I think ultimately try to identify – I’m not sure whether I’m answering the question, but here certainly what we try to do is make sure that at least one of the panelists is focused on values.
Are they hardworking? What is it that they stand for? Then probably the hiring manager, as well, should participate in that particular conversation; but doing it across the board for all panelists is challenging. Quite frequently during the debriefs, those that do try to head that direction are typically not getting the full the interview.
Mihir: Yes. I’ll add one of my questions on here from the debrief. I’ve been in debriefs personally where the recruiter has taken a backseat and let the interview loop fill the room. I’ve been in rooms where the recruiter has been in front, central, quarterbacking the dialog and bringing people back on track when people started to meander, maybe against or away from the structured approach.
Daniel: There’s a big difference.
Mihir: There’s a big difference there. So can you talk about recruiting recruiters who can quarterback the process? Because that seems like a central strategic advantage, to have a recruiter that can help do that. What do you look for in recruiters that can help bring diversity forward like that?
Daniel: So honestly that is not something that I think recruiters – I think that’s part of that accountability piece that we talked about. So when we are rolling out interviewer training, we’re very, very careful to make sure, just as you referred to earlier, that people are bringing their authentic selves. It’s really important for interviewers to feel empowered to provide that. You’re giving them the tools, but they’re investing the time. They are forming their opinion based off of questions; hopefully behavioral, statistically based questions, that allow them to get a strong signal.
So quite often I’ve encouraged recruiters, actually, to get out of the way. Obviously, hold people accountable. For example, one of the things that we look at out for is people coming to the debrief with their feedback submitted or with that scorecard. Luckily we have almost 100 percent scorecard completion before debrief starts it avoids that groupthink. If you have an overbearing recruiter or, to a point, a wallflower.
People will defer to, quite often, the most senior person in that room. But if you have a calibrated, well trained, and accountable interview panel that are going to call out biases, that are going to call out people who aren’t holding up their part of the process, then I think you get a wonderful synergy where actually you’ve got almost a self-policing system. I’ve been in debriefs where a recruiter just lets that flow, but I think it’s important. The rigor and process is really important; and one of the reasons why, I think, we’ve been very successful in this area is because there is that calibration, and people understand that they can’t show up without their due diligence and without populating those scorecards.
Mihir: Got it, Daniel. Well, I think we’ve probably got a couple of additional follow-up webinars out of this dialog.
Mihir: I know we’re running short on time here. I want to thank you for your time and your insight. The AdRoll Group – for those on the webinar, to learn more about the AdRoll Group, please check them out at adrollgroup.com; and about Eightfold’s Talent Acquisition and Management Services, eightfold.ai – Daniel, you’ve been fantastic. I’m looking forward to continuing to work with you in the coming months and years.
Daniel: Can we do more of these webinars? This is great.
Mihir: I would love to do more of these webinars. Maybe next time we’ll grab a drink too.
Daniel: Happy to – thank you very much, Mihir.
Mihir: Thanks so much, everyone. Thank you for your attendance on the webinar. We’ll be recording this and sharing it broadly with the groups. Thank you so much.
Aligning Talent Management Needs with Company Culture Diversity
Mihir: Hello, and good morning from the Bay Area. Thank you for attending the third and final webinar series focused on innovating the candidate experience. My name is Mihir Gandhi. I’m the Head of Marketplace Operations here at Eightfold.ai.
As a hiring manager for nearly two decades myself, sourcing, hiring and retaining talent has been a central theme in my career. Managing at hyper-gross companies like Lyft where I was the first general manager for their Flagship region in northern California, I acutely felt the pain of hiring rapidly and hiring right. I’m thrilled at how Eightfold is addressing these challenges and so much more. Specifically, today, we’re diving deep in strategies for recruiting and talent acquisition with a focus on diversity and inclusion. We’re joined by an esteemed guest. Russell Williams has exceptionally robust content to cover, but first a little bit about Eightfold.
At Eightfold, we’ve created a talent intelligence platform for enterprises that leverages artificial intelligence to hire, engage and nurture talent. Talent-centric applications built on top of this continuous learning platform enables enterprises to manage the entire lifecycle from prospect, candidate to alumni. With over 100 customers including Tata Communications, AdRoll, Hulu, Grand Rounds, Nutanix and more, Eightfold has helped companies vastly improve their talent acquisition, talent diversity, and talent management capabilities. Why was Eightfold created?
Historically, Legacy products like ATSs were developed to replace tracking paper resumes and as such provide similar workloads. Now ubiquitous and onerous online application processes that companies require from applicants is unduly hard both on applicants and on companies simply replacing paper problems with digital ones.
Eightfold was born in the AI era specifically to address and solve challenges with employment in today’s society. More information than ever is being communicated about jobs, companies, and candidates. These reside on job boards, career pages, social profiles, professional profiles like GitHub, Dribble. More and companies have more information than ever across multiple systems like ATSs, HRISs, CRMs, et cetera.
As hiring managers have specific visions into the skills, experience and knowledge and culture they’re building, recruiters are simply overloaded with information. More data isn’t necessarily better. It just means that there’s more places to find and dispread the information to try to cobble together and get a holistic view of the candidate.
Is it humanly possible to take in all these data and identify if candidates fit let alone their potential to excel let alone their career trajectory let alone do that across thousands of candidates and hundreds of jobs? The short answer is no. Those were rhetorical. This is where Eightfold’s talent intelligence platform comes in. Eightfold was designed to improve the lives of candidates, recruiting, HR, hiring managers, employees and alumni. The platform aggregates and digests multiple sources of data marrying internal data like your ATS with externally available information to create an enriched talent repository. The Eightfold PIP platform uses these data to help surface what candidates are good at today and what they’ll be ready for in their next career steps driving better talent strategy and execution.
Once the Eightfold platform has ingested robust data from Legacy and public profiles for each person, we create a rich profile of each candidate and calibrate each open role according to the specific needs of the organization. We drive improvements for recruiters and hiring managers to an improved intake experience, provide an instant pipeline of qualified candidates for each open role, improve the overall candidate experience, improve the employee referral experience and ultimately drive retention to improve internal mobility.
After our discussion and before our Q&A, Jason, Eightfold’s Director of Sales Engineering will give us a brief demo to bring some of these words to light. A quick note, as we get into the actual presentation section, please feel free to submit questions to Russell and to me via the questions from the audience, that section in BrightTALK. I want to give a couple of examples to bring to light what Eightfold has done for a couple of our customers.
First, Hulu. Hulu was using a host of tools to assist recruiting which was Jobvite, LinkedIn Recruiter, agencies, job boards, sourcing tools, homegrown tools, et cetera. They were receiving more applications than their team could keep up with. Given their hot trajectory, the volume of applicants and the number of tools they were using, they found that they were missing out on highly qualified candidates simply slipping through the cracks. When Hulu implemented Eightfold which aggregated data across all of these tools and sources, they were able to have a single view across the entire talent network.
On average, recruiters saved four hours per day and quickly stopped using in-mail because their talent pipelines were full of highly qualified candidates. At Tata Communications, as we heard on Tuesday, they were similarly overwhelmed with massive inbound. Hiring processes were in line with what you would expect from a 10,000 plus company that was experiencing explosive growth. Hiring managers were spending time interviewing candidates that weren’t the right fit. There was constant recalibration across what a right fit looked like.
In general, the processes were inefficient. With Eightfold, Tata was able to immediately rank, sort and prioritize candidates who were the best fits for each job. Recruiters and hiring managers were able to calibrate needs in real-time grabbing more efficient hiring manager’s time during interviews, 50 percent fewer meetings and in that a four to six-hour save per person, per day. Now, almost two-thirds of all of Tata hires come from Eightfold.
As I mentioned earlier, Jason will be giving us a demo of the Eightfold platform to demonstrate how both Hulu and Tata, amongst other customers, have been using the platform. Now, let’s get into our conversation.
I’m very excited to welcome our featured presenter, Russell Williams. Russell joins us from HR Global Link where he is the President and Founder. With over two decades of experience in the talent space, Russell’s thought-leadership in diversity, equity and inclusion is monumental.
In today’s conversation, we’re looking forward to hearing how Russell has seen the evolution of the talent space, where it’s been, where it is now and where it’s going across a series of content areas. I’m also specifically excited about this because, Russell, even though you’re a highly strategic thinker, you’re also unique in your ability to get into the weeds and actually talk through real-life implications.
Let’s get started. Russell, the primary goal with recruiting, quite simply, is hiring. It’s a timeless challenge. It’s time-consuming. It’s demanding. It’s never-ending. I know you have a very specific approach in framework. Can you share your framework around hiring talent with us?
Russell: Yeah. Thank you, first of all, for inviting me and providing an opportunity for HR Global Link to engage in a conversation. I first want to take a few moments and help give a mindset and give a framework for the conversation.
My approach comes from a strategy and business approach. What we want to explore today is looking at the culture of an organization and looking at the role of diversity and building a winning team. It’s very important to realize and I think we all know this is that the nature of business today is global. The challenge of business today is bringing in talent to all of our organizations at the right time.
The challenge that we have today is making sure that if you look at the talent management process, if you look at talent acquisition, talent development, redeploying that talent once you’ve brought it into the organization and you have identified new ways in which to optimize that resource, you want to have ways to do that. Then if the talent decides to become alumni, you should have a very efficient and effective way of still utilizing that resource for the betterment of your business because of the investment in both the candidate and the company.
The first point that I want to make is that the Eightfold profit using AI technology is at the forefront of the transition and transformation that all companies are in today. What’s central to an organization being successful is hiring. What’s essential to understand here is that culture and hiring play hand-in-hand. You can’t have one without the other. One of the core principles that we want to help people understand this morning is that what makes for a best practice software application? It needs to be transparent. It needs to be mobile. If you have an internet connection, you take the deep level of knowledge with you all the time. It’s on-the-go. It’s on the move. Then, finally, it needs to be customizable.
Each of us in our different companies, in our different mark niche, we have uniqueness. The Eightfold application, because of the technology capability, enables you to custom-build your profiles and your searches. One of the things that immediately it brings to the hiring process for professional staffing people is it helps you with if I can have that additional four hours a week or ten hours a week, how would I use that? Will that enrich my process? The answer is yes.
If I have uniqueness in the profile that I’m seeking and the talent that my organization needs, does the application help do that? Yes. One of the challenges that you face in identifying candidates is your own personal bias. We have a masking technique that enables you to build in more objectivity on the frontend.
In addition, as you use the application, we have the masking capability to mask the bias of the hiring manager. What, in effect, you get is the ability to reach out into the available global talent market based on the partnership that you build with AI and identifying the sources, where you’re going to pull potential candidates from. You pull out the bias in the process. That’s really critical because one of the challenges that we face is how do you have access to a greater and greater talent pool? Our application here at Eightfold, the application at Eightfold does that.
Mihir: What’s interesting, Russell, when I hear you talk about bias, bias is a loaded term. It typically has negative connotations. The way you describe it is simply something that everyone has. Once you recognize that it is simply a part of a daily routine, it sounds like you’re saying we need tools to help overcome that.
Russell: Yes. One of the things that we all face is to make diversity effective, you first have to adopt the mindset of inclusion. For the talent pool, that’s a great asset. If we can say our search geography is in this area, we don’t want to exclude anyone. What’s the goal? The goal is to bring the best talent to the business. In order to bring the best talent to the business, you have to have capability that can identify, match, rank and organize the data. We can’t do that as a human. We need to have a tool that enables us to gather the deep knowledge about the candidate pool. Artificial intelligence is the stepping in this transformation of if you’re going to win a war in talent, you need intelligence about your competitor. You need intelligence about the talent that’s being brought into the organization.
We cannot do that on a 1980 or a 1990 or a year-2000 methodology. The only way that we can compete effectively in today’s world is to be the best at intelligence, at the information gathering that we have. What we know today, that is one of the key boxes you need to check, if you’re going to be a winning organization, is that your intelligence has to be better than your competitors.
Mihir: That’s right. As you talk through that process, the way you laid out the prospect to candidate to employee to alumni, that’s a really long process. It’s one where the employee and the company get to know each other exceptionally well that lasts well in perpetuity. However, on the frontend when we talk about nurturing talent. That process is typically much more transactional in terms of introducing yourselves to a company, introducing him or herself to a candidate, the candidate learning more, going through a pretty rough interview process. Then, they start. All of a sudden, it’s one of the biggest decisions in their lives. Can you talk a little bit about nurturing talent and what that looked like on the frontend at the competitive vantage pool?
Russell: Some of my experience was that there’s a significant time-constraint in the front end of the process. We have different databases that we’re gathering information, gathering input and gathering profiles. Then, we have to sit and read through all of that process, all of that data.
The solution at Eightfold is that the machine, the brain of the technology does that for us. What would normally send inefficiently now is done by automation, and I get the output of that? Now, I can spend my energy and my focus in looking at the short list of candidates that our process has now produced. Based on my partnership with my hiring manager, determine who should be moved forward in the process of deciding whether or not they pass the first step in the selection.
Mihir: You know, we had lunch last week, Russell. One of the topics of conversation was how the front end of recruiting is a high effort, low value and that candidates move through the funnel. It starts becoming more targeted, less time spent and maybe more value. Can you talk a little bit about that?
Russell: Yeah. Going back to where we are in the process, there are two things that the professional staffing organization can now do. Your capability has now changed with the use of artificial intelligence. You not only have the shortlist but now if you think about this in terms of business, the reduction in time that you’ve not spent, those are dollars. The ability of the companies now or the hiring organization to spend less dollars puts more money and financial resources available for other projects across the hiring organization or in other areas of the business. In effect, you are now contributing to gross margin.
Every CEO wants every function in the business to contribute to profiting gross margin. It only makes sense from a business perspective if you understand that your survival depends on growth and profitability that you would embrace this kind of process change now. In addition, on the backside, what you get if you can be responsive to candidates, then they develop a perspective that says, “They’re really interested in me.”
If you have this short list of potential candidates, you can do something else. You can now initiate a campaign. Whereas in the past, you would not maybe have time to initiate a campaign. What we know is that from our experience with current customers, they’re getting four to ten hours a week in additional time. You have a choice of how to invest that gained time.
Mihir: Yeah. You know, the investment time as I hear you talk about that can go a number of ways. Certainly, I think the approach around nurturing talent, it’s very few people will apply the moment you reach out to them as a recruiter. The second, third, fourth outreach as they really get to know you a little bit better drives much better results. It’s a pretty ubiquitous approach here.
Russell: That’s one of the unique solutions within the Eightfold product. It enables you to customize your campaign. It enables you to change, in real-time, the unique aspects of the profile so that you get the right kind of matching that you want. All of that’s very important. It really emphasizes how important execution is in the talent management process. Each step of the process, the key to success is can I execute timely? In order to do that, your intelligence, the information that you have needs to be really, really accurate and, most importantly, timely.
Mihir: One of the things that I am particularly interested in hearing from you as you talk about execution, it’s not just execution for the sake of execution. What you want to do is hire rapidly and hire right. You know that when you have a high-performance culture and a high-performance organization. Can you talk a little bit about how you have thought about building high-performance cultures and how the frontend on the recruiting side really is the gateway to it?
Russell: Historically, I think the success of how management has been more focused on operational excellence, time to hire, cost of hire. That’s become our mantra. I think the gap in that whole thinking process and that whole tactical execution, we left that strategy. We only focused on what we needed to do.
The key is what and how because the how is embedded in your culture. It’s embedded in what we believe, what we think, what we do, all of that. In terms of the hiring and talent management process, the shift today is hiring– talent management needs to be holistic, systemic and strategic. What that means is, from an organization development standpoint to grow the business, you need talent.
The only way that you’re going to get there is if you have an organization development strategy. Talent management is the heart of organization development strategy. In fact, execution of your talent management process is the key. You need to be very proficient in each phase of that process, acquisition, development, deployment, alumni.
What we know is that the difference between a winning organization and organizations that are climbers, tumblers, and losers is that winning organizations are strategic. They have the following components. They have a strategy. They have a structure which is how we do things. They have a culture. They have the ability to execute. They have leadership. They have strategic partnerships with core customers in their marketplaces, and they’re innovative. What did I forget? Talent. You can’t do a darn thing without talent. That’s why it’s so critical for today’s professional staffing organizations and professionals to really have both an operational perspective which is important.
More importantly, you need to be strategic-minded. You need to focus on what are the needs and concerns of the business in terms of growth? The only way you do that is by garnering the best talent for your business and your markets and your customers. That brings direct value to internal stakeholders and external stakeholders. Talent is the key.
Mihir: It’s interesting as you mention that and talk through challenge and the process of doing so historically operations, execution, time to hire, cost of hire, none of that takes in quality. Quality is really driven across a series of qualitative components. As we all know, we’ve all had the experience where we’ve reached out to a company proactively and maybe never heard back or was told we’d hear back within a certain period of time and then never did. That’s never a great experience from a candidate perspective. What I think I hear you saying is that in order to get the best talent, you’ve got to be on top of your game from before that first communication let alone after the first communication.
Russell: I think from a talent management standpoint and if you invest the time to look at the capability of the Eightfold solution for your business, you’ll find that you’ll end up with better quality in your process and in your candidate selection and in your hiring. You’ll be more timely in executing every phase of the process. It will be cost-effective because there’s an emphasis on execution using time properly.
The other thing that you get, what we understand in today’s world is that information and intelligence is power. If you have that basis where your decision-making and problem-solving, you’re sort of ahead of the game. This tool enables you to have that timely information to make the right choice at the right time and bring that resource to your company and deploy that resource. It’s innovative. It’s best practice. It’s transparent. It’s seamless. It integrates. There’s no significant, deep changes you need to make to your existing architecture and configuration from a systems standpoint.
More importantly, if recruiters and professional staffing people and hiring managers are effective in bringing talent and utilizing talent in the business, that will automatically lead to better inclusion. Of course, you have done the masking for the key people in that process. You will start to bring more effective people in the business who are a better cultural fit in terms of values, norms, standards, all those kind of things that we look for in terms of what is the capability of this individual? More importantly, what is the potential of this candidate? That’s the other hidden gem in this AI solution.
Not only do you get the broad matching from a big universe, potentially, talent but you get the ability now to send some of that additional time that you’ve gotten. I know you can do this position coming in. What we know is that your attrition rate is ‘X’ and the probability of this person staying longer than that, you need to have a plan for that. That’s why talent management is part of the strategy of the business because you need to have a succession plan. Every employee should have a succession plan. Every manager should have a retention strategy for their people. The way that retention strategy works is with deep knowledge. You have that capability, but it’s a tool.
Mihir: We talk so much about recruiting. Retention is arguably much more important to an organization’s performance and especially to their culture. Can you talk about some of the retention approaches and the impact on culture once you’ve brought someone in?
Russell: To have a winning company, you need to have a winning culture. What we know is that every company is unique and different, and that’s great. That’s one of the beauties of our universe today is that most organizations no longer work in a very confined space. They look globally for talent. That’s the heart of diversity.
When you think globally, inclusion and diversity are no-brainers because you want the best people. You’re reaching into geographies where maybe your competitors haven’t looked, and there’s some great people there. You now have that capability. The key point, I think, is engagement, how you engage people in your talent management process. The Eightfold artificial intelligence platform enables you to be more proficient in that process because there are some mechanical steps.
Mihir: I think when we talk about broadly-speaking diversity initiatives and the integration of diversity initiatives, most companies’ first step is with existing employees. Can you talk about how we can bring something along the diversity inclusion parameter into the recruiting?
Russell: I think there’s a relationship between recruiting the population that you want in your – the best population in your organization to execute the business strategy. One of the things that happen when you engage Eightfold in a conversation about their solutions, it’s a very collaborative process and not only does it touch talent management and the various phases of the process from hiring to alumni. When you bring a person into the organization, that person comes in with some understanding of the principles and philosophies and values and how things work. What’s really core to having that person be successful is the performance management component of the process.
The performance management component ranges from performance appraisal to coaching to learning, building new skills. At the end of the day, people stay motivated when they’re learning and they know that there’s additional opportunity from their starting point or from the plateau that they’re currently at, and so performance management is really key. What that means is that means that you need to explore the potential.
Potential translates to more capability. Potential translates to more value for the business in terms of being able to do more, contribute more because the knowledge base is now greater and skill base is now greater. The way you get there is through intelligence, knowledge, information. That is translated in the dialog that the hiring manager or the individual manager has with that staff person. That’s really core because that will address the fundamental needs of the candidate. How do I get from where I am today to here knowing that the possibility of hitting that attrition point? That’s another way to build efficiency and be more proficient in what you’re doing.
Mihir: You think of recruiting as a strategic partner, as a strategic business partner. Can you talk a little bit about how AI is a catalyst for creating an ideal proficiency and candidate-matching? If you think about depths within an existing organization, there’s a hiring manager. I like people with these types of profiles, with these types of skills to really round out my team at my organization. How do I describe that to a recruiter that can then go help bring people in quickly and efficiently?
Russell: I think we all understand that the process starts with some definition of, “Here’s what the job is. Here’s what we want to accomplish.” We sort of build a specification, a profile. We would typically run with that. What we’ve learned over the years is that there also needs to be some understanding of what are the competencies from a skill standpoint, from a behavior standpoint, from an execution standpoint? What are the real competencies that an individual needs in order to be able to execute this role in a very high-performing, very proficient way? That needs to now be built in. Then, you want to make sure that the recruiter’s and hiring manager’s biases are masked. That’s one of the features of the application, so we have that capability.
Now when we reach out to the potential candidates, we bring that data in. Then in addition to that, we can rank those individual candidates based on the ranking criteria. You end up with a very focused candidate pool.
One of the other beauties of this solution is that it’s real-time. You don’t put in a report and wait for it. It’s real-time. It’s mobile, and it’s customizable. Once you have that data point and you have this short list and this dynamic, time is moving. Maybe something happens in the marketplace that changes that. Now, you can immediately go back and adjust that data set and bring forth the true candidate list. Then once you get that information, you can say, “How should we approach each of these candidates? Do we do a campaign? Do we reach out to them?” Part of what’s really transformational and really current, state-of-the-art here is that we can now take jobs to people. We don’t have to let people come to the job. We have that capability. You have that additional time now to do that.
Mihir: As you talk about the evolution and the static nature of how we currently do things versus the reality which is much more fluid and evolutionary, candidate-matching and needs of an organization will evolve if not minute-to-minute, certainly month-to-month, quarter-to-quarter. As we know, sometimes recruiting cycles can take significantly longer than that. I’d love to hear a little bit more about how you think we can improve the way that hiring managers and recruiters engage and collaborate to do that.
Russell: One of the words – I think this is a very exciting time for hiring professionals and anyone involved in the talent management process. For hiring professionals, for internal hiring professionals, I think it’s a great time to be in that role because you’re in a transformation from operational perspective to strategic.
We’re in a period of time in the information age where information is power.
Power is influence, more capabilities to influence the business. That means the staffing professionals are in the part of the business that has to do with organization development. The heart of organization development is answering timely and effectively the question of, “Who is the best person for this particular opportunity in our business?” In order to make that decision timely and more accurately than we have done in the past, automation is the key.
What we know today, artificial intelligence is the best available tool that will influence providing our ability to have more time to make the right choice, to make the right decision. That’s very disruptive because as humans, we like to be comfortable. The next generation of our business world globally is that things need to be faster.
Winners need to do things faster, more accurately, more timely that delivers value to your own business as well as any customer. The end game is how do we compete effectively in this marketplace? We do that through talent. We do that through continuous improvements in each phase of the talent management process. The only way you can do that is by being a strategic thinker and openly accepting the premise that once I have the information, I need to make a decision. I need to be action, strategy, execution-oriented.
Mihir: I’m going to read a little bit into what you just said. The current modalities are truncated and frankly siloed between recruiting, organizational development and then alumni relations. I think what you’re describing is something that is a much more continuous process from that first outreach through the alumni phase.
Russell: Yes. The AI technology, the application that’s been developed here, I think and I was struggling with this a while back in terms of where are we in this transformation to this new set of operating principles and way of doing business? That’s why I think it’s so exciting to be at this point and have access to this kind of opportunity and building a partnership with Eightfold. It’s moving the technology, and it’s moving our capability as individuals and as companies and as stakeholders. It’s the momentum that’s driving this. We aren’t going to go back at this rate.
Mihir: I don’t think anyone’s going to be collecting paper resumes any time soon. That sounds so archaic in this day and age. Even an electronic resume is, by a definition, a truncated reflection of someone’s experience, skills and capabilities let alone their performance review. Each one of these becomes deeper and deeper in terms of their richness of data and information. The richness and depth of data is frankly impossible to comprehend without the tools to do that.
Russell: Just a quick comment to hitchhike on that, you mentioned in their performance appraisals and all the different tools an organization uses today. You don’t necessarily do away with any of that with adopting the application here. The application seamlessly integrates with your current processes.
Obviously, there is conversation around does your process need now to change some? If so, how does that need to change and getting into the implementation of that? That component – we just don’t bring you an application off the shelf. We bring you a product and service that fuels your business growth that drives profitability that drives business excellence and drives personal excellence so that from a personal excellence standpoint, the individual has a way of being more inspired and sustaining that inspiration so that they are constantly at a level of job satisfaction that’s future-oriented. Most people will want to know what’s next.
Once you put me in this seat, I want to know what’s next. In order to help that individual work through a process of being entrepreneurial and deciding what’s next for them is the manager, the coach needs to have deep knowledge. The tool solution here provides that deep knowledge in the performance management part of the process.
Mihir: Russell, there is so much more, I think, that we need to get into. We are running on time. I want to make sure we save a little bit of time for Jason to be able to help bring this life a little bit. As we dive into this and we’ve already received a couple of Q&As, there are questions from the audience, a quick plug here for more attendees.
If you have questions for Russell, please feel free to drop them in. You and I will be digging into this not only in the Q&A but well beyond that as well. Right now, I’d love to turn it over to Jason. Jason is the Director of Sales Engineering at Eightfold. He’s going to give us a demo of the Eightfold platform to give us some tangible examples on how Eightfold partners have been able to use the platform to drive forward their business. With that, Jason.
Jason: Thank you, Russell. Thank you, Mihir. What we’ll do now is if you’ve been – this is the third part of a three-part series in the webinar. I’m going to switch it up a little bit and really focus on deconstructing bias and promoting diversity. Through this demo, we’re going to look at how we can smooth bias as it relates to the recruiter’s conscious and subconscious, a bias that they generally have. Also I’m looking at hiring based on meritocracy so matching candidate records for those hiring managers, also matching skill diversity.
It’s important to have a diverse team with varied skills yet a lot of similarities as it relates to those skills. Then, how can we nurture previous applicants and target, perhaps, gender and/or skills to promote further diversity as we hire on? Without further ado, we’re going to turn right into the application as if I’m a recruiter and I’m sourcing and screening and working with my hiring manager.
To that effect, what we see here on the left-hand side here, software engineer. I jumped in there but open position, and I’ll quickly go back. What I’m seeing is new applicants and also previous applicants and ones I’ve saved to a pipeline here. I even see three likely to respond. There’s AI being surfaced there where this is based on people who have been in the position for probably longer than the average, or they’ve moved many positions over time up the ladder. These are people that are likely going to respond to a reachout. Let’s dive into the open position.
When I go into the screening process previously, before Eightfold, I was going through various job boards and looking for candidates and looking for specific colleges because now I like to recruit two or three colleges for our open software engineer positions, thus my subconscious bias or conscious bias by showing that. With the automated, deep AI matching of Eightfold, there’s already a list of new applicants, 167 that you see here that are all based on the fact that they match, 91 percent match rate. Nine out of ten of these matches. If I were to do this before without Eightfold, I might get three out of ten because I’d be ignoring six of them that would have matched previously. Because of the matching and looking at like universities that have strengths in places that I used to recruit from, I’m getting a much more robust list of candidates. I can sort on them too.
If I was looking specifically around diversity for women because my current team is heavily skewed to men, if we’d like to smooth that out, I could make that happen. Also now as I take that off, I could drill into the top match here and I’m going to see the relevance. I’m not going to have to worry about the university. I just know this is a great match thanks to the AI that transpired. I can see that he has been quite the climber. He’s the top 30 percent of senior software engineers. What that means is that it only took him four and a half years to get to a level where his peers took about six and a half years so over-achiever, always executing.
I can also see publicly available data like GitHub. Does he have followers? Does she or he answer questions on Stack Overflow? Do they pertain to this position, other personal info, recruiting activity and what not? Now, I’m going through this list and setting up phone screens, perhaps. This has helped me tremendously to get the right candidate into the hands of my hiring manager. Also, we could look at this as a mass profile.
When I take multiple candidates and I send them forward to my hiring manager and they click on the email and they come into the system like I am now, they see Ankur as AG. They’re not getting bias from that ethnicity, perhaps. I don’t see his school. I’m strictly looking at the meritocracy, that he was an up and comer. He had tremendous growth in his last two positions. I can see blue boxes that match those skills. We pulled them right from his text for semantic analysis.
Those algorithms match into the actual job calibration that we see. This is tremendously helpful. The hiring manager, I can just add to pipeline. This person looks great. That whole concept is promoting diversity through just the fact that what did they experience? What did they promote and execute on rather than me stuck in as a hiring manager or a recruiter with those things that I think always worked for me in the past? Now, the next piece here I like to think about is how does this all work?
If we come back here and look at this software engineer role and we go look at the calibration and we think about matching, diversity is not just ethnicity and gender. It’s also skills. We need a diverse set of skills.
We go into the calibration of this particular opening. You can see the job description. Sure. That’s showing on the website. On the left-hand side are these different, ideal candidates we’d like to target and find people that are somewhat similar, then also keywords or skills.
For example, how I can bring this to light for the audience here is natural language understanding. That is a skill that we want from this developer. If we put natural language understanding in their CV, we pick them up. What we might be missing on is related skills of natural language understanding.
If you look on the right-hand side where my mouse is circling, there’s things like computational linguistics, text classification, knowledge representation, semantic technologies. These are all like skills, related skills to natural language understanding. If I have CVs, resumes that talk more to semantic technologies and knowledge representation, I would have missed them before as a human reviewing it. With this deep learning, training set and matching, Eightfold’s also pulling these other diverse candidates in terms of skills. We could have a team made up of a variety of disciplines that are also very related to one another. This is another aspect of promoting diversity using AI.
Finally, we’ll go to campaigns. Campaigns is an area where there’s market automation essentially embedded right in the Eightfold application where I can create a campaign targeting individuals by maybe specific diversity or alumni. Maybe I just want to share a blog or webpage because I’ve got future openings for machine learning, so I’d love to be able to match the blog to those people in my applicant tracking system, my passive applicants. I want to reinvest in the things that I’ve already spent money on such as a recruiter of 140,000 people in the past.
Let’s go and grab that blog post around machine learning that we identified that they’d love. I’ll enter it in here. All of a sudden, the target audience estimate goes to 10,600. Those are the people that are going to be into this article. Furthermore, I want to promote diversity because I have a team that’s skewed heavily men towards women. I’d like to add – really target women in this case. Sure enough, I’m now down to 1,800 of the 140,000 that really match well from a diversity perspective. Think about it. We’re parsing this blog post. We’re looking for related and identical skills to machine learning, so we’re promoting diverse team matching as it regards to skills.
Then, I’m looking for women because I want to balance this team that we’re building of the future or right now. I go ahead, review the emails, send this out and lo and behold, I start seeing the opens. The engagement click-throughs come in. I’ll show you this specific one that I already ran where I sent to 30,000. Where our customers are seeing anywhere from 50 to 70 percent open rates, I can see the top locations that these people are responding from, the diversity element. Are they coming from competitors, schools, referrals, et cetera? This herein lies my ability, again, to have a diverse reach out based on passive applicants. If we come back here to what I was talking about at the beginning is this deconstructing bias and promoting diversity through smoothing the bias during the sourcing process. Recruiters are getting all the best candidates and not just those that they have leaned on in the past, hiring based on meritocracy so that hiring managers are really looking at the experience and attainment of these individuals and then matching the skill diversity, matched skills that foster team diversity so you have a robust team, finally nurturing previous applicants by targeting gender and skills.
I’ll turn it back over to Mihir. Thank you very much for letting me show some of these things that, Russell, you have been talking about.
Mihir: Jason, I know – thank you for your time. I know you had a 3:30 AM call today, and you’re running off to another one. I appreciate you taking the time to show us how the platform works. We’ll dive into some that, again, in the future. Russell, we’ve got a couple of pretty hard-hitting questions that are coming in the Q&A. I want to dive back into those. I think you’re particularly well-positioned to take these. The first is around the definition of diversity. The question is gender and race are the primary definitions to diversity today. What will it take to move beyond?
Russell: That’s an excellent question. That’s a very complex question. I think it’s a conversation that’s still in play today. I don’t think we have reached a concluding answer to the solution to that. What I would say is the following. Gender and race is very critical because I think if we looked at our own individual ethnicity, that’s part of our fundamental, human quality and characteristic. That’s critical and important to each of us as individuals.
I think when we move beyond ourselves as an individual and we start to envision and see ourselves participating and functioning in the broader society and in the broader world that we live, then I think that begins to influence how we view things, what we believe, how we come to terms with what do we need to do as individuals to be successful in this larger participatory environment? Race and gender does matter because, obviously, we have a history.
Our history has been significantly influenced by those two variables. If you take a step back and say, “What really makes the difference in my world today,” I always say start with yourself. I think one of the things that makes a difference whether you’re poverty-stricken or you are wealthy is merit. What are you willing to do? Everyone has to make a choice. I think the significance of diversity from a race and gender standpoint in terms of influence on change and transforming our individual environments in our larger society where we participate is that you need help from others.
We talked about diversity in terms of being inclusion. The opportunity to have an organization that’s representative of our broader culture is really important. To me, I think that’s one of the bi-products of the Eightfold solution is that it doesn’t say that race and gender aren’t important. It sort of gives you a more objective way to begin to influence the change and the transformation that’s here. Someday, perhaps race and gender will be in its proper place. Today, it isn’t. What we do know is that there’s a significant voice in our individual communities where we live and around the globe in terms of this particular aspect of the human condition. It will get better because I think there are people who are willing to take on the accountability to use it in a very positive way as opposed to a negative way. That leads me to something very specific here.
What is the value proposition of diversity and culture? If we look at diversity as a way of bringing more capability into your organization or into your community, it’s increasing the talent. It’s increasing the participants, in that community, their capability. In our organization, once we bring that talent in, we need to develop that talent regardless of their race or ethnicity or whatever the components are. The commitment to being a winning organization is in the performance management process and this broader talent management process, succession planning and all of those things focused on action strategy.
Then, finally, I would say in terms of this question, culture is the collective capability which drives possibility and growth, execution of organization development strategy and job satisfaction for talent. Race and gender does matter, but it’s in a collective sense in terms of inclusion.
Mihir: I love that. I feel like maybe we should have a webinar specifically focused on that, so we can dive deeper. Unfortunately, we’re running a little bit short on time here. Russell, I want to thank you so much for your time, your insight and bringing your experiences to bear for us and for our audience. We’re in the early days of AI in the HR tech space and the talent tech space. I think it’s pretty exciting. We’ll see what the few years will bring.
We, at Eightfold, are looking forward to partnering with you, of course, with our current customers and with the future partners to bring some of these capabilities to bear across the industry. Audience, I want to thank you so much for your participation and your attention. As you know, this is the final of a three-part series. Please, check out our other two webinars with Ashish Mediratta, the Head of Global Talent from Tata Communication, then Amit Prakash, of course, the Founder of ThoughtSpot.
Thank you for spending your time with us, again, today. I look forward to connecting with you very soon.
Russell: Thank you.
Finding Ideal Candidates Even Before the Interview
Mihir: Hello, and welcome to the second of the three-part webinar series focused on innovating the candidate experience. My name is Mihir Gandhi, and I am Head of Marketplace Operations at Eightfold.ai. As a hiring manager for nearly two decades, sourcing, hiring and retaining talent has been a central theme in my career managing at a hyper-growth company like Lyft where I was the first general manager for their Flagship region in northern California. I’ve acutely felt the pain of hiring rapidly and hiring right. I’m thrilled at how Eightfold is addressing these challenges and so much more.
Today, we’ll talk about how that’s happening. Specifically, we’re diving into strategies for recruiting and talent acquisition and how AI is changing the recruiting process. We’re joined by our esteemed guest, Amit Prakash. Amit is the Co-Founder and CTO at ThoughtSpot. We’ll have robust content to cover with regards to how he approaches AI, in general, and also specifically talent acquisition and the interview process.
First, a little bit about Eightfold. At Eightfold, we’ve created a talent intelligence platform for enterprises that leverages artificial intelligence to hire, engage and nurture talent. Talent-centric applications are built on this constantly-learning platform, enables enterprises to manage the entire lifecycle from prospects to candidate to alumni. With over 100 companies as paying customers including Tata Communications, AdRoll, Hulu, Grand Rounds, Nutanix and more, Eightfold has helped companies vastly improve their talent acquisition, talent diversity, and talent management capabilities. Historical Legacy products like ATSs were developed to replace the process of tracking paper resumes, and as such provides pretty similar workloads.
Now ubiquitous and onerous online application processes that companies require from applicants is unduly hard on both applicants and companies replacing paper problems with digital ones. Eightfold was born in the AI era specifically to address and solve challenges with employment in today’s society. As this slide communicates, more information than ever is being communicated about jobs, about companies, and about candidates. These reside on job boards, career pages, social profiles, special profiles like GitHub, Dribble and more. Companies have more information than ever in their ATSs, in their HRISs, CRMs, et cetera.
Of course, hiring managers have specific vision as to the skills, experiences, knowledge, and culture that they are building. More data isn’t necessarily better. It just means there’s more places to find dispread information and try to cobble it together to get a more holistic view of a candidate. It’s not humanly possible to take in all of your data and identify if candidates fit or to figure out their potential to excel in a given role let alone their career trajectory. Then to do this across thousands of candidates and hundreds of jobs is simply a superhuman task.
That’s where Eightfold’s talent intelligence platform comes in.
Eightfold was designed to improve the lives of candidates, recruiting, HR, hiring managers, employees, and alumni. The platform aggregates and digests these data marrying internal data like your ATS with a plethora of sourcing and recruiting tools you could be using with externally available information to create an enriched talent repository. The Eightfold platform uses these data to help surface what candidates are good at today and what they’ll be ready for in their next steps in their career. This drives better talent strategy and talent execution. Once the Eightfold platform has ingested robust data from Legacy and public profiles for each person and thus created a rich profile of each candidate, the platform calibrates each role according to the specific needs of the organization. The results impact the entire ecosystem. The intake process is redefined around content. An instant pipeline of highly qualified candidates is delivered to recruiters and hiring managers. The candidate experience is transformed from being, “Do it yourself,” to, “Let us help you.” The internal referral experience is streamlined to be friendly to recruiters, employees, and candidates.
As we talked about in yesterday’s webinar, the platform drives retention is smart and targeted internal mobility. After our discussion with Amit and before our Q&A, Jason Gray, Eightfold’s Director of Sales Engineering, will give us a brief demo to bring these words to light. Additionally, I’d love to have the audience participate by sending questions throughout the course of the webinar that we can then engage with Amit during the Q&A session. I’d like to give a couple of examples of how Eightfold has helped our customers. This first example is from Hulu.
Hulu was using a host of tools to assist in recruiting such as Jobvite, LinkedIn Recruiter, agencies, job boards and sourcing tools. They were receiving more applications than their team could possibly keep up with. Given their hot growth and trajectory, the volume of applicants, the number of tools they were using, the Hulu team found that highly qualified candidates were slipping through the cracks.After implementing Eightfold, which aggregated data across all of these tools and sources, Hulu was able to have a single view on their entire talent network. On average, recruiters saved about four hours per day and quickly stopped using in-mail since their talent pipelines were full of highly qualified candidates.
At Tata Communications, they were similarly overwhelmed with massive inbounds. Hiring processes were in line with a 10k plus company that’s experiencing close of growth. Hiring managers were spending time interviewing candidates that weren’t the exact right fit. With Eightfold, Tata was able to immediately rank, sort and prioritize candidates who were the best fits for each job. Recruiters and hiring managers were able to calibrate needs in real-time driving more efficient hiring manager time-use during their interviews. Fifty percent fewer meetings could recalibrate on expectations for candidates and approximately four to six- hour saved per recruiter, per day. Now, almost two-thirds of Tata’s hires are driven by Eightfold. As I mentioned earlier, Jason will be giving the demo of the Eightfold platform for the Q&A to help bring some of these examples to light.
Now, let’s get into our conversation. I’m very excited to welcome our featured presenter, Amit Prakash. Amit is Cofounder and CTO at ThoughtSpot and has built numerous high-performance machine learning and analytic systems. Prior to ThoughtSpot, Amit led multiple engineering teams in the Google AdSense environment. Prior to that, Amit was one of the early engineers on the Microsoft Bing team where he built a web-scaled graph computing system responsible for computing algorithms and capabilities like page rank on graphs over trillions of data. Amit is also a co-founder of, “Elements of Programming Interviews,” books where he has tried to help both interviewers and interviewees better prepare for technical interviews. He received his Ph.D. in computer engineering from the University of Texas at Austin and a Bachelor of Technology in electrical engineering from the Indian Institute of Technology in Concord. I’m so excited to welcome you today, Amit. Thank you for joining us.
Amit: Thank you so much for a great introduction.
Mihir: Absolutely. Amit, let’s jump in because I think there’s a lot of content to dive into here. You spent several years at Microsoft and at Google, and there was tremendous growth at each of those companies in your time there. Your teams must’ve grown dramatically during that time, and so you’ve had to hire a lot. As a hiring manager, why is hiring so hard?
Amit: I think hiring is hard because everybody’s realized that recruiting is the most important function in a company. If you get the right people in, there’s nothing like intensive growth and success. There’s a lot more demand for great-quality people everywhere you go than there is supply. What you end up doing is essentially playing “Moneyball” with your candidates because you know that the superstars where whom everything looks perfect on their resume, everybody’s after them. You can go after them, and sometimes you’ll win. To really succeed, you need to find your edge as to which dimensions that you can look at, that you can predict somebody’s going to be an awesome star that not everybody else is looking at. I think that’s where most of the recruiting energy needs to go.
Today, it goes so much more into the process and to the mundane aspect of searching through LinkedIn profiles and resumes and just inbound applications. That sort of makes it very hard. At the end of the day, when you find the right candidate, you need to spend a lot of one-on-one time with them to show them your vision of why it’s going to be a successful place for them to come. To get to that point where you know who you’re looking at is going to be a great candidate, there’s so much effort that goes in. There’s such a small percentage of those applicants that actually pan out that you end up wasting a lot of very, very important time. If there was a better system, you could actually concentrate on the right candidates much more.
Mihir: As you say that, the mental image that comes to mind is a really broad funnel, top of funnel that narrows very quickly. That broad, top of funnel as you describe it is a sifting through hundreds if not thousands of profiles. It’s pretty laborious and intensive. As a co-founder of ThoughtSpot and as a hiring manager, can you describe your interaction and engagement throughout that top of funnel piece and how you widdle it down to the few candidates that you’re going after?
Amit: To make it concrete, I can talk about a specific role that I’m right now looking for. I’m looking for somebody who has a good experience with statistical techniques, data science techniques as well as somebody who is an engineer and has exposure to machine learning. This being a hyped up field, almost everybody is writing those buzzwords in their resume. You did not cross a single resume where there’s not a mention of machine learning or a mention of data science or something. The moment you start to funnel, within five minutes you realize that they have maybe used a couple of machine learning tools and have a couple of projects but don’t have nearly the depth that you want. Again, it becomes a very laborious process to go through all these resumes that match the keywords that you’re looking for and then actually figure out who has depth in there or not. Does that answer your question?
Mihir: Yes, it does. I think what you described is the ability to quickly ascertain the reality of someone’s experiences versus maybe the thought of what they purport to do. Can you describe a tool that you’ve used today or in the past that has helped streamline that top of funnel so that your time as a hiring manager is more efficiently spent on good candidates and not on the 25 extra minutes of interviews that you know you’re not going to proceed with?
Amit: Yeah. Unfortunately, I think – I won’t say that it’s a fault problem. For us being a startup, what has happened is that since all other things are extremely noisy, the most reliable signal we have with employee referrals. We’ve been able to find a lot of really high-quality candidates to referrals. At least a year ago, we were not even in a position to invest the human energy needed to go through all of the inbound resumes and things like that and the ignoring that. Now, we realize that there are a lot of high-value candidates in there that we could have gone after. We just didn’t have the manpower to go through it. Referral-based hiring has been extremely helpful to us. We have an amazing team, very, very high-caliber individuals.
One problem with that is diversity because you tend to know people who look like you, who have gone to the same colleges. Those people also know, again, other people who look like you and went to the same colleges. Your entire workflow starts looking very much like the co-founders. I would have loved to have introduced this to people with diverse backgrounds and give us the confidence that we could go after them.
Mihir: We see something somewhat similar here at Eightfold where when you grow from two to ten to 20 and beyond, each hire is incredibly important and impactful to the organization. That doesn’t change when you’re a 1,000 or 2,000 or 5,000. Generally, in that process, you do lose candidates, really highly qualified candidates because the bandwidth required to actually sort through and sift through them simply doesn’t exist. How have you seen, in your experience, this evolve over time? Can you describe to a recruiter or agency what you’re looking for in a candidate to help drive this forward?
Amit: Yeah. I don’t think we have really innovated there. We still go through a painful process of writing a job description and talking through what is important, what is not. One of the things that one of my mentors told me at Google is that most human beings are good at looking at maybe five or eight dimensions at most. Beyond that, it gets very hard for a human to put all the details in their mind and work through a lot of data. That’s where machines do a better job than humans is when there’s tons of dimensions that you need to care about. A machine is going to be very dumb in terms of depth, but it’s going to be great in terms of breadth. Sorry, I lost my train of thought.
Mihir: No, no. That’s helpful. When you say that, how do you and I think your work at ThoughtSpot is actually very pertinent. You see AI in tools that drive those types of deeper insights, empowering the human element that’s required to do the work.
Amit: Yeah. I love the engineers on my team. I think we have an amazing team. What I tell my recruiting team is that “If you can just find me exactly these kinds of people, just send more of them that will be fantastic.” It’s very subjective to know what do these kinds of people mean? Do they need to have gone to the same colleges? Do they need to have the same job experience? Do they need to have worked on the same project? That’s where a lot of subjectivity creeps in.
Sometimes I see my view of who are the high-value candidates, and the other is different from the recruiting team. Then, that leads to missed opportunities in terms of who’s candidate was prioritized higher? It’s somebody who’s just waiting for a week because you’re rushing through those other candidates.
Mihir: It’s interesting that you say that. You mentioned the job description process and frankly how broken job descriptions are. That is actually the candidate facing a description of what they would be doing. The reality is you’re looking for someone like someone else. You say like someone else. Can you help describe a little bit more about what that means? How do you actually translate that to a recruiter that then translates that to whittling through the top of funnel?
Amit: We had a good success initially hiring engineers with years of experience from Google. That was a great profile for us like people who have spent a few years at Google, the best place to learn engineering on the earth. It’s also very hard to go to people who are in very, very high demand. People like them, again, there’s so many dimensions to look at. It could be the college. It could be the project. It could be the quality of their project. It could be that they are friends with somebody that is in my trusted network. It could be that they have published something that has won awards or something like that in a confidence that I know high-quality talent through. That’s where once you’ve spent a lot of time with your recruiter, they can get to see how you evaluate candidates and get a better and better picture all the time.
Mihir: The dimensions that you outlined are almost impossible to sustain, stack rank and prioritize a school like this or experiences like this or evaluate they’re getting. The reality is candidates are so diverse that the ability to stack and prioritize is a nontrivial task. When you talk about spending a lot of time with your recruiters, you talked a little bit about the recruiting channels that you’ve used. We’ve seen some pros and cons at different types of recruiting channels be it advertising channels, agencies, in-house recruiters and so on and so forth. What’s the level of success across these modalities? What are the pros and cons? How do you spend your time investing your prospects?
Amit: In my personal experience, there’s nothing worse like your team’s referrals. That’s probably the highest priority by a factor of ten or so. Beyond that, I think we haven’t had much success with agencies and such. There are a few areas where it’s a very routine hiring process, where you don’t have to look at many dimensions. You just look at a few dimensions. You’re okay with that. In those cases, we have had decent success with agencies.
The referral effort is great where it doesn’t scale well. The other thing is there are a lot of inbound candidates. Potentially, what we have done is that we have staffed up a recruiting team so that they can go through all of the inbound applications and figure out which ones are worth going after and which ones are not.
Mihir: What you’re describing is a bit of a tipping point where you’re going from being the hunter trying to get people to come into the organization to being an organization that has so much inbound that now you need to staff up, provide the tools and processes and resources to whittle through that. I think one of the things you mentioned earlier is when we were talking before the webinars.
There’s very qualified candidates who simply just fall through the cracks when you have that massive inbound. Can you talk about some of the challenges that you face with sourcing and screening post-tipping point when you’re fielding all the inbound and actually kind of whittle through those folks who are interested in working for you?
Amit: I think when you talk about if you start looking at your inbound, there is a narrow fraction that obviously is good. You can’t know that they’re going to be good because there’s a very small fraction that’s very much in the line. Most of the time that time you reach back, either they have moved on or they have their props and creds. That’s a great pool, but the success rate of that pool is not that great. Then that’s where creative thinking and analytical approach comes in where you find things that are not obvious to the market that are good predictors of the success.
For example, there is a tiny company, not tiny actually but a decent-sized company in India called Directi. We’re hearing as we talk to people, nobody knows about them. What we have found through hiring two or three people is that that was fantastic training them for a lot of great engineers a few years back. Any time we see somebody from Directi, we go after them. Similar things that we have found is that people may not have a great pedigree. If they have participated in programming contests, particularly a few good ones that tends to be a very good indicator of their performance. They need other aspects too, but you can test in the interview. In general, that’s a good signal to go after.
Mihir: It’s so hard to communicate that to a recruiter or to an agency, “If this, then that but not this,” and, “We’ve seen some traction internally around this. Can you go proactive with a better analogy? Go fishing in that pond or in that part of the lake where we have had success in the past, and we think we have competitive advantage?” If you were to take a step back from using modalities, can you talk about what an ideal sourcing process looks like for you?
Amit: I think an ideal sourcing process would exactly look like what I said. I have a team of 500 people. I know that they are fantastic. “Just find me five times more of that.”
Mihir: You almost don’t need to say more than that. I mean you shouldn’t have to say more than that. There’s such rich data that already exists not only in your head but on their resumes and their publicly available information that it should be the extent of which you engage at the top of funnel. When you –
Amit: The other thing that I’ll add to that is that not everybody that looks great is recruitable. The other signal that I would love to be included in the sourcing process is people who are likely to perform. This could be based on how long they’ve been at a company, or there has been communication from their side to the world that they are ready to move on or maybe an additional change indicator. That’s the piece that’s hard. Once you found what looks good and you found the signal that they’re looking to move, that’s when things really start moving.
Mihir: Those are not impossible to find. Those data exist. They’re just difficult to parse. If you take the time to look at someone’s resume over a five or a ten- year career span, you generally get a sense of could they be stagnating or ready to move? It takes a lot of time, a lot of resources to do that and frankly a fair amount of skill. When AI is developed correctly and applied in the right way, how do you see it helping recruiting?
Amit: I think where AI does a fantastic job is when there’s lots more than eight or ten dimensions to consider, and you have some data that lets the machine say, “What correlations have what we are looking for and what correlations have what we are not looking for?” This seems to be a great problem to apply here too. In an ideal world, all these different signals that are available about a candidate would be processed by an AI engine to properly scale and tell us that ‘A’ they are going to have great career potential and ‘B’ they are likely to consider.
Mihir: A lot of that time is currently spent that recruiter is guessing, hoping, frankly spraying and praying. That time is pretty valuable time that could be spent nurturing, engaging, educating candidates. Can you talk a little bit about the importance of not just the outreach but the actual nurturing process between finding candidates that could be a good fit and actually getting them in the front door?
Amit: That’s the other thing that it’s a very significant investment on the candidate side to prove to us that they are worth spending time on. The actual human part of the recruiting is also very, very intensive. I often find my engineering teams burnt out, with the number of interviews that they have to give to a target. Sometimes, we talk about why aren’t we programming to filter down the people that we interview? Then that’s asking somebody to invest a chunk of their time when they don’t even know whether they are interested in the opportunity or not. It’s just somebody needs to spend the time painting the vision for them and telling them why it’s going to be a great move for their career. That whole process requires a lot of time and compassion and passion. It’s great to know to narrow down where we spend that.
Mihir: There’s always a balance between do I keep sourcing for top of funnel, or do I spend time trying to help candidates learn more about the organization? The human element associated with that that you described is paramount. The tension between spending time doing one versus the other is a natural tension. I think it’s a place where AI can help really turbocharge to help recruiters function and help them allocate their time very differently rather than 50/50 or 80/20 being 20/80, along those lines. As you think about that and as we continue to think about how progress is made, it’s going out and finding new candidates and new candidates and new candidates. It’s just nonstop.
Then, there’s this massive repository of candidates that have been found that maybe were lost or came through the door at the wrong time. Now because of the growth of an organization, they could be a great fit for that role. How do you currently go back to that repository of people who’ve either indicated interest in your organization that maybe weren’t the right fit at the right time or didn’t respond because they didn’t know who you were? Now you’re at a place where people like, “We should re-engage.”
Amit: I think, sadly, the current state is that unless somebody just remembers to do that, it just doesn’t happen. There is a lot of lost potential in there that we haven’t tapped into. Every once in a while, it’s either one of us remembering that “We talked to that person. It didn’t work out that time, but it could work out now.” Once in a while, we’ll go and look at older feedback and see where whatever there is potential for the growth for you or for them. Because of the management growth, they could be a good fit there. Right now, it’s very grave, human-centric and walking on people’s mindshares.
Mihir: Do you have the time to go back and think about previous candidates who you interviewed 12 months ago or 24 months ago? I mean what you’re describing is it’s a highly manual process. I ask that because not only do you not have time to do it or bandwidth or the mental resources, but the current process is not set up to help those candidates learn more about the organization at the right time.
When you think about identifying internal candidates on your team and as you worked at places like – It’s very different when you’re at a 10, 20, 100 even 500-person company. When you start to get to 1,000, 2,000, 5,000-person company and you saw this at Bing – you saw this at Google – how do you identify people across the organization that could be great, internal fits on your team and then also provide opportunities for people on your team to find other places within the larger organization for mobility? Can you talk a little bit about that?
Amit: I think where we saw growth at Google and Microsoft was a lot of willingness organization’s part to allow this kind of mobility. The process of matching like people wanting to move and people wanting to hire was no different than – maybe a little bit more information available but then without two, you don’t have the ability to go look at everybody’s profile and things like that. The process was no different than external recruiting where people who advertise their job descriptions and hope that somebody applies would mostly reach out to teens where they had friends. They had used that –
Mihir: As you describe that, it sounds like that’s what you said earlier. You’re almost limited by the networks that you’ve already created or this. It’s difficult to look beyond those. As we see this accelerating plan of people migrating jobs within from ten years to five years to 24 months or 19 months, retention becomes incredibly important. As you continue to grow ThoughtSpot, how do you think about retention versus recruiting, the inflow on the spigot versus stopping the bleed on the other end? Can you talk about your approach to retention versus recruiting?
Amit: I think that most people like to do two things, ‘A’, that they’re making an impact and they’re growing while making an impact and, ‘B’, that they’re being treated fairly. Having a great team, people being treated fairly is kind of a no-brainer. You have to do everything you can to make sure that they are being treated fairly. Then, the other piece is around just giving people the right opportunities to grow and learn and things like that. That’s where internal mobility becomes one important factor.
There’s some people you just love to keep pointing their skills in one direction and keep working, but there’s some people who love to learn new things and try different things out and just go in and figure out what works for them. For that, we are – I feel like there’s a little bit of tension between you don’t want somebody switching teams every three months or six months. When they have reached a certain level of maturity, we are very open to internal mobility.
Mihir: At our webinar yesterday, we spoke with Ashish from Tata Communications. The way he described their approach is external recruiters have no problem reaching out to our staff trying to poach them. Why shouldn’t we also be able to use our own talent as a repository to find growth opportunities? Tata’s at a very different scale and stage than ThoughtSpot is. How do you, right now at your organization and as you think about the next three years or five years, proactively identify the people that you want to move to different parts of the organization to give those different experiences versus reactively having someone come to you and say, “I really want the –
Amit: What we’ve done is we’ve been very open about the staff that once you’ve spent a year, year and a half, we will be very open to moving. Once you’ve reached two, two and a half years, we actively want you to think about whether you want to stay on this team or you want to try something new and learn something new. It’s okay if you want to stay. It’s okay if you want to move. If you haven’t thought about it, we would encourage managers to bring up those things, whether they are at the best place that they could be.
Mihir: It’s a lot of burden not only to manage someone’s existing workflow and priorities but then also think about the best growth on their behalf especially for junior staff that may or may not be adapt at proactively asking for new types of opportunities. I want to pause here for a minute. I want to turn it over to Jason for a demo. We’ve had a couple of great questions come in through the webinar. We’d love to dive into that after the demo. Hold on for just a minute, and then we’ll dive back in. I’d like to introduce, at this point, Jason Gray. He’ll be giving us a demo of the Eightfold platform. We’d love to dive into it.
Jason: Great. Thank you for very much for the time today. I should be sharing now. As we go into the demo, the key takeaway here is a deep AI matching and how you see, throughout the platform, it relates to the candidate experience, sourcing and screening, the candidate nurturing and internal employee mobility. Underneath all this is smoothing out bias and creating more diversity as it relates to pulling in – sourcing talent, nurturing talent and so forth.
When we look at careers pages and you can look at any career page, they’re very confusing and are keyword-searched. You search for ‘software engineer’, perhaps, and you can find hundreds and hundreds of openings at any particular company you choose. Here at Eightfold, we really to improve that candidate experience. We’ll see that here when I simply go click ‘apply’, it brings me to a window where I can upload my resume. Eightfold’s going to automatically match my applications of roles that will best fit my skills or experience. This is on the actual Eightfold site. Our customers use this. I go in, and I grab my resume. We’ll do a software engineer. I upload this. We’re automatically seeing the deep matchings as we’re parsing the resume, applying it to all the different job descriptions and how they’re calibrated.
We’re predicting, in this case, Amy Jones, predicting what she’s going to do next. This is the same experience that we see when we do referrals, employees do internally or when an employee goes into internal job postings we’ll see later in the demo. I can see full-stack engineer, product management leads, senior front engineer so two software positions that I’m interested in. I actually have some product management experience in my previous engineering roles. Obviously, it pulled that in not obvious to me, but that’s why they matched it. These are the best positions out of all there at Eightfold, so I’m going to apply to both of them.
Then, as part of that candidate experience, we can also ask questions. I can state them specifically or even have text-based questions. I can go ahead and submit my application. Then, we can continue to enrich that with blog posts that relates to their position and other individuals they might know. That makes the candidate experience better. They get email notifications and updates through the Eightfold platform that our customers are leveraging.
Now, as it relates to the sourcing and screening side of the house where we deal with recruiters and hiring managers, what do they see? We really want to promote ease-of-use so that they’re not spending all this time going through physical resumes, going onto job boards trying to find individuals. Rather, they come in right in the morning and then get right to work with the best matches available. As we land here, we see all the positions on my right-hand side that I’m managing.
Then, I see a newsfeed of updates on the various positions. For software engineer, here I see there are 17 recent applicants. I see four leads that stayed in the pipeline where is the top 30 percent senior software engineer at Airbnb. I also see 26 new leads and two likely to respond.
We actually see some of that AI matching happening here because we’re looking at the career trajectory, the skills, the titles to match the right open positions. We also look at some of them have been in that position for a long time, thus compared to the 10 million resumes that we put print against that says there are two that are definitely looking that they most likely would move. That’s interesting to me.
Now, as a recruiter, the first position I want to work on here is the software engineer because I’m excited as I have a whole host of new applicants. I can see new applicants, 167. I also have leads here, 174, 176 now. It’s building now constantly because it’s pulling from the applicant tracking system. Those are people that might have applied in the past.
First, before I go to the people that applied in the past, I want to look at the people that are fresh and new and interested. I can quickly, if in a scenario where we’re working on diversity where we have, in this case, a very skewed team of men, perhaps I want to look specifically at women. I can look for those women. I can see that if they’re a top US school, top Canadian school. If I mouse over, it will also show here the relevance. As we’re doing this matching, we’re matching in skills and titles and ideal candidates either ones that have already worked here at my company or perhaps that I’ve pulled right down from a job board that this person would be perfect. The school elements work and so forth and so on.
Now I’m going to uncheck diversity ‘women’. I’m going to see just the top- ranking here. I see Ankur Garg. That’s a new one. I’m going to go ahead and drill in and work down my list and see what is Ankur like? He’s a lead software engineer. He’s got eight years of total experience. Then, we see some more of the matching eight years of relevant experience to this position. Everything he’s done is relevant to this position.
Then I look over here to the highlights, and this is where really interesting things start to bubble up. He’s the top 30 percent senior software engineer at SnapView and top 40 percent lead as well through his different positions he’s held there. It’s shown that what does that career growth mean? Well, it took him 6.9 years to get there compared to his peers that took 7.9. If I can see these top percentiles, that can help me hone in further on an ideal candidate. A lot of times, these candidates also might be – maybe he just got his Ph.D. who maybe had a year or two experience before that after undergrad, and he’s also had some internships. He’s really buffed out his resume.
Eightfold’s going to be able to identify that because we also bring in social elements like GitHub. Do they have a lot of followers? Are they committing or doing repos with projects and Stack Overflow? Are they asking or answering questions, and what are they answering questions about? That, I see right here those are major components of what we care about for this particular job opening. As I scroll down, I can see personal info, recruiting activities and emails sent and openings, any notes and also other experience they have. That experience they have, we’ll see these blue boxes. These are actual semantic pulls right from their resume that says they know MongoDB. They know SOAP. They know sales. They know finance, whatever might be that specific skill we care about. This deep AI uncovers these hidden meanings. I, as a recruiter, don’t have to go through resume after resume. I just get these top exact matches that are best for me.
Now I might want to get a bunch of these resumes over to the hiring manager, but we want to promote diversity so we’d like to mask those. I actually can make that happen through sending them over. Let’s just take a look at an example of Ankur here who’d be masked for the hiring manager. Now, I can’t see his actual name, not by suggest ethnicity. I don’t see, perhaps, the schools he went to. Any of this can be masked so that we can make sure it’s based on meritocracy of his experience or her experience in the application process. The hiring manager checks a couple of boxes on the people they like, sends it back to the recruiter who will then continue the screening exercise.
All of this would have taken a tremendous amount of time if I didn’t have this deeply embedded AI algorithms taking care of it. In my morning, I work the new applicants. I work the leads that are actually past applicants that Eightfold has also matched to this. I have my pipeline, people I’ve added there and also those ones I’m actively interviewing. Great. I’ve done some phone screens. I’ve scheduled some face-to-face interviews much more efficient than I have in the past. Now, I’ve got a charter. We have a lot of open positions that will be upcoming in machine learning. Wouldn’t it be great if I could go and send a notice out to those applicants in my applicant tracking system that are passive that I’d like to try to bubble up? We can do that by clicking on ‘new campaign’ here. I select, in this case, I’m going to share a blog or webpage but it could be alumni. It could be a specific opening or location.
This is literally like marking on, embedded right into the system. I’m going to go ahead and grab this great blog post from our site or from another area on the web that suggests our thought-leadership and would target the right people. All of the sudden, you’ll notice here that my target audience went down to just under 11,000. I take that back out again and press return, I would see that number further increase back up. I might want to say, “This is a diversity scenario. We want to target women.” It went from 10,000 to 1,800 now.
Then furthermore, I want to just select a degree like a master’s degree. Now, we’re down to 782 possible passive applicants in our ATS. This is all about taking your existing investments, all of that money you’ve poured in overtime trying to recruit people and hire people and thus bubble those up and engage them for new campaigns. The beauty behind this and what our customers are seeing and you’re going to see here when I drill into a particular campaign that’s already run, I see the number of sent campaigns. I see the opens.
On average, our customers are seeing over 50 percent open rates because of this deep matching of how we parse the content of that blog post that I showed and matched it to the right people in my applicant tracking system. I can further see what that email looked like, the audience deliverability of that email and ultimately the recipients. I can see how engaged they are like Nicole here, two opens and 20 clicks and also Nivien and Michael.
I’m going to go ahead and share these right now with the hiring manager and let them know that these look like awesome applicants from previous attempts to get them on board, so let’s go after them again. Now, all of a sudden, the ability to nurture candidates and do it quickly is not a dream. It’s an actuality.
Finally, let’s go take a look at the internal mobility where I am in the sales department. I’m looking are there any positions that are relevant to me? Here we go. It has predicted that I’m ready to move for up to a director of sales role. I can drill into that, look at those particular jobs or job or even look at other jobs that might be of interest to me, my applications, my referrals so I can take a resume, upload it. There may be hundreds of openings. It doesn’t matter to me because Eightfold will automatically match them for me. Career planner, I can find mentors within my company as well as projects that might be of interest to me that I would want to improve my skills and so forth.
Now, finally, I also might be an administrator in the HR department. I can come in here and look at people in our organization and come down here and say, “Who is a high attrition risk,” people that have perhaps been in positions too long. Thus, we want to make sure that we retain this talent and keep moving them forward. I can look for those and be proactive. Thanks to the matching identify their career trajectory as being an opportunity for us to improve. As we look at this, the candidate experience, the sourcing, and screening, this wonderful nurturing and employee mobility has this deep AI matching to drive tremendous efficiencies and ease-of-use for all those involved in the process. I’ll kick it back over to Mihir to finish up.
Mihir: Jason, thanks so much. I think you touched on some key elements that Amit covered during the earlier part of the presentation in terms of challenges and opportunities. I’d love to kick it back over to Amit with a couple of questions from the audience. As we talk about AI and just broadly as an industry taking over key functions or key parts of our daily life, a question that came is will AI replace humans? Then he says broader than necessarily just recruiting, how do you think about AI versus a person ally?
Amit: I think it’s just a silly thing that gets a lot of interest. I don’t think we are anywhere close to AI being anything but an extremely powerful tool to help everybody realize their further potential. As this society moves through more technology, there’s always some jobs that get replaced with some other jobs. Throughout this, some people feel the pain. It happens with automobiles. It happens with an industrialization. It will happen with AI as well. I don’t think that we are moving towards a dystopian world or anything like that.
For example, my company at ThoughtSpot, what we do is that we make – we enable anybody to be able to integrate their data. This used to be not possible before for most of recruiters. They relied heavily on Atlas or people who – so there’s all those questions of what’s going to happen to my job as we deploy ThoughtSpot? Time and again, what we have seen is that these people actually get promoted when ThoughtSpot is deployed. Instead of doing the tactless job of repeatedly doing approach, then they’re doing higher-value things. They drive more value for business. That’s a base for them to get promoted to higher responsibilities.
I think similar things is going to happen with recruiters as well. They will just make a recruiter a lot more valuable to the atomization and a lot more effective. They will be able to source more candidates, choose more candidates and be better at the job.
Mihir: The human element you talked about earlier and AI is a tool to help recruiters spend more time with the right candidates, that is actually probably a way to hone that in a little bit. Tools like this should help them scale. When you think about how you direct your recruiting team through the growth and you talked about diversity earlier now, another question that rolled in was how do you think about AI for diversity? Does it promote bias, or does it actually help with diversity? Can you talk a little about AI in the sense of –
Amit: AI is like a power tool. You can create beautiful things with power tools, and you can create a destructive course in power tools. You have to know your tools, and you have to direct it in the right direction. There is a case to be made that all that if you’re feeding to your AI engine is people look a certain way or come from certain colleges, the AI will learn the same thing and reduce diversity. They will be progressing that. It doesn’t have to be a reason to stop using the power tools.
Mihir: It’s interesting, as you said, I think that analogy is particularly cogent. A tool is only as good as the operator and then the direction that you’re pointing it. When you think about recruiting and the next phase of growth for ThoughtSpot, how do you communicate some of those changes of what you’re hoping for as you continue to grow from a recruiting perspective?
Amit: Right now, I think I’m not seeing anything else change other than scaling in recruiting. With scale, you have to change your operation. You’ve got to change the structure in which you recruit. The kinds of people you will recruit, the quality of people doesn’t change. The other thing that changes, at this point, we have enough named recognition and brand recognition that more and more people want to come and apply. There’s a lot more candidates to go through. There’s a much larger pool, and so you need to be more efficient with that. Other than that, I’m not seeing anything change.
Mihir: As you talked about scaling operations, you either scale with people or you help people with better tools. As we come to the end of our time here, I think you’ve touched on and have frankly gone deep on a few things that are core challenges for recruiters across the spectrum be it sourcing, screening through the funnel and then internal mobility use. You talked about the entire spectrum. I found this to be an incredible learning opportunity to understand how you go from an early-stage company that is fighting, scratching and clawing to get the next piece of talent to how do you now harvest a lot of that coming in. I’m looking forward to having future conversations to track how you’re managing and scaling that growth. Hopefully, it’s not a linear scale with people that process as you go from a few hundred to a few thousand to maybe a few hundred thousand in the future.
Thank you so much for your time. I know it’s valuable. We found it incredibly enlightening. Audience, I want to thank you so much for your participation today. This is the second part of a three-part webinar series. Please, tune in tomorrow at 10:00 AM. We’ll cover the third piece of content. I’m excited to continue this series. Amit, thank you, again, so much for your time.
Amit: Thank you. It’s been fun talking.
How AI is Changing the Recruiting Process
Mihir: Hello, and welcome to the first of a three-part webinar series focused on innovating the candidate experience. My name is Mihir Gandhi, and I am the Head of Marketplace Operations at Eightfold.ai. As a hiring manager for nearly two decades, souring, hiring and retaining talent have been essential themes in my career managing at a hyper-growth company like Lyft where I was the first general manager for their Flagship region in northern California. I’ve acutely felt the pain of hiring rapidly and hiring right. I’m thrilled at how Eightfold’s addressing these challenges and so much more. Specifically today, we are diving deep into strategies for recruiting and talent acquisition and how AI is changing the recruiting process. We are joined by our esteemed guest, Ashish Mediratta from Tata Communications and has a robust content to cover with regards to how Ashish and Tata Communications approach AI and talent acquisition.
First, a little bit about Eightfold. At Eightfold, we have created a talent intelligence platform for enterprises that leverages artificial intelligence to hire, engage and nurture talent. Talent-centric applications built on this constantly-learning platform enables enterprises to manage their entire lifecycle from prospect to candidate to alumni. With over 100 customers including Tata Communications, AdRoll, Hulu, Grand Rounds, Nutanix and more, Eightfold has helped companies vastly improve their talent acquisition, talent diversity, and talent management capabilities.
Historical Legacy products like ATSs were developed to replace tracking paper resumes and as such provide very similar workflows. The now ubiquitous, onerous online application processes that companies require from applicants is unduly hard on both applicants and companies replacing paper problems with digital ones. Eightfold was born in the AI era specifically to address and solve challenges with employment in today’s society.
More information than ever is being communicated about jobs, companies, and candidates. These reside on job boards, career pages, social profiles, professional profiles like GitHub and Dribble and many, many more. And companies have more information than ever in their systems. They have ATSs, HRISs, CRMs, et cetera. Of course, hiring managers have specific visions as to the skills and experiences that they are building on their team. More data isn’t necessarily better. It just means there are more places to find different information and try to cobble together a more holistic view of a candidate.
Is it humanly possible to take in all of these data and identify if candidates fit or their potential to excel in a role or their career trajectory let alone doing this for thousands of candidates across hundreds of jobs? This is where Eightfold’s talent intelligence platform comes in. Eightfold was designed to improve the lives of candidates, of recruiting, HR, hiring managers, employees and alumni. It both aggregates and digests these data marrying internal data like your ATS with a plethora of sourcing and recruiting tools you could be using with externally available information to create an enriched talent repository. Eightfold’s tip platform uses these data to help surface what candidates are good at today and what they’ll be ready for in their next steps in their careers. This drives better talent strategy and execution.
Once the Eightfold platform has ingested robust data from Legacy and public profiles for each person and created a rich profile of each candidate, Eightfold calibrates each open role according to the specific needs of the organization, drives improvements for recruiters and hiring managers’ intake experience, provides an instant pipeline of qualified candidates, improves the overall candidate experience, improves your employee referral experience and, of course, drives retention to improve internal mobility. After our discussion and before our Q&A, Jason Gray, Eightfold’s Director of Sales Engineering, will give us a brief demo to bring these words to light.
A quick example of one of our customers, Hulu was using a host of tools to assist recruiting such as Jobvite, LinkedIn Recruiter, agencies, job boards and sourcing tools. They were also receiving more applications than their team could keep up with. Given their hot growth, the volume of applicants and the number of tools they were using, the Hulu team found that highly qualified candidates were slipping through the cracks. Hulu then implemented Eightfold which aggregated data across all these tools and sources. Hulu was then able to have a single view on their entire talent network. On average, recruiters saved four hours per day and quickly stopped using in-mail because their talent pipelines were full of highly qualified candidates.
The next example actually comes from Tata Communications. We’re going to go ahead and skip it since we have the source of truth from Tata Communications with us here today. As I mentioned earlier, Jason will be giving us a demo of the Eightfold platform before the Q&A. For now, let’s get into our conversation. I’m very excited to welcome our featured presenter, Ashish Mediratta. Ashish joins us from Tata Communications where he is Head of Global Talent Acquisitions and the Associate Vice President of Human Resources. With nearly two decades of experience in the talent space, Ashish has held leadership roles in esteemed companies such as Wipro, DennPack, Nokia, and Huway. In today’s conversation, we’re looking forward to hearing how Tata Communications is innovating the candidate experience and how Ashish is using AI to turbo-charge internal mobility in recruiting capabilities. Ashish, welcome to the webinar.
Ashish: Thank you so much, Mihir. I’m truly excited to be here.
Mihir: Great. I understand you had some slides prepared, and you’d like to walk us through.
Ashish: Yes, for sure. Before I start off, a quick one minute about myself and my organization. I’ve been well over at this organization for almost two years now. Wow, what a phenomenal journey it has been in terms of AI. Tata Communications is a $3 billion organization. It’s part of the Tata group which is having more than 100 organizations. TCS, that means one of the better-known brands of the Tata group.
When I look at the page that’s in front of us now, what have we really thought of? What have we realized from the current acquisition function? We gave ourselves this acronym for ROADS which is standing for real-time, on-demand, quickly online, do-it-yourself and social media-enabled. This has been our real sense from the thought behind our entire talent acquisition strategy. We have been using a design-thinking approach where we have retaught our processes current perspectives of the hiring managers as well as the candidates.
The last in our part has been the recruiter. What we look at is can we have an optional everything in our process that makes the role of the recruiter king in the future to a large extent? I would realize our recruiters as becoming talent acquisition business partners from the guys who understand the business so well. They are actually marketing the organization and these areas. With that perspective – can you hear me?
Mihir: Yes, we can hear you.
Ashish: Okay, great. One of the things that – the first point that struck people when we talk about AI in the recruitment world, what will the recruiters do? In fact, recruiters in my own team asked me this question, point-blank, when they saw the presentation which is going to follow in the next few seconds. My only answer to them was, “Folks, what we are going to create now is probably going to be one of the earliest things done in the industry. If you are the ones who are the early adopters of this technology, rest assured, your CVs are going to be so powerful. You’re going to be hot properties in the market.” Trust me, two years down the line, what have I to show? Maybe one or two attritions in a team of 30. Again, nothing much to regret on that in terms of the top talent being lost. No, none of that sort. I’m pretty happy with what we have as of now. I think let’s move to the next one.
This page, as you see here, I think this is the heart of the engine that we are driving. On the left-hand side, you see it says new job acquisitions list. How can we imagine an auto-sourcing engine? Then, we have a profile pool just having internal jobs, market applications. It’s got our own database and employee referral. All candidates that we are getting to job boards, agencies and to social media, how do we enable an engine that is smart enough to reach out to prospective candidates? In the coming slides, we will show you a few samples of the areas where we’ve actually grabbed the coat on this one.
In fact, that makes me truly, truly excited that, yes, we have been able to make a paradigm shift in some of these areas. The next slide being auto-cleaning up profiles, again, thinking about how do we get AI to look at the social fitment and the cultural fitment of a candidate to the organization? We’ll talk about that as well.
The next piece being auto-assessment. Can we have an engine which is smart enough to read the job description and then decide what kind of assessment from the pool of assessments that we have in our organization that it can administer those assessments automatically to candidates? With that perspective, we are talking to our own internal IT team to get that platform where all these assessments can be picked up by AI and administered to candidates.
The next one that you see here is a pre-screening video interview. There are many and more solutions out there which are offering pre-screening videos, simply and straight-forward. All along that we would noticed we have mentioned notifications to candidates. We want the system to keep engaging the candidates all throughout. Imagine if you have a database having 100,000 resumes which are possibly even six months, one year or two years old can we have a smart database with a notification to candidates that, “Ma’am or sir, it’s been almost a year since you interacted and shows you’re- learning or some new certifications, et cetera. We would be happy to have you upload or share with us your latest profile.” Imagine the impact that it causes and the amount of peace it provides to candidates and to us.
The next piece that we see here is an auto-scheduler. Again, that’s to be much- these days. I think we can move to the next slide, please. I mentioned to you a little while back about auto-sourcing. The first, the bar you see over here, the first two IJP which is internal job posting, as we call it, for our internal market. Up here, I think this is where we have done the most significant change for our organization. Actually, I can say we have turned the paradigm upside-down.
Up to now, what happens in most organizations that at least I’ve come across in my career is that employees have visibility to jobs in the organization. However we ask the employees that a job came by my friend, and he did not apply for it. Though you were entrusted in this, what happens? They’re going to say to you, “I was on vacation,” or, “I was not well for a few days. I just didn’t get a chance at all. I was so busy. I had no chance to look at the internal job market. I happen to lose on so many job roles.” It’s always the focus has been on employees to go on a hunt on their own. That’s where I think using this AI from Eightfold, I think we have made a complete paradigm shift.
The algorithm, now what it is doing is it is taking a look at the profile of all employees. The moment a new job acquisition is raised, the algorithm matches our employee database. Those are for them who are available to apply. We have known around having been in a role for 18 months, et cetera, et cetera from very basic availability criteria, the algorithm does the match, the criteria. Basically, those employees who are the best fit will get notified by the algorithm.
Of course, the employees need to log in for the first time and set the other logins. Having done that, they can be rest assured that the algorithm is going to be hunting roles for them in the organization. It can always be argued that is this not something like internal fortune. But that’s the way we have positioned it in our organization that we are trying to replicate the external job market situation. There are agencies outside who would not take our permission to reach out to our people and offer them options. That’s where we want to turn the paradigm that hiring managers now know that, their people, if they’re not happy in doing what they are doing, then the organization is having a platform to allow people to navigate internally within the organization. The same benefits applies to them also. If they are getting tangled in their role or it’s been too long and they’re getting frustrated, the same benefits and teachers of this tool can apply to them. With this approach, I think we have just changed the paradigm completely.
Take the next example. It’s called a TC. I’m sorry for the language here. It’s called Talent Cloud. That’s our internal language. I’ll probably change this one before sending it back over. Employee referral, my experience, again in organizations, has been that employees reach out to HR folks. They reach out to hiring managers requesting them that, “Please see if you can do something for my friend. He’s a great person and fantastic experience,” and all the good stuff. However what happens in real life is, with that at least, that the algorithm is now suggesting the best jobs to employees from the CVs of their friends and relatives. They no longer need to chase after anybody in HR or with the hiring managers requesting around, no need. You just upload the resume of your friend, and that’s it. The algorithm does the rest, to you and to your friend, what should be done.
Coming to the next slide that’s on this tray now, it talks about auto-screening and social profiling. Here, as you again look to the right, we’re talking about a masking feature. Now, as an organization, we, as Tata Communications, pride ourselves on diversity. The challenge for us or the target for us this year is to hire 35 percent diversity globally.
Over here, how do you ensure and this is a perception that’s carried by our CEO, how do you ensure that there is no bias at the very initial stage of the screening process? Then, the recruiter has submitted resumes to hiring managers. How do you ensure that they’re not getting biased? With this feature that we have from Eightfold, the algorithm is actually masking the profile, the CV really and the photograph, mail ID, LinkedIn ID. Everything gets hidden, even the pronouns are hidden. The hiring managers are now being asked to do their shortlisting based on the merits of the profile that they see, skills and experiences. Part of them looking at the name or the photograph and then trying to figure out what they ought to do next. I think, again, a huge thanks to the Eightfold team for doing what they have done.
Here’s a sample of a normal profile that a recruiter would see. Go to the next page, please. This is the masked profile. There’s the photograph. All the good stuff is hidden. Now, the hiring manager needs to make a decision. I think this is being appreciated by our top management as being a real, I would say, radical change from the past. The next one, please.
This stage, I think, is the one where we talk about the benefits to our employees and to the managers regarding the usage of the new internal job market platform. The benefit to managers is that they don’t have to do much. The algorithm is matching the best of internal employees. Those are the digital notifying them. These profiles are now also visible to hiring managers. Then, these employees have applied for the job. They get to see and also match ratings as to what the algorithm’s getting. To the right side of this page, as you’ll see, the benefits that we have accrued so far in terms of diversity, we have seen a big jump by five percent already. We are going for more. When you see our offer, instantly, that’s how many offers are being made in the stipulated number of days.
Our target was 80 percent. We went on to 84, 85 and now 87 percent. This was probably around the highest points that we have reached. I think in terms of the advantages that we are seeing for niched skills especially on high-technology areas, I think that’s where we have seemed to grab the coat. The kind of calibration that we have achieved with the algorithm with the profiles that we see that is a huge, huge benefit to our recruiter. Mihir, over to you.
Mihir: Ashish, thank you so much. I specifically love the way that you framed the internal mobility of your own employees as Tata, as a whole, having an internal marketplace. I think that resonates especially in the HR and recruiting front where talent is so difficult to come by. We have such a deep focus on recruiting. The retention is really as, if not more, important to ensuring that you have the right talent in place. Thank you so much for walking us through that.
What I’d love to do over the next few minutes is maybe just a few questions for you, Ashish, to help us understand a little bit more about how your operations work at Tata. You guys have a massive organization, obviously a great brand name and incredible product. Why were you motivated to improve talent acquisition and talent management at this time?
Ashish: We look at talent acquisition and talent management as two of the most people-intensive areas. In our quest to improve the stakeholder experience while dealing with HR processes in the organization, we feel that the greatest impact we can give to our employees is through technology interventions.
We live in an organized world. I can’t, frankly, recall the last time when I tried to hail a cab on the roadside. The cabs and the cabbies, they end up locating you and very, very quickly. We are literally taking our HR services to employees rather than them having to go looking. I think that’s been the essence of what we’ve been trying to do.
Mihir: As you do that, how do you think about refining your current processes versus moving to an AI-powered solution? Help us understand the decision to move to AI versus maybe existing or Legacy solutions.
Ashish: Our Legacy systems, as most organizations would have in the form of ATSs, we already have success factors that we use here. Other organizations have Taleo and a host of other products. What we believe or hear is that our technology is not replacing humans. It’s merely improving the quality of work that’s been put in by recruiters and HR personnel. We are basically automating the time-intensive or redundant tasks. We are taking this ideology further.
AI is not only automating our processes in our Legacy solutions. It’s also going to impact the decision-making of our stakeholders. I can give you data and facts. About a year and a half back, we, as an organization, were recording one offer on a base of 12 resumes which is now down to one of six. That’s significant in terms of the time and the effort that people are saving. It’s for recruiters, most importantly the hiring managers. They’re able to get people faster, better and that’s what really counts.
Mihir: It’s great to hear you talk about AI as an assist for human capital and human power. With the number of AI solutions out on the market today, why did Tata ultimately choose Eightfold?
Ashish: That’s an easy one for me to answer. You have a great product that is loaded with functionalities. On top of it, you have a strong leadership at the top level that is driven towards innovation. I can vouch from personal experience how these customers can pick people. They are very, I think, able in delivering a product team who are very understanding and responsive to customer requirement. I really hope that other customers that are working with you, they have a similar experience. There will always be challenges. They will be largely to do with making customizations on our existing Legacy system. I’m sure that’s one apprehension everybody would have. That’s where I think the Eightfold team has swung the needle.
We have another organization with which we have tried the AI-based solutions. Honestly, I do not like to name over here on the platform here. We found that the integrations with success factors as a big thing. I was not working at all. This is the first thing that we had a chat with the top leadership of Eightfold from around March 2017. Within a month, we are actually very, very surprised to note that they had integrations done and complete with the successes while we were testing and calibrating on the product entirely. These things gave us a lot of confidence that we are dealing with the right people who are very like-minded in terms of creating something new for the future and extremely responsive. I think those have been the clinkers for us.
Mihir: Great. Thanks so much, Ashish. I’d love to jump into another question. Before I do that, I’d love to also ask the audience. Some of you have already typed in some questions from the audience. We’ll be doing Q&A a little bit later in the webinar so just a reminder to type in your questions, and we’ll get to them as we can with Ashish at the end of the presentation. I want to move and touch on something you talked about a little bit earlier, Ashish. You mentioned that HR team feels that AI is a solution and an ally. I think we’ve also heard from others that, perhaps, this can be a threat and potentially eradicate some of the roles within the HR sourcing, recruiting functions. Can you talk a little bit about how your HR team feels about AI as a solution, as an ally versus a threat?
Ashish: Sure. I think that’s an easy one, again. For us, there has been unanimous acceptance of the AI-driven solution in both the HR team as well as the talent acquisition team in particular. What we have seen is that the quality of work, the quality of outcomes and stakeholder experiences are getting better with these solutions. I suspect that in maybe five years’ time, literally, every organization will have solutions of this nature. I think that’s what I am also emphasizing in our team here that being ahead of the curve from the industry while creating solutions and services of the world is just going to enhance your own credentials. You’ll be the early adopters, have a strong resume. Maybe you’re the ones that are going to help other organizations evolve. That’s been an easy one for us to motivate our people.
Mihir: Thanks, Ashish. I love the way that you frame that. I want to go back to one of the things that you touched on earlier in your presentation where you talked about internal mobility and viewing Tata’s human capital and talent capital really as an internal marketplace. I also love how you framed that outside recruiters won’t hesitate to contact your own employees, so why shouldn’t your own team be able to do the same thing? Can you give us a little bit of a sense of what the Tata employees say about the internal mobility capabilities and opportunities and the impact of internal referrals on the organization in the past year?
Ashish: Before I go there, I’ll give you some data points. Almost 28 percent of our entire hiring happens through internal mobility. This is one data point that gets reported to the board on a quarterly basis. That’s the, I’d say, important and seriousness given to internal mobility and internal careers for our employees. Given that as a background, it’s been very easy for us to implement the mobility solution. It’s easier now for employees than ever before to view the relevant opportunities for themselves. It’s easy for them to keep track of the status of their applications. This was a huge pain point earlier. There are so many employees taking part in the internal mobility process. How do you just keep them informed of what’s happening? At what stage are they in the hiring process? That’s getting done by the system now.
They get to know more about the opportunities and the people they would get to work with along with the job description. They get to see that and I think most important to be proactively informed about any new developments regarding upcoming opportunities that feed their aspirations. With this, I think AI is working with employees enabling their career growth. We are getting some very good feedback from employees for this specific solution and likewise for referrals. We want to really follow up with anyone to seek the board for CVs of your friends and relatives. You can be assured that the relevance – they will search for relevant profiles and match them with the jobs that are being created and keep you and your referral candidates notified. I think that’s the beauty of the solution.
Mihir: Ashish, thanks so much for this. I feel like we could go on for a long time. I know we’re just scratching the surface. There’s actually a lot of blood, sweat, and tears that go into not just implementing the solution but the process and operational changes that you and your team have put in place to enable this kind of a transformation. I’m sure that we will have many more opportunities on future webinars and panels and certainly during our Q&A later during this webinar.
Right now, I’d love to turn it over to Jason Gray, the Director of Sales Engineering at Eightfold, to give us a demo of the Eightfold platform, a bit more tangible examples of how Tata and others have been using the Eightfold platform. Again, I’d love to remind the audience to continue to pipe in some questions. We’ve got some great ones loaded up for Ashish right after the demo. I’m looking forward to jumping back into that dialog, Ashish. In just one sec, we’ll jump back there. First, Jason.
Jason: Thank you so much. Thank you for having me and thank you, Ashish. I’m going to jump in right into our screen here. You’ll see my browser where I’m going to upload my resume. Three things I want you to take away from this is one, how this deep matching and natural language understanding improves the candidate experience, the recruiter’s experience as well as the internal employees and referrals and then, finally, how this with deep matching and so forth drives these efficiencies and what not. As a user, as a candidate, I can come onto a website. Rather than searching across thousands of different opening positions, I can simply upload my resume.
In this case, I’m going to upload a software engineer resume. Automatically, the deep matching looks at my resume and the job descriptions and the calibrations from Eightfold and predicts what’s best for me. These predictions are really key through our semantic understanding. Now I can see software engineer, that’s what I do. I love that. Solutions engineer, that’s more forward deployed. Because I’ve been customer-facing in the past, it probably will recognize that. Senior data engineer, actually I’ve got a little bit of data science in my past. That’s a priority hire.
Finally, product manager. I did do a little product management and liaison stuff in the past. These predictions are really interesting for me. As a user, I already know this. I just know that these are great matches. I’m going to apply to these two positions. Automatically, I’m going to get a thank you. I’m going to get also other data like what great blog posts relate to my position, what team members I might know at the company. It really streamlines the experience for the candidate. The recruiter, now on the flipside as we go to the recruiting view, I can see all of the positions that I am owning as well as a nice feed of updates around those positions that I’m actually working such as software engineer. I can see that I’ve got recent applicants, leads. I’ve saved a pipeline, one that shows AI as the top 30 percent senior software. We’ll talk a little bit about that in a moment.
Then, two, likely to respond and 26 new leads. Because there are certain individuals who have been in a position a real long time or maybe they’ve moved fairly quickly in terms of their trajectory, Eightfold exposes that so that I know those would be good people to go after. Then, I drill into this now. I’m actually going to see all one view. I no longer have to go and spend hours upon hours on job boards, you know the names and try to find applicants until my eyes bleed. I can see them right here in a five-star matching mechanism through Eightfold that shows me their overall relevance, their skills, their title, ideal candidates that we’ve targeted or calibrated this role that may be an employee or maybe someone outside the company that we’d love to have.
Let’s find similar people, school, work, experience, all very important. As I look through this too, I might also have a scenario where now I’ve got a very skewed team to men. I’d like to really target women, so I can filter on that and look at the diversity there. There’s also unconscious bias smoothing. What I mean by that is perhaps I’m a recruiter that is always going after engineers. I always go after ones that, perhaps, graduate from Stanford, Berkeley or MIT. Now, I may not notice that top Canadian school like Miguel in Montreal or top agent school in China or India. Those are now identified as very similar and ones I should go after. Taking off this diversity element, I can now also drill into these individuals like Ankur and see what is it that makes him such a great fit? He’s got eight years of relevant experience. That’s not just total experience but relevant experience. He’s also top 30 percent in senior software engineers. Well, what does that mean? Well, this candidate took almost four and a half years to reach this level compared to the peers that took six. He’s an overachiever. That’s great. Sometimes, these resumes are padded.
Let’s go out to the public data like GitHub and Stack Overflow and see are they contributing to these projects, open-source, et cetera? What kind of answers and things are they doing on Stack Overflow? Wow. There’s a lot of great elements that they’re truly active participants. This drives a tremendous amount of engagement for me to go after this candidate. I can see all the recruiting activity, personal information if we want to show it. We start to see all the matching mechanisms in these blue boxes where Eightfold semantically pulled out the right matches from this person’s resume against the job calibration. Also, too, I may be interested in actually sending this to the hiring manager or perhaps even a recruiter should have a masked profile. I don’t see their actual name and ethnicity. I don’t see their personal info. I don’t see the schools they went to. It’s strictly based on merit, and that’s really key. This is a quick demo, so we’re going to keep moving on here.
We also look at campaigns and nurturing people. How can we do deep matching and leverage all those existing applicants we have in our applicant tracking system, 140,000? Now, I can go and actually grab a blog post from our website or somewhere else and say, “I want to target these applicants that are passive.” Matter of fact that reduces 140,000 to 10,000. I may also say this is a diversity element back to the fact that we’ve got a skewed male team. Let’s go after female. That’s 1,800 applicants. I can continue to add additional elements to refine the audience including ATS information from that ATS integration to any ATS that you may or may not have.
Ultimately, what this means is that we’re targeting people with this great matching of parsing the blog to who they are. We get these wonderful open rates, 50 to 70 percent. I was in market automation many years past, three to five percent open rates were amazing. Well, 50 percent open rates for a recruiter is astounding. Now, we see that engagement by the cities, by locations. We can see the recipients and how many opens they have. I can go ahead and checkbox and say, “You know what? I want to go ahead and share these people with my hiring manager right away and get that started.”
Finally, to close out, when we look at internal mobility, I can come in and see what jobs are right for me automatically matching me to those specific elements. In this case, if I am under HR and I have admin privileges, I also can see who is a high attrition risk because we want to go after those people and make sure that they find the right career path. They can go to the career planner, find projects and/or openings and/or mentors that best represent what the matching sees in it for them, a whole variety of matching elements. So to remember here is driving a great candidate experience, a great recruiting experience and allowing for those internal mobility and a self-service model that makes it disarming for anyone to get involved with. With that, I’ll close out. Hopefully, this has piqued enough interest. Reach out through the website to the sales department. We’d love to do a deeper dive demo with anybody. I’ll kick it back over to Mihir to finish this off.
Mihir: Thanks so much, Jason. I really appreciate that overview. Just as a quick plug on the website, it is Eightfold.ai. Please, feel free to go there to learn a little bit more information about the Eightfold product. Ashish, we’d love to jump back into a couple of questions that the audience has asked of us. Do you have a few minutes left before you have to head back to your duties?
Ashish: Yes. Please, go ahead.
Mihir: Fantastic. Where we dropped off just a second ago before the demo was around the operational challenges that your team has faced. Can you describe how you actually address those operational challenges and how you prepare your team for changes like implementing new tools to drive adoption to actually move the organization forward?
Ashish: Great. Like I mentioned earlier, challenge number one for us was the integration with the existing ATS that we were using. The next thing for us was to do customizations. There is an existing tool, and we want to bring in new changes and functionalities. In some instances, what we are doing is, for example, for the masking tool, we have practically migrated our hiring managers onto the Eightfold platform to basically look at the profiles, give their feedback and then do the process practically on Eightfold.
For other parts, for example, the internal mobility piece, we are using the auto-match functionality very well and the triggers and the tracking. We have literally done a huge amount of customization. I think that’s been the clinker for us with Eightfold, the flexibility that’s shown by the product team and delivering team to make changes and do them very, very fast. In terms of our recruiters, the experience they are able to provide, I think we have also tried to drive their behavior with the help of incentive.
Almost 15 to 20 percent of their benefits and compensation is in the form of variables. We have made adoption of technology and deliverables. For example, I mentioned to you about conversion ratio. That jumps from zero to 12 then an offer from 12 resumes down to one offer from six resumes has been a big thing even for our recruiters. We give them benefits for their performance toward diversity. We run programs like the star of the month and the champion for the quarter for diversity. We are basically trying to model their behavior and make superstars out of those who are doing the best of things in the interest of the hiring managers, of the employees and of the company. You are rewarding the right behavior, and we are seeing good results.
Mihir: Ashish, I think it’s a novel approach. It dovetails very nicely with the way that you talked about the future vision that seems to be being realized as we’re talking of the recruiters and HRBPs as true business partners that are helping move the organization forward and really be ambassadors for the organization both internally and externally. Part of the process of doing that is building massive trust with the hiring managers. Can you talk a little bit about how AI tools have helped your – and some of the processes and operations and innovations you’ve talked about have helped drive some of that recognition and trust from the hiring managers with the recruiting team?
Ashish: Very early in our hiring process, we hold that this company calls between the hiring managers and the recruiters. What we did was almost a year ago, we started having our recruiters to make a demo of the Eightfold product to the hiring managers. What happened actually on the ground was they realized that their job descriptions was usually gibberish. Then, they started playing with the job descriptions on the Eightfold platform. Then, they realized the power of every single word that they write.
Usually, in almost a two-page job description, maybe three lines are absolutely critical to the hiring manager. That’s where in that experience of discovery call, they realized that those three lines were produced so beautifully and clearly crafted by them. We could show them the change in the profile, before and after. I think that’s where the conviction spread in the organization that we’ve got the right product. The quality of CVs that they were receiving, the calibrations on these profiles, those were the big difference in driving the behavior of hiring managers, two words, Eightfold.
Mihir: Ashish, I love how you called job descriptions largely gibberish. When I suffer from bouts of insomnia, I generally open any careers page and start reading through job descriptions. I find that seems to solve my insomnia much faster than any other type of natural or herbal remedy. I think we share a similar version for that. Ashish, I think with that we are running just short on time.
I want to thank you so much for your time and your insights, your valuable guidance on how to really change the process and operations within the organization and use tools such as Eightfold and others that you’re employing to drive that forward. I personally found this really enlightening. I learned a lot from you. I’m looking forward to not only working with you as a partner but also learning from you and helping drive Eightfold products sweep forward to help more customers with their recruiting and retention capabilities.
Ashish: Great. It’s been a pleasure and honor for me to be on this platform. Thank you so much for this opportunity. If there is any way I can be of help in the future to any of our colleagues who are listening in, you can reach out to me over LinkedIn and I will be happy to help and learn from you. I look forward. Thanks so much.
Mihir: Thanks so much, everyone. This concludes this webinar. Please, tune in tomorrow morning at 10:00 AM Pacific for the second of the three installments on this webinar series. Thanks so much.