Praneeth Patlola: okay. It says we are good to go.
Praneeth Patlola: Awesome. Can hear us okay. We are on.
Praneeth Patlola: We'll just give another minute here for people to jump in and out. I'm pretty sure they're jumping from one session to another, but that gets it started quickly.
Praneeth Patlola: Well, thanks a lot. Three of you for joining us on the session, I'm pretty sure we'll have some fun here.
Praneeth Patlola: So, why don't I go ahead and start kicking this off at a really high level introduction, and then we go around the table kind of kicking this off. I think this is the most important topic of this era, trying to see where we are. So I think most of the people probably will have feedback, so we'll keep it interactive.
Praneeth Patlola: So just to kick this off my name is Praneeth Patlola. I am the CEO and co-founder for Willhire. I have been a technologist and HR technologies for quite some time building applications to solve talent solutions and talent acquisition challenges and happy to be here. This is my second time at WSS and doing my sixth session, I guess, almost so.
Praneeth Patlola: It's going to be fun and going forward, I have an amazing speaker panel today starting from the top, right? Lindsey Friedman who is with SAP field class. Lindsey is a senior solution advisor for SAP field class. She's been closely embedded in helping several large customer implementations from how do you implement, but also how do you enhance your delivery from.
Praneeth Patlola: External workforce management and also services procurement through global consulting and key practices that you bring in from delivering services to several organizations. And she allows outdoor activities by the lake and having a lot of coffee all day. Hopefully they had one today, lots of coffee.
Praneeth Patlola: And next is Satish. Satish is a serial entrepreneur in the industry as you know, he is a graduate from IIT Kharagpur and he ex Oracle he has built a company in the past in the assessments and K-12 world. He exited and went onto his new venture in solving the problem for contingent workforce. So it brings not just industry experience, but solution experience for a very long time solving assessments as a problem, which is one of the critical elements.
Praneeth Patlola: I think we'll talk a lot about today. And then we have Vik Karla, who is the CEO and founder for Mindlance. One of the top companies around in our space are suppliers and ViK. I know, I remember meeting Vik a long time ago in an SIA conference where he was one of the sweetest guys talking about always having a positive impact in the CWS industry.
Praneeth Patlola: And he's super handons. He has built a very large-scale operation of delivery of talent to several large enterprises in multiple facets and forms. And he's also an active participant and delivers a huge amount of curation services, part of the direct sourcing which is why curation is such an important topic for all of us.
Praneeth Patlola: Thanks a lot, three of you. And I'll give it to each of you. You kickstart this and then go around the table and we'll kick off topic. Lindsey, maybe you can just go and speak a few words and then.
Lindsey Freedman: Yeah, absolutely. Well, welcome everyone again. My name is Lindsey Friedman. You know, I work at SAP field class, and basically every day I work with different organizations across different industries on best practices to manage and optimize the external workforce as well as their services procurement spend.
Lindsey Freedman: So, you know, as Praneeth I mentioned, I'm just really excited for this conversation today.
Praneeth Patlola: Hopefully. Thank you Lindsey. Satish?
Satish Kumar: Hello everyone. Glad to be part of this panel and thank you for your time. So this Satish Kumar CEO, co-founder of Glider.ai a little bit about Glider because we live and breathe the talent quality day in and out. And honestly, our existence depends on this topic. So a Glider is a talent quality and a fraud prevention solution for the contingent and full-time workforce.
Satish Kumar: We are committed to making hiring fair and opportunity accessible, right? We fundamentally believe in competency over credential, which means if anybody is capable, he or she must get an opportunity. Right. And add the contingent programs where cost and efficiency metrics are tracked primarily. We are pushing another data point about talent, quality, and want to make sure as a leading analytics in the supply chain falls in the ecosystem.
Satish Kumar: Now today with Glider, a suite of products, including assessment hundreds and hundreds of agencies, including Mindlance use Glider to vet candidates out with confidence and stand out in the crowd, in fact, more than 60% of the world's top IT staffing agencies believe in later. Right. And not to mention, we want the most coveted SIA shark tank award for the most innovative solution last year.
Praneeth Patlola: Well, satish, which is why you are with me. We are so good at elevator pitches. Yeah. Thanks a lot Satish. You know, as obvious you're super deep knowledgeable in this topic and passion Nate about it and assessments are super highly applicable. Thanks for that, Vic.
Vik Kalra: Thank you Praneeth. I should have probably gone before Satish but either way I'm a student of the staffing industry for the last 20 plus years.
Vik Kalra: And have closely worked with Willhire and Glider. And obviously we are using Fieldglass VMS on many of the programs we support. So glad to be part of this panel and be able to represent the voice of a staffing partner.
Praneeth Patlola: Awesome. Well, thanks a lot for that long table intros back again. And thanks everyone for joining us here in the session as keep promise to keep this as exciting as possible and fun.
Praneeth Patlola: Yeah. Hopefully you won't get bored, but you know, use the chat session here. We want to make this interactive as much as we can so that we don't hesitate to post questions. We're going to take passes through the session and take questions and answer through the group as much as we can. Let's make this as interactive as possible because we don't get to do so much fun stuff.
Praneeth Patlola: Doing all the zoom calls all day long. So. Then, let's go to the topic of what we reintroduced as quality of talent and this, and what it really means in the age of the great resignation, which is a really tough problem to solve for, because when you, there's a huge amount of shortage of talent.
Praneeth Patlola: And with this shortage of talent comes along with the problem of having the right talent to get the right job in the place, which is even making the challenge even go 10 X harder. So I was thinking, why is there so much emphasis on quality. Can we start defining what quality of talent is to start with, and then start addressing several aspects that maybe just go around the table, you know, Satish, Lindsey, Vik, one of you can start picking this up and give your 2 cents around that.
Satish Kumar: Okay. Sure. I can pick this topic. So at the core of talent, quality is the ability of a candidate to be able to do the job with a satisfactory outcome, and that defines the baseline of quality of talent. Now it has two components, right? One of the hardest skills to be able to do the job. And then the another party, the human traits that are needed to succeed at the job.
Satish Kumar: In other words, the cultural fit, right. And these boths have very different dynamics, very different success criteria for both these components, right? For the hardest skills, depending on the job role it could be pretty much black and white, right. Either you have it or don't have it, right.
Satish Kumar: Hence it is more automation as well. Right? The other one, the human traits, is not that much black and white. Right. We try to figure out the fitment with the team group and the organization. And that is why I no wonder we have only very few high performing teams as against the entire company, the reason behind it, because those mix of traits matter.
Satish Kumar: So the point is that all these combined together need to be considered to define talent, quality, and one trend. Probably we should not miss that calibration. Right. We all know that different organizations have different levels of calibration to define the talent quality. And so depending on the job and the role a candidate could be super assigned to one organization and might not even qualify for another because there are different benchmarks.
Satish Kumar: So we need to consider all these things when we define talent. Quality.
Praneeth Patlola: Awesome. Thanks Satish. Anybody else want to chime in to add a few more insights on that? Defining the quality?
Vik Kalra: Sure. I take this to a very tactical level. You know, we play in the contingent staffing world, which is a lot about speed and quality.
Vik Kalra: So from a Mindlance perspective, what is the baseline of talent we represent? Is that the assessment or the positioning of talent we are providing to our client based on the job description, how accurate is that? So for it is up to the hiring manager to evaluate as such Satish said, is the alignment there or not, but to the extent we are positioning that candidate, how accurate and objective is that.
Vik Kalra: So for us, that's the talent quality.
Praneeth Patlola: Awesome. Awesome.
Lindsey Freedman: Yeah. I mean, I'll just add that quality is tough, right? Cause I think it's so subjective. Like, you know, I just think this weekend we, I tried out a new hamburger joint and I thought it was the best hamburger in the world, but you know, my husband was like it was meh.
Lindsey Freedman: Right. So in terms of quality of talent, you know, I think different departments. You know, it's a great exercise to kind of set a benchmark, what you define quality. As you know, I think of a marketing department, they're going to have a wildly different set of benchmarks and requirements than an engineering department.
Lindsey Freedman: And especially, you know, not only I Satish mentioned, not just the competencies, but kind of the soft skills. And if they're a cultural fit, I think kind of defining some of those elements too, is a great exercise to help drive what that measure of quality is for your organization.
Praneeth Patlola: That's awesome.
Praneeth Patlola: That's awesome. And that's great definitions from calibration, hard skills, soft skills and delivering speed with the quality and fulfillment and around that one one, one other thing I'd like to add from my end is really that focus on the cultural aspect of it. I know. I think the past decade and the previous, not the recent five years, but before that we all talked about in HR and HR technology, world culture, as the biggest buzzword cultural fitment was the biggest principles with multiple aspects of tools, technologies built around that.
Praneeth Patlola: And I think a cultural fit meant as a quality is also another aspect. How do you see how you define quality also comes into it, right? And with that, I'm thinking for a while. So these, you raise the benchmarking for it. I think it's interesting because we can slowly move into something much more deeper.
Praneeth Patlola: It's like, when you're talking about this quality, how do we measure this quality? What are the KPIs or what attributes are necessary here to define quality from a data point of view or from a measurement point of view,
Satish Kumar: Sure. So first of all, for this metric to be meaningful, it has to be scientific.
Satish Kumar: It has to be objective. It has to be standardized and it has to be repeatable, right? Once you figure out that they are the core elements of what yardstick we should use to measure the talent that is only meaningful. Wait, now a typical evaluation mechanism for talent quality are through evaluating through screening boards or through automated assessments, or even through live interviews that humans conduct.
Satish Kumar: Right. And in that order for the hiring funnel it covers pretty much all modalities of engagement. Like for example, bot conversation over phone or in an automated assessment over a laptop or a live human interaction. Assisted by the tool in the remote hiring now in all those modalities, those four elements, I said, still need to play a role.
Satish Kumar: Right. And you know what, in some cases we can also derive the talent quality through certain certifications, because remember to opt in that certification, they have gone through a very rigorous evaluation process on their own. So we can take it as a signal towards talent quality as well. Now, when it comes to how to measure it.
Satish Kumar: Right. Remember I mentioned the calibration earlier, right? So, we take the large set of data of candidate performance, and we norm the performance to create the benchmark that ultimately is going to define the stack ranking or the candidate standing. Right. It could be company level. It could be at the world level.
Satish Kumar: Right. And definitely. If I applied that to the soft skill part, it is a very different dynamic because there it's not really no black and white, right. I mean, we can assess the traits of human beings, but how, whether I want that trade matching with my team or not, is a philosophical question for the organization.
Satish Kumar: Right. So even though we can measure it, how we take it could be very different for different organizations.
Praneeth Patlola: Awesome. Awesome. Vik and Lindsey
Vik Kalra: Yeah. So, you know, I think I will just focus on the very tactical aspect so that I can bring the vendor's flavor to the equation. At Mindlance, how we measure performance generally within our contingent labor programs is around speed, quality, race, compliance, and service.
Vik Kalra: So I would add one more, which is coverage. So it's coverage, speed, quality, price, compliance, and service. So now we let's get to the quality part.
Vik Kalra: When we look at the contingent labor talent supply chain, we are looking at a few data points across the flow, which are external summits. Short-list interviews offer premature terminations, which are more involuntary in nature, and then successful completion of the project.
Vik Kalra: So we are looking at all these ratios, performance ratios. What is a shortlisting
Vik Kalra: percentage? What is the interview percentage? What is the author percentage back out percentage successful completion of the project and in voluntary, early termination, which is somebody was let go for performance or some other reasons, right?
Vik Kalra: So now. We all understand, you know, our industry is not the most efficient, so mathematically trying to assign a number to eight, maybe doing a little disservice and the output and the interpretation may, could be wrong. So while we are measuring all of these to look at warning signals of where we need to improve or where there could be bottlenecks or inefficiencies in the workflow when I look at it from an assessment perspective, the one benchmark we use it and then Mindlance, which is more within our own control is the interview to offer ratio, which means I have provided an assessment of the candidate to my client, the hiring manager, based on what I provided, they requested an interview.
Vik Kalra: And then did that interview result in an office. So that's the one we find to be more, most meaningful and within our control of influence. But if I'm the hiring manager or if I'm the client, what would also become very important to me is the premature early voluntary termination ratios and the successful completion of the project, right?
Vik Kalra: When we use a tool like Glider and it was quite interesting, we were looking at our stats for Glider per se. And we found out that our interview to offer ratios where we have used the Glider tool is not 80%. Wow. Right. But that doesn't mean that our overall submission to hire ratio is 80% because there are several inefficiencies on our side of the equation and the client's side of the equation.
Vik Kalra: Right. So the final numbers are much lower. But if I were to just contain it to our definition of quality and objective assessment and look at interviewsx where we used Glider versus where we didn't use a tool, then the numbers are quite contrasting.
Praneeth Patlola: Wow, nice. No, that's I think I think Satish is going to send you some checks
Lindsey Freedman: And I'll just comment, you know, from a VMS perspective, you know, I always say you can't measure what you can't see. So it's always great just in terms of having first visibility until you're into your external workforce to have some sort of technology or a centralized place to have that visibility.
Lindsey Freedman: And, you know, I know, you know, we talked about quality from a candidate perspective and that's important, but it's just as important to measure that quality after that worker is hired. As well as, you know, are they eligible to return to your organization? One of the key things is just having power and having that historical data to know, Hey, I'm at the point of hire.
Lindsey Freedman: Potentially do not rehire. So again, just having that historical data is going to help organizations drive more quality and compliance in their future hiring decisions.
Praneeth Patlola: That's awesome. That's awesome. Much more in depth discussion here. I want to close out those attributes and measure our KPIs around the quality.
Praneeth Patlola: It looks like we have assessments and scoring systems out there, which will enable us to score a candidate using more of an in-depth assessments where Satish you probably have proctoring and several aspects of it, which will also reduce the amount of or increase the amount of credibility around that.
Praneeth Patlola: Along with several aspects, as Lindsey mentioned, the post hire metric which correlates to what Vik also indicated the combination of Glider, but also the combination of metrics assets to the whole life cycle probably has to determine how do you define even the quality of talent, or even how do you measure that?
Praneeth Patlola: But I think one important aspect for us also to keep in mind also is that post hire, as Lindsay mentioned, one of the key things which I experienced which I had a hands-on experience was, especially when you're looking at a light industrial or or even any parts out of a island, which is much more sometimes repetitive in nature from the slots of, because of the dynamic shift the work and on demand based. It's only possible if you have the measurement of quality from a hiring manager directly correlated so that you can repeat that and fill those roles faster, what it will impact is actually the filling of the roles faster, but it also impacts an experience.
Praneeth Patlola: Does the candidate have the right experience to come back? Does the hiring manager have the right experience to bring them back super important? And I think VMs just play a key role part of that because that inflammation of the data recites there and itself, and the assessment data will prequalification also is reusable in nature.
Praneeth Patlola: All this data becomes so much reusable that the time we would address from that great resignation and the shortage of talent, the funnel, which you're generating, becomes so important because the data is available to you. And the more you can build on the data, the more you can do it. It helps us to do that.
Praneeth Patlola: So one key thing we're just thinking was while we are talking about different stakeholders here, we have VMS. We have a staffing side of the business, and we have the assessment side of the business and direct sourcing who is responsible for this because they're not industry. There are so many more stakeholders.
Praneeth Patlola: You have MSPs, you have payroll providers, you have applicant tracking systems, but there's a system side of it. There is the organization side of it that is MSPs who are running or organizations managing a lot of vendor pools. How do you say, where should this quality component be more controlled and residing?
Praneeth Patlola: You can take that.
Vik Kalra: So, you know, this is a topic of deep debate internally within Mindlance all the time. Because what we perceive as good quality may or may not give us the yield we want. And we wonder who is the authority on this? Obviously, the hiring manager is the authority. No questions asked right.
Vik Kalra: And disputed authority, but then who next? And at least our viewpoint right or wrong is the second best person is the recruiter. And when we are talking about anything in Mindlance, in terms of why performance measures are in charge or what is an opportunity to improve, we always bring the recruiter to the room and say, what do you think?
Vik Kalra: Unfortunately, the way our industry is designed, we have too many of us in the middle who tweaked the process and. Making it inefficient in terms of the connection between the recruiter and the hiring manager. So if we can take what the hiring manager wants and use that as a baseline in our design thinking in terms of how we define the workflow, then the fundamental challenge between quality and speed will go away.
Vik Kalra: Hiring manager doesn't really care if you give the resume two days late, but those are quality candidates, right? The concept of shortlisting is not based on scientific evidence. It's based on a lot of individual bias and is, did any recalibration happening from the hiring manager in terms of feedback to the recruiter?
Vik Kalra: So there are a lot of things which are making the process inefficient, but to the extent we can make the recruiter and the hiring manager. Interact in a controlled fashion and have a 360 feedback loop. It will help us tremendously in finding the best available talent in the market and qualities.
Vik Kalra: Basically, you know, who is available, who is interested, who is qualified and who will take the job and will complete the job. If these are the parameters, how do we redesign our workflow to ensure that it is designed for quality?
Praneeth Patlola: Well, I couldn't agree more from a workflow and design thinking approach to apply that overall.
Praneeth Patlola: But I think there's a lot of stakeholders. You have to come together to create a process of automation and a mechanism, which is also supposed to be a bit more of an open communication and data driven. And one thing I think I do almost in every call when I want to, is why it is not working in this workflow, it's, there is a lot of blame game.
Praneeth Patlola: Look, I don't get a response in time. The candidate is gone on the other end. We give enough responses, but we don't get the right ratio from the recruiter. I think it's a constant battle in our industry. We keep going towards, but still from what you indicated, yes, we do need to think through a different lens from an industry point and rethink and there are several aspects.
Praneeth Patlola: I think most of this kind of is formulating much more indirect sourcing. Because the interactions with the hiring managers are much closer in nature. They're a bit more vested. Enterprises are more vested within that process, which enables also tools and VMS as an assessment place, all combinedly to address that workflow process and allow the part of design thinking, because that's exactly what you do is when you apply design thinking to this multiple fit of the problems across multiple stakeholders, tools and techniques, that's exactly what you end up is in the calling that a hot object as direct sourcing right now, but it's actually a solution to it.
Praneeth Patlola: Great. Satish. I'm pretty sure you have something.
Satish Kumar: Yeah. Vik said that ultimately the hiring manager is the authority, but there are so many touch points in between by the time it reaches to the hiring manager that that delays the process brings inefficiency. Right. But one thing that in the process, why not, we make it more data driven that needs that added here.
Satish Kumar: Why did there disparate sources? Right. And in the Jan thing that we guarded, if we can understand what the hiring manager wants and remember the intent is there to assess candidates, but they don't have time. They're so busy delivering their project, right? It becomes tactical in their nature. So the design thinking I angled that we brought up right now.
Satish Kumar: Imagine we can get that expectation one time from the hiring manager and systems like Glider can really articulate that in an objective manner and have all other participants, including MSP suppliers. Just follow that benchmark. Isn't it better for us, everybody? Right now we do. When somebody says, Hey, I need good quality talent.
Satish Kumar: Well, what does that mean? It doesn't mean anything, but once you translate that I need these skills at this level, coming from the hiring manager. Now we know what it means, and it brings transparency. It brings the sense of ownership that I am responsible to submit a candidate who meets this threshold to the MSP.
Satish Kumar: MSP also gets the visibility that yes, the assumptions coming are passing the benchmark, and everybody is clear and happier having quality candidates submitted.
Lindsey Freedman: Yeah. And the only thing I'll add to, you know, I agree everything with what's been said so far, but whenever I talk to companies about managing external workers, of course you think of contingent labor, but you know, I also stress thinking of the external workers tied to project based work and, you know, statements of work because that's oftentimes called the invisible workforce.
Lindsey Freedman: And so typically in those scenarios, it's absolutely a combination. The request manager working with that service provider, that vendor not only hopes for quality workers, but really is of the outcome. The quality of the work received, you know, was that delivered on time on budget. Was there any rework that's needed?
Lindsey Freedman: And so, that's kind of a trending area that I'm seeing organizations not only wanting to manage quality in the contingent workforce, but also for this invisible workforce. So those external workers are tied to the services procurement spend. So again, that's kind of helping getting that holistic overview and data that most companies don't have today on managing that type of work.
Satish Kumar: So Lindsey wondered if we can really benchmark that staff or pool of candidates and this invisible workforce to see how they fare with the same parameters as in the benchmark.
Lindsey Freedman: Absolutely. Oh, that would be huge.
Praneeth Patlola: Yeah. Yeah. And only the largest sort of new players in the market who don't want to do that because the premium has to go down now. And so they go back to the, to fight.
Praneeth Patlola: But great points. And I think I want to just extend one point on the data side when its comes to things like, yes, hiring managers has this emphasis primarily because they are, you know, have to be unbiased. Also have to be more organized in making an assessment makes that even better.
Praneeth Patlola: But at the same time, I think there are some more patterns we have seen to optimize that design thinking process. Right. So one of the key things from a data point of view, it's like many, a times we look for patterns where we say we like to hide candidates like this, which we passed hired was very successful, is a pattern from a data and a platform oriented.
Praneeth Patlola: I think we can embed that into the process. Many times when I'm talking to a recruiter too, I usually give here is a particular candidate or a list of samples, LinkedIn profiles, or any of that I can give before they even start the search. So they have this thought process of what it is and the pattern matching.
Praneeth Patlola: And that's several tools and techniques in today's world. You're going to make that highly data driven which will enable us to kind of optimize the total process around it. Right. But Tools techniques, processes on multiple checkpoints creates another challenge for us, especially because this is not like this is a talent market.
Praneeth Patlola: This is an extreme crunch in talent while there is so much crunch in talent and resignations and people have this large amount of flexibility to work. And probably one is to nine ratio of offer to candidate. How are you? How do we battle these credentials versus fulfillment? Because you want to fill the role with the shortage of talent, but you're looking for an exact credential.
Praneeth Patlola: How do we battle that? And what techniques do you advise or look for some techniques used in industry to battle the competency over credentials of the talent.
Lindsey Freedman: I can go first on this one. You know, one of the things that I've seen with some Fieldglass customers is they use a feature called resume ranking, right? So it automatically ranks candidates, how closely the resume matches the job description. So, the credentials helps get an interview, but you know, a piece of paper is not a person, right?
Lindsey Freedman: And so there, it requires not only from a technology standpoint, making sure this candidate meets the requirements for the job, but there's also that human element to interview them and get a feel if this human is a great fit culture for the organization. And if you do, they're going to work well with your team.
Lindsey Freedman: So I see kind of a balance of using technology to at least shortlist some of these candidates, but still adding an extra element of that human assessment.
Praneeth Patlola: Awesome. Awesome. Without human assessments, I think it's kind of learned through the journey, at least in multiple facets that even with assessments and even with several amounts of data, you still are looking to have that human curation aspect of it to increase that quality of that funnel. Totally.
Vik Kalra: Yeah. I would say in an ideal world, at least in the contingent labor industry, we can have a sprint which is a time box of one week. You give the vendor two days to find and screen the candidate one day for it to hit the hiring manager, give hiring managers three days to interview and make a decision. And you do the sprint with the first 10 vendors and 10 quality candidates limit only submission of one candidate per supplier.
Vik Kalra: Right. And if the first sprint doesn't work out, recalibrate the requirement to reeducate the various actors within the supply chain into the second sprint. So currently the way we work is that it's like the top of the funnel is so heavy by the time it gets to the bottom of the funnel. It's a 30 day exercise and good candidates are already out.
Vik Kalra: So lots of wasted efforts and it doesn't serve anyone any good.
Praneeth Patlola: Absolutely. Totally understand.
Satish Kumar: I think we need to work with them MSP to. Implement the idea that we just said right now.
Praneeth Patlola: Fun fact I remember my days in 2010 when Jan was getting heavily adopted out of coming in almost every, especially the software specific projects. And we had the recruiting problem on the other end to grow the team in less than 30 days to 50 people. But nobody has time because we are so busy doing the projects.
Praneeth Patlola: And the idea was that we actually would have stories written down in JIRA, which is basically to review candidates every day and migrate them into the next two onboard. So there was, at some point we discussed about hacking out the solution of JIRA to integrate it into an ATS or a VMS to make that work so that, you know, it's not like an option, whether I will have a time to go to do it, but actually it's highly collaborative sprint where all can come and do and execute together and create idea week.
Praneeth Patlola: Totally. So, one other thing I was thinking about is we touched on the quality of it, but I think Satish we were discussing this a long time ago and we talked about competency versus credentials. So you have a large set of competencies out there. But how do you measure credentials and what is the battle between competence and credentials, which we still fight in our industry, even in the current age of 2022.
Satish Kumar: Yeah. So I think, you know, we would all heard the news that a lot of large organizations have dropped the even college degree requirements, right. For the right reason. They don't want to just rely on credentials, but rather in today's digital world, people who are driven, people who have become better now are a lot more willing to work hard and learn new things on their own and arbitrarily give them a chance.
Satish Kumar: Right. So I'm so glad that the world is moving in that direction and innovation has accelerated that part as well. Right? So this idea that if somebody is competent, must get an opportunity needs to be really followed through outright to change it a bit. Now. While I say that, you know, I sit in the, bring that our goal is to make hiring fair and opportunity accessible.
Satish Kumar: I really care about the candidate, but on the same token, if I have to look at it has to be fair for both employers, as well as the candidate, right? While I'm trying to
Satish Kumar: the capability. And I know you brought up this element about proctoring and whatnot.
Satish Kumar: If we do not assess competency upstream, the downstream cost is very high, right? And as a company, they have to find a way to assess, not to waste the time of the hiring manager. Remember they're busy delivering their project.
Satish Kumar: And I know in this world of great resignation, they have to balance it out. Right. And one of the resistance always hears that no candidates do not want to go through this evaluation process. They don't want to go through even competency evaluation, but remember this attitude towards quality evaluation and the resistance to undergo through such a process is a function of ever-changing demand and supply of the talent.
Satish Kumar: But what remains the same is the need for talent quality by the employer. So how do we design that process and reduce the interview tax for the hiring manager? So they do not waste their time. It's win-win for both. And on this floor that candidate gets a golden chance to showcase their ability and not to be just biased by the hiring manager.
Satish Kumar: But it really needs to be taken with the right attitude. Right. I can get offended by that, Hey, I wait, somebody asking me to take a test. It's not about that. It's about maybe finding the right fit. Maybe finding you areas where even though you're not good today, I can upskill, reskill and bring you that still that opportunity, unless I know where to stand, how can we push it further?
Satish Kumar: Of course if somebody says to me, you know, hire me without even taking an interview, of course I would love that opportunity, right? Always there is always an unfair advantage we are going to win, but really we have to make sure that the right processes and the steps are in place to ensure that talent quality through competency evaluation .
Praneeth Patlola: And while we are talking about quality competency and credentials and this multiple checkpoints that we have via. How do they balance this act? Because as Vik indicated in our industries, speed and quality has to come together, you cannot just do quality and then speed. And then, you know, you're, you basically submit to high ratio and response times are so bad.
Praneeth Patlola: Now you're kidding. Eliminated auto programs too. But if you flip that at the same time, we still have to fill the role. So you still have to do this balanced act in the shortage of talent of labor, where people might be reluctant. People might have too many offers because they have so many options.
Praneeth Patlola: Unlike the other side of the market, where we were back in the days in 2008. So how do we balance that act here in terms of enabling, encouraging, or doing anything still for a candidate to go through this qualification process of assessments? Are we seeing like most of the candidates drop off when you bring off an assessment?
Praneeth Patlola: Like what do we counter, how do we counter that.
Vik Kalra: I'll take that to begin with. I, it's a fine balance, right? A recruiter has a good intuition on a candidate based on their subjective evaluation, but the candidate may not be open to taking an assessment. What do you do at that point? And obviously you're working against the clock.
Vik Kalra: So keeping all of that in mind. I think what we have realized is if our recruiters are more transactional in nature, then our ability to influence a candidate to take a test will be much lower. If you're able to better sell the end client brand to the candidate that you know this channel offers you multiple opportunities.
Vik Kalra: You take one assessment and it can be used within our network. If they extend, we can make a recruiter more knowledgeable to speak the language of the talent so that they feel that it is as much in their best interest to invest their time in building a relationship with that recruiter as it is for the recruiter.
Vik Kalra: Right? So to the extent both parties can see this beyond that transactional you know, relationship, it will improve the percentage of candidates taking the assessment. But still what we see is senior candidates are less interested in taking the assessment. Some feedback for Satish or other providers is.
Vik Kalra: Can we condense that assessment time? Can we make micro assessment? Can we make it more mobile friendly for the industry at large? Can. Offered portability of these assessments that the candidate can carry the assessment with them. Can we keep Fieldglass as a system of record and with some unique identifiers, it can automatically tag in assessment, which was done in the past.
Vik Kalra: So here, the problem is for every role, the candidate is taking another assessment, right? And it's a perishable assessment because it dies after that some mission, some more something for the industry to think.Is there a better way of, because like Uber, like anything else, we want the reviews, we want more objective data, but our processes are, again, I'm coming back to the same thing again.
Vik Kalra: And our processes are very antiquated. They're 20 years old and we are trying to force them on the new model. Why aren't the results improving? We are doing more of the same, but not improvising.
Praneeth Patlola: Great point Vik. I couldn't agree. More writing. I obviously have a selfish mission for that, with direct sourcing and consolidating reviews and integrating that from a data to be usable makes it, but it actually goes beyond that too, because well, there is a debate between public and private and I share talent pools around the data privacy has become such an important aspect of today's conversation.
Praneeth Patlola: Anytime you are starting to roll out a new solution and an enterprise and almost the tone boxing, the data privacy aspect of it, and getting assessed around that of personal information that we will be dealing with about a candidate. It is becoming much more. Impossible to do the, any data interoperability given the restrictions, which are growing every day from privacy requirements.
Praneeth Patlola: But I think at the end of the day, I think if a candidate can control that, which is why I love to talk all day long about the decentralization of the industry from a data point of view, which will enable us as as the future state, that problem statement where the data ownership is an identity around that us towards a candidate and the candidate.
Praneeth Patlola: Assessments candidate history, candidate enablement. It's not like you did a bad job. Now. You can eliminate the review. You can't. So, so it's, it has to be as vetted as possible. And I think there is a huge humongous applicability around the future state of de-centralized contingent workforce management solving almost most of this problem.
Praneeth Patlola: And the first way, I think, is barely kick-starting with this transition of direct sourcing, which is solving only the level one approach. But I think the level two and level threes will be much better in the next coming years.
Vik Kalra: Yeah. If I can add, you know, it would be really interesting to see if this can happen over the next five years.
Vik Kalra: If there is a consortium based, you know, blockchain enabled network of talent where talent has the right of who they want to share, what with, and it's in you protected. It is practically doable from a technology standpoint, from a data standpoint, if you can get to where some of the hurdles and, you know, collaboration
Satish Kumar: very well thought point Vik. So there is a network that Glider also part of which is working in that direction, what you just said.
Satish Kumar: So Praneeth, some of the points that you mentioned right now, right? What are the things that we can do to encourage candidates to take the test in this tight market? Right. So the point that Vik , one of the things that I realized in the given constraint of how and our old processes are still being used today in that constraint, there are a few points I'd like to add that, you know, I'll respect candidates, right?
Satish Kumar: Human touch is needed. To set the right expectations. Don't just send the link. Hey, the process is to take a test. Right? So the human element will still be needed. That really we have seen increase the completion rate messaging that there of course is very important, right? It's a jump ahead in the interview process.
Satish Kumar: And as we work with our clients, MSP enterprises, we really guide them how they should adopt this process, not just bolt on your existing process, so that it also increases the conversion rate. And the last point we're going to make out here is that we can actually, if your organization believes in upskilling reskilling, right.
Satish Kumar: You can add it is a part of the communication channel saying that, Hey, if. Find that you're not good in a certain area, we can actually help you upskill reskill, then bring the opportunity as well. And that was well with Lets say if you're targeting the veteran community, or if you're targeting a diverse pool of people who are coming from economically poor backgrounds.
Satish Kumar: So it is not a disqualification stage, but really a discovery stage to understand what the strengths rest can fulfill, or I can find you another matching opportunity. Maybe not this one, but understanding in an objective way is very important, but this is a tough moment.
Praneeth Patlola: Awesome. Awesome. Well, we are almost near to the last 10 minutes and we have this one big question, which is popping up almost every time, the most important one.
Praneeth Patlola: Why do we have this automation, great ideas of future automation and ongoing embedment of new processes and new ways to move the needle faster, enabling hiring managers, which much more data and information, and with respect to making an unbiased decision through this process is this data points really enabling that challenge to be unbiased or with this huge amount of high touch qualification process, which we are going through this multistage, is it actually making that alerts is it's becoming, although we wanted to be unbiased, visit becoming more biased.
Praneeth Patlola: How do you see that like quality of talent in the shortage of it while you have this great diversity of talent goals and keeping that by unbiased decisions, part of the process,
Lindsey Freedman: You know, no amount of technology can ever completely eliminate bias in the process, unfortunately. But you know, I think we, we've kind of talked about, but ways that organizations can try to come back, this is really try to diversifying your sourcing channels, your sourcing pipeline, you know, not just from staffing suppliers, but obviously direct sourcing platforms, freelancer, marketplaces, and inherently you're going to have, or drive more diversification in your candidates.
Lindsey Freedman: And I think we've all seen two organizations that have a clear DNI goal for their contingent workforce program, with clear KPIs and goals to meet. Or some of the more successful at combating some of this bias in the hiring decision. But you know, I think it's really just being aware of it and being intentional about it.
Lindsey Freedman: And as an organization doing what you can to meet those goals,
Vik Kalra: My 2 cents. As far as the contingent labor industry is considered today, DE&I is in the infancy stages. We want the output, but we don't know the input or the process, but we are all expecting a different output every time. And that's a basic problem. I think there's a lot of top, but very little action. So let's call it what it is. Second part is that human beings are biased. We are very biased individuals. We come with a lot of baggage. At least at this point and objective assessment, a data-based assessment will do more good than harm.
Vik Kalra: Maybe two years down the line, we will have the challenge that the systems are being biased. They're profiling using some scientific methodology, which creates you know, negative discrimination. But I think at this point it will do more good than harm.
Satish Kumar: Yeah. So, there are already steps in place.
Satish Kumar: So when I do an assessment provider, we have to take care of those things so that no biases are injected in the process. The way the question is articulated, the way things are evaluated. But Puneeth data is data, right? You heard the garbage in, garbage out. So it just, how you treat the data to take decisions is what needs to be considered here.
Satish Kumar: So, we have to be very mindful of not eliminating a, not eliminating a lot of candidates, the top of the funnel, but really capturing the data to, beside a downstream with holistic evaluation. I think that elimination credit, and you need to be evaluated very carefully. Otherwise data is always going to be helpful.
Satish Kumar: How do you process that and garner the insights out of it?
Praneeth Patlola: Awesome. Yeah. And I think to Vik's point, I think we do need that solution all while we are in an infancy stage of the decision making or even initiatives around that one key thing is as Satish indicates the top of the funnel, I think that's a bigger solution aspect off.
Praneeth Patlola: You see our top of the funnel diverse so that when the top of the funnel is diverse as the top of the funnel using data X assessment, which really becomes like a self assessments data coming in, which is a score becomes an unbiased decision-making we still need if we are. Human interview process, standardizing that process of quantifying that into more of a process stream.
Praneeth Patlola: Many times organizations have the practice of using a structured interview process with a rating based on a predefined questionnaire, which is coming out of a group early from a team, which is saying that here is how we'll interview. This is why we would interview. And this is what we need from this interview.
Praneeth Patlola: That structure is much more important. I don't know how many people as such we'll practice that more diligently because we have to move the needle faster too. But I think it's super important to have that from the top of the funnel, through the interview process in doing that, but also I think anonymity.
Praneeth Patlola: So one of the key defects we have seen in industry is while the initiative diversity is going around and driving this traffic on traction. Let's say, even if you work on the top of the funnel and the talent pools you're building are truly diverse in nature. The challenge comes in either a curator or a recruiter or any other fancy terminology.
Praneeth Patlola: We want to put it into from a screening of a candidate process. That particular process needs to be anonymized. So we did one experiment where we said, we will have a set of hundred candidates where we'll have resumes, physical resumes without any photos on it, or without any personal information or social status.
Praneeth Patlola: And then we only exported the LinkedIn profiles and did that. The same hiring managers in different instances had made different decisions for the same datasets. Because the LinkedIn information that we are surviving on has a different set of information, which is making the human brain. As you said, we come with a lot of baggage and empire.
Praneeth Patlola: So we really need to rectify, even through the screening process, all the way to hiring managers, to create anonymously. This is something which we are seeing heavily missing out on how much you can anonymize the data, how well you can anonymize the data. What information can you anonymize at a segmented skill, not a skill level, but you know, one big topic, which is always debatable is like the credentials part of it.
Praneeth Patlola: Should we hide the credentials part of it and focus on the skill set and assessment data, which is much more unbiased to see the qualification as such. But again, go ahead.
Satish Kumar: I really don't want to add, so what we have done here at Glider that during the evaluation process of the. We enable all kinds of tracking, prompting, making sure they're self aware of what they're doing, things to be monitored.
Satish Kumar: But when it comes to presenting those reports to the hiring manager, we have a way to hide all of these personally identifiable data emails, video, name, everything that's you're in, and what you see that, what, how do you manage to get to see it? Just the competency, and then they can sort list people based on competency and then reveal who they are.
Satish Kumar: So we are aware of that part of building the workflow as well.
Praneeth Patlola: Totally. Again, amazing dialogue and great insight. Hoping the audience here who was participating in the session, got the 2 cents as you're referring to from this at least and enjoyed the session. I personally enjoyed the session a lot because I have a quality of talent problem in my own team, all this every day for all my life.
Praneeth Patlola: So I don't think, I think we can equally appreciate every aspect of the conversation from the sourcing aspect of it, qualification of it, the design thinking approach applied to enabling ourselves to bring that together, the variety of techniques from a human touch and a brand enablement to in this current market.
Praneeth Patlola: I think we still have a challenge and I think we'll still continue to have this challenge for some time. We just need to embrace ourselves and prepare and invest more into this process to be more successful from a talent acquisition with that. Thanks a lot. Satish, Lindsey and Vik. For the amazing insights that you've shared.
Praneeth Patlola: Thanks audience for the great comments. I didn't get a chance to read through all the comments here, but there are some great comments here. And I think there is an outstanding question about diversity within the two minutes. I don't think I can answer that. I'd probably reach out to that person to individually answer.
Praneeth Patlola: Thanks again, everyone. Enjoy the rest of the WSS session. This is the one which is bringing our industry together. I think we would want to have more of WSS as you move forward. Thanks everyone. Thanks.
Praneeth Patlola: Yeah, and we have two minutes left, so enjoy the two minutes break.
Praneeth Patlola: Thank you.