Technically People
Technically People

Episode · 2 weeks ago

To Accurately Predict Who Will Thrive in Your Roles, Use People Analytics

ABOUT THIS EPISODE

As a leader, would you rather make business-critical decisions based on your often biased and incorrect gut instincts? Or on data that can predict with a high degree of certainty which candidates are likely to succeed, for instance, which employees are likely to leave your company, and which strategies will best retain people?

It’s a rhetorical question, but it gets to the power of people analytics.

In today’s episode, guest Brett M. Wells, PhD, the global head of people analytics at Perceptyx, shares how this discipline uses data (census surveys, pulse and lifecycle surveys, performance reviews, and more) to help leaders make sound decisions, including about attracting, selecting, and retaining talent.

Organizations have never had more access to data, but it’s overwhelming, noisy, and difficult to interpret. People analytics finds the signal amid the noise, giving organizations insights they can act on.

As an example, it can determine criteria that predicts success for specific roles at specific organizations, whether that’s experience, knowledge, skills, abilities, traits, or a mix thereof. The success rate for hiring is often cited as 50%. According to Brett, people analytics bumps that to 70%.

“You're already using certain criteria to make selection decisions,” he says. “You can see under the people analytics microscope which of those factors are more indicative of success.”

Another application that would make any HR team swoon: Perceptyx can predict which employees will leave an organization, and their reasons why, within the next 12 months with 85% accuracy. That leaves enough time for a company to intervene before employees set sail.

“We get a really good sense of which way the wind is blowing for them,” says Brett. “Are they committed to the organization? Do they have intrinsic joy at work? Those that do not are 300% more likely to leave the organization in the next 12 months.”

In this far-ranging conversation, we also explore Brett’s theory of “officism.” As hybrid work becomes the likely norm, officism is the prospect that leaders could come to view people who opt to work remotely as less committed than their in-office peers, who would then potentially be promoted faster and further.

Given that parents, women, caregivers, and people with chronic illness and disabilities tend to benefit from and prefer remote work, the specter of officism raises equity issues.

Painting a picture of the implications for just one of those groups, women, Brett says: “All of a sudden, you start seeing the glass ceiling arise again, and if anything turn into a concrete ceiling, because the office in large part is heavily male dominated [if officism were to take hold].”

Listen in to learn Brett’s recommendations for getting ahead of this potential blow to workplace equity before it's too late.

KEY HIGHLIGHTS

- Predictive criteria for the success of any candidate

- The attrition risk for remote employees who never worked in your office (and what to do about it)

- People analytics as a means to improve DEI

- Why years of experience is a poor indicator of success

- The benefits of bringing on a leader dedicated to the remote experience

Read Brett’s article in Forbes:

- What ‘Officism’ Means For The Hybrid Workforce (And How To Curb Its Effects)

Contact Brett:

- BWells@Perceptyx.com or LinkedIn

Find every episode of Technically People on Apple, Spotify, and more. Find us on our website and join the conversation on LinkedIn.

Listening on a desktop and can’t see the links? Just search for Technically People in your favorite podcast player.

Welcome to technically people, a communityconversation by and for workplace futurists brought to you by the tech recruitment platform builtin. The podcast features insights from leaders, thinkers and doers on the vanguard buildinghuman centered workplaces of the future. Along the way, you'll hear conceptsthat will stop you in your tracks, concepts that inspire you to ask yourself, what's the most future forward way to approach my people leadership? We allknow the future of work isn't waiting around, so let's get on with the show. Hello, welcome to technically people. I'm tiffany Myers. I'll be hostingthe episode today. have an exciting, interesting, fascinating conversation with Brett Wells. He is director of people analytics at perceptics. He has spent hiscareer using people analytics to help organizations like the navy, seals and Esta aladder. So pretty polar opposite. Companies attract, select and retain top talent. So he's going to explain what is really possible when companies leverage people analytics. He said something the other day, which is that he can predict who'sgoing to leave a company and the next twelve months with an eighty five percentaccuracy rate. That is pretty impressive. So Hi Brett, thank you forbeing here. Thanks, Tiffany, it's my pleasure. Thanks for having me. Yeah, so let's get to it. I wonder if you can give thesense of what the practice of people anatlets can do, and obviously alsohave perceptics does it? Yeah, so to level set on what is peopleanalytics, it's really, in my mind, the practice of gathering and connecting thedots between your people data and then a whole host of organizational data,and the point of it all is to make smarter business decisions. People analyticsis often pointed at a variety of issues such as how do we attract,select retain talent, how do we improve...

...sales or productivity, or even thingslike workforce planning and creating a diverse inclusive environment. So all these challenges thatwere faced within organizations, people analytics can shed some science and some light toinform leaders. So I really liked this idea you brought up, which isthat people analytics is actually not anything new. Now it's just, you know,the what's the phrase, new wine, old wine, skins. So it'sbeen around for many, many years. We've been studying people at work inindustrial organizational psychology for fifty years plus and making strides in terms of scientificallyimproving the work lives of people, and we do that because a cascades overto the rest of our lives as well. But we've never been at critical juncturewhere we have so much data, maybe too much data, to makesense of. Big Data is all around us now. It's about finding thesignal among all that noise of what to focus on, because often that datais messy and it's difficult to interpret, and a strong people analytics team canreally cut through all that noise and help leaders make the soundest decisions with whatthey have at hand. It perceptics. We design, collect the analyze ahost of employee listening and sentiment data. So the typical annual census survey thatorganizations do, and but also pulse surveys, life cycle surveys to get a senseof what's happening at on boarding and exit as people transition throughout their career, what happens when they get promoted or do a job transfer? Three hundredand sixty reviews. So we help connect those dots for our customers and thenthe extra roll we also provide is a data aggregator, and that's where we'llsay, let us see all of your terminations and all of your hires forthe last few years. Let's put that into the analytics engine and see whatinsights can be garnered from looking at who...

...stayed and been successful versus those whohave left it. It's still hurting the organization. Fantastic, so let's breakdown one of those factors. I know you can uncover predictive criteria for whethercandidate will be successful or not, and I'd love to hear about that.Yeah, there's a lot of success stories over the course of my career ofdesign assessments all targeted at trying to identify successful people. We're going to makea huge in aestment and someone think of that number one draft pick in theNFL. You're going to lay out tens of millions of dollars. You wantto make sure you're making the right decision. Or even if it's the counter atBobby Brown, you want to make sure you're hiring the right beauty advisorthat's going to give the very best customer service. So we take a scientificapproach within the field and first is really understanding what is success look like inthe role and before working with us a ladder, I had no clue.But applying scientific principles in terms of what's the knowledge, skills abilities that definesuccess? When people have failed in the roll, what are the reasons why? And you start coming out with hypotheses like, oh, they need tohave really high customer centricity and they need to be able to problem solve andthey need to be able to have a team work and you come out withthese characteristics and traits that would be ideal for successful performance. And then yougo out, there's already hundreds of people in these roles, some are moresuccessful than others, and you ask them to go through a battery of psychologicalassessments and you test those hypotheses. So is it true that the very bestbeauty advisors, who are selling more than anyone else, have the highest customercentricity? Do they have the highest teamwork? And out of all that noise youdistill down what are those key factors that recipe for success, then youcan apply to every higher going forward and make smarter decisions. Yeah, soyou know the way that you describe it. And then more boil down senses thatyou're looking at data of all the candidates of are the last several years, let's say, so data and aggregate...

...over time who were hired and turnedout to be successful, comparing that to those who were unsuccessful and using thatto understand those criteria. Yeah, and all likelihood you're already using certain criteriato make selection decisions and you can see under the people analytics microscope which ofthose factors are more indicative of success. So, as an example, onecriteria that often has undue amount of weight in the selection equation as years ofexperience, and typically that's a very poor predictor of performance. So organizations aresaying you need five to ten years experience and when you boil it down andstart looking at the data, it predicts pretty low especially is compared to othercriteria that would allow a much wider funnel of applicants to create a more diverseapplicant pool, like all these other pluses that go along with it. Soyou know, my follow up is, what's a criteria that's super predictive?Yeah, so if we look at the last, call it fifty years ofresearch and industrial organizational psychology, we look at cognitive ability, personality, intereststo knowledge skills, like all these different aspects, years of experience, age, education level, mean, the list goes on and on, and onethat routinely comes to the top is cognitive ability. It's probably the most predictiveacross all those criteria, but it also comes with a little heartburn as aresult, because it creates something called adverse impact. So certain groups of individualstend to score lower on average than other groups, not because there's any inherentdifferences, but just because of disadvantages in terms of equity standpoint. So wetend to supplement cognitibility with other measures that are also predictive but don't come withthose biases like personality. So those in combination are very predictive and play welloff of each other, regardless of the...

...role. And you know what,maybe I skimmed over a little bit too quickly on this idea that years ofexperience is less accurate predictor tell me your sense of why that is cheese.Well, I think you're taking someone and there's transferable skills and knowledge, butyou're plucking someone out of this experience and putting them into entirely different experience,even if it's the same industry, it's two different cultures, it's two differentgroups of people you're working with. So just because I have ten years offinance and experience in this one company where it's incredibly hierarchical, it doesn't meanthat it's going to make me a great leader in an organization that's more collaborativeand people centered. So I think in large part it's because organizations are quitevaried. What I would say is too exactly identical candidates on the cognibility,personality and like you go down the list of things, years of experience mightgive you a little incremental bump. So instead of being, you know,a success rate to fifty percent, maybe a bumps you up to fifty onepercent by going with the candidate with more experience. But by no means wouldthat be the first knockout that I ever look at when making decisions. Okay, so that reminded me of the Russian Roulette analogy you gave with and itwas specifically in regard to hiring. Let's hear it. Yeah, so Ithink how most organizations approach selection is they're using old ways of thinking. Solet's look at years of experience in the school they went to and their gradesand all these things that can be scraped pretty readily from a resume. Andimagine you're that hiring manager. In essence, you're spinning that roulette wheel hoping thatyou land on read and you get about just under fifty percent success ratebecause you have the to the zero, the Green Zero and the Green DoubleZero. And with leveraging people analytics, imagine taking all the black spaces onthat roulette wheel and now shading about half of those two read that's really thepower of leveraging people analytics when making selection...

...decisions and using science, because you'reall of a sudden focusing on for that role. Here's what success looks like. Here's the recipe, are Algorithm for success. It's these types of personalitytraits, it's these types of interests and this type of background and skills.And now, when you're spinning that roulette wheel, by no means is itever a hundred percent successful, because it's called science. It's not perfect,but it's far better than just going at it with that gut reaction like,Geez, I'm the hiring manager. I like this person because they're from Chicagoto and they grew up rooting for the bears and wow, they're just likeme and I love this candidate. As opposed to focusing on the things thatreally matter, there's too many biases that come into play when using the oldway of thinking. Let's science do it for you and then have a finalreaction as a hiring manager of all the candidates that meet that criteria so you'renot making a bad decision. Then you can start going with more of thatgut feel and reaction and how that synergy is between the hiring manager in thecandidate. I know that they're maybe kind of myth floating around out there thatpeople think people analytics is science, it's going to be one hundred percent accurateall the time and absolutely everything, and I think it's important to know that. It's going to make you more likely to win a Russian roulap, butit's, as you said, not a hundred percent accurate. So take downthe house. Playing on the people analytics wheel, you would lose every time. Playing on the hiring manager with exactly exactly what it like, and withpeople analytics you're spinning the wheel with a seventy percent success rate versus the typicalfifty percent success rate in terms of new hires. Yep, that's right.So imagine, thinking your mind the best performer you know in a role andyou want more like him or her. You're spinning that wheel. You mightbe lucky fifty percent of the time. So they turn out to be atop performer and they stay long term in the organization. Now, coming tothe people analytics wheel, you're spinning it and you'll get that person about seventypercent of the time. It's not perfect,...

...but the cost of using the sciencepals and comparison in terms of making the wrong selection decision. You thinkof the miss of hiring the wrong CEO. It's estimated to be anywhere from tento twenty times their annual salary, and it's only more in terms oflike a fortune, five hundred, fortune one hundred organization. Even at anhourly role in an organization, making a Misshire at that level still cost thebusiness tremendous amount of money, anywhere from twenty to fifty percent of their annualsalary. So I would rather spin on the seventy percent success and look foropportunities to keep bumping that up. Yeah, me too. And Bright, youhave the distinction of being the first gambling conversation we've have on technically people. I was waiting for it and now we've got it. So okay.So you've mentioned Dei. I would love to hear success story in terms ofhow you've helped an organization get better. Adi. Yeah, if I thinkof one healthcare organization that I helped, they had a big goal of howdo we attract, engage and retain their diverse talent, and in the beginningthat organization was very much soul focused on selection. So how can we putbetter practice? This is in place, so we're not looking through the managerLens and more so looking through the Science Lens. So over the course ofa few years, their percentage of diverse hires increased by nearly forty percent,which was outstanding. But over that three years span of time we got tosee who stayed and who left. And although they are bringing on diverse candidatesfaster than they ever were before, they were also losing them at a muchfaster rate than they ever were before. So when you look at their population, diversity really didn't change at all. So they focused on diversity as theNoun as opposed to inclusion as a verb. And again looking at employee sentiment data. Connecting the DOTS will, we...

...found was that diverse candidates were verymuch attracted to the organization and sold on this idea of a diverse environment,but when they got to their teams, their respective teams, they didn't seea leader like them. So the path of career growth and development was verymuch lackluster and they went and found that elsewhere. So they're almost sold afalse vision or promise of what it was going to be like. So theorganization immediately pivoted and started to put a lot of intentionality around how do weidentify and promote diverse talent, and that all of a sudden had a cascadingeffect in terms of retaining talent like those leaders, because those fresh people they'rebringing on with diverse backgrounds, they want to see someone like them that it'spossible to succeed and go up the career ladder. So that organization is donewonders and their communities to reflect the demographics of those they serve in are reallypioneering the way in terms of creating more of an inclusive environment and showing thatpath forward. A lot of conversations I've had in particular a podcast with Lourenvirgus towns, and her really strong point of view is that you have tostart with culture. You can hire diverse workforce the day before you roll outyour DII manifesto, but if your culture is not, as you said,doesn't live up to the verb of inclusion, then those people are going to massexit. Is the BOTOM line. They'll find it somewhere else. Soall right, nice segue mass exit. So we established this incredible accuracy rightin terms of when you know a person may leave a company. But thepandemic, of course, has made retention tripli important. So tell me whereretention and the pandemic intersect, Jay's well, first, in terms of our baselinemodels, in terms of predicting nutrition,...

...like you said, they're eighty fivepercent accurate. So we collect a whole host of sentiment data from employeesand we get a really good sense of which way the winds blowing for themin terms of are they committed to the organization, do they have this intrinsicjoy at work? Do they intend to stay for the next twelve months ornot? And those that do not are three hundred percent more likely to leavethe organization in the next twelve months and we're able to predict with that eightyfive percent accuracy if someone stays or leaves. Just being able to predict if they'regoing to stay or leave. That's that's a nice parlor trick or parlorgame, being on the gambling hat, but the double click into that isalso being able to just to tell leaders why. What's the reason? Why? What are the barriers that are getting in the way of People's success atwork? Is it the relationship with the manager? Is it having more worklife flexibility? Yeah, and when someone is hired fully remotely, there isnot that honeymoon phase that you would have that if you're in person and gettingthe chance to drink the Koolaid and everybody seems so nice. You're spot onand again points to the importance of people analytics and why you should always belooking at data. So if you would have asked me and my biased mind, I would bet my bottom dollar on always seeing this notion of a honeymooneffect and the honeymoon effect and what we see in every survey administration are thoseemployees that are newly brought onto the organization are the most engaged they're seeing theirwork lives through the rose colored glasses or the course of the pandemic, though, those that were hired and onboarded during the pandemic, they are acting,behaving, feeling more are like they've been in the role for three to fiveyears, and that's the critical juncture where people tend to decide are they stayingor leaving? They're also the most at risk for leaving right now, thosethat pandemic cohort is we've as we've termed...

...it. And again, that's whywe need to keep looking at data, because these things change with with somuch pressure of an environment like a pandemic, on boarding look completely different. Evenif you were on boarding in person, it's not like you're sitting in thebreak room talking to friends, sharing a meal. You're still very muchin your isolation during the pandemic. So it looked completely different and employees didn'tget that emotional attachment to their organization. They didn't fall in love with themand have that honeymoon period. Yeah, so so many people in the HRspace are really rethinking how to on board and you know, in a waythis is a good framework. You know, create some onboarding that replicates the honeymoonexperience to whatever extent you can, and I would say one practical pieceof advice. The single most important relationship that we're finding right now that mitigatesmany of the effects that we're seeing is the direct relationship with a manager,and we're seeing overall that's pretty strong and when it is the strongest, that'swhere we're getting that emotional attachment to the organization. But where employees are missingout as on those fringe connection. So they're really close with their manager,may be close with their direct a team, but when looking Cross Department or Crossarea where you'd be bumping into people in the office, they're really missingthose connections right now. So they don't have multiple connections, they're almost onthis little island that's pretty isolated. Yeah, the weak ties that they're most Rada, which is a misnomer, of course, because those ties are notweak. They are very important for innovation as and, as you're saying,for retention in this case. Okay, so let's see. Let us talkabout this concept. Office is m. So it is the idea that aswe move into the hybrid world, leaders could view remote employees as less committed. As you know, maybe less productive...

...right because you can't see them,can't see them other than you know are they logged on, and there areall sorts of inclusion implications around that. We know, though, that themajority of tech workers want flexibility. They want to choose how and where andwhen they work, and the smartest companies are giving people that flexibility. However, if office is m becomes a reality and workers who do have that flexibilityface some form of discrimination, tell us what we can do about it.Well, let me paint the horrible picture first, and I think we're goingto take decades step, words back in terms of inclusion in the workplace,and the reason why is when we look at right now, the delicate balancingactive home work lives, what we're finding is that working mothers in particular wantto remain working remotely more so than their male counterparts, and for those thatdo want to go into the office, they want to go in about onefewer day per week on average. So the post pandemic world, where wehave this flexibility, where people can come and go as they want, you'regoing to see a far more male dominant work environment. Now you throw intothe mix this notion of office is M we're just not leaders, but manyof us harbor these feelings. It's pervasive that those that go to the officewill have better relationships with their manager, are going to be the first onesto be thought about for developmental or promotion opportunities. All of a sudden youstart seeing the glass ceiling that we've been trying to chip away at for decadesarise again and, if anything, turned into a concrete ceiling, because theonly ones that around the office, by large part, are heavily mail dominated. So I think that's the the picture that could go, that could getpainted in terms of why this is such a critical issue to focus on rightnow and get ahead of it before it's too late. Yeah, and Ithink compounding that, I would add that...

...there's estimates that as many as twomillion women could just split, could leave the workforce. We know they're downshiftingtheir hours or leaving their job at much higher rates and also considering career changes, and it seems like it could be pretty pretty dire. So tell mehow to fight this. Are there any any areas to look at? Youknow, from a people analytics perspective, I would consider that group. So, whether you're in the office or you're working remotely or hybrid. I wouldclassify those is almost like a dei category. So for the analytics team you shouldbe focusing on making sure that there's equity among those groups. So whatdo we look like in terms of pay for performance? What do we looklike at promotion rates? What do we look at in terms of retention?So you want to make sure that you're creating a great experience for employees,regardless if they're going into the office every day or they're working remotely every day, and make sure that those outcomes are very equivalent to the best you canand have some intentionality around that and dispelling many myths. So the myths ofthe people are in this productive with all of the digital exhaust that we giveoff in terms of workers for many roles, especially the roles that can be doneremotely, you can back up with some pretty concrete evidence from a peopleanalytics team perspective in terms of that productivity, that they're just as productive, ifnot more productive. So I think you can dispel those myths. StartLooking at it through a Dan Islands and the most progressive organizations are really thinkingabout the future of work. They're creating roles where they're just responsible for thishybrid so like directors of remote experience or directors of our extended community, orso they're really putting intentionality on. We know that how the work gets doneis maybe a little bit different and what each group wants is a little bitdifferent. Let's make sure we're meeting the unique needs, and that's where theemployee listening strategy can play a large part, where your sense of seeing those groupstask. What do they want to...

...be? What do they need tobe successful? What's getting in the way of their success? What are theyworried about? And really catering to those individual groups is opposed to some blanketumbrella. The blankets statements or the blanket approaches rarely work because you have segmentsof groups that want different things and need different things to be successful. Yeah, so, Brett, I read your article in Forbes and you mention thatyou should move away or just totally forget annual performance evaluations where the goal is, to quote unquote, meat expectations. I thought that was interesting. Sowe're moving away from meeting expectations. What, then, instead should we do?And the rationale behind that is whenever I get performance data as a consultant, I start getting excited because wow, we have something tangible to predict.This is what the organization cares about. And when we get the data finallyin hand, you find out that, you know, eighty percent of employeesmeet expectations, very few are far exceeding and very few are struggling. Soit's meaningless for trying to predict anything. So instead it's thinking about what doessuccess redefining what success looks like in the role. How can we measure itmore accurately with concrete things? Is opposed to abstract manager ratings, which areriddled with air and are not the most reliable indicators of performance. So rethinkingperformance in the hybrid world is going to be very critical and I think willdispel some of the officism. What many of us think productivity means is wego to an office and where they are nine and twenty five, or weleave after the boss leaves. That's impossible to do in the remote world andespecially where employees are asking for flexibility. So instead let's redefine what productivity meansand measure it that way and give employees what their expectations are to meet,regardless of where you're working all right, so, Brett, how about wemove into our two minute takeaway and actually, you know what I want to sharemy key takeaway from this conversation,...

...which is, you know, Iwas always fascinated by your concept of officism. I just think it's brilliant. Butyou know, when you paint to that picture and said that, yoube taking a giant step backwards in terms of Dei and inclusivity and creating asense of belonging and allowing people to be their whole salves at work. Youknow, that really struck me as something people are going to need to thinkabout and are going to need to fight if they care in fact, aboutcreating a great workplace of the future. So, anyway, that my keytakeaway. So tell me a couple of things you want us to understand,and I think your spot on, and the I'll just extend your great insightand many organizations are probably feeling right now. We're doing exactly what our employees askedfor. They want to work remotely and we have plans of doing that. But now they need to think beyond just meeting that need and how dowe create equitable experiences for things that employee still value and want like career growthopportunities and promotion, and how do we make sure that office is M isn'tgetting in the way, regardless of where people are working? Second one isjust to remind people that they're sitting probably on a treasure trove of data andif they don't have a people analytics team today, there's still opportunities to goin and get what I think is a quick win. Start looking at yourturnover data, start looking at your selection decisions, start mining and finding thosenuggets, because I promise you they are there in terms of making smarter decisions. And then our final takeaway would be with so much change that we're experiencingand pretty severe gravity into the changes, with all of that going on,there's no better time to listen to employees, stop having the mindset of we thinkwe know what our employees want and instead just ask them the questions.But then asking isn't enough. What we find in our research is that theorganizations that are performing the best frequently ask...

...their employees for feedback but, mostimportantly, they act on it quickly. So I can have a great conversationwith my spouse tonight and she could tell me that, you know, I'dreally appreciate it if you would put away the dishes more often, fold thetowels, you know, etc. Etc. Maybe this is fresh in my mindexist what happened last night, but I need to act on that.I can't just listen and say, Oh, good talk, honey. I needto now today, act on it if I want to re engage her. And organizations need to do the same thing. It's no different in termsof a relationship they're trying to create with each and in every individual employee.So listen to your employees, but respond and help them connect the dots.We value your input. That's why we asked. This is what you toldus and here's what we're doing about it. And not always will the organizational decisionalign with every single employee and what they want, but showing that kindof bread crumb trail for employees will incentivize them to share their voice more often. Maybe it wasn't the decision I wanted, but one time it will be.So I'm going to give my voice because I don't want to be forgottenabout. So, okay, I think you've probably have a lot of peopleanalytics converts after hearing your conversation. So if they want to get in touchwith you and learn more about perceptics and you, how do they reach you? Yeah, they can follow me on Linkedin. So just search Brett Wellsat perceptics and it's peer CEP ty x and you can see a lot ofour latest research, whether it's on office is mm or turn to work underour resource library on our website. And we only got to skim the surfaceon people analytics. Anyone that would love a deep dive conversation, here's somecase studies, success stories, or just want some help in terms of howwould we stand up people analytics when we're more in that infancy or adolescent stage? Reach out. I'm happy to do a one on one. Fantastic.I think people will take you up on...

...that and my email. I'll justthrow out my email be wells at perceptixcom. Awesome. Well, I can't thankyou enough. As you know, I really respect your work and yourinsights as so happy to have this conversation and bring some of what you're upto our listeners to thank you for being here. My pleasure, tiffany.Thank you so for our listeners, you will not be surprised to hear meencourage you to subscribe to technically people. All you need to do is visitour site, technically peoplecom. I hope you enjoy the conversation and we willtalk to you next week. Whether you're looking to fill opportunities or find them, built in has you covered. If you're seeking to meet aggressive hiring goals, will help you attract sought after tech talent you might not otherwise reach,and if you're on the market for a career change, visit our site toexplore exciting jobs with our customers and even with built in find talent, findopportunities built incom.

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