Speaker 2: 0:06

Welcome to Real Talk on Talent, a human resources podcast where we talk about talent acquisition, recruiting and all things hiring. Hi, hi, dina, how are you? I'm good, welcome back. Hey, thank you, great to be here. Are you all springy in the middle of summer? You know, I like my pink, I like my pink. I'm here for it. Yeah, which we need some of this, because I would like to today to just complain, oh, you know what Will you join me on this journey?

Speaker 3: 0:39

Let's do it.

Speaker 2: 0:47

I'm so for um, yeah, and, but it can be productive complaining. It's purposeful. Purposeful if we're pointing out potential issues or red flags, because today is data. This is perfect, which and I think last time when we talked about data we had like clowing reviews. We're like, we love data, love reporting love it, we love it, we do.

Speaker 3: 1:00

Let's talk about when it goes bad, though, the worst. Yes, it is so true, though I mean it definitely goes bad.

Speaker 2: 1:07

Yeah, it can go bad, it can go because data is there's so much like we talk about big data and how like we went through this whole era of like the more data, the better get it, splice it, have it. But there are some real pitfalls there are absolutely Collecting, using understanding, can be a real pain.

Speaker 3: 1:29

So yeah, I mean, we know we love it, but we also hate it.

Speaker 2: 1:33

Kate, you want to start Give me? Give me a pet peeve when it comes to data.

Speaker 3: 1:37

OK, just one? Well, we'll start with one. Ok, so first data without context. Ok, tell me more. Just don't just throw something at me and expect me to understand how this fits into the bigger picture. So a lack of analysis. So a lack of analysis. We know this about data. Anybody can splice the data to make it tell the story that they want.

Speaker 2: 1:59

for the most part, Well, because if you have enough data, you can to your point, you can pull out the pieces that tell different stories.

Speaker 3: 2:06

Yes, so I'll just pulling it back to what we're here to talk about, or what this podcast is.

Speaker 1: 2:12

Complaining about data.

Speaker 3: 2:13

Complaining about data. No, like human resources, oh yeah, okay, just to be like. Oh well, our turnover rates 27%, okay, okay, is that good, is that bad?

Speaker 1: 2:23

How's that?

Speaker 3: 2:23

compare what's industry. Give me context. Yeah, there are moments Just like don't just give me a data point, I need context around. Or like not having a baseline.

Speaker 2: 2:32

Baseline, like where are you today, where were you yesterday, where were you a week ago? Where do you want to be, like yeah.

Speaker 3: 2:39

All those things.

Speaker 2: 2:39

I also kind of going along with that. I really get frustrated when you are arguing data versus anecdotal opinions and I had this whole experience once where I spent weeks, literally weeks, arguing with a company. It was kind of arguing, but they-.

Speaker 3: 3:03

Debating is what we call that.

Speaker 2: 3:05

I was telling them they were wrong and they didn't agree with me Hillary wasn't on the debate team.

Speaker 2: 3:10

That was not you were. I needed you there because if you'd been there it wouldn't have taken so long. But it was so frustrating because we helped set up a new ATS and then the hiring manager started complaining that they weren't getting enough. They weren't getting candidates anymore, and so I went I said okay, well, tell me. They said well, we used to post a job and get hundreds of applies for hard to fill positions. And I went back to all the historical data. I was like that's not true. One, it's not true. And two, you're actually getting better candidates, better, like the data shows that it's there. And they're like well, no, our hiring managers aren't happy. And I was like I don't know what to tell you, because if here are the numbers, I pulled them straight from the job boards and you even get in weeks where they literally like no, yeah, no, this isn't true. And I was like I don't know.

Speaker 3: 4:01

So you know. It's so interesting that you say that. Because, so you know, it's so interesting that you say that? Because data often overlooks the qualitative feelings, the softer feelings, the more subjective feelings, so to speak If you were, if you were, and so people will often lean on how they feel as an out for what data is. So, with data, it is important that you have a champion and somebody who is there to be analytical, but you do also have to factor in the people part.

Speaker 2: 4:33

You do and it kind of reminds me of, I think, last time. Or you talked about the gut check. Like, gut check, yeah, you use the data to gut check, or you use data to validate or disprove the gut check, because there is value in saying like, okay, what's my human intuition, what's my experience telling me? But if you get to a point where it's like no, I reject all of the data you're showing me, then it's like that's my frustration.

Speaker 2: 5:01

One plus one does not equal two. Why am I here? Yeah, why am I here For this podcast? No, in that conversation.

Speaker 3: 5:07

I know, I know I get it, I get it. Yeah, anyway, you know that's a whole different scenario it is. We'll talk about how to sell to people your narrative. I'm surprised, that's kind of your thing. You're the marketing person.

Speaker 2: 5:21

That. That's why I was so frustrated because I was like look.

Speaker 3: 5:23

Anyway.

Speaker 2: 5:24

Yeah, one thing as a marketer is we do have to. There's this constant balancing act of like you collect data and you analyze data.

Speaker 3: 5:34

Yeah, what do you do with?

Speaker 2: 5:35

that? What do you do with it? And so over the past couple of years, as more countries and more states have put in privacy like right to privacy, right to forget laws and stuff, that has been something that's been, as a professional, a little frustrating, but at the same time, personally, I love it. Okay, tell me why? Because I do really enjoy the feeling of anonymity even though in our world. Is there really?

Speaker 3: 6:01

true anonymity, but believe it.

Speaker 2: 6:03

One of my favorite stories on like the misuse of data is there's a example with Target and I'm not throwing them under the bus Like this is very well known. It's a great case study. But the story goes that a father got really ticked off at Target because Target started to send his teenage daughter like baby coupons for like diapers and strollers and he's like, and he goes. He goes and complains to target. He said what are you doing? I have, you know, I have a teenage daughter. Why are you sending her all of these baby related things? That's completely inappropriate. We'll come to find out. His daughter was pregnant and because of her buying patterns and Target actually has they've said it's something like if you start buying a certain type of vitamin and unscented lotion and like one other thing they found that that buying behavior tends to three, six months down the road, start to buy all of the. So Target knew this because of their data related to buying patterns. So they used very targeted marketing, perhaps a little too targeted.

Speaker 3: 7:12

Way too targeted, way too targeted yeah.

Speaker 2: 7:14

And so it's. I think it's one of the most fascinating stories on. Oh no, that's really interesting, not just like what do you do with data, but like the stories. You who would have thought that's crazy, like three completely unrelated things that they found were one of the first trigger points for moving into a pregnant person.

Speaker 3: 7:32

Yeah, very interesting.

Speaker 2: 7:34

So be careful with data. I guess is where I'm going on that.

Speaker 3: 7:36

Or don't sign up for any of the memberships where they track what you're buying. They track what you buy anyway. I like to pretend anonymity. I like my coupons too. I will say Good deal, Like are you a member? No, oh, you should be. Hey, they track what I'm buying.

Speaker 1: 7:50

So they always send me great coupons.

Speaker 2: 7:54

So one of the things because I studied the Target case study in school and talked about it many times in my professional career what they do now and this might be tall tale, but I pretend it's truth is, instead of sending, like, all baby coupons, now they'll have their standard, but they'll start to insert more baby related coupons, so you don't know you're being targeted because people, they want the convenience of customization without feeling like you know everything about them.

Speaker 3: 8:24

The illusion of privacy. Listen. We love the illusion of privacy Listen.

Speaker 2: 8:26

we love the illusion of privacy Listen we just sell our data to get things for free like Gmail, oh yeah.

Speaker 3: 8:32

Totally free? Totally fine? Yeah, that's fine. And then serve me up the ads for what I want yeah. And then I get mad at Instagram. I'm like dang it, instagram, you're making me shop too much, but that's the thing, but that's the thing?

Speaker 2: 8:43

Okay, my own fault. Okay, what about you, weirdest?

Speaker 3: 8:48

targeting you've had. So I keep getting stuff for private school for children. Okay, I do not have children, I have dogs.

Speaker 1: 8:57

I was going to say does Buddy need to go to private school?

Speaker 3: 8:59

My mutt needs to go to private school and I'm like, why am I? Continuously getting pieces for private school education. Maybe they're trying to get you to go back to school. Maybe I don't think they want me in an elementary school, though, teacher yeah, maybe I don't have the patience for that.

Speaker 2: 9:15

No.

Speaker 3: 9:16

Yeah, that is kind of a weird one. Yeah, I get that, do you think?

Speaker 2: 9:19

of anything in your life that would have set that off.

Speaker 3: 9:22

I mean my guess is somebody is just doing like very generic, unthoughtful demographic screening and going oh, this is a woman in her late to mid mid 30s.

Speaker 2: 9:33

Just own it Dina.

Speaker 3: 9:35

You're not a millennial. We could do the math this is a woman in her early 40s. She's probably has kids going to wherever.

Speaker 2: 9:40

Yeah, that's a good point.

Speaker 3: 9:41

And I'm like oh, be more thoughtful, okay so that's a question, so be more thoughtful.

Speaker 2: 9:46

So you're grumpy that they're not more thoughtful, exactly.

Speaker 3: 9:49

Why isn't my husband getting that piece of direct mail?

Speaker 2: 9:51

That's what I want to know that is a great question. Don't send it to me.

Speaker 3: 9:56

That's a better question than the age one. Don't send it to me, send it to him, send it to him. You know what I started thinking about on the data thing. So you know I know before we were talking about AI and we were talking about some of the biases with it, and now I'm not a machine, so I don't understand machine learning. But what I want to know is what are the different factors that are going into all of the considerations? Like what is every data point that it's looking at when it's deciding whether or not a candidate is good for you?

Speaker 2: 10:32

I mean, we don't have time to get into that, I know, but like is there like.

Speaker 3: 10:36

I mean again, I don't know machine learning, I don't understand this you know AI, but is it like.

Speaker 2: 10:41

All the algorithms, so AI and machine learning and like they're all different levels and variations of it, right? So if we're going to think about the I'm going to speak to the customization of an individual within like a recruiting process, is that kind of where you're thinking on that? Okay, maybe, okay, so there are a couple of ways that it will look and make those educated decisions. Very often it's like the target example. It's like if you see this kind of behavior or a data point, what is the most common outcome or behavior that will come after that and so there's a level where you can say individuals who have this on their resume or who visit your website five times in a week are more likely. There's that predictive behavior, that of saying if they take these behaviors, they're more likely to take those behaviors. So you should prioritize your outreach, your sourcing, your conversation or, going back to the customization, then you can serve up something that says if someone has visited your website five times in the past week, they're probably closer to the decision-making stage. So start serving up really specific content and so it'll make decisions based on that behavior piece. There's also the whole idea of pixel tracking and cookies to say there are a lot of companies where they'll say we'll put a pixel on your website and then we will track where your users are elsewhere.

Speaker 2: 12:13

So I actually used this before, where I had access to a dashboard. That said, I actually used this before, where I had access to a dashboard. That said, the people that come to your website tend to be in this age demographic. They tend to watch these types of TV shows, they tend to drive these types of cars Like what cars they drove? Yeah, all from the behavior of their online. And I've kind of diverted from your original question.

Speaker 3: 12:35

No, no, but that's super interesting.

Speaker 2: 12:36

But if you have that, then all of a sudden you can say, okay, well, if someone is a 41-year-old, thank you. Like married woman who recently purchased a larger car.

Speaker 3: 12:53

Ah, mm-hmm.

Speaker 2: 12:55

Maybe she needs to ship her kids off to private school, and that's kind of taking the data and doing like a okay persona. Yeah, adjustment. So there's the behavior and there's the persona. Okay, interesting very interesting.

Speaker 3: 13:06

At what point, like does the data go bad?

Speaker 2: 13:09

so you know, like that's what. What about? I'm gonna ask, put it back to you from a recruiting perspective yeah, that that's what I was thinking about.

Speaker 3: 13:17

So you know, one thing that we do is we have people who've applied for gosh any job we've had posted for who knows how long. So we've got a massive database. Most companies do, and you can go back in and you can source for candidates based on keywords, kind of like your basic Boolean strings. But, like, at some point the data is just too old, it just it's not relevant anymore. What somebody did 12 years ago isn't really applicable for what I'm looking for, I think. Hubspot.

Speaker 2: 13:43

I read this a year ago I think, so it's probably changed and I may have the number wrong. Whitney, let's find the right one. Correction section potentially that every year or every six months your database depreciates by like 30%. So in that time frame, 30% of your information is no longer relevant. So I guess that's why you have to maintain your database, you have to keep it clean, you have to audit what's in there. Maybe that's. The other thing that's annoying is when people are working off of poor data.

Speaker 3: 14:22

Yes, so love that. You say that I was doing a HubSpot cleanup earlier today. Okay, and I'm sitting there going at it. I'm like, oh my gosh, I just can't take it. It's such a mess.

Speaker 2: 14:32

It's such a mess. So there really absolutely organized and clean.

Speaker 3: 14:35

Flawless, super clean, a plus to all of our users. No, no, not at all, not at all. Myself included. Yeah, okay, that's why you were doing the cleanup.

Speaker 2: 14:49

Yeah, exactly, Exactly. That is actually not a pet peeve. I am super proud of anytime someone goes into a system and they're like I'm just going to do a little bit of cleanup at a time. Oh so kudos to you.

Speaker 3: 14:54

Thank you so pet peeve of mine is dirty data. Like I will, I will get this and I will be like and I'll call like an all hands meeting and I'll be like are you aware that you do not have the first and last name, you only have their email address. That is not acceptable. So that's how you look at it is like you do the visual check yes, I do the visual check and I'm like how many missing pieces are we have? You know? I mean just simple things like here on data. You never want to send out an email to hello. First name.

Speaker 2: 15:23

Don't do it. Yes, oh, you know what? Honestly, don't do it. The bane of a marketer's existence Like hello, friend, yes, yeah, or then what really grinds my gears is then it's my fault as a marketer, oh yeah, that's my. Other thing is like when it comes to data and data usage and customization, it's a team effort.

Speaker 1: 15:47

It is a team effort, I will give human.

Speaker 2: 15:48

Tons of credit for this. Yeah, sales and marketing work together flawlessly. We truly are just trying to provide a great experience to everyone who interacts with us. I concur, and so don't blame me if the data is bad, if I don't own the data. Yeah, I'm trying here. I get it. I get it. I'm trying to customize without not being creepy.

Speaker 3: 16:07

So you know what? So here's another thing. This is where I think companies get themselves into trouble. It's trying to get too much data and data that they're not going to use. And we'll actually we'll take this back to a recruitment perspective. Going back to an application, like you know people, some people have super tedious applications where you have to complete ABC who's your cousin, joe's first reference and what was your second car? No, the worst.

Speaker 2: 16:28

Oh, sorry, side note. Please upload your resume. Great, upload my resume Now. Fill out every single field of all the information that you just uploaded on your resume.

Speaker 3: 16:39

Yeah, so like why do you need all this? What are you actually doing with this information? So that is a pet peeve of mine is when people just ask for more information than is necessary and they're getting data that they are not going to use for anything.

Speaker 2: 16:56

Well, so let me ask you this, because we talked about this. We talked about, like, throttling the pipeline I think it was our last process discussion where it's like you increase the burden on your candidates to throttle it. Should you give context as to why you're asking for certain types of information in an application?

Speaker 3: 17:18

No, no, no, okay, no, that just makes the application longer.

Speaker 2: 17:23

Well, I'm just thinking you were like saying what are you doing with all this data? Are you meaning from the candidate side or the employer side? So no, I mean.

Speaker 3: 17:29

I'm saying first of all, employers, just don't ask for irrelevant information from your candidates. You don't need to do that.

Speaker 2: 17:34

That is fair, even if we're trying to throttle, you know you don't need to do that. That is fair, Even if we're trying to throttle.

Speaker 3: 17:37

You know you don't need to do that. There's just some pieces of information that. Does it really matter where I went to high school at Like? Does it Well?

Speaker 2: 17:47

if I want to judge you Does it? Let me tell you something. It depends.

Speaker 3: 17:51

It was the same school that sent me a mailer for my faux child.

Speaker 2: 18:01

Are you serious? No, no, I'm not. I was like full circle here.

Speaker 3: 18:03

That is great customization. Public school, florida public school yeah.

Speaker 2: 18:06

No, but that's a great point, Because if you're asking for all this data and then you're not keeping it clean you're not keeping it clean, Then you're just making it messy.

Speaker 3: 18:15

And then what you're doing is you're actually putting yourselves at risk too, like, think of, like, the impacts of a data breach, you know.

Speaker 2: 18:20

Oh my gosh. So which are happening more and more?

Speaker 3: 18:23

No so, but there truly is a risk of you know, the more data you get, the more responsible you are for securing that data, and so you know why ask for information that you are not going to use.

Speaker 2: 18:35

So, and this is that you are not going to use, so, and this is going off of that.

Speaker 2: 18:43

At what point do we give up the illusion of privacy and just say selective access to my data? Yeah, right, because when you're born, you're given a social security number and, like, I still have my paper one. I don't know if they still give those out anymore. I don't know either, still give those out anymore. I don't know either. I have mine as well, but that I guess it's like everything's are being digitized and like our whole world is digital. Yeah, so like, at what point do we, like I I don't you know what I mean like I'm a big believer in privacy and right to date like I, and that's literally an american right that we believe I'm also a big fan of blissful ignorance too, and that's kind of where I'm like yeah security firm a few weeks ago that grounded like a million planes

Speaker 2: 19:30

yeah, yeah, that was not from an attack, though. That was poor coding, you're. You're right, though, but that's my point is saying we're kind of living in this world where, yeah, we believe in all of this like data protection. We still live in big data. Our whole world exists because of data. I don't know if that's a pet peeve or not. It's just an interesting consideration when we think about data and privacy, and individuals?

Speaker 3: 19:57

It definitely is. I did enjoy the times when I could have a conversation in my house with my husband and not get an ad for it on my cell phone an hour later, but at the same time I understand that I've given that up because I have Alexa and I have Google and I talk to them and I tell them what to do, and I know my Siri's listening to me, yeah, so you know.

Speaker 2: 20:18

I mean and see, and I do not have any of those, like I don't have any smart speakers and I don't have Siri turned on, like all the time, I still get those ads. Yeah, yeah, yeah, it's because there's somebody in, like all the time I still get those ads.

Speaker 3: 20:31

Yeah, yeah, yeah, mm-hmm, it's because there's somebody in your closet, you just don't know about them Dina.

Speaker 1: 20:36

Dina I've got your data.

Speaker 2: 20:39

I've got your data.

Speaker 3: 20:40

Honestly, I would Surf up this ad guys. I'm like as long as.

Speaker 1: 20:43

Dina can hang out with me you can have my data, it's fine.

Speaker 2: 20:52

Last thing, I um, I I uh last thing, I'll say on this, because I think that we're probably coming up on time. No, I would say so, is it? Um, it reminds me of parks and recreation. Okay, you watch that show. I have you got ron swanson. His like tipping point in the final season is like his whole thing is his own, like data privacy, and it's like to the extreme. And it gives me so much joy when he's just like living off the grid and I'm like that. That'd be nice man, I tell you.

Speaker 3: 21:12

But also not. So to be clear, I often I like to watch the um doomsday movies, just whatever they are you? Know, apocalypse, all those things um, I would not make it off the grid I am not making it. I am not prepared for that type of living.

Speaker 2: 21:26

So I could, I think you could, but my thing is there's a surviving and there's a thriving, yeah, and I'm willing to trade off my data for some of those. I don't know if it's right to call it like a personal luxury, but there is like existing in the world the way we are today doing the job I do. I have certain social media accounts that I want to delete so badly. I don't, can't.

Speaker 3: 21:54

No For my job. No, I get it.

Speaker 2: 21:54

And that's, I get a trade off, and that's the, that's my thriving. There we go. Cool, wonderful. Any last thoughts on data.

Speaker 3: 22:01

Or we started with pet peeves and then we just yeah, we just rolled, so just don't send me stuff, because I'm a woman of a certain age.

Speaker 1: 22:08

Honestly.

Speaker 3: 22:09

Please refine it a little bit more. Get some originality. People Send it to my husband.

Speaker 2: 22:15

Honestly yes. So I think if you're going to customize, there's certain assumptions I'm comfortable with you making but that is one that's Just, it's so passe. I will say, though, from a margin of error standpoint you're never going to get that Exceptional that is you are exceptional. You are the exceptional to the rule. There we go, love it, love it Whit. Oh, hot takes for hot topics.

Speaker 3: 22:49

Well.

Speaker 1: 22:50

I'm not sure about a hot take, but, um, the hot topic obviously the uh olympic summer games just wrapped up in paris.

Speaker 2: 22:57

So celine dion queen, forever I cried, love, I'm not gonna lie.

Speaker 1: 23:02

Um, I'm just gonna rattle off a few fun facts that people may not have known, and um, we're gonna wrap it up with a fun fact from Hillary.

Speaker 2: 23:12

I like how we started, like what are you annoyed about? And now we're like hooray Olympics, yeah.

Speaker 1: 23:19

So fun fact number one is the opening ceremony for the Paris Olympics drew nearly 29 million viewers.

Speaker 3: 23:28

So that's half as many as are listening to this. So that's pretty cool.

Speaker 2: 23:32

Okay, got it uh where's your data set on that one, dina? I'd love this is an emotional data response, well it's also nearly half as many viewers as the 2021 olympics that only drew 18 million viewers.

Speaker 3: 23:49

Okay, interesting Twice as many.

Speaker 1: 23:52

Twice as many. Correction section I don't know.

Speaker 2: 23:57

So people are a lot more interested in the Paris opening ceremonies than in Tokyo. Correct, interesting Celine Dion.

Speaker 1: 24:06

Yeah, that is.

Speaker 2: 24:07

I mean honestly. I think that's your answer.

Speaker 3: 24:09

That dress. It was a big deal yeah.

Speaker 1: 24:12

Number two, after Team USA's Emma Weber lost her swim cap during the women's 100 meter breaststroke.

Speaker 2: 24:20

That's the worst feeling as a swimmer.

Speaker 1: 24:22

Oh no, this is great. A hero came to call and he has now been dubbed Bob the Cap Catcher. He became a national icon.

Speaker 3: 24:31

I miss I missed that. Oh, I'll tell you, bob is like we were thinking of having bob come and speak here to the company how did no one tell me about bob? Oh my god, bob is such a big deal.

Speaker 1: 24:45

I am excited yeah straight face um so you know how the olympic winners they get a little box with their medal. Well, apparently inside is a poster designed by the parisian illustrator who did the main art. Um, it took him over 2 000 hours to create that main poster.

Speaker 2: 25:13

That's a long time. But here's the other thing the medals actually have a piece of the Eiffel Tower in it. Interesting, was that on your list? No, but thank you, so I was reading about it where, as they do maintenance work, pieces of the Eiffel Tower will come off and so they actually have bits of the Eiffel Tower in the medals Very cool. Well, why don't?

Speaker 1: 25:35

you end us off Hilary with how Flavor Flav made a debut at the Paralympics.

Speaker 3: 25:41

Wait, I don't want to let you end on that, because I just want to do two things very quick, okay, okay, shout out to Team Rhythmic Gymnastics and shout out to Synchronized Swimming.

Speaker 2: 25:51

Out to Team Rhythmic Gymnastics and shout out to Synchronized Swimming Best sports ever Done. I do really enjoy those, although I will say my favorite sport to watch is I think this was from the last Olympics Snoop.

Speaker 3: 26:06

Dogg doing commentary for dressage, because I love the horses. Yeah, dressage is.

Speaker 2: 26:09

Dressage Snoop Dogg, but um. So I found this out and it is like my new favorite olympic fact is that flaviflave personally sponsors the entire women's water polo team. I mean freaking awesome. Like he found out that they were working multiple jobs while trying to train. Yeah, he was like no, you guys are like literally the best in the world. So there are pictures of him. If you look from from the, from the Olympics in Paris, he's got his big like clock necklace but it's all like women's water polo branded.

Speaker 2: 26:36

Oh my God, it's amazing, fantastic.

Speaker 3: 26:38

I love it. Thank you, Flava Flav. Oh, if you want to be a guest on here, you can. He's already a guest. He's coming.

Speaker 2: 26:43

He is.

Speaker 3: 26:45

Okay, good, god, we've got a packed agenda. Man, things have really picked up here 58 million viewers, flavor, flav, it's true. Bob the Cap Catcher.

Speaker 1: 26:56

Hillary and I are going to do.

Speaker 3: 26:57

Celine Dion is coming, lady Gaga, gaga, pet peeve. We're weird, yeah, or like I don't know, delightful Gem. I think both yeah, something in between you, I don't know delightful gem.

Speaker 2: 27:11

I think both. Yeah, Something in between. You know what, though? Data does this to you?

Speaker 3: 27:15

It really does.

Speaker 2: 27:16

It gets you really excited about life. It really does Opens up a lot of possibilities.

Speaker 3: 27:19

It does, yeah, it's a good time, great times, tina, speaking of great times, great times, uh-huh. Thank you, oh, hillary, my pleasure, thank you Okay.

Speaker 2: 27:29

Till next time, till we meet again. Okay, bye.