Caitlin MacGregor is the CEO and Co-founder of Plum, a robust talent assessment platform that is revolutionizing how organizations manage talent. Caitlin is passionate about helping people realize their full potential and about helping companies see beyond resumes to understand what their employees are truly capable of achieving. In this episode, Caitlin talks about psychometric data, what it is, and how it can be a game-changer for companies looking to add innovative talent to their teams.
[0:00 – 3:08] Introduction
• Welcome, Caitlin!
• Today’s Topic: Revolutionizing How Global Enterprises Acquire and Manage Talent with Psychometric Data
[3:12 – 9:04] How Using Psychometric Data in Talent Management is Revolutionary
• What does it mean to use psychometric data?
• Why psychometric data drives leaders toward more objective and equitable talent decisions.
[9:04 – 21:36] Looking Beyond Resumes and Past Experiences When Hiring
• What does a resume really say about someone?
• How looking beyond resumes and past experiences can lead to innovative talent acquisition.
[21:36 – 29:33] How Psychometric Data Helps People Grow and Develop
• What you can learn about yourself from your own psychometric data.
• Why objective data is game-changing for organizations.
[29:34 – 32:20] Final Thoughts & Closing
• Episode summary
• Caitlin shares her closing thoughts
Connect with Caitlin:
Connect with Dwight:
Connect with David:
Resources:
- “You can line up a hundred people from the same school, with the same experience, and you cannot credit which of those hundred will be successful in a role versus the other. You have to look at people’s innate talents, their ability to innovate, communicate, and work well with others.”
- “We need to recognize that [talent management] is about adding objective, fair data into the process and being able to see people holistically.”
Announcer:
Here’s an experiment for you. Take passionate experts in human resource technology. Invite cross industry experts from inside and outside HR. Mix in what’s happening in people analytics today. Give them the technology to connect, hit record, core their discussions into a beaker, mix thoroughly. And voila, you get the HR data labs Podcast, where we explore the impact of data and analytics to your business. We may get passionate and even irreverent, but count on each episode challenging and enhancing your understanding of the way people data can be used to solve real world problems. Now, here’s your host, David Turetsky.
David Turetsky:
Hello, and welcome to the HR data labs podcast. I’m your host, David Turetsky. Like always, we try and find you fascinating people inside and outside the world of human resources to give you the latest on what’s happening with HR technology, HR data and HR analytics. Today we have with us Caitlin McGregor, who’s the CEO and co founder and plum. Hey, Caitlin, how are you?
Caitlin MacGregor:
Fine, thank you.
David Turetsky:
And like always, we have with us our co host, Dwight Brown. Hey, Dwight.
Dwight Brown:
Hey, David, how you doing?
David Turetsky:
Great. Caitlin, why don’t you give us a little bit of your background? And where are you coming from to talk to us about the world of plumb.
Caitlin MacGregor:
So I’m the CEO and co founder of software as a service platform that enables everyone to realize their full potential at work. We’ve started our company to take best practices from industrial organizational psychology, and figure out how to scale that so that you have a positive employee experience and get access to objective fair data that allows you to really realize people’s potential that may have been hidden before.
David Turetsky:
That’s outstanding. So one fun thing. If you know, Caitlin, you may not know that Caitlin was a windsurfing instructor. Caitlin, how did you become a wind surfing instructor.
Caitlin MacGregor:
So when I was early teen, my cousins from the US would come through every summer on their way to a family cottage, and they would stop in small town in southern Ontario and pick me up for a week and take me to their summer cottage. And they taught me how to winter. And after spending several years learning to win surf, I got to kind of get back to the community become a wind surf instructor and my claim to fame was anybody from seven years old to 70. I could get up and and went surfing within an hour.
David Turetsky:
You haven’t met me. So there you go. Well imagine that. Yeah, that would not be first of all, it’s a pretty picture. And second of all, they’d say, is that a Sasquatch trying to learn how to wind surf? Yeah, it would not be fun. Sorry for the mental image everyone.
Dwight Brown:
You let her who’s that guy flailing in the water all the time?
David Turetsky:
Well, that would definitely be the result. No offense to Caitlin. She might be the greatest instructor in the world and ain’t going to work with me. Sorry. So today’s topic is talking about how to revolutionize the global enterprise hire process and the ability to use psychometric data to help predict outcomes in the future. Let’s go into question number one. So Caitlin, what is so revolutionary about using psychometric data for talent management?
Caitlin MacGregor:
So I think there’s a couple of points that really has to be revolutionary. One is that psychometric assessments have been used for 30 years, but often by consultants that are using outdated personality models, outdated technology, I like to compare it to kind of the flip phone version. Now this is 2021, we’ve come a long way with being able to improve the quality of the science to have a gold standard around best practices for testing, problem solving ability, social intelligence, personality that you can’t gain, but also creating a really fantastic employee and candidate experience where they get value from the process, not a black box that they’re giving 25 minutes of their time. And in return, they’re learning a lot more about them, this data has become valuable for them as well. So I think really recognizing that science has come a long way. But the user experience has as well. And the scalability of it. You don’t have to use it in a single use case, one and done, that the data can be a foundational piece for every talent decision. So being able to take that data throughout the entire lifecycle of an employee and through every level of the organization is really something we haven’t seen in the industry up until now.
David Turetsky:
So Caitlin, then I guess the data has to mature as well as the person matures, and they have to constantly be asked either the same questions or new questions in order to be able to test how they’ve matured and how they’ve grown in that position, correct?
Caitlin MacGregor:
Actually, it’s not. So what changes constantly are the behavioral requirements of a role. So we’re hearing all the time from enterprise companies that as quickly as every six months, roles are changing. That’s what we need to keep up to date. That’s what we need to understand. It’s constantly evolving, but a person after the age of 23, ish, their priorities, the things that really allow them to thrive, and continue to provide exceptional results and things that come easily to them. And it gives them a sense of self worth, those are pretty stable throughout their career, and the things that drain them, and really lead to long term burnout, those things are also pretty stable. What changes are the coping strategies somebody has, What changes is this, the hard skills that they’ve been able to accumulate over time, but really what drives them and what drains them and allows them to be exceptional? Those things are quite consistent. And so it’s about understanding how they can apply those transferable innate talents to roles as they change and grow. And their readiness may change over time. But we’re looking at that potential if they were just given the opportunity, how likely are they to adapt and excel in this new opportunity?
David Turetsky:
So you’re saying that the assessment, once taken at the beginning, then doesn’t necessarily change. But that the role definitions and the way in which we’re measuring what the person is working on at the moment changes and needs to be kept up to date? And what’s the drumbeat? What’s the cadence where that data gets refreshed.
Caitlin MacGregor:
And so it’s like, any job that you’re looking at it six months later, and now the old has a new purpose. The roll is has new requirements, that’s a good time to be updating it, I like to think about it. Also, in terms of KPIs key performance indicators, we’ve all bought into the fact that best practices are to define success based on what goals you want somebody to accomplish in the role. Well, if you think that those KPIs for that role has changed, 12 months later, or 6 months later, 18 months later, then probably the behavioral requirements to change will have changed as well. And what we’re really focusing on is quantifying those KPIs, the key behavioral indicators that define success for a role. And soon as you’re depressed, why not take an eight minute assessment instead, to quantify those behaviors and rely on subjective job description?
David Turetsky:
Typically, who are the people you’re asking about those behaviors that you’re asking managers to do it? Are you asking HR to do it? Is it someone who’s an IO? Who were the people who have to then judge what those behaviors are for success?
Caitlin MacGregor:
Yeah, so best practices in the field bio psychology, this is a standard job analysis, where you would have industrial organizational psychologists come in and interview three to eight job experts. And the question is, who the job expert? Well, manager is often the same person that was set the KPIs, so they have the same knowledge to be able to prioritize the KPIs, key behavioral indicators, but manage there’s only one data point. So who else 360 view on that roll? Well, maybe a couple of top performers got the quote, number to say, hey, what if you were to hire your best friend? What would you tell them to do to please the boss, and then maybe that HR business partner, or maybe that manager, you want to kind of get this view of who would sit on an interview panel, for that new person coming in to say if they could definitely meet their requirements. If you get three to eight people with these different perspectives on the role, and they’re all aligned, they all say, hey, yes, you need somebody who’s really good at execution and innovation and teamwork. And there you have that alignment. When you get somebody into the role that a 94 match or a 98 match, then you have a great deal of confidence that they have the behavioral requirements that you’re looking for.
David Turetsky:
So let me ask a different question. Caitlin. Is it important to look at resumes or to look at other past experience when you’re hiring or promoting people?
Caitlin MacGregor:
I like to think of it like reference check. We always want to do reference checks. We want more data. Of course, it’s just a question of where you do it in the process. And I think this is the dirty little secret in our industry, is that we’ve got decades of proof showing that where you went to school where you previously worked, that historical view of where somebody has already been that there’s two problems with it. One is embedded with the systemic barriers and biases that dictate access to education, internships, how fast you progress in your career, but also, statistically, it doesn’t correlate with future success. You can line up 100 people from the same school with the same experience. And you cannot predict which of those hundreds will be successful in a role versus the others. You have to look at people’s innate talents, their ability to innovate, communicate, work well with others. That’s what defines long term success. future work. we’ve all read the studies before the pandemic, everything was about the future of work and transferable soft skills. So we’ve been talking about it, but the point that you can actually measure it. And by measuring those transferable skills, they are four times more accurate at predicting long term success. So wouldn’t you want to start your process with the most predictive data, and then bring in the resumes, after you’re already focusing on those people with the greatest potential, use the resumes to talk about readiness, after those tend to hit the ground running? Do they have the experience that you want the salary requirements, you won’t use that data later, to help you continue to narrow down the people but once you’re looking at and speaking with the people that have the greatest potential for long term success?
David Turetsky:
Yeah, Caitlin I think the problem is right now that equations flipped, though, you have to get the resume past those people who are the gatekeepers, because you’ll never get to assess someone, because the gatekeeper whether it’s the AI, who’s the new talent expert, who tries to find the right keywords. And when they don’t see enough of a keyword density, they they toss you in the reject pile, and you go on to the next one. So how do they flip the equation and start finding people before they actually even see the resume?
Caitlin MacGregor:
Well, it takes bold leaders, often from purpose driven organizations that have realized that Gone are the days of understanding employees nearly as a collection of current skills and past experiences. So we know that employees are so much more than that. And we know that employees want to be seen for their full potential. So this is an opportunity for companies to differentiate and say, we want to understand you holistically. As part of that, we’re going to give you data on yourself as to what allows you to thrive and where your flourish more. But you can’t do that passively. You can’t scrape resumes and get that insight. You can’t look at social media profiles. This is where you know, this, this entire field of science and industrial organizational psychology, you have to assess it, you need a psychometric assessment. And yes, it’s 25 minutes, but it takes less time then building a whole LinkedIn profile. And that one data set can be used for all these different use cases we just been talking about at the beginning. If you’re applying for a job, how do you stand out with 1000 other people? Well, that gives you a chance to truly stand out. But you can use that data, then with that person, you can use that data to help with professional development with manager one on one conversations with internal mobility to identify your future leaders. So it’s a small price to pay more time commitment, and then that person is now fully seen and has that data to really drive their own career as well.
David Turetsky:
But it does take that change to go from the resume based hiring process to what what’s the alternative? How do you find people in that case? Do people have to have these assessments banked as they are if you think about 23andme, like our our DNA, our skills based DNA, and that if I if a company needs somebody who has my particular I don’t even use the word genetics, but if they need my genetics, that they go to this database, they look for those particular skills on those particular nodes in the job DNA. And that’s the people that they select,
Caitlin MacGregor:
I think long term, this is the other side of the coin, LinkedIn. LinkedIn has given us that hard skills and that historical view, I think, to be able to complement that with this additional missing data set. Right? What’s happening right now is companies, it’s part of the application, it’s part of the employee experience. So if you want to apply, you don’t have to apply to a single job or company anymore, you can just apply to that company. And the company can use this data to then say, hey, absolutely. I don’t know if you’ve been thinking about this. I know your background and underwriting, but you think a fantastic product manager, are you interested in having that conversation? And so it really changes how you’re applying, you’re applying with a single assessment, or you’re an employee. And when you go through your next, you know, professional development conversation, Hey, take this 25 minute assessment. And now we can have a really rich, personalized conversation and we can identify opportunities that you may not even know exist in the organization, we can get away from the Marco Polo effect of only getting referred by my bosses that have worked with you and now it’s show your talents to anybody inside your organization is looking for what makes you unique.
Dwight Brown:
So for those listeners that may be wondering how does this differ from some of the assessments you go to indeed.com or zip recruiter and they advertise that they have a lot of assessments that can be used. How does this differ? And is there a way to mesh that into those current processes?
Caitlin MacGregor:
Yeah, it’s a really great question. So first and foremost, it’s the quality of the science. So you can’t get these accurate, valid, objective results in 90 seconds, or 15 minutes, you really need the 20 to 25 minutes minimum, to get enough data to find that consistency. And to get the individual parts. It’s not just personality, you also need that problem solving. That’s social intelligence. You know, there’s no language in math, but we’re still figuring out how do you solve abstract problems? How do you solve people problems? And how do you prioritize their behavior in a way that you can’t fake or game. And so we work with a lot of mid market and enterprise companies, specifically, that the science and the validity is the number one priority, especially for legal reasons. When you’re using this for selection, even internal mobility selection, you have to make sure that is job relevant. And so that proper talked about earlier in eight minutes, that’s giving you your job relevant. But if you have this office down catalogue, not only have they been proven not be accurate, but they’re often not job relevant to that exact company. So the first thing that differentiates us is the quality of the science. The second thing is that because it cannot be any role, even as those roles update, you get to use it in much greater scenarios. Most companies do an internal benchmark that require 50 to 100 people have all done the same jobs. So it doesn’t scale. Beyond that bottom 20% of your organization or even a follow you, or they use core very common into a job analysis. It’s very expensive, and can only work on the top 10% of organizations because of how exploited the middle 70% of organizations don’t actually have data on the behavioral needs of their role. And so a lot of these internal mobility use cases are looking at even you know, creating an earlier pipeline for succession planning, or looking at emerging leaders, leadership potential on early talent to fill a more diverse pipeline that data isn’t, isn’t really touching the middle of 70% of employees. So yes, it might help maybe with one role that you’re hiring for, but you’re not going to get that data being repurposed for all these different use cases. And you’re not going to be happy with the quality and validity of the data that we’re providing. Those are the biggest things that are really standing out for us.
David Turetsky:
What jobs do you typically see that are the best candidates for this? Or do you think it’s all types of jobs?
Caitlin MacGregor:
For now, I think professional services mostly because of the length of the assessment, I still find that it hospitality and retail, they want the very quick validity isn’t the top of of the list of needs for them. So we find that professional roles, white collar roles tend to be what our customers use this for primarily, but at all levels of the organization. It’s this idea that it creates a common language that if you and your manager, say, Hey, I can see that teamwork is something that really drains you, I’m going to I’m going to make the effort to make sure that we’re being mindful about the teamwork, time that we’re spending, as I’m going to fill in some of that heavy lifting to that, and I’ll work with you to create coping strategies, if they’re using the same common language, it really creates this new way of really supporting people. So we’re seeing across all levels, we’re seeing it mostly in professional roles. And we’re seeing it in industries that are going through transformation. And that’s a really broad set of categories of who’s going through transformation, and who’s purpose driven, where they’re really focusing on that employee experience and giving back to their employee, banks and insurance companies and kind of industries going through transformation.
David Turetsky:
One of the problems that we typically see, especially on this podcast, but across consulting activities that we do is data is typically a problem for clients. And it seems like this is going to be one of those things where data cleanup is a very critical issue prior to even collecting this data, because you have to connect this data to data that you have about the employee in order to be able to make this useful, right. So what becomes the priority the collection of the data or the connection of the data, so the data that they have on the back end?
Caitlin MacGregor:
I think this is a really big question that people are trying to understand right now. For us. First and foremost, we believe that data is completely missing from the decision making process. And so our first priority, it really does sometimes feel like you get to put on like your superhero and you get to put on special expert glasses and now you see the world entirely different and you can see people you never saw before. We just want to get those glasses on to everybody as quickly as possible so they can see what they’ve been missing out on and that we can really enable people to realize their full potential and and we think that this could change businesses and change people’s lives and have a real impact. So for us our main priority is is getting the data out there. And then once you start using it, then it becomes Okay, well, how do I want to marry this with other data, and then you start to realize where you are prioritizing other data maybe needs to change. And honestly, the systems that exist out there weren’t built to bring in the rich visualization and the intuitiveness that we’ve created in our platform. So a lot of our clients want to get started right away, and they can, they can hit the ground running, using it right away getting all of that. And then we handle the integrations and the data merging as a secondary issue. But it’s never gotten in the way we always get to that, after the value is fully realized. In some cases, it’s done upfront, for sure. And we always find ways through that with enterprise companies, just the volume of data that they’re using. Sometimes that’s a prerequisite. But I think the real issue is getting this data huge, first and foremost. And then we can figure out the workflow and the integrations and the marrying of the data.
David Turetsky:
Our experience has been that you can’t even identify the people to take the assessments because sometimes the descriptions are really bad, or the the job titles don’t tell you what the people really do. So you kind of don’t even know what they really are, who they are, until you fix that data first. And then you can go on to the collecting data on them. But I understand what your point is. They’re they’re basically two independent pieces. Because the richness of the data that you’re bringing, isn’t in the job description today. And it’s not in any of the assessments that they may have taken already. It’s something that new.
Caitlin MacGregor:
Exactly, you nailed it.
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David Turetsky:
So let’s move on to the third question, if I might, which is how can you actually use psychometric data to help identify people and grow them to develop into future leaders? How do you do that? What’s the process steps?
Caitlin MacGregor:
Yeah, this is a piece of the puzzle that I think is really exciting for me, because I haven’t seen the industry do it this way. Typically, you see, you know, big companies in the consulting space focusing on leadership potential, where they’ll come in with sometimes three different assessments or three different logins. And they’ll focus on directors and above that have already been identified for some sort of succession plan. And they haven’t taken assessment to then say, hey, do you have the foundational building blocks to be successful as a leader? Do you have that leadership potential? And I think that’s the biggest opportunity is really saying, Where do you have the greatest diversity in an organization, it’s often all the numbers. So there’s greater diversity earlier in the talent lifecycle that in those more junior roles, you tend to have greater diversity. And as you move up the ranks and start to lose that diversity, there’s a real opportunity to identify that leadership potential much earlier in the organization. So instead of saying, well, this is my pool of employees that have been nominated by their managers that they think have future leadership potential, let’s give it to every single employee through the company, let them take a 25 minute assessment, immediately get their own professional development guide that talks about what drives them, and train them gives them a roadmap for their own development. And on the back end, let’s look to see which ones of them have those foundational dimensions that predict long term leadership potential, and not just leaders, but your organization, but across the board that has been proven, again, from industrial organizational psychology to see these foundational dimensions. And let’s give everybody that opportunity. And then the company can focus on the top 10% or top 25%, to actually invest in giving them the on the job experience to develop that leadership, but also be learning and development to do it so that you can start to build that sense strength of future leaders. Right from the beginning with the most diverse talent, we’re spending a lot of energy trying to bring into their talent, which is fantastic. But the next step is how do you take the talent you have within your organization and nurture it and bring those diverse, early talents into the process. And so our leadership potential is really about identifying at all levels, those foundational dimensions.
David Turetsky:
But Caitlin, let me push back on you a little. One of the clear things you said before was that you should be also looking at people outside your organization who may actually be interested in looking at opportunities in your organization. So wouldn’t you want to develop not just the future leaders who are internal but also looking at the potential for people who’ve identified themselves as being potential applicants or potential hires, and ask them to take an assessment and then then be also considered for the spots that become available. And I’m not just talking about for succession planning purposes because obviously, they would be But for roles that may open up that may require their specific set of skills.
Caitlin MacGregor:
Absolutely, the idea is that once you have this data, you can just keep looking at it from different angles, every talent decision you would ever want to make, you now have this data to help enrich it. So you’re not just necessarily hiring that person in the organization for the role they have today, you now have that data to say, hey, what other roles right away, what I see that they could potentially move into. This is where you see roles that have massive labor shortage, we know there aren’t enough people in the world that have backgrounds in cyber security, this is also an opportunity to say, Hey, I see that somebody could be amazing in this field, I’m going to hire them in and I’m going to upskill them within the walls of the organization, I’m going to fill the labor shortage that way, or I’m going to bring them in for this role. And now I see that they also, if I worked on them, I could not only move them into being a software developer, but that’s my future Scrum Master. And that’s gonna be my future lead, develop like team lead, because they also, in addition to developing their coding skills, we’re going to develop simultaneously their management skills, because they have that free big Foundation, that will just make it a fantastic ROI. For the company and the individual, this still comes back to like, what drives people, what comes naturally, where did they excel, it’s not that other people couldn’t be trained to be leaders, but they’re looking for who is going to feel great at the end of the day, because they’ve spent the majority of their time leading others, versus there are people that will feel great at the end of the day, because they felt really complex problems as part of a team or individually. But leading was not the thing that was going to fill their bucket. So you have this data, and you can apply it, every single human being that now has put their hand up to say I want to be part of your company, or it’s already investing your time being an employee.
Dwight Brown:
So there are two, there are really two key aspects that are being addressed here. Number one, candidates come in and day one, they sort of have a career path mapped out. But it’s a very personalized career path to their their talents, skills, and abilities. And then the other dimension of this is also the organizational career path, if you will, everybody is part of this overall vision. And it helps the organization to be able to move the chess pieces accordingly. As opposed to always kind of working on instinct and guesswork. In terms of how to fill these positions who might be next in these positions. Is that accurate?
Caitlin MacGregor:
Yes, is 100% accurate. And I would also say that once you have this data on your applicant pool, you can start to say, Hmm, we’re getting a lot of applicants like this. But we’re not getting actually a lot of people that are innovative, are we attracting the people that we need for the type of roles that are going to be coming up, or looking in the organization and saying, We’ve got some really innovative projects coming up, who are the most innovative people that I should be having are looking into, and we need more of those, it’s really an understanding of how to make sure you have a balanced workforce as well, or that you can lean in on certain areas that you want to develop in your organization. You can also get that, you know, holistic view of where there are trends in your own organization and potential gaps you want to start working on so that three years from now you have a better mix of what you’re looking for.
David Turetsky:
So Caitlin, I’m not trying to presuppose here, but can someone who’s listening to this, say, take the Plum assessment and see something there, you know, see some magic in there and then be able to utilize that for themselves?
Caitlin MacGregor:
Absolutely. So this is one of the things that we think is really important is giving people the opportunity have that self awareness. So people can go right now on to the Internet, and type in use.plum.io/tg, which is for talent, guys. And it’ll allow you to create your own phone profile for free. And normally, you only get your top three talents. But we with this, you’ve got from.io/tg, you’ll get your full talent guide all kinds of your talents, really see what drive in brand new. And you can use that and you can promote it on your LinkedIn, your top talent, you can share it with your manager or your spouse and have a conversation about it and compare now
David Turetsky:
Well Dwight and I are definitely going to take it afterwards and then we’ll compare notes and let you know. So thank you very much, Caitlin, I think we learned a tremendous amount about your platform. We learned about what is so revolutionary about psychometric data in the world of talent management. We talked about its importance and being able to look at people from the assessment, not looking at it from the context of the resume into what are they bringing to the table and potentially even before we actually See the resume, looking at who they are and what they are through the assessment. And the last thing we talked about is how can you actually use psychometric data in place of the gut feel to grow future leaders? Is there anything else that you wanted to add? Before we close?
Caitlin MacGregor:
I think that we need to really recognize that this is about adding objective fair data in the process and being able to see people holistically and define it. Now. I know it’s a bold move. I know it’s different. But we’ve got the science, we’ve got the technology to be able to do it. What are we waiting for it? Last 18 months hasn’t caught up anything, because this is the time to really embrace people who they fully truly are not just a collection of hard skills and past experience. Sure.
David Turetsky:
Cool, Dwight, anything else?
Dwight Brown:
No, this has been fascinating. It really has challenged me to look at the traditional way of doing things because I’ve been at this for many years. And that’s what my mindset is. So the idea of being able to identify my talents, skills and abilities, my my KBIs, and as you talked about, a little bit mind bending.
David Turetsky:
We’re definitely gonna want to, we definitely want to rip up our resumes now. Right, right. Just take the Yeah. On to take the pom assessments that Well, again, thank you very much, Dwight.
Dwight Brown:
Thanks, David.
David Turetsky:
Thanks, Caitlin.
Caitlin MacGregor:
Thank you so much for having me.
David Turetsky:
And thank you for listening. And if you liked this episode, please hit the subscribe button. And if you know somebody who might find use of this episode, please do forward it to them. And if you have any comments or questions, please leave it to us on your favorite social media platform or go to Turetsky Consulting comm slash podcast and let us know your thoughts. Thank you very much. Take care and stay safe.
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