Anne Fulton – Companies Remaining Fit and Agile to Thrive in Modern Times

Connect with Anne:

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Connect with Dwight:

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• dwight.brown@salary.com

Connect with David:

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• david.turetsky@salary.com

Podcast Manager, Karissa Harris:

• HRDataLabs@salary.com

 

Production by Affogato Media

Resources:

• Compensation Consulting Services
• Anne's Books
• Fuel50
• HR Data Labs Season 6 Episode 9
• HR Data Labs Season 6 Episode 7

• “We have an opportunity as leaders to ask powerful questions that allow people to coach themselves toward answers and a focus on solutions.”
• “Every organizations needs to think about how it’s going to create safety for the organization and safety for the individuals [when using new AI technologies].”

Announcer: 0:02

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 for 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, that 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: 0:46

Hello, and welcome to the HR Data Labs podcast. I'm your host, David Turetsky. Like always, we try and find very fun, interesting, exciting people to talk to inside and outside the world of HR, about what's happening in the world of HR today. Today, we have with us a fascinating guest, who's going to give us some really intriguing insights Anne Fulton who is the CEO and founder of Fuel50. Hello Anne, how are you?

 

Anne Fulton: 1:10

Oh, Hi, David. Great to be on the call today.

 

David Turetsky: 1:13

Anne, why don't you give us a little bit more about your background?

 

Anne Fulton: 1:16

Yes, so not only CEO and founder of Fuel50. But I think really my story is, I have a lifelong commitment to trying to predict careers for people around the world. It's been my lifelong passion since the age of 14. And that led me to become an organizational psychologist, builder of psychometric tests, author of two books with the second one out of the talent revolution from Forbes on August the eighth. So yeah, predicting careers is my game.

 

David Turetsky: 1:42

We'll put links to those books in the show notes so people could reference them to get access to them. Okay?

 

Anne Fulton: 1:50

Super.

 

David Turetsky: 1:51

So Anne, we're gonna go into your topic in a minute. But before we do, what's one fun thing that no one knows about Anne Fulton?

 

Anne Fulton: 1:59

On the note of that career predictions, my first career prediction was that it was suggested that I could become a funeral director at age 14. So there's given two career choices funeral director or vocational guidance counselor. And that's yeah, that sparked my lifelong interest in where an earth did that science come from that would suggest I've could be an undertaker, a funeral director? What's the science behind it? And could I possibly do better at career predicting than that pencil and paper test?

 

David Turetsky: 2:31

Now you weren't wearing goth clothing. You weren't like dressing up Halloween all parts of the year? They didn't. They didn't have that. Right? There wasn't they weren't bringing that data into the equation?

 

Anne Fulton: 2:42

No, it was a very antiquated little pencil and paper test that you self scored. But presumably, there was some science behind the relationship between careers guidance counseling and funeral directors. So it started this lifelong fascination of how could I possibly do a better job of career prediction for people around the world?

 

David Turetsky: 3:01

That is a fascinating story. And one, which I think people are now thinking because I'm doing the same thing. What did my guidance counselor say I should be when I was a little kid? And for the life of me, I can't remember. But I'll get back to you on that Anne, I'll tell everybody.

 

Anne Fulton: 3:18

I've heard some great stories. One I remember was a couple of twins, young men, age 15. One was predicted according to the science we were using at the time, as a bricklayer, and his brother was predicted to be a TV producer. And I was thinking, how am I going to explain these results to his parents both ended up in these careers. One's a tradie. And then the other one is currently producing a TV show that is absolutely memorable. And yeah, was was exceeding my expectations in terms of that career prediction.

 

David Turetsky: 3:53

Wow, that's amazing! So Anne, our topic for today is thrive or survive organizational resilience, how to go from surviving to thriving? So Anne, our first question is, what's the journey from survive to thrive in this economic era?

 

Anne Fulton: 4:17

Yeah, great question. And I think that we all know that there are challenges at the moment economically, as you know, you know, do we have recession globally? Do we have recession in the USA? If so, what's it going to look like? And how quickly are organizations kind of recover from this recessionary era? So it's something that many organizations are facing. And I think the way that we're thinking about it is around focusing on organizational fitness. So, you know, what does a fit organization need to look like, you know, through this era of optimization? So I'd like to start with a question for you, David. Reversed, psychology here. And, you know, I'd love to understand, you know, what does fit mean to you personally, you know, how do you feel when you're fit and on your game? What's that mean to you?

 

David Turetsky: 5:05

Well, so I think it's a holistic fitness, I think there's a mental fitness, there's a physical fitness, and there's actually even an economic fitness. And that whole being, and maybe you can you even throw in there social fitness as well. But there's that whole being or whole purpose that everything is working in concert, that there are balanced levels, there are balances in you know, the different pieces of your life, so that you feel like a whole person, that you feel your relationships, you feel your interpersonal relations, you feel your you feel strength, you feel you feel happy, there's a balance to things. So if I, if I can borrow from Star Wars, you know, there's a balance in the force that, you know, drives you. And so to me, when you ask, you know, are you fit? Or how do you feel about fitness? I feel like fitness is something that it can't be judged in isolation of physical versus mental versus other pieces. It has to be judged as a holistic thing. Does that make sense?

 

Anne Fulton: 6:12

Absolutely. And I love that definition. And it's exactly how we need to start thinking about fitness for organizations. But you know, I guess for me, personally, you know, like your holistic, it's really important that you have the sense of being on your game, you're feeling well, you're ready for what challenges are ahead, you're prepared, you you are planned, you've done your best to, you know, to be prepared for whatever is ahead of you. You know, there's an element of caretaking, your your nutrition, your whatever your goal might be, you know, your overall wellness, your rest your sleeping, and, you know, how are you tackling whatever goal it might be in terms of your own personal fitness. So, you know, I love your Star Wars analogy in terms of the feeling the force. So we think about fitness in terms of our own organization. So, fit is one of our values, right, so we have a few values for our organization of Fuel50 around the letter F. So fast, fun, fantastic, and fuely, you know, four of our values, but the fifth value is fit. And what we talk about for our organization in terms of being fit, it's actually rather than necessarily being fast, it's been fit for purpose. Sometimes we need to move fast, sometimes we need to move slow and carefully. But we also caretake across the entire organization, everyone's wellness, their own personal resilience, you know, having a balance. So we so we have what we call refuel days, you know, for everyone wants a quarter. And it's really around caretaking individuals to allow each and every person in our organization to be at their best. So if we were to then apply, you know, that kind of thinking around fitness, you know, whether it's a J&J or a United Nations or a Meta, you know, those organizations, what does fit mean to them in terms of their own organizational resilience, and wellness and allowing each and every person to be at their best. So bringing in a marketplace mentality that allows every individual across that organization to be ready for a future and it may be an unknown future, but to be reskilling, to be investing in their learning, to be on their game, to have goal alignment with the organization so you can see what the organization's big picture goals are. And what am I doing to contribute towards that goal, so that each and every individual is is in effect optimized to be at their best. And if we can do that one person at a time, we're able to scale that into an organization. And then what we can see from those organizations is when we scale one person at a time, we can we can have everyone on a learning journey towards a career path. And identifying the skill gaps on that journey. There's multiple ways that you might be able to tackle a career goal. But for each step along the journey, you've got your defined learning needs, reskilling that will be personalized to you. But for every single learning need or skill development requirement, you are connected to a mentor, you're connected to a coach, you're connected to learning assets, online learning, you're connected to stretch assignments and gigs and projects that are going to allow you to develop that that skill for the future of both yourself and that organization. So true organizational alignment, doing it one person at a time. And I think just on that point, the last thing that I would say around that is one of my favorite sayings is snowflakes can turn into avalanches. And what we mean by that is snowflake you know if you think of every individual creates a snowball if we get a whole team aligned, values aligned and thinking about the mission and working towards that mission and goal. And next thing you know, you've got multiple snowballs across an organization. And you know, then we're able to create that impact were one of our customers first in the world to develop a COVID 19 test. Not only were they redeploying people fast for a world crisis of trying to solve this global problem, so that redeploying people using, you know, a Fuel gigs marketplace, but also, in the six months prior to that moment in time, we had 375,000 reskilling actions taken by employees across their organization. So this is truly a fit organization that was resilient, agile and able to respond to a global crisis in a way that was absolutely meaningful, one person at a time, but collectively, agile, fast, quick to solve the organization's mission at that moment in time.

 

David Turetsky: 10:55

One of the things that strikes me though Anne, is that that agility has with it a tax. And what I mean by that is, there's a ton of transitions that get made, there's a ton of actions that happen. Even the mentoring takes a tremendous amount of work, to ensure there's alignment and to ensure that there's data that tracks all of those things. Because one of the things that's great about agile is that it's, it enables an organization to react to the market. But one of the other problems about agile is that so often, artifacts that had happened during agility tend to get lost, because agile kind of assumes or agile excuses, I think, is a better word, the lack of transparency in that. So I guess the question I have for you is that does the agility lead to much more data? And then a maintenance and that kind of being a tax on the agility?

 

Anne Fulton: 11:59

Absolutely amazing question. And, you know, do agree that we need to talk about that. And I love the use case of mentoring. For me as an individual, you know, who might have the right skills and experience that's going to help me with a particular skill gap. So you know, who might I best work with and possibly a mentoring transaction might be for a particular skill for, you know, defined period of time, three months, mentor matching is happen, you know, is supported by AI as you're matched with a mentor, checking their availability, able to then track, most importantly, the outcomes. So the example that I often use is Excel, right? I love Excel, you know, I could spend days, you know, fiddling around with spreadsheets, it's not necessarily my top talent. But, you know, if I, if I have an engagement with my mentoring engagement with my CFO who's an absolute wiz, I've got three questions or three skill development areas within Excel, I can have a before and after, you know, here's my skill level before I can ask my manager, I can ask my mentor for, you know, what's my progress against, you know, particular skills that I'm developing, and we get that through 360 feedback, so that you can see, you know, what gains are there at an individual level, but also at aggregate across an organization as we invest in those learning moments, whether it's mentoring or coaching or stretch assignments? What's the skill state before? And what's the skill state after? So an organization can start to get a lens across the entire employee population? Of what skills are developing? What skills are emerging? What skills gaps do we have? And how are our people at aggregate, you know, learning and growing that skill set that we need as an organization for the future?

 

Announcer: 13:46

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David Turetsky: 13:57

So if there are three things HR practitioners should be investing in today, what do you think they would be?

 

Anne Fulton: 14:03

Obviously, you know, from, you know, that we think about it from an employee empowerment level. You know, we've seen quite a shift to democratic principles now, as a result of, you know, Me Too movement and Black Lives Matter. So that employee voice is really important and empowering your employees to be at their best would be number one. I think number two was thinking about bringing leaders on that journey. So you know, supporting your leaders to be able to have great coaching conversations, to be able to ensure that you've got goal and values alignment across the organization, but also that you've got a really robust skills architecture across the organization so that you're able to do this at the macro economic level. So three things we think about, you know, focusing on the employee, supporting the leaders to do a great job of people enablement on their team, and then you know, thinking about things at the aggregate level. From the organization skills, intelligence point of view.

 

David Turetsky: 15:02

Those are three very important things. But those are three very difficult things especially to do together. Because the more empowerment you do at the employee level, the more you need to grow the skills of your leaders to be able to listen better to act on those issues that they find or that they're listening for. And then you mentioned about the career framework and being able to build on organizational skills. That's tough, especially in large organizations to build those taxonomies appropriately, and keep them up to speed, especially an agile workforce in an agile environment. So how does HR practitioner actually enable the organization? What practical steps can they do today? Because those are three fascinating, wonderful things. But gosh, there's a lot of work each one of those things requires!

 

Anne Fulton: 15:57

Yes, there's no question. And I think that if we thinking about, you know, career frameworks, and what's needed to build that, you know, we're on the cusp of absolute breakthroughs, you know, with generative AI and large learning machine models, and, you know, chat GPT is transforming everything that we're doing. So wonderful opportunities to build out agile architectures, that you know, will no longer need the kind of updating that, you know, we had to do manually, you know, taking five years to build out a skills architecture, you know, can now be done, you know, really quickly and powerfully leveraging some of those AI technologies.

 

David Turetsky: 16:34

So let me let me kind of pull back to the employee empowerment piece, because it's really critical in this environment, to be able to listen to people and to hear their issues, and to be able to utilize the beauty of the differences that people have. Listening to them is a critical skill. And the reason why I'm bringing this back up again, is because I often find that one of those, and maybe I'm guilty of this as well, probably more so than anybody else. Listening skills are not key to everybody. But leaders, especially so. So let me let me pull on that thread a little bit more. How do you develop leaders, especially leaders who are great, and most every other way, to be able to listen to the world have the employee empowerment today, and be able to deal with issues that they've never really had to deal with before?

 

Anne Fulton: 17:29

Absolutely, I mean, every I mean, as the world changes, and evolves, and, you know, we survive challenge after challenge, you know, whether it's a pandemic, you know, that we've all experienced, in recent times, return to work, hybrid work, you know, methodologies, and, you know, now economic challenges requiring, you know, optimization of an organization. So, how do you support people through those challenges? And I think, you know, we have an opportunity, as leaders, you know, to ask powerful questions that allow people to coach themselves almost to answers and bring that kind of solution focus. So, you know, I'm sure most of us are, you know, playing with AI today, but, you know, as you're heading into a coaching conversation, you know, it's very easy to go and visit chat GPT and say, you know, what are three great questions that I could be asking, you know, to support my employee on XYZ, so, you know, we can, we can leverage some of these technologies. And I think that I'm not suggesting for a minute that AI is going to replace us as humans, I think, you know, anytime that we're, you know, contacting an organization for some help and support, don't we love that moment, when we get through to a human, you know, as opposed to, you know, going through multiple threads of press one for this, and three for that. And, you know, by the time you've got through the list, you've forgotten what the order was, I know, we all have that moment of joy when we actually connect with our employees. So, you know, going into any employee conversation, taking on, you know, three questions that are going to help this employee, you know, move forward in their thinking about whether it's a technical problem, or, you know, whether it's a, you know, a more important question, or a personal challenge that they're facing between, you know, work life balance. So, I think, you know, going and prepared with three great open questions and to every conversation that's going to help progress that employee's thinking, and empowerment, you know, it's a really powerful, simple way of building empowerment one person at a time across your team, but you know, exponentially as we've got people thinking about their own solutions, and with the support of their leaders can be a really powerful move forward towards empowerment.

 

David Turetsky: 19:36

Hey, are you listening to this and thinking to yourself, Man, I wish I could talk to David about this. Well, you're in luck. We have a special offer for listeners of the HR data labs podcast, a free half hour call with me about any of the topics we cover, on the podcast or whatever is on your mind. Go to Salary.com/HRDLconsulting, to schedule your free Are you 30 minute call today! We've been talking about AI. Let's dive into the third question, which is, how should HR be thinking about AI today? And you brought up a couple of really great examples. And one of the things I find fascinating about things like chat GPT is that, and whether it's Siri or whether it's Alexa, we, we struggle today, right now, we struggle as users of those technologies, with the interface between us and them. Obviously, it's a brilliant interface. And we'll get there. But one of the things I've seen, and I'm going to turn it over to you to try and find the answer here is, why are people being so strange about it? Because they're afraid of the AI, when they don't know how to use it, yet. They haven't been trained on how to get the most out of it. Like, even Siri, no one knows how to really use Siri or Alexa, then they're mostly afraid of it, because they're on conversations when they bring up a word that kind of sounds like that. And she pipes up. So So when are we going to get to that, that goal of being able to be more of a better, more informed consumer of AI?

 

Anne Fulton: 21:15

Yeah, and I agree, I mean, we're on the cusp, you know, of an incredible revolution and technologies, you know, this is this is going to be as disruptive as that moment in time when we experienced the internet emerging. And we had the green screen and, you know, incredible technology that was at our fingertips, but everyone was a bit confused on how to use it. And I think we're at that moment in time, that we're that we're all learning. But I also watch my three year old grandson use Alexa and go Alexa, play the Wiggles, play me Sesame Street or you know, whatever he wants to listen to, Lyle the Crocodile. But it's amazing, just the the command that a three year old can have of that technology while we're all sitting there thinking, how else can I be using this technology myself? So

 

David Turetsky: 22:03

But that's a brilliant example of that though Anne, which is that we use it very transactionally. Which is I'll ask it if, I'll ask it to do something and it does it. But it doesn't go beyond that one statement or that one question. And usually we get very frustrated when it doesn't understand us, like you say, Alexa play, Yellow's Mr. Blue Sky, and it'll go, Okay, we're playing new selections from Mr. Blue Sky. And no, no, I didn't want selections by it I want. So we don't know necessarily the phraseology yet. Or we're not keen to the ways in which the AI wants to get instructions, wants to be fed instructions. And therefore the three year old, and we are basically learning as we go along, and the probably the three year old is going to grow up in a world where it understands how to get more out of the AI than we do, because they're growing up in that world.

 

Anne Fulton: 23:01

And a three year old brings, you know, a playfulness and a curiosity. And you know, I'm going to ask this to do anything, right, because I've seen what it's going to come back with. But I think it's the art of really good questions and good commands is where we're at today with some of these technologies. And not for a minute, am I suggesting that somebody has a coaching conversation using GPT! Because I think going in prepared with your three questions, you know, can be useful, and some tips on how to progress, you know, solutions focus into a coaching conversation. However, you know, you would not be wanting for wanting to wait for GPT to come up with the answers of what you should ask me. So, I think I think, as you say, it is the art, you know, of masterful questions, that is going to be the clue for how we unlock, you know, some of the power of these technologies that are emerging.

 

David Turetsky: 23:53

And as HR I think, as a practice, we don't know everything, HR doesn't know everything. And using Chat GPT as a methodology of research. It's like we used to use encyclopedias or dictionaries, I don't see any difference. It's a tool for us to leverage or a call center or an expert or consultant. Well, no, they're not gonna replace consultants ever. But you know, there is a reason that it's could be so fascinating for HR. The fear to me seems a little unfounded at the moment. But I mean, so many companies, and even the governments are starting to say we should put restrictions on it. Really, why? Why Why wouldn't we let let the market figure it out?

 

Anne Fulton: 24:39

Yes. And I think we're at this wonderful inflection point where we're not 100% sure around how these technologies are going to emerge and how they're going to, you know, augment, you know, the kind of human intelligence that we have today and the way that we work. And so what I'm seeing is that HR are being incredibly thoughtful and embracing of some of this technology. But I think the thoughtfulness with which we use it is going to be super important. So yeah, we were at the Josh Bersin Irresistible conference a couple of weeks ago. And one of the things that struck me and some of my colleagues was how open HR are to embracing some of this AI technology, but the real importance of how we're going to apply it, and where we're going to apply some of this capability within our organizations so that we are advancing and augmenting our capabilities, but we're not creating risk. So one of the things I've observed is that, you know, that we've got to have some emerging controls on how the technologies are utilized, where and when, and being incredibly thoughtful to make sure that we're not creating unnecessary risk for an organization that you're unnecessarily perhaps sharing some data with, you know, a wider audience. And have heard a story of, you know, an employee going on and saying, you know, can you help GPT, can you please help me summarize this data, but risks created, while GPT starts to summarize this data, but then goes to another tab within that same spreadsheet, and accidentally getting access to some, you know, really important data that wasn't part of the original sharing! So, you know, how are we creating controls and protocols to make sure that we're not creating risk for our organizations.

 

David Turetsky: 26:29

And to that end, I think that's just like every new technology that we offer, whether it's the Internet, whether it's voice response systems, or whatever, you got to be able to put in not even just appropriate controls, just put in intelligence into what is it we're exposing to the stuff? And how are we utilizing it? And what kind of to that point, what risk are we putting out there? Because, you know, we all put our information wildly on Facebook, Instagram, Tik Tok, whatever, the, you know, technology du jour is. And that's being used, whether we like it or not, by Facebook, Instagram, Tik Tok, to then sell our data to other companies so that they can sell stuff to us. And so chat GPT and all these other technologies, there's no difference. Because we kind of don't know what the backend looks like. Maybe it's because it's too confusing for a lot of us to understand. But I mean, to me, that's guidelines, its rules. It's not laws.

 

Anne Fulton: 27:35

Yeah, I agree with you, it doesn't need to be at the state level, or, you know, federal level in terms of laws of governance, but every organization needs to think around, you know, what sets protocols that's going to create safety for the organization and safety for the individuals. So, you know, I think there's a, you know, a risk, if we're even talking about open source AI, you know, the very fact of that terminology, open source means that, you know, you are sharing, and having a really good understanding of what you're signing up to. And, you know, as you're sharing data, and making sure that people understand what, what and how they might be able to use some of these technologies. Personally, I'm a great fan of augmented intelligence. So if you're thinking about shades of AI, right, you know, we can go to completely, you know, autonomous AI, you know, controlling, but I'm a big fan of, you know, going down the route towards augmented where we still have, you know, people at the forefront, you know, the human face of, of our interactions, but, you know, I love the thought of my lawyer, my doctor, having all of this information fast and available to them, but I still want to talk, you know, one to one with that expert, so that they're controlling what information gets shared.

 

David Turetsky: 28:46

And let me get take that example back to what you're bringing up in questions, one and question two, which is, you know, engaged leaders in a fit organization, understanding their employees and understanding the engagement of their employees. Wouldn't it be really cool that the AI would enable the conversations, not just being hey, what should I go in asking this employee? But knowing what's going on with the employee knowing where they are in their performance evaluation, knowing where they are in their engagement scores? What are things that I could bring up? Or what are questions I might be able to best ask them in order to be able to make them feel more a part of our organization, and that we're actually paying attention and care about them? You know, and give the manager the tools to not only ask the question, but also understand what the answers might be, and what the alternative scenarios could be.

 

Anne Fulton: 29:39

Absolutely. And that's the opportunity that you know, we do see, which is particularly around employee engagement and satisfaction and motivation. So you know, imagine a world and we think this is possible today where in a, a leader has, here's the top three motivators for this particular employee. This person on my team that'd be a retention risk for these reasons and being told, you know, here's three questions that you might want to ask this person, you know, to allow them to become, you know, more satisfied, more engaged, if you knew that one of the people on your team was looking for more challenge, or somebody else wanted a little bit more appreciation, you know, being able to, you know, have that augmented intelligence, but you as your, as the manager, you know, want to be able to ask these questions in an informed way, and where there's transparency around what data is shared, so that the employee feels comfortable, you know, that their data is being used appropriately within that organization, and that's not being intrusive. So, you know, again, you know, some controls around what is used, and how it's used has to has to be carefully thought of, but yeah, absolute empowerment, so that we, as leaders are asking the right questions and supporting our people.

 

David Turetsky: 30:50

Well, that's a fascinating example, because you know, that there are certain organizations, certain governmental organizations, especially in the EU, that have made certain data, you know, very sensitive data unavailable, or that the employees got the right to privacy, the right to forget, you know, other things. So, the emerging technologies are going to have to skate with not around or flow with not around the restrictions on data, especially personal data that managers can't have access to not just shouldn't, but can't have access to given that the regulations that exist in those locations, don't allow them to have those conversations.

 

Anne Fulton: 31:34

Yes, and I, you know, I commend those organizations and love from what we're seeing with the New York AI audit, you know, as being probably the forerunner of something that we're going to see across every state and around the world is setting, setting some standards that we need to adhere to in terms of, you know, what, and how we're applying, and where might there be some bias created in the AI. So this comes back to, you know, the earlier point is that HR needs to be thinking really carefully and intelligently around the application, you know, make making sure that AI is being used for good, not harm. And I think that that's the underpinning principle that we want to use to continue to adhere to. So where's the benefits, where's the care that we need to take to make sure that there's no harm done?

 

David Turetsky: 32:16

And the robots are not taking over? And that there is this is not a terminator situation where we have to worry about Arnold Schwarzenegger, you know, coming out of out of the past or the future to take things away. So we're not gonna go there yet, because we don't believe that that's where AI is taking yet. So hopefully, it doesn't get there. Anne we could talk about this stuff for another couple hours. But I know that we can't do that. So I want to thank you so much for coming on and spending time with us. It was a very, very interesting and intriguing conversation. And we might actually ask you back to keep going on it because there's so much to talk about there.

 

Anne Fulton: 33:00

Absolutely. It's been my pleasure. And as you say, you know, predicting the future is one of my favorite topics. And you know, how are we leveraging some of this technologies that are available to us today into the future, you know, is something that I could talk about forever, so I really appreciate the opportunity, David being on the call and joining you today!

 

David Turetsky: 33:17

Thank you again, and thank you for listening, take care and stay safe.

 

Announcer: 33:22

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