AI and Data Dynamics: Navigating Tomorrow's Terrain

Chris: [00:00:00] Welcome to another data driven podcast. My name is Chris Detzel and today we have
Ansh Kanwar back. He's the senior VP of technology at Reltio. Ansh, how are you?

Ansh: Very well. How are you, Chris? Happy New Year.

Chris: Happy New Year. Yeah, it's already here. It's crazy. And we have our special guest, Asha Saxena, and Asha is a strategic innovative leader with a proven track record of building successful tech businesses for over 28 years. Asha, how are you doing

Asha: today? I'm doing good. Happy New Year to you too.

Chris: And happy new year. Glad to have you.

Chris: And I'm going to give the reins over to Ansh. Ansh, go ahead.

Ansh: Absolutely. Thanks, Chris. Asha, I'm reading over your bio here, and I have to share it because you've done so many amazing things over the years. As Chris said, you've been the CEO at Aculus, which is a healthcare data analytics firm that you founded.

Ansh: You have been the CEO of Future Technologies, which was an international data management solution. Now you're currently the [00:01:00] founder and CEO of Women Leaders in Data and AI, which is an organization that brings senior leaders together to create this impactful digital world with parity and equity. And we'll spend hopefully some quality time talking about that initiative.

Ansh: You're also the CEO of Coaching International, which is a leading coaching firm for growth focused CEOs and entrepreneurs. You're a board advisor and adjunct professor at Columbia University. On top of everything else, you're a published author and a columnist at Entrepreneur Magazine. You're a well known keynote speaker.

Ansh: That's, in fact, how we met at one of the conferences. And you talk about entrepreneurship, leadership, women in data, artificial intelligence, big data. And you have a book that just came out that we're going to talk about. Wow, that is an amazing few years of work, I would imagine, Asha. Very happy to have you here and welcome to the

Asha: podcast.

Asha: Thank you. Thank you for having me. No, I had, I've had a great journey and I always say, That this time, [00:02:00] I don't think we've ever seen this kind of a hype in technology that AI has brought into our lives. So I'm really excited about what's in store for us in 2024 and how companies are going to embrace it.

Ansh: Yeah, I'd love to get your take on it. But before we go there, we'd love to get to know you, Asha, the person, Asha, the entrepreneur, a little bit better. So would you mind starting us off with your journey? And really, how did you get into tech? How did you get into AI and specifically into data?

Asha: Very typical, I would say that being an Indian origin.

Asha: My parents, of course, expected me to be an engineer or a doctor, and I took a very straightforward path of being an engineer. And I graduated as a computer science engineer. My very first job in New York City was of being a programmer. I was a mainframe programmer, worked on DB2, started my career as a database.

Asha: Engineer and been with data analytics [00:03:00] and AI from very beginning. I started my career as a programmer, but very quickly climbed the ladder to be an engagement manager, worked for a consulting firm and then started my own consulting company. Very early on. I always say that having a mentor.

Asha: I had a mentor in my job. My first boss who truly inspired me to do more. But I also say that it's never just one thing when you're climbing the ladder. It's multiple elements that influence your career. Of course I had to work hard. I had to be good at what I did. I had to build a relationship with my client and make sure that I had a brand and was recognized for what I did.

Asha: And then somebody pushing you a little bit further, helps you go to the next level. And started my first company at a very young age early twenties. And I grew, I'd be doubled every year, grew it to about 350 engineers. Then I built a actually partnered with a large manufacturing [00:04:00] company took 3000 dealers online and then build a healthcare software company where we sold the software to Hackensack University Medical Center, Frederick Memorial, and so on.

Asha: And I've been teaching at Columbia University as an adjunct professor for 13 years now. Started at Columbia business school where I was a entrepreneur in residence. And then I started teaching at Columbia Business School and then moved on to Columbia Medical School of Public Health, where I teach entrepreneurship.

Asha: And so that's been my journey, I think, an entrepreneur, a technologist and educator. And I think being an educator, you somehow start sharing your knowledge with the world. The book came out of that, the book came out of getting in the habit of teaching and saying I teach and I execute, in our organization as a business, how can I package it and put it out.

Asha: And I think the COVID time was a really pivotal time where. I think a lot of people got a chance to [00:05:00] pause and reflect and that's when, I reflected and gave birth to two, two children, one was my book and the other was women leaders in data and AI, which was a mission based organization.

Asha: So both after reflecting on life. And

Ansh: That's an amazing outcome of the isolation of that year. Would you since you mentioned Wilda, let's we'd love to know a little bit more. I have heard you very passionately talk about the mission and, the the mission off the company and all the change that you wish to bring about through that as a vehicle, but we'd love to have our listeners also.

Ansh: Hear that from you directly and then perhaps get an update on where you are. You have been making a difference over the last year or so, you
Asha: know, when you talk about, I was talking about COVID and pausing and reflecting, I think in spirituality, they say, pause and reflect, right?

Asha: The whole meditation is about, Meditate to be able to [00:06:00] reflect to me, COVID was that time when a lot of my friends, closed one were passing away. My landscaper passed away. And the question was, and I was having a conversation with my older son and we were talking about, what are we going to leave behind?

Asha: If the life comes to an end, what did we leave behind? And so my immediate thing was, which I was working on a book, but I was not rushing to write a book, I was just putting things together. And at that time it was like, I'm going to write a book. I'm going to finish my book. And as I was writing the book, it was the realization that, Oh my God.

Asha: As you think about the data during COVID, everybody was on digital. We were all creating more data than we ever expected to create. And the models were going to get stronger. And everybody who was in machine learning, work, they were doing the work, they knew that these models are going to get stronger during the COVID time that can help accelerate our progress during, this time.

Asha: And my immediate concern was that, oh my God, these models are going to [00:07:00] enhance the biases that we're going to code into this. model and what are we going to do about it? And during my conversation with my son, I was talking to him about that. I said, I'm writing this book. I realized that how important, responsible, ethical AI is going to be, but also I realized that my voice would not be heard.

Asha: Women don't write a lot of AI books, women are not on the, a lot of the women are not on the senior roles, how do we make sure that these women or minorities have a say, becomes a really important issue. And I was having this conversation and I said, there's nothing we can do. This is a, it's an issue.

Asha: What can we do about it? And my son looked at me and said, why don't you do something about it? And I said, What can I do? I'm just, I know how to build companies and I know how to, build a product. This is a social issue. I can't solve a social issue. He looked at me, he said, mom, if not you, then who?

Asha: And I pondered on, I ignored him. I [00:08:00] tried not answering him and I walked away. But what I then, called a few of my friends who were in the c-suite leadership role. And I knocked on a few others, and I said, let's come together as women leaders in data and AI and do something about it.

Asha: And as I started on, I realized that it's not just a woman's issue. We need male leaders. I need our allies working with us and I end up talking to Seth Dobrin, who was the chief AI officer of IBM at that point, Michael Kingston, who was the CIO of L'Oreal, and I, as I started talking to these guys, and I was like, Oh my God, they care about this too, and we say world leaders coming together for women leaders in data and AI.

Asha: It's really, truly the world leaders who are coming together for this cause. So we have about 30 percent men and 70 percent women in our organization who care passionately about making sure that as we execute technology, listen, science, when you think about science, it's always pro and con, right? When you talk about AI, they're going to be good and [00:09:00] bad, but all we can do as leaders in this industry to do the right thing.

Asha: And if I take one step, you take one step, together we'll hopefully create a, create the magic. So that's really the mission behind Women Leaders in Data and AI, is to bring the consciousness of leaders who are impacting. So we started with the C suite leaders who have 10, 000 employees or more, so they can create the impact.

Asha: It's me, mine, and ours. You start with you, create an impact with mine, and then create the impact of ours, and hopefully you create a change.

Ansh: That's amazing. That's really amazing and inspiring. What are some of the activities or actions through which will the sort of engages with the world?

Asha: Get involved, yeah. So you could be able to leader, if you're a senior VP or a C suite leader, you become a member and you get engaged in your own circle. So it's a peer to peer community. And then we have Build A Nation, which is anyone who's below a [00:10:00] director level, they are Build A Nation.

Asha: So we have two categories of Build A Leaders and Build A Nation. But usually what happens is a corporation comes in as a member, and then they, by the spots for leaders and nation through that membership. We have events in person events and virtual events where we talk about tech talks. We want to make sure that our audience is up to date on what's going on in the world of AI.

Asha: We have in person events where we have taught leadership summits. Very intimate setting 100 people or less of senior leaders. So we partner which we are partnering with Chevron build a bear Mars IPG media and so on, where we go regionally around us and in Europe, where we bring about close to 100 C suite leaders.

Asha: To have these thought-provoking discussion and challenge each other and learn from each other and create this peer-to-peer community. And then we do awards. We want, we talk about recognition. We wanna make sure every [00:11:00] November we have award gala where we give award awards to women. Male allies and the corporations who are creating some kind of a change and shift, you if you it's so important to be able to recognize, good behavior.

Asha: Hopefully, you can create the repetition of that behavior and we do our summit and annual summit in New York City and then our regional summits are. In Chevron at Houston, L'Oreal in LA, IPG in London Build a Bear in, Twin City, and so on.

Ansh: Yeah that's really amazing. And for everybody listening, the website is wlda.

Ansh: tech. Please go take a look at all the amazing work that WLDA is doing right now. Also. Entrepreneurship, Asha is something that that you were known for starting companies, for teaching about it and so on. And some of our listeners, they're very interested in the inspiration, the seed behind starting the 2 different, very different companies that, that you started.

Ansh: Can you walk us through [00:12:00] your inspiration at that time and, how, hopefully others can hear it and spark their own entrepreneurial journey. Yeah.

Asha: As I said that when I jumped from being a engineer to an entrepreneur, it was three things. The first was you have to be good at what you do, your core heart skills have to be good.

Asha: So that was one. Second was Your EQ, your soft skill, your leadership skills, relationship understanding the consumer, whoever your consumer is, understanding how do you connect the dots of your heart skills and the soft skills. So number two was my brand, what I built as I was, delivering on my my heart skills.

Asha: And and number three is to do something about it. A lot of time you have the hard skills, you have the soft skills. It's Oh, when the right time comes, I'll make the move or I don't think I'm ready. So you wait. So I think for me first of all, I started my first company when I was 24.

Asha: So I think a youth or ignorance is a bliss, when you don't know what you're jumping into. So you just jump [00:13:00] and you say, Oh my God, what did I do? But listen, I still do startups and I still build companies and I think it's really the thrill of trying to figure out if I can make it, you jump in the ocean and you say, can I swim?

Asha: And I think that's really what an entrepreneur needs is to have that. dire passion that doesn't matter if it's going to work or not. I'm going to keep swimming, so those three skills are really critical to be an entrepreneur. I started my first company. It was the right time at the right place.

Asha: I was working for Merrill Lynch. My existing consulting firm was getting bought out. My boss basically gave me my non compete bag because they wanted to keep Merrill Lynch happy and I, so I started my first company with a client in hand which very rare, so the right time at the right place.

Asha: But I also think if I was not an excellent performer, they wouldn't have done that. If I didn't have a brand, they wouldn't have done that. The second thing, which I think is really important is to stay hungry, so my [00:14:00] second company, which I did with a partnership with a manufacturing company, I was hungry.

Asha: I was always asking questions of what is the opportunity? How can I partner with you? What can I do for you? And the third company was the. Healthcare software company was through Oracle. We were Oracle partners and Oracle said, Akinsac, is looking for, someone to manage their database and analytics.

Asha: We went in and we land up building a product around it. So I think it's about having the hard skills, having the curiosity or the soft skills, but also having the passion or the gut to be able to jump in and say, I'm going to survive no matter what. You know that passion to help you survive.

Asha: So I think those were the three important skills. Which I feel I needed to continue being on that entrepreneurial journey to keep making and building. They said there's a reward, of course, being an entrepreneur, there's a reward. But there's also a lot of struggle, have a lot of sleepless nights.

Asha: But if the passion [00:15:00] is stronger than your struggle, then you keep moving forward. That

Ansh: is such great advice, Asha, and just you're living proof of that, yeah. So let's fast forward a few years now, you're in COVID times you've decided to write a book about AI. And also talk about timing.

Ansh: That was great timing just because the before the big wave of 2023 AI hype cycle really took off. So tell us a little bit about the book. I have some specific areas that I find very exciting that I want to ask you about, but why don't you give us your approach to the book and what you're trying to share through
the book?

Asha: Being a technologist, a business owner, I built solutions for business community. And when I realized that every time I was talking to a business user, they hated technologist. They're like, they don't get our business. They are making things. We, and then if you talk to the technologists or engineers.

Asha: They can't tolerate the business users because they don't have patience. They don't know how to use it. They keep changing them. So there was [00:16:00] a constant battle between the business users and the technologists. And I always came as a strategist. And so my position was always to figure out how you build the gap between business and technologists.

Asha: And so my goal in the book was to really and as you mentioned in my bio, I was a partner at a CEO coaching international firm where. I was working with about 12 to 15 CEOs of large companies on using tech to grow hyper growth build hyper growth organizations. So I was working directly with the CEO and their direct reports.

Asha: To figure out how to create the growth, the exponential growth in their companies for an exit. So I was working with private companies for an exits and what I realized that a lot of time the senior management really didn't spend enough time on technology and during the COVID time. My whole thought was, Oh my God, they're all going digital and how are the [00:17:00] CEOs going to, jump in and move faster than they can truly.

Asha: And so I was writing the book. My goal was for, so the first part of my book is all use cases. I talk about Netflix, Domino's pizza, and so on. The companies who really embrace technology and how they have used technologies to create the growth. And the second part of the book is the how to, I talk about four step process of how to use, the data readiness, the four quadrants and, the power the data performance index the AI flywheel and prioritization to be able to create use cases that can give them the high value, it's all about the value and if you are walking into a meeting, if you don't add value, You're only going to be there for so long as a senior leader.

Asha: They say CDO term is only 18 months and the CDOs won't survive if they can't add value. So we all come with a a term. And within [00:18:00] that term, if you're not producing the value, we are going to be out. And same thing with technology. How much you remember those days? I still remember those days when we build this technology, it gets shelved.

Asha: It's so frustrating because as an engineer, as a creator, you're building the technology and it gets shelved. Even today, in my company, I get frustrated because our technology is not used fully. We only use 20 percent of the technology, all the, fee, the cost I incur as a business owner for technology.

Asha: And my team is only using 20 percent of it. It's super frustrating. So my goal was, how can we make sure that the business user understands technology enough? To be able to communicate with technologists and how can technologists understand business use case a business language to be able to communicate the value, I think, so I emphasize on the value of technology here we are talking about AI and I call it the AI factor.

Asha: What is the AI factor you need to have and when you talk about [00:19:00] timing my publisher I wrote the book in 21. And then got it all cleaned up and 22 we were ready to launch it. My publisher said we'll launch it October 22. I was done printed July and they said we are delayed because of COVID and we can't publish anything until October.

Asha: And in September, they said you are now pushed back to February of 23. And they said, sorry, we can't do it. And I was like, I'm in no rush. I wrote it because I wanted to get the book out. I'm in no rush whenever you want. November, ChatGPT comes out. January, Microsoft buys invests in 10 billion in OpenAI.

Asha: And February my book comes out. What was the time? You couldn't have asked for something better. And I had named the book before Chad GPT came out the AI Factor. It was just the timing.

Ansh: Yeah preparation meets opportunity. That's the example of that. You

Asha: know, you have to have hard skill, you have to have the [00:20:00] soft skills, and then you have to have the right timing,

Ansh: absolutely. And that's what I loved about the book, just reading through it. You present very practical frameworks that are very much at that intersection of the business and the tech community and the linchpin holding it together is value. And so I want to talk through a couple of examples that I found very both easy to use and valuable.

Ansh: First one being the data performance index. Do you want to give us a little bit of a feeling for that?

Asha: Yeah. So it's all about performance, right? When you talk about data, I have so much data. I had, I meet so many entrepreneurs, they'll say, Oh, you do you work with data and AI tell us about, I got so much data.

Asha: What do I do with it? And I think it's not about just the raw data, or, it's the good data, the bad data, you got the data. But if you don't know what problem you're solving data is just data, you're not solving the problem. So I talk about it. In the book, I talk about the data performance index because it's really [00:21:00] important to understand the what the value the data is providing, what is the business value and having that and measurement, so it's a scientific equation where you said, This is my data value.

Asha: This is my business value. And this is where the power comes from. So I say I talk about the data value indicator multiplies with a business value indicator that gives you the data performance index. And that's what you want to use as you think about what is my viable data projects? What are the projects which will actually give me the value?

Asha: So it's important to think about it more scientifically instead of just saying that this project right now is the most exciting project or technologists might say that this is the most interesting technology I want to work on. But really, Julie, what is the business value? And you need to make sure that you have the right data and you have the right business issue to be able to create that.

Asha: Performance.

Ansh: It feels we need something that is a little bit perhaps less quantitative that something like an [00:22:00] internal rate of return or something, which comes further down. But if you're just really trying to evaluate a number of options that are in front of you, which, being that time of year right now is a good time for planning and so on.

Ansh: It's a great tool. So to go and pursue that. The other, which is how I actually became aware of your work, Asha, was I was preparing for a talk where the question was. How much should we expect from our A. I. Investments? And my answer was very simple. It is. It is based on how much work you've done with the data and what shape your data is in to be able to extract that value.

Ansh: A. I. Being one of the engines that you can use. It's ultimately advanced statistics in one form or another. And I needed to communicate this idea of of data readiness. One of the comments that that I made was around ethics in AI models. And my argument is if you don't have a framework, if you don't have an approach to ethically using data, then it's very hard to have an [00:23:00] approach to ethically using AI models because they, one builds on the other and so on.

Ansh: And the same kind of mindset applies to the. The, what expectations you can have in terms of outcomes from A. I it, it really is a reflection of what kind of outcomes you've been able to drive with data and so on, right? Perhaps in a much more amplified, much easier form but there is a strong correlation there.

Ansh: And I was very happy to see your data readiness framework talk to similar themes and would love to hear from you about that as well.

Asha: A lot of times when you're working with a complex problem, it's always easy to put it into some kind of a framework, when you're working with a complex problem, you break it down to simple pieces, it's more digestible, it's more, it's easy to communicate and it's easy to understand.

Asha: And so in data readiness framework, my goal was that, you can go in a hundred different direction, but truly there are four basic elements. Do you have a clear objective? Do you have a data management element in it? Do you have engagement and do you have the [00:24:00] transformation? And when you really think about it.

Asha: To have a clear objective, you need to understand, do you have the executive buy in? Do you have the alignment? Do you have the goals and do you have, some kind of operational efficiency? Do you know where you are in the four quadrant? Where do you sit on? The second, which is a very important, which you just touched upon is, what is data management?

Asha: Do you have accessibility to the right data set? Do you have the security? Do you have the quality? Can you trust the data? And do you have the governance? Do you know who owns the data? What are the definitions? If you don't have that basic element, you can't go to engagement. People are not going to buy into it.

Asha: Engagement is about usage. Are people going to use it and trust it and reuse it? Now you have data sitting in the data lake. You want the data scientist to be able to come and say, all right, I can find some gems here. I can make sense of it. And then comes the literacy. Then you say, okay, now I've got something which is tangible.

Asha: I can create the literacy. I can create the culture around it, or I can create the enterprise engagement. [00:25:00] And only then you can transform. You can't talk about transformation unless you actually hit those three pillars. To be able to give something of value. Absolutely.

Ansh: And I think the readiness framework also acts as a diagnostic.

Ansh: If you're not getting the results that you want, then, just work backwards. Try to figure out which piece is deficient,

Asha: right? Exactly. And when you talk about synthetic data, right? You can start creating synthetic data, which people don't trust either. You're just creating bad data over bad data.

Asha: So it's so critical that the investments on data is made appropriately and you create the right buy in. Otherwise. Clearly, the business and technology is going to constantly keep butting heads,

Ansh: absolutely. So that brings us to the, January of 2024, where we're at, we've gone through perhaps the peak of the large language model related hype cycle, but AI is out there.

Ansh: It's in the open. My mother is asking me questions about how AI is going to change the world and so on. I don't know. I don't know. [00:26:00] So if, as we move forward through the hype, obviously the conversation is going to turn to value. It's going to be, it's going to turn to commercial viability of offering different variations of this technology.

Ansh: We'd love to hear your point of view on how should companies approach the at this juncture approach AI approach, this whole space, what are the big do's and don'ts from your perspective?
Asha: First of all, I always say you can't run away from it. You can't hide under the covers and say, Oh, it's not happening.

Asha: It's just a hype, I'm going to stay out of it. I always say to the organizations, you need to jump in. This is something which is going to, is here to stay. It's not something which is happening, only today. We've been using mathematical models for such a long time. And now, this is about the language models, the natural language processing.

Asha: This is here to stay. It's going to happen. There's some amazing work, which technology, all technology company and consulting firms have done in gen AI, where [00:27:00] now you can read the charts and it'll talk to you about the chart. They can have a conversation about your data.

Asha: Generative AI is here to stay. Now the question is how you're going to use in your organization. How can you create little clusters to test it? Maybe implemented. But my first thing I always say to the organization is that you can't run away from it. You can't fear it. You can't run away from it.

Asha: Jump in. What you don't want to do is jump in so much and invest so much into it at one point that you don't have any kind of a hold on it. So you don't want to get engaged so much that there's no measurement. So what I really talk about is building small wins. Walking into this huge ocean of generative AI, but taking baby steps.

Asha: Look at where your data, what kind of data do you have, and where can you create use cases where you can start creating small [00:28:00] wins. Only if you create the small wins, you can now take it as a baby step to go to the next level. Jump in, don't be scared. But don't do it all, start small, and then create wins.

Ansh: That's great advice, Asha. Are there any companies or any non profits, something that, what's an example of doing it right? What's a good example of bringing these innovations to market in a, sustainable manner that, that sort of goes beyond the hype and is likely to stay?

Ansh: So

Asha: we did two examples. The first is Ellen Nielsen, who's with Chevron chief data officer of Chevron. What she's done is they've created a marketplace. So having curated data, have the, really investing in data to create good data and have it available as a marketplace where analysts can come in and pick the data and start working on it.

Asha: So I, it's really, as you said earlier, investing in making sure that you have the right data [00:29:00] marketplace to make it available for the community of your within your organization. . And the second one Jane Lauder from Estee Lauder was at, the keynote speaker for our November summit.

Asha: And she shared a really great example. She spoke about the AI is such a hype. Everybody's talking about it, every department wants to do it. So what they did, they, they created a ID idea tho. And they said, you have an idea about AI, send us a 30 seconds, a minute video of why your idea is the best idea. And really taking the ideas and then aligning it to their strategic initiatives and see which idea matches with what they need to, implement, invest in, and then giving funding to the top three winners of those ideas.

Asha: To shoot and then to have them show what will work. I thought those two are really great examples. One is on the data side, the other is on application side, application AI.
Ansh: And that's again, great advice for, CDOs, CIOs, like looking to jumpstart [00:30:00] the AI journey or really.

Ansh: The other side of it, which is the role of data in companies that may still be struggling in extracting or managing value which is almost a guarantee that they're going to struggle as they get to the AI piece of it.

Ansh: How should that be approached?

Asha: So first I'll say it's a great question because it's a real problem. I was talking to a client earlier and a senior leader said to me that there are too many cooks in the kitchen. Everybody, we don't know who owns the data and everybody wants to own the data.

Asha: We are getting no strategy out of data and this person I was talking to said, maybe I should just build a strategy and jump in, and so this is a real conversation. There are, especially with the data organization, if you don't have a centralized owner, or if you don't know who the owner is, It can get very confusing because everybody owns data.

Asha: So having data governance is really critical and that's why a lot of data governance initiatives fail because there are too many cooks in the [00:31:00] kitchen. So I think that's number one problem is not having clear definition of who owns the data. Number two is priorities. A lot of times you will have so many requests come in that you are busy on the day to day task or just putting off the fires that you're not focusing on the strategic initiatives, you're getting stuck with day to day challenges.

Asha: So really, truly having the right leadership to create the priorities so that you don't forget about the strategic goals. Instead of just becoming the note taker, or the order taker, as you say. And I think those are the two biggest challenges organization face. And these are real problems. And the last one, which I've heard a lot of times, the CDOs complaining is that we are brought in for value, but we become the infrastructure leaders.

Asha: All we are doing is just getting the, infrastructure ready. So we don't have enough time to [00:32:00] produce the value.

Ansh: That's right. That's getting to that insight and converting that insight into action. It still remains elusive despite all of the progress that we've had with technology.

Ansh: Asha, that's all we have time for, but I wanted to thank you very much for being with us today and sharing your passion and your journey. And I know that listeners of Data Driven would really benefit from your experience. And don't forget, everybody, the website is wlda. tech. Thank you, Asha. Thank you for having

Asha: me.

Chris: Great. And thank you, everyone, for tuning in to another Data Driven podcast. I'm Chris Detzel. Don't forget to rate and review us. Thank you, Aj. Thank you, Asha.