Hi folks! Welcome to yet another insightful episode of the Leader Show with Lou Carter. Today, Mr. Carter interviews Bhavin Shah, CEO of Moveworks. The conversation in the podcast mainly revolves around the organizational culture of Moveworks and how it has become a most loved workplace.
Now, without any further ado, let’s get straight to the meat of the matter.
Bhavin explains that Moveworks’ mission is to use conversational AI to improve the way businesses work by providing support to employees so they can focus on their work and have a sense of belonging. He mentions that when it comes to hiring, they look for the best talent but also focus on certain attributes in individuals, such as the ability to work in an ambiguous environment, focus on perfection and details, act on impartial information, and have a strong building and execution quotient.
The goal is to bring on people who can work in this innovative space and help Moveworks continue to improve and grow.
Next, Lou and Bhavin discuss the importance of automation and its trend in enterprises worldwide. They talk about the use of conversational AI and reference architecture to build a conversational system. The training of these systems involves annotation and the use of label training data.
They also talk about OpenAI, which has hired thousands of human annotators to provide label training data to ensure precision and recall in the system. In addition to that, they emphasize the importance of looking at precision and recall metrics and improving the results over time through regular evaluations and real-time feedback.
According to Bhavin, building an AI system is not just about adding more data, but it is also about paying attention to the details, like the type of model used, ensembling techniques, and ensuring that the system is not regressing.
Moving on, Bhavin strongly believes that building a successful organization requires time, experience, and iteration. And then talks a bit about the customer-driven culture at Moveworks, where decisions are made by individuals closest to the customers and data rather than relying on hierarchy.
He also mentions the standups at Moveworks, which are focused on asking what has been done, what has been tried, and whether the same insights are still holding true. The CEO then emphasizes iteration, encouraging people to try new things as long as they are not irreversible decisions and to develop a strong gut and intuition about what works.
The company’s focus is on execution quotient and making sure that the smartest people are looking at the data to make the best decisions for the customers. A customer-driven culture is one where the customer’s needs and experiences are the primary focus of the organization. At Moveworks, they believe that decisions should be made by the individuals who are closest to the data and the customers rather than by hierarchy acting as a gatekeeper.
Bhavin mentions that the goal is to get the smartest people involved in looking at the data and having conversations about the customer’s needs in order to arrive at the best outcomes. This approach is reflected in their standups, where the focus is on what got done, what was tried, and what was learned through iteration.
Also, the company encourages its employees to try new things and make decisions, as long as they’re not irreversible, in order to build a strong intuition and understanding of what works for their customers.
In this way, Moveworks strives to create a culture where the customer is at the center of everything they do, and all decisions and actions are guided by a deep understanding of the customer’s needs and experiences.
Bhavin suggests that to ensure a customer-driven culture, leaders need to create an environment where employees feel comfortable proposing new ideas and taking risks. This can ensure they are able to serve customers better.
Leadership can create this culture by giving employees access to data and information that will allow them to make informed decisions about how to better serve customers. This includes data on sales, engineering, and earnings, as well as customer feedback and market trends. By giving employees access to this information, they are better equipped to understand the needs and wants of customers and can act on their insights in a more effective way.
In addition to information access, it’s also important to create a culture of collaboration and teamwork. This means that everyone’s ideas, regardless of their title or role, should be given equal consideration and weight. Leaders should foster a culture where people are encouraged to work together, share ideas, and collaborate to find solutions that benefit both the company and its customers.
Finally, it’s important to have a violent reaction toward bureaucracy, inefficiencies, and slowdowns. In Bhavin’s opinion, leaders need to be proactive in creating an environment where employees are free to act quickly and make decisions that will benefit the customer without being bogged down by bureaucratic processes and red tape.
By doing this, companies can create a customer-driven culture that prioritizes customer needs and leads to better outcomes for everyone involved.
Another thing that Bhavin emphasizes is the importance of creating a culture where smart people can thrive and be motivated to do their best work. He believes that smart people don’t like to be managed, but instead, they want a clear vision and direction, challenges to work on, and an environment where they can freely engage with their colleagues and have the opportunity to have a real impact.
According to Bhavin, creating a flat, transparent, and fast-moving organization that hires smart people is the key to success. He learned this lesson early in his career when he transitioned from being an individual contributor to a manager and realized that his success was dependent on the output of his team, not just his ideas and brilliance.
This is why he believes in building organizations that are designed to empower and motivate smart people rather than limiting their potential through hierarchy and bureaucracy.
Next, Bhavin talks a little about the interview process at Moveworks. It mainly focuses on finding people who are ambitious and want to grow and develop in their careers but are not only focused on their own individual success.
The company looks for people who are invested in the company’s overall success and have a team-oriented mindset. Moveworks also places a strong emphasis on development and has a clear system for leveling employees based on impact and ability.
Performance reviews are also a big part of the company culture, happening twice a year to provide feedback and help individuals improve.
Lastly, Bhavin and Lou talk about the importance of self-improvement and ineffective leadership. Bhavin believes that personalities drive companies and that it’s important for leaders to have a growth mindset and a desire to always improve. This extends to not only professional aspects of life, but personal ones as well, such as relationships with friends and family, taking care of one’s health, and more.
He also mentions the role of self-awareness, which can be brought about through performance reviews and a culture of giving feedback. By continuously striving for self-improvement, leaders can drive their organizations to greater success and reach.
Bhavin and Lou discuss more on this episode of the Leadership Show. Do share your thoughts on this insightful episode with us.
Louis Carter: : Hey, everybody. Welcome to The Leader Show. I'm Lou Carter, and we have Bhavin Shah on with us today, the CEO of Moveworks, and Bhavin's awesome. He is an entrepreneur. He grew up in Silicon Valley, and he has had Moveworks for five years now, growing this company, amazing company with three other founders, and it's become a Most Loved Workplace. It's very impressive what they do, the information and processes that they've developed to make really our lives easier inside of companies, the processes that normally take us so many hours to do, he has in Moveworks, really made them truly simple so that we can have the time to do things that we need to do in our lives and in our work. Bhavin it's great to have you here today with us.
Bhavin Shah: : Lou, thanks for having me. And it's, it's great to have this conversation today. There's a lot of, a lot of timely topics I think we can cover.
LC : We can, and you know, we have so many different things to talk about, right? We have organizational culture, how you've developed that at Moveworks, and how you've become a most loved workplace, which I want to go, I want to dive into. And, you know, part of the reason that I see brings together a lot of companies, isn't just- it's a combining or unifying vision or mission and your folks, at Moveworks do something fully extraordinary, machine learning and AI, and really reach training models and doing something that they have a unique talent to do. How does that play into how you've created your culture and choosing the right people for your team?
BS: : Yeah, there's a lot of to unpack with a simple question like that. I think when it first comes down to our mission and how we think about the job to be done. And that is, we're using conversational AI to transform how businesses work. And fundamentally, that transformation sits at this location of support. If you think about support as kind of a fundamental need that employees have at work, they need access to tools and they need to get unstuck when they do or they need access. Once you provide that, then your employees can actually focus on the work that you hired them for. The work that they're specialists in, the work that they enjoy doing and have set out their career to become good at. And then last but not least, once they can do that work, they become, uh, they have a sense of belonging. They have a sense of ownership that really only comes together once they're distraction-free. They can focus on their work, and then they can really act and think like an investor, like an owner, like someone who belongs at the organization. That sense of belonging really matters. So when it comes to, you know, our world and who we hire and who we bring on, of course, like any other company, we look for the best talent, the smartest talent. But there are a lot of principles and attributes that we look for in terms of the individuals, in terms of their leadership, in terms of their ability to act and operate in a fairly unknown space. We're inventing a new category. We were starting this journey about six and a half years ago, and, you know, we were telling everyone that conversational AI was going to be, you know, front and center in terms of how employees could get more work done to be more productive. Fast forward to today, I don't think anyone is denying that fact, given the popularity of some of these more consumer-driven solutions like Chat GPT. So when we look at folks, we look at a variety of attributes of whom to bring on. We look at their ability to work in an ambiguous environment. So you have to act on impartial data. That's number one. Number two, we have, you know, this mindset that no improvement is too small. And so from there, you know, we look for people who are really focused on the details, who are focused on perfection. There's a lot of perfectionists here at Moveworks that we hire. And then we also work with people who are unafraid to act on impartial information. People who have strong building and execution quotient is key. So I think these are the types of attributes that we look for. And, then you have an exciting project and the rest comes together.
LC: : That's critical, isn't it? The execution component and having that kind of perfectionist detail work- showing up on time, doing the work specifically, caring about that outcome- because in machine learning, we have to annotate, we have to think about the details, we have to retrain constantly. And if you, if you miss something, we can get caught with something that looks ridiculous and it makes us look terrible in the meantime. And so, and one of the things we were talking about, Bhavin was a talk I had had with the CEO of Automation Anywhere, is that when we do this, when we can train into perfection, these models and what you're doing, we will then, as a society have more time to sort of, surf the rings of Saturn and harness the energy of black holes. Do you have that vision too at Moveworks? And how does that work for you? So instead of coming back Sunday and giving him the car back Sunday night, I just stayed into Monday and then I traveled back and gave him the car Monday night. I think I might have sent him a text, maybe just saying, “Hey, I'll be a day late.” I don't even remember if I did that, but I just showed up at his door Monday night with his keys like nothing happened. So I hand him the keys and I'm turning to leave and he says, “Hey Andy, I need to tell you something.” And very calmly he said, “you know, when I loaned you my car, I expected that you'd have it back on Sunday night. And on Monday we needed to use that car to do some things with the family.” He said, “Now we've figured it out. We were able to make it work, but that was hard for our family. And in the future, if we do lend you something, we'd appreciate you bringing it back and the time we discussed and if not that you'd let me know or gimme a chance to talk to you about it.” And that was it. I don't remember what I said, but I still remember that that was about 21 years ago when I graduated. I still to this day remember it because of the way he engaged with me and he gave me the reality of the situation, and how he perceived it. But there was clearly, there was no relational loss there. I think that's the first time I remember somebody really engaging with me in conflict and saying, this was not good what you did, it's okay, but here let's talk about next time. So that's the good, I would say I thought I was great at managing conflict until I got married. I've been married now for coming up on 10 years and I thought I had learned a lot about conflict. From that leader- I learned how to, I thought manage conflict. But looking back, anytime I would engage with my wife in any serious conflict, those first couple years of marriage, the tears would start to fall. Hers, not mine, and it took me until the tears would start to fall to think, “Uh oh, I did something wrong.” Up until the tears, I thought I was doing really well, I was working through conflict. And then my wife would cry and she said, I need a break. And for me, I thought, “Uh oh, I'm not as good as I think I am about working through conflict issues.” And what I realized was my approach to conflict was like a courtroom drama. I was the lawyer. I was presenting evidence, making arguments, trying to show how right I was and work through like the facts of the case, you know, to show, oh, I'm in the right, what my wife needed was someone very different. She didn't need lawyer Andy, as we started to call it, she needed husband Andy, Andy with his arms lowered, not defensive, but defenseless and open, willing to listen to be wrong instead of somebody like in the courtroom seen in a few good men just hammering at the witness.
BS: : Yeah, I think, well, let's talk about automation as a larger topic in a trend. Obviously, there's been a very big push towards, you know, digital transformation and automation across enterprises worldwide. And that is for a lot of reasons. Obviously, automation helps organizations do more with less, but it's our greatest deflationary tool that we have as business leaders, right? And over the last 18 months, we've all experienced a lot of inflation, and a lot of extra costs to run an organization. And so automation really becomes central. But you bring up some of these other points, which I think are very critical in terms of conversational AI in general. And that is, as we build bigger and more sophisticated systems, large language models are becoming the kind of reference architecture to how to build a conversational, you know, system that can interpret and that can respond. But to do that, you know, you train it on data, but that's not it, right? That's not the only thing that you have to do. You also have to annotate. You know, there's this debate around unsupervised versus supervised learning. And, you know, it turns out, if you want the kind of precision and the recall that you and businesses expect to have with solutions that can work out of the box, that can actually deliver real employee impact, well then you have to do a lot of annotation and you have to train. The folks at OpenAI, have hired thousands of human annotators to actually provide label training data. And it's all in the details, right? Because as soon as you're talking to a system that is aware of, you know, the knowledge or the information that you're seeking, small perturbations in the models can actually lead to pretty unsatisfying results. And so, um, what we do a lot in our team is very indexed on, is really looking at all of these different outcomes and looking at precision metrics and recall metrics and, and the curves of these, sort of, you know, phenomena to ensure that we're achieving better results with more data, or it's improving over time, not regressing. That's the detail work that has to happen in AI. And, you know, sometimes people just think it's a data problem. You just add more data and thing just takes care of itself. But new types of models are coming out on a regular basis. Ensembling these techniques, looking at them, evaluating them, putting 'em in production, and getting that real-time feedback is central.
LC: : Because we, you know, we could take these off-the-shelf models pretty easily and, say, well, that's a great idea. The thing is, it may or may not work with our work, right? And I think of hugging face or the other kind of open AI models, and they're wonderfully brilliant, and I can take one and say, well, let's retrain it. Let's think about how it works for our processes, how we create our own. It sounds like you have found those people and you actively- tell me about your, like, what is a standup like at Moveworks? What is your standup, you know, what your Monday morning standup, what does it, what does it look like?
BS: : There's a variety of them, right? Depends on which department you're in. I think if you are on the machine learning team, you'll see a lot of calculus on the whiteboards here with, you know, uh, figuring out how some of these models can be managed and manipulated to achieve a certain type of outcome, a certain type of response that we're looking for. But, you know, there's a couple of principles that really define our organization. And, you know, I'll just take one step back, which is culture design, organization design is not something that most, actually, I don't think anyone is born with. You don't come out of the womb knowing exactly how to do this. You can short circuit many things in life, wealth acquisition, you know, you can have a company that goes from Zero to Infinity overnight, and all of these other sorts of things that can get short-circuited, but good management practices, knowing how to inspire people, knowing how to lead being a supportive manager is something that takes time and it takes iteration. I've had the benefit of starting several companies. I am grateful for everything that we've built here at Move Brooks, and this is the one, this is the one that we're gonna take and build to infinity. But the point is, is that it takes some of this sort of experience to do so. So, if you're building an organization and you're trying to come up with, or you're trying to listen for, you know, key kind of advice and sound bites, I'm glad you're here, but more importantly, know that it's very difficult to get it right the first time. So keep trying, keep applying, and keep developing your intuition around this and your gut around what works. But going back to your question, we're very indexed on what we call execution quotient. We are not an organization that is built on a lot of, you know, debate and in sort of, you know, consensus for something to happen. We allow individuals who are closest to the data and closest to the customers to make as many decisions as possible. We actually don't believe hierarchy is designed to sort of be a gatekeeper for decisions. The decisions should be made by the organization in a cross-departmental function, um, functional group or you know, individuals themselves. And the hierarchy is really designed to help us give each other feedback and support one another. But as a result, if decisions come to me as a CEO, I often ask the team, why? Why is it had to come to me? Why wasn't there an individual who is closer to the problem space, closer to the customer, to be able to make that choice? You know, we say something around here, which is, are we an engineering-driven culture? No. Are we a sales-driven culture? No. We're a customer-driven culture. And so to the extent that we understand our customer's needs, to the extent that we can actually get the smartest folks to look at the data and have these conversations, we will get to the best outcomes. So a lot of the standups are really about people asking what got done? What did we try? And there's a theme I talk a lot about here, which is iteration. People will tell me, look, we figured something out. Great. Have you done it three times? How about 15 times? Are we seeing the same insight? Is it still holding true? Or if people have an idea, I always tell 'em, go ahead, try it. You know, as long as it's not an irreversible decision, it's okay. And that sort of develops a strong gut and a strong intuition around what works.
LC: : You know, you had mentioned about management and leadership and iteration, and it really gets to the question in AI of probability. And when you manage and lead with the understanding that iteration is the norm, you get closer to a higher probability of success. And, some call it make mistakes. I call it iteration, because it's really not mistakes we're learning from. It's what we can do better in the future that we learn from. We learn from our successes even more than our mistakes, because it's how do we change it? Make it more probable? Get from the 40%, 50%, 60%, 70% probability, we'll never get to 90. Alexa, Google, Siri, they're not even close to like 95%, right? But we can get to 60, 70, but in order to get there, we need to have the right signals, right? And, you know, if you get no signal, I'm gonna need some ideas to get to a 10% signal or some signal. So iteration is extremely important in your business, and inviting not just ideas, but inviting people to keep working towards success, keep working toward what's better. How do you enable that kind of culture within your employees where they feel comfortable with gaining iterations and, and going toward that success and probability and greater signals?
BS: : Yeah, look, I think speed solves many problems in life, just in general. If you make decisions quick, if you can act quickly, you will learn faster, and you will be able to then get better as you're pointing out. Now, my machine learning team may have issues with what you said previously, about 60% accuracy. They are building models with a 99% precision, you know, but it might be a 90% recall. So there's 10% of things that the model won't actually decide on, but for the stuff it can decide on, it's gonna be very, very accurate. So that's a choice that you have, which is coverage versus precision. And when it applies to culture these are the considerations that our team is continuously making, which is, do we solve this problem for all customers, or do we solve it for these three customers, but get it very dialed in to their specific needs, right? And so those are the types of choices. Now, when it comes to how do you create that culture, I think there has to be a culture of safety, a culture where people can propose ideas, where people can also get access to information. You know, a lot of times in organizations, information is guarded, and, you know, perhaps in the defense space, that's important because you don't want everyone to know all of the secrets before. A software organization, a SaaS company like ours, we actually want that information to be as widely disseminated as possible. So access to reports, access to, you know, earnings and, you know, data, sales data, engineering data is really central to enabling people to then decide for themselves what to do. What they can act on, what they can't. A thing that perhaps you've used as well or heard, but culture is really the sum of everyone's actions every day. It's how we treat each other. It's how we treat our customers. It's how we treat our ideas and how we think about the interactions that we have with one another. And I think when we look at that combined with this idea that people can take an idea, doesn't matter what your title is, what your role is, I think what we strive greatly to do around here is just because someone has a big title in a room doesn't mean their idea or their decision should have a greater weight than someone else who might actually have deeper insights into the particular problem. So I think that's where we kind of, you know, encourage people. We do have to police it and sort of make sure that things aren't being slowed down by bureaucracy or things of that nature. We do have a violent reaction towards that. And as a result, we sort of keep getting better.
LC: : I can see that with, uh, having especially violent results, when you have brilliant people working, and this is an extraordinary place where there's funding for, and cash positive for amazing people. So when you're not listening to those amazing people's ideas, you're essentially losing thought capital.
BS: : Yeah, yeah. And look, there are some companies that are run exclusively through the brilliance of one founder, and there's mega-cap companies that I can think of that, that would represent that. But I think ultimately you decide what kind of organization you want to build. And, you know, if there's anything that we've all learned from sort of managing individuals, smart people don't wanna be managed. They don't like, they're smart. They, they're their own free agent. They have the same brilliant thoughts that others might have. And essentially what they want when they come to work is a vision that they agree with, a direction that everyone is heading in the same direction, you know, together on, and, you know, to then be challenged, to be given these problems that they have to have to go solve and go figure out. So I think that as long as you can create a culture in which there is no entitlement and there is no kind of organizational design that is predicated on hierarchy, but that it's flat and it's transparent, you move fast, you engage people, and you hire smart people, a lot of wonderful things happen. I learned this maybe 15 years ago, but the output, when I went from an individual contributor to manager, you learn very quickly that your success is predicated on the output of the people that report to you, not your own ideas, your own brilliance, so on and so forth. So I think, you know, as you're building even large organizations, that continues to apply.
LC: : This whole idea of output, it's an interesting one because when there is no output, one could easily blame or one could look within and say, what can I do to help? And secondarily, to all of that, are they the right people for the team? Because that's essential and in the beginning, you had mentioned how you have to have people who really have the same vision, right? Which is very important and as the company really believe in it, right? How are you enabling that to happen where you know that they're the right people for Moveworks? What do you do to ensure that they are the right people for you and your culture?
BS: : Yeah, that's a good question. So just on the point that you made leading up to this, you know, I think something that we talk a lot about is that the mindset here is one in which nothing is someone else's problem at Moveworks. So when you're interviewing someone, you're listening, right? And you're looking for how they think, how they process information, how they act. And when people complain about other departments or something was missed or something didn't come together because of this, or it was late, you realize they don't have this mindset of nothing is someone else's problem. And that's something that we look for, which is how do people describe their wins and their losses from the past, and how much of that is internal reflection? How much of that is a team mindset? And I think that sort of idea of teamwork really is central to how we build the ownership that we look for. And, you know, there is a level at which people here are unencumbered by some of the, I guess fears that people have oftentimes in making choices, making decisions. I think as a leader, as a manager, when people are in a meeting and there is a mistake that's made, or an idea that's perhaps not feasible, how you react to that, how you engage really determines a lot of how they're going to act the next time. And I think that's something that, you know, we are, you know, constantly thinking about. But when it comes to the Moveworks culture and the hiring process, we do a series of conversations. We have obviously, you know, half a dozen people that interview the individual. We do, what we call the Jedi interview, which helps us get to some of the more softer topics and, you know, how they view the world. Some of these operating principles that I talked about, acting on impartial information, nothing in someone else's problem, there's no detail too small, things of that nature, the openness, the transparency are cultural attributes that we look for. So sometimes that comes from hiring people from certain backgrounds, who've experienced that, and they know what good looks like. Other times it's teaching people what that looks like if they're coming straight out of school or they're new to the field.
LC: : The Jedi interview, this is interesting. Are there specific questions to the Jedi interview?
BS: : It changes depending on the role. It is looking at- it's some situational sort of examples that we give people in terms of how they would handle things, how they think about their teammates, colleagues. I think that's important. How they attribute their success. How much of it is about themselves, how much of it is about others, and you know, what they really think of becoming a part of a team. What we try and filter out in these conversations, Lou, is the stereotypical person who is very smart, but also very unkind and very much about their own outcomes and their own journey. And you hear it sometimes, you know, people come to interview and they'll ask questions about the business, which is great, you know, and they get excited and we obviously need people who care about this category. It's easy too, by the way, since we're all employees, many of us have worked at large organizations and, you know, we know how slow things can be, takes three days on average to get a typical IT issue resolved. But we also look for people who are really kind of looking at how to create impact and how that impact needs to include others and how they are going to go about motivating others, how they're going to go about convincing and getting consensus around certain topics. I think these things that we look for are critical for people, to have as they, you know, come on board. And as we filter people out.
LC: : What you said resonates with me about, uh, people who come on board are you interview them and, uh, the first thing that comes to mind is: there are other businesses. I've had that on several occasions and, uh, there are other desires for other lives. And I say, my main thing that I say is, what are you doing here? You should go out and start that music business. Go out and start that whatever business. I encourage you to and it's a developmental conversation at that point. I didn't realize you're coming in here for therapy or counseling or career coaching. If I would’ve known there would've been a different billing process. So it sounds like that happens with you too. I've always experienced it too, you mentioned development cuz once you people come in the door who have the vision, who are ready and are thinking and ready, and the movement that you're, you are leading, what does your development process look like for those folks? Career advancement, career development? What do you do to help them as well?
BS: : Yeah. Well this also goes back to, I'll start with the interview process. We want people who are ambitious, who want to grow, and develop in their career. But one of the flags that we look for in the interview is, are they coming here only for that? Because if that's all they're looking for, which is how do I become a manager? How do I become a director, VP, et cetera, then really, you know, going back to our previous conversation, they're in it for other reasons than the overall success of this company. And what is a company, it's a collection of people who have agreed on a common pursuit. And you know, I guess economists would say a company’s purpose is to produce profits in solving the problems and needs of the world. Combine those two and that’s why we should all be at work, in our point of view. But when it comes to development, I think there is a series of sort of piece of infrastructure that you need to develop understanding of where people are from a leveling standpoint in creating levels and creating definitions of what those levels are and aren't very important. And it's not just about tenure, it's not just about very kind of loosely defined, you know, tasks of things. It's talking about impact. And I know that in, uh, our, our leveling documentation, you know, to go from one level to the next, it's like you have to be in charge of, let's say, an entire product. That product has to have a certain type of impact. You have to have this certain scope. And so sometimes it's actually a constraint of the business because, you know, to go from this level, you know, five to six or something of that sort, there has to be both the opportunity that the business has for you to take on as well as your ability to be successful at that. And so, when you're moving up, you have to be able to run multiple products that you have to exceed expectations for certain number of quarters. There are products have to deliver certain kinds of outcomes. Well, what if there's only two new products this quarter and there's six folks who wanna lead them? Well then, you know, others are gonna have to think about, you know, other ways that they can deliver a similar impact than perhaps, what we've outlined. So there's a lot of discussions around that. I think we also are a company that has really focused on performance reviews since the early days. I remember when we were six people, Lou, and we did performance reviews, and it felt completely ridiculous to do because we're all in the same room. But you know, when you give people feedback, it's the greatest leverage you have on them. And it is uncomfortable. It can be difficult, sometimes to hear, but it is really the best way that we all can get better at what we do. And so, performance reviews, we do 'em, uh, twice a year at this point. We used to do 'em every quarter, but just at our scale, we've kind of found that twice a year is a good cadence.
LC: : One of the things that at Most Loved Workplace we have is something called, do well do better. Uh, there's some feedback here and it sounds like you're in the same mind in terms of the Feed Forward approach. What can we do, what can you do as a more effective leader? Is that something that you also follow?
BS: : Yeah, and you know, I think the, you know, companies are driven by personalities, and personalities are, you know, I think there's a lot of different kinds out there. The founders and I have all had the mindset that, you know, there's always a better, like, there's always something better we can be doing, you know, or we could achieve than what we just did. And we just finished our quarter yesterday and it was our best quarter ever. But I'm not celebrating, there's no wine being poured and, you know champagne being popped. I'm just thinking now, okay, how do I keep building and how do we keep creating our impact and, you know, reaching more organizations, you know, it's great that we are in organizations like LinkedIn and Chubb Insurance and DocuSign and Broadcom and, and many organizations, but what about the ones that we aren't yet in and, and how do we, how do we, uh, you know, get there? So I think the growth mindset is something that you hear a lot, which is how do you get better? I always tell people there's a better version of yourself. You just gotta go have the desire to go find that person. And it extends through everything. It's how we are as professionals, but also how we are as individuals, how we treat our friends, how we treat our families, how we treat our body, and how we take care of ourselves. All of these different aspects of improvement are ones that I think feed into each other quite like seamlessly, and they influence one another. If you get very fixated on something over here, you know, another aspect of your life just starts getting better too. And so I think that self-awareness is something that the performance reviews bring forth, but also the culture of people just giving feedback, I think is a big part of that.
LC: : No thrashing, number one software feed forward ever. Focus, getting to that high 95, 99, you said level of, of probability, that's amazing
BS: : For certain models, right? You, you need to have them be, cuz you don't want them to misinterpret. What you'd rather them do is to skip so you can leave that particular interpretation for a human agent in our world, an HR person who can then maybe interpret something. But for the vast majority of things, these are quite mundane routine things. So yeah high precision.
LC: : Awesome. I can't wait to see it. Cause you're, we're talking about things like, like contracting, you were mentioning, right? And HR processing thing, things that can be done easily, right, by humans, but takes up a lot of time and AI can, that you've done at Moveworks solves for that.
BS: : The frontier of AI right now that is really, um, getting worldwide attention is language. And we've talked about computer vision and self-driving cars, you know, five, seven years ago that was sort of where a lot of investment dollars were going. But now what we've seen is that there is a lot of opportunity to interpret language, and language is at the core of our species, but more importantly, it's at the core of how we get work done. And so we wait for each other to read our message, to then take an action. What we've discovered, but now the world is discovering, is that using AI, we can actually have the machines interpret a good majority, you know, our customers see 50, 60, 70% of all issues completely resolved by the machine. And these aren't simple Lou, these are like, you know, people will say things instead of saying, I need a new laptop, they'll say, “Hey, I've been here for two and a half years, I think I deserve a refresh, who can help me”? And for an AI conversational AI bot to come back and says, “ah, sounds like you're looking to update your primary device. I found a form that we can fill out together”. Paperwork, like exactly, that's what I need. That's what I wanna, I want to get to, rather than waiting a day and a half for someone in IT or HR to kind of get back to you and say, “Hey, here's the, here's the process”. So I think we're gonna see a new frontier over the next several years where a lot of the busy, mundane work that even these support teams are trying to get off their plate, trying to make more self-serve, is really gonna go through sort of this Cambrian explosion where a lot of these things will get done through machines and then we'll focus as individuals, as support agents, as leaders on more, you know, sort of intense complex problems. The one-off problem that occurs once a quarter, not the problem that occurs once every seven minutes.
LC: : Absolutely. Wow. It's really been a pleasure, Bhavin and, it is been a great half hour with you on the Leader Show and congratulations, on being a Most Loved Workplace. That's where the sentiment comes in. Emotion analysis of all the text, comments that your employees provide to you. We're listening to that, our employee listening tools and annotating that and understanding that you, I didn't know you, I don't know if you realize that, but we do that as well, uh, to make sure to, for our most loved workplaces, to ensure that we know that you are really a place that people love and that you have these attributes and characteristics of people who love you and they do, with the vision that you're setting forth with the team that you're building, the way that you co-create, the way that you respect each other. We've talked a lot about that and what you give them to develop and grow and succeed. So Bhavin Shah, CEO of Moveworks, thank you so much for joining us today and me on The Leader Show of Newsweek.
BS: : Thank you, Lou.