Particle Accelerator Episode 31 | Aditya Rastogi

In this engaging episode, we dive deep with Aditya, a seasoned sales leader with over 20 years of experience in SaaS solutions, data-driven sales strategies, and leveraging analytics for success. Discover how blending metrics with emotional intelligence transforms the sales process and creates scalable growth opportunities.

🌟 Key Highlights:

Aditya's journey: From managing a family hardware business in India to leading SaaS sales teams globally.

Problem-solving mindset: How disassembling appliances as a kid shaped his analytical approach to business.

Conversational analytics: The future of insights at scale and transforming decision-making in industries like retail.

Driving transformation: Practical ways to connect technology innovations to real-world business strategies.

🎧 Key Takeaways:

Every problem is solvable with the right mindset and approach.

Empowering teams and iterative learning are essential for innovation.

Real business use cases are the cornerstone of impactful AI and tech solutions.

📲 Don’t miss this insightful conversation on data-driven sales innovation and business transformation!

Connect with Aditya:
LinkedIn: https://www.linkedin.com/in/adityarastogi/
Learn more about Ben Johnson at Particle41.com

🔔 Subscribe for more forward-thinking discussions on topics like AI, business growth, and leadership!

#saas  #leadership  #analytics  #businesstransformation  #p41  #podcast #mindset #entrepreneur 

Transcript

 Hey everyone, welcome back to the Particle Accelerator Podcast, where we talk to future thinking business leaders about how to accelerate business and grow their team. I'm here with Aditya. Can you please introduce yourself? Hello, everyone. This is the story. I'm a sales leader. I'm sold. Uh, I have led solutions, uh, for software as a service company, SaaS companies for past 20 years. And, uh, kind of, I believe in, uh, leading sales with metrics and emotions. So kind of a balance of that. And I've kind of, uh, led different aspects of sales from partnership, business development, go to market and made it more kind of process and metric oriented. And that has led left. That has led to my, uh, success. So great to be talking to everyone. Awesome. All right. Thank you man. It's good to have one of our sales friends on here. Uh, we've had some really, uh, really cool science people, and, um, it's going to be great to dig in to, uh, talk about science. And I would like to add that my background is in data science, so I was, I, uh, before I was, was the buzzword, uh, neural network, fuzzy logic. I was doing that, uh, in school and after that many, uh, quarter of a century ago and then kind of continued that in my professional building applications, retail specific applications, uh, for our technology companies and then since then, kind of, uh, used that has helped me kind of brought those insights, analytics into the sales process. And that has been some interesting journey. Really cool. Really cool. Yeah. Yesterday I was talking to you, uh, scientist, about microbes and, um, using AI and machine learning to understand different, uh, genetic data sets. And so that's what I meant by, like, you know, it was it was it was pretty happy. Um, so cool. Uh, cool to be talking to you. So to get started, um, what was your what was your first job? So for me, you know, the first way I made a dollar was, uh, I had a paper route. But for you, what was your first job? Yeah. So that's interesting. I don't know what my first job was. The first paying job was different than my, uh, so my parents I grew up in India, so my parents had parents had a hardware home construction, uh, kind of a shop kind of mom and pop shop. And I was kind of. I started that, uh, and, uh, I was when I was about 12 to 12, 13 years old, I was asked to take care of, uh, the business for a little bit while they were away. So they weren't going out of town. I would be kind of in charge of selling, uh, uh, selling to the products. Right. So to think about that, either in bars or kind of constructions, uh, cement that, that is used for homebuilding. So that was it was not the right kind of you can say, yeah, it was in different ways. And then as I kind of, uh, uh, came here, uh, so then I kind of my journey was I came to us, us to do my, uh, masters, uh, in industrial engineering and operations research. This was many years ago. And at Arizona State and their my first role was at schlotzsky's And uh uh, so I was the cashier there. So I would say that was my first paying job. And that was interesting. I find myself in Austin, Texas, and where Schlotzsky's was, uh, found it so interesting. Uh, events. Oh. That's cool. Um, yeah, I definitely after my paper out journey, I definitely, uh, I liked, uh, during college, I could pick up a job at a pizza place. I, you know, could, like, stretch the doughs and do the do the spinning of the pizza does. Yeah. So many a pizza place. Uh, as I moved throughout my, my college years. So really cool. Well, what toy or hobby did you have as a child that inspired what you do career wise today? Yeah. So it seems it's interesting, right? So hobbies, uh, if I reflect is I used to play play. Right. All kinds of sports. Cricket. Cricket is one of the sports that I grew up playing. But, uh, kind of as a hobby. Not not something serious. But then what I really liked was dissembling things. So I would take any, uh, uh. Appliance and I would open it up very well. The challenge was putting it back together, right? And then I would get into trouble, uh, all kinds of, uh, kinds of troubles. But, uh, I think the challenge, uh, the thing that inspired me was solving a problem. Right? So I would open it because something has gone wrong and you're trying to resolve it. So I was like, let me, let me get my hand dirty and try to solve it, to resolve it. Even though sometimes, most of the times it didn't work. But what bought my intention was, how do I go and get my hands in and try to resolve it right? And then in kind of as I, as I grew up, is like, you can get help, but at least the first thing is, let's let me get my hand dirty, uh, get hand in and try to understand what the problem is. Be there kind of doer. Uh, and then kind of, uh, seek help to go there. So and I kind of kind of drive that in technology as well. I remember a situation where our company built a product was kind of, uh, latest workflows with, uh, at that time, uh, the Ruby on the rails, uh, Ruby on Rails was kind of that latest tech, very fancy. And we had a pretty good workflow and good solution. We took it to the kind of customers and said, this is the AI driven, uh, results. And they said, I don't trust it. So I was like, okay, so we build all that. So then kind of I went in and kind of looked into the data, gave them something that they could relate to, and that's where it kind of it worked out. And they started seeing the value. And uh, I continue to do that is, uh, a problem solving mentality. Try to get in even though not really sure what I'm going in. I'm pretty good at, uh, if it is not well structured, I do really good to kind of make make sense out of it. And the drive value. Yeah. That's cool. Uh, I can definitely relate. I completely destroyed a toaster. Uh, my mom's toaster. I took it to down to its smallest part, and, uh. Yeah, I could not get it back together. It was not the most fun. When you're trying to struggle, it's like, yeah, if you open this, then you can open that. It's like, okay, what do you do after that? Yeah. And I can also relate. I spent quite a bit of my time as a Ruby, just, uh, writing programs in Ruby and, uh, really enjoyed, uh, really enjoyed just the framework, just how comprehensive the framework was with Ruby and then, uh, looked for that feature richness in other frameworks. Um, and so, yeah, I think Ruby on Rails was just like this great example of like, uh, uh, an all you can eat, like everything was there for you reduce some choices, but gave you, you know, all the things to make, uh, setting up a platform, uh, really streamlined. Um, what was your favorite and least favorite course in school? That's interesting that I would start with the least favorite. Right? So my back again kind of talked about industrial engineering. Uh, I did my master's, uh, MBA as well after that, but kind of the most interesting, least favorite I'll start with that was numerical optimization. And that was talked about nonlinear optimization. So I was not going to take that. Uh, this was I'm a PhD dropout as well. So I started my PhD and it's like, okay, this is not I don't see myself finishing this. Uh, I started with industrial engineering optimization, and then I was kind of, uh, the market, uh, the stock markets and just, uh, markets in general kind of fascinated me. I didn't understand it very well, but it just fascinated me. So I kind of went to the, uh, business school, spoke to the, uh, kind of, uh, professor there and said, I want to learn about markets. Took us a finance 701 course, not knowing much about finance. And, uh, uh, first I was kind of, uh, I was like, what the heck am I doing? I first do exams. I was like, I don't think I can do it. Like the professor said, Keep. Keep it up, keep up. I kind of keep, keep running. You have to finish the course. It's like, okay, I don't have any other options. Kind of. And then eventually it's the class. So that was, uh, it was the most tough class that I've taken. The best class that, uh, is taken is in my not not during the school, but after I took a a course from Harvard, disruptive technologies and disruptive, uh, strategies from the professor, uh, Clayton Christensen, Christensen, Clayton. And, uh, here's some amazing view, um, the views on how the market works, how, how and essentially life works, right? You hear we talked about the concept of jobs to be done and then and then kind of, uh, where he inspired me to read his book, which was, uh, how would you measure your life? So take takes the life concept and then applies it to business as well. And that's where it kind of you connect, uh, that what you are doing in life, what you're doing in the business. How do you align those so that you kind of, uh, are driven every day when you wake up, uh, to, to, to do the right thing and, uh, you have you get value out of it. Yeah. Um, I'm a big fan of, like, OKR framework and whatnot, and I when I learned about this in one of my companies, uh, I put all my teenagers on OKR. So I was like, hey, how are you going to like, what's your goal? And then how are you going to measure your progress to the goal? And, uh, you know, one of my sons was like, I want to be a professional video gamer. Oh, okay. Well that's fine. That's an interesting objective. But how would you measure your progress towards that? And, uh, you know, it took him a long time thinking about it. Uh, but he's like, well, I guess I'd have to play competitively more often and like, well, how much time do you play video games? And he gave me that, that number of hours per week. Like, okay, well, how many of those hours are competitive hours. He's like, well, none of them right now. Like, okay, well how many of those hours could you shift to playing in a league or in a competitive. And so, yeah, he shifted just so much to realize that that's not something that he really wanted to do. But without the, uh, without the tracking of it, then our goals are just dreams or wishes. Uh, they're not like, actually, um, they have not actually become part of us. And so a really cool oh, what quote from a famous person lives in your mind rent free. Yeah. So that I would say kind of, uh, uh, every problem can be solved if you, if you put your mind to it. Right. Uh, the one thing that I do not remember if we said that, but it's not me. Uh, and another other one is, uh, that that definitely I think of it every day is from, uh, Martin Luther King is, uh, uh, if you, uh. And I'm not doing a justice in the South, but I'll paraphrase what it meant was, uh, uh, if you're not helping others, what's the purpose of life? Right. So every day that I'm kind of giving things, that ideas, how do you help others to get value, right? And we are living this life. And the idea is how do we put ourselves in help others? Yeah, I totally, um, it takes a lot of personal development, right, to actually shift, um, shift that I find that if you're, uh, seeking approval from others, if you need to be valued right, then it's hard for you to give value. Uh, so, um. Uh, I love that. I love that thought. Cool. Um, what do you feel was the greatest invention or discovery in the past 300 years? Well, I don't know about, uh, kind of. There's there's a lot to consider. Right? But, uh, I'm more, uh, weighted in the recent history. So obviously, iPhone has changed our life. The next invention that would change our life is self-driving cars. It would totally transform how we think, how we live our life, our daily activities and everything else that we do. Yeah. So I don't know. I mean, I'm sure if past 300 years, I could not relate to that, right? The electricity has has been so pretty amazing, has changed our life. But just, uh, what I've experienced life. Everything else, I'm assuming it's given. Uh. From there. Have you tried a self-driving car yet? No, I've not. Uh, and I'm kind of, uh, excited to sit in Waymo. Uh, I think they stopped in Austin. They were. Uh, they were testing it out for. I think they are paused for now. Yeah, yeah, I, um, a couple of friends have mentioned that they've tried the S mode, the S drive mode in their Tesla, and that that was pretty, uh, pretty exciting. Yeah, sorry, I misunderstood. You're talking about self-driving cars. The completely. But yeah, I've. I've driven seven kind of the they say pilot assist, right. Where they, they kind of help help with cruise as well as the up. Yeah. So tried that. I don't think I'd trust it yet. Uh, or anywhere close. It's good. Good. Uh, kind of good to have that additional assistance. That's about it, I would say. Yeah, I, um, I, I drove a BMW once that had the, uh, it wasn't nearly as much, um, as the the Tesla s drive mode, but at least, um, I could set a speed that I desired to go. It was like assisted cruise, right where I could set a speed I desired to go. And then as I would come up on a car, it would match that car's, uh, speed. And it was, like, effortless. Like absolutely effortless. I still needed to be in control of the vehicle. Um, but, uh, like, the lane assist was pretty amazing. Like it was keeping itself between the lines, and then it was regulating itself based on the car in front. So all I really had to do was just kind of sit there, um, and get it into position. I mean, that was, uh, that was pretty advanced. I mean, definitely getting getting better at, uh, the, uh, I think they started a few years back, about 5 or 8 years back. Right. And, uh, uh, kind of, uh, it's just where, where I've tried the newest and, and some of the older times as well. It's definitely got much better. But there's still I'm that's where the risk is. Right? If you if you think it can do it in the moment, you trust it and it does not. There's too much, too much at risk. Yeah for sure. Well cool. So what tech trend, uh, has significantly impacted you or your industry and how has your company responded? Yeah. So that's definitely the big buzz is Jenny right. So but but talking about AI it's it's about conversational analytics where I believe there's a lot of impact. But I think uh, conversational analytics from because I'm, I'm a big analytics buff in terms of there's, there's a lot of information to be gained from the data. Uh, and you can kind of slice and dice and spend a lot of time with Tableau and kind of visualizing, uh, insights, uh, as a like consulting teams and consulting projects. But taking that with conversational analytics, what you can do is you can take that and do at scale. Right? So you, uh, companies hire consulting firms to give them insights to, uh, get insights from the data, what they would not do. But now you can do that at scale. You still need kind of the business, uh, domain experience and knowledge. But now you can kind of productize and create a system where you can get those insights and recommendations a lot quicker and at scale. So I believe that is where, uh, kind of that has done, uh. When the industry is shifting. And then if you layer it with LMS and kind of JNI, this is where you can kind of make it more user friendly from a UX perspective, how you engage. But the underlying concept, I think, uh, is where you can do it at and there are few companies that are getting there is because there's a lot of, uh, contextual data that you have to gather at scale. But, uh, I think there's a lot of scale challenges, and there are few companies that are doing pretty well, companies like Datastax and others. But, uh, I think it's not it's not, uh, in, uh, it's not done across across the industry yet, but I see a big potential there. Mhm. That's cool. Um, well what are three technology innovations you are like betting on to drive your business growth going forward. Right. So one one would be uh, definitely. Uh, and it's I would not say it's a technological innovation, but that would help drive that. One is integrated tools. Right. So when we think about, given my focus on the sales for last for. Last few many years. There is a lot of systems that are available for teams to use, but they're not really connected. Salesforce would say they are kind of they can integrate with anything, any, any external tool. But is it right? Is is the information flowing or is it just the data flowing. So you need to architect a solution where you're connected with kind of your outbound technology, your market research technology or your, uh, your ad systems, your CRM, Salesforce, HubSpot. And then that is making decisions. So I think, uh, integrating this with uh, uh, the, uh, genie layer on top can automate a lot of this go to market activities, can automate a lot of these business development, uh, cycles. Right now, the, uh, businesses are spending a lot of time and energy for, for right reasons because there's no other options right now. But slowly, there's so much curation that can be done. Automation with intense signal that, uh, can can resolve. Can give more time to companies to strategize rather than on the execution. Yeah, I totally agree with you. I think the like the number of emails that I'm receiving, just even in that like in my inbox, there are intents that I have. There are people who, even if they were emailing me cold because of my intent, I would want to talk to them. But there's also a whole lot of things that I have no intention around, and I want that stuff to be discarded and blocked out. So it does seem like, um, so I'm super interested in what you had to say. And I think even just the idea of improving the email experience, um, could be huge there. Like, I intend to find a technology partner. I intend to, um, uh, you know, I intend to buy a house. Okay, well, if I know your intent, then can I do a good job of filtering your email or you. Probably. Right. Probably. Then majority of. But even, like, um, around, like my LinkedIn messaging. Right. There are certain people that I would love to talk to and many people that I would love to just give it quiet or, you know, a polite, um, a no thank you. But to do all of that, to spend that time, you know, when it really could be data driven is probably pretty straightforward. That definitely I think, So that that was one I just said three. So I think I combine one and two a third one. I think there's a lot to be said how enterprises exchange data. Right. So we have, uh, we have uh, three big clouds, Azure, Google and Microsoft and AWS. Right. And then there's a bunch of kind of solution providers who are ingesting data, sending the data back and forth, and that creates kind of, uh, cost as well as inefficiencies. Um, I was working closely with Google, and Google has something called uh Analytics Hub, which is and others, uh, cloud, uh providers have something similar. But where it is going is now you can have one data set, give access to whoever it needs to have without ever transferring data. And that is huge in so many aspects. And now this is a way you can kind of, uh, multiple things if you are internal for your internal ecosystem, you can have one data system where everything is connected and some people are trying to get there. It's not there yet, but think about taking that model across the enterprises with the right level of security, because security is the key component. But now you have the efficiency and availability of data that people are not not used to and imagine. And that created amazing use cases and value for the businesses. Hmm. Interesting. Um, well, give me an example of how this would work. Can you give me a practice? Yeah. So let's talk about a retailer. Right. So retailers, uh, kind of have, uh, CPGs right there. They have, uh, they talk to, uh, hundreds of vendors. Right. So Johnson and Johnson, Procter and gamble, uh, let's say, uh, retailers are to have the data from their for their, uh, transaction system that they sold 500 units of, uh, bag of chips in, in, in a certain store. And in a given week, the way they transact, how the, you know, P&G would know is either they have kind of curated set of data that the retailer is sending them or kind of or, uh, accessing that data for the retailer. Now, retailer can say, this is my POS data, uh, in this cloud environment that is being updated and this is my system, you come in as a P&G or Johnson and Johnson, you come in and you have access to this portion of the data for this time frame at real time, right. So we talk about APIs and data transferring through APIs, real time. That all goes away. Now you have access to that data without data ever moving. That's what I think about the efficiency is that you're creating the is that you are creating the simplification that you're creating and at scale. Mhm. Uh, wouldn't that require something like blockchain or something to describe all of that data. Like to tag it for, for some, for an abstraction of that magnitude. Not not really. Right. Because for example, BigQuery has kind of. Well, I'll give you an example of BigQuery or redshift or anything. Right. They can handle large set of data. The question is why would a retailer allow someone else to access the data within their cloud environment? Right. So that's where safety and security comes in is ah, I don't want to give you access. I'm very protective. Right. Especially in this day and age now. Uh, these cloud providers are providing tools where they are managing that access level. They're giving controls to the level and obviously with a lot of trust, built a lot of factors built in that this person can have this level of access to your data set, and the data set does not move. So so now I think those are the level of kind of technological innovation that would allow easy access to data across the enterprises. Right, right. And and to in your, uh, analogy, even some level of segmentation, right to access. Right. You share the data, what you want to share with that set of folks. Right. Because because you don't want to share everything with everyone. Yeah, that's really cool. Um, going back to conversational analytics, I'm not sure I completely understand that concept. So it sounds like it's an approach to study, um, some level of the social interaction. Um, but explain that a little bit better. I know I should have asked you before, but. Yeah. Yeah, definitely. I'm glad you asked. Uh, let's talk about retailers as well. Right. So they have transactional data, right? Thousands and 100,000 people are Walmart. Right? Uh, a lot of interaction happening online, a lot of interactions happening in store. They have a bunch of information sitting there. Uh, how would how would, uh, category manager. Right. Say that which products are trending or which products are trending for, uh, age 15 and 25 or it's back to school time. I was expecting this set of this category to really take off. It did not, however, some other categories as they came up. I need to find more products to fill in my store. Right? So somebody really has to build out what has happened in terms of buy in the last ten, 15 years. Is people are curating. I want to have this set of views available. So I want to look at my business in a certain way. You have kind of in one axis. I want to see the time frame or the axis. I want to see the type of sales other x the third axis, I want the the who was buying that the demographics of that. Right. So you are designing all that. What conversational analytics does that is you do that definition. You say these are the 15 parameters. These are the types of questions that I'm going to ask. Right. So now you're taking LMS. You are feeding the initial questions. But now you're saying these are the types of questions. Apply that to these 15 or 80 different parameters and tell me what is off or tell me what is interesting. And slowly then you can say, okay, this is really taking off. You may want to look here versus look there, right? So now you are doing those analytics consulting work at scale in the regions that you have not really explored or didn't even think of. Yeah. Outlier analysis becomes just like give me the outlier analysis. And it's uh, it's it's abstracting that where we typically have to do, uh, you know, custom reports. Right. And outliers, you are looking at things that, you know, now you're looking at things that you have not even considered. You just have that factor or parameter, and you just kind of it scans through it and say it does the trends and then find out outliers where, wherever it exists. Cool. Well, what do you think some gaps are between your ambitions and the realities of today? Yeah. So it's kind of, uh, tools and architecture, right. And just the level of awareness and the, uh, adoption across different, uh, aspects. I think one challenge that I've seen across teams is they are so, uh, and for all good reasons, everyone is trying to do their best to solve their problems. Right. To say that is. Now don't look there. Look here at the shiny object. It's like I don't have time for it. And that's the balance in an art, right? Is how do you make something, uh, a concrete where you get their attention, you carve out some time to test out and and then roll it out, invest, uh, in that. And it's a kind of slow process that you need. And there are different kinds of people and organizations for a reason. You need people who can run business as is, people who can kind of give a short term and medium term strategy. And then there are people who can kind of think, what happens? Where is the industry trending in three years? And this is the combination of all three coming together. And that that's where kind of, uh, those technological innovations either fail or succeed. Because then that option is how can you tell the story? How can you continue to make the execution life easier while having them transformed into something where they can do it more effectively? Yeah. Typically you would just be talking to the horizon three people, the people who are kind of laying out the, um, emerging technologies. Um, but what you would like to do is be able to talk to all three horizons at the same time. Like this could actually impact your bottom line today. Um, yeah. That's interesting. So that's kind of the team. What about the tools? Yeah, the tools is, uh, kind of there's, uh, and one, one thing that has stopped, uh, kind of challenge is the ecosystem with the different clouds. Right? So the way the cloud structures are set up is you're in one cloud, multi-cloud. People started with that, and you just cannot, uh, uh, you cannot have that strategy. Right. Because then the data transfer becomes then you're, you're creating a new set of problems. If you do AI in one place, if you do kind of compute another place and so on, it's just uh, uh, not set out. So eventually I think, uh, in few years, uh, I think it will have to, uh, then slowly, I think, uh, folks are realizing that and there's a lot of pressure in the from the industry to kind of reduce that friction. Right now there is some friction created, but eventually that would go away. And once that goes away, then you can seamlessly integrate, uh, redshift with BigQuery and using the Gemini with the open AI. Right. That's where the power comes in. And right now there are guardrails on purpose. Yeah. Well, it's still very much an arms race to who has the most complete solution. And uh, the consumer cannot, um, mix and match. Um, right. Uh, without without tremendous effort. Um, well, what's the biggest challenge to maintain a competitive edge in your industry? Yes. I think the, the biggest challenge I would say is having, uh, having a tool or a solution that is really solving the business use case, right, with kind of, uh, when we talk about AI, right? You could create a, uh, uh, the self created AI and say, this is the leading edge, and you would create routines that would solve very specific purposes. Now you go to Python and you have everything available, all the tools available, uh, everything available that you can build, a Gemini you have built, you can build anything at scale if you have the right, right, folks. So that kind of building, building the best AI solution, uh, competitive edge is long gone. It's now the the best way to gain competitive edge is when you're solving real business use case and doing in a way where, uh, where your interaction with the, with the people who are using it is more human. So that's where more effort comes into the UX. Uh, and say, what are you designing? Right. So I was talking to, uh, this, uh, my, my collection, uh, somebody I know haven't picked a name, but essentially the building are generally a solution for for the tour. And the idea is that somebody comes in and it gives them kind of walks them the process of how to create a workflow. So the question there is, how do you keep it engaged? You can give them 15 different workflows to choose from. And it's inundates the user and say, okay, screw that, I'm not using that. How do you make it curated? And that's where a lot of a lot of experience from what are you trying to solve, what jobs are to be done by back to the fact of what has influenced me, and then how do you simplify that? And it has to be as simple that you say, what's the value that you're at? And that's the value that you're adding is you're simplifying it and everything else is happening in the back end to give you the right answers. And then you can dive in and get transparency. And that's how you create the edge, because at that point you cannot be replaced. You people are using it, using it with ease and spending more time thinking about their business than execution. Yeah, it has to be customer centric. It can't just be a primitive, right? An underlying tech is very difficult to sell. Totally agree. Um, well, um. What? Uh. What? How do you approach risk when you're implementing, uh, cutting edge technology? Yeah. So obviously, as I said, there are risks, right? There are all kinds of risks. And the risk is, uh, if you're implementing a new AI for a better forecast, but if the data is not there to even do anything right. So question is, how do you, uh, uh, and goes back to do do you understand the business that you're solving? Right. You do you understand the use case? And from that perspective, what's the decision? Do you have the right data to make the decision, and how are you going to resolve if there is no data to back your decisions? Right. So those are the kind of layers that you have to think through. And and also then kind of from um, the other risk is also, as I mentioned from a change, change management, how do you de-risk, how do you ensure that every layer, uh, of the organization is incented? We have solved your solving there there challenges and it's just not a three year down the project. It is something that you put in front of them, get their input and, and revamp. Right. So kind of uh, one thing that I've learned, uh, through my experiences, if you build a product and say this is the best product in town and this is the best solution you can have, the moment the user uses is like this. This sucks. What do you do from there? So when you're building a product it has to be iterative approach. And you you put something out there fail fast right. Do you kind of say, okay, what doesn't work? How do we make it better? What have we what doesn't work? How do you make it modular? How do you configure it. And then kind of continue building that. It's not one and done. Mhm. Yeah for sure. I think, uh, keeping, uh, common thread here is to keep an eye on the user and then, uh, just make sure you're not biting off more than you can chew, like, you know, don't do it alone. Right. Um, well, what advice can you share for connecting the technology roadmap with your overall business strategy? Like, how do you guys do, um, your planning and how do you make sure that where you want to go and your roadmap are all aligned. Right. So and that's a very important question. Right? I think, uh, uh, when uh, uh, Jenny was the big thing, uh, when it first came up from a OpenAI. Uh, right. Uh ChatGPT was was the buzz. Everyone wanted to kind of say, okay, now this is a this is either you you are using this or it's end of the world. Uh, there's a lot of pressures from that. But I think you have to understand what's the underlying business problem that you are trying to solve. Uh, you have to keep that, uh, test out. Right? So you have to say, what is what are my test modules? How do how do you test ensure that you're on the right strategy. You use the feedback from the field and then be ready to pivot as it comes along. Right. So if you you can you definitely have to create a kind of a year, two year, three year vision of where you are headed to go. But uh, be ready to kind of, uh, provide inputs of how you are going to, uh, change or adapt as you're going along that and that that becomes very important as you're thinking about your strategy, uh, your perspective and how you are going to sell it to your customers. Yeah. That's cool. Um, do you guys typically do like a quarterly planning or annual planning or how how do you go? It starts with the annual planning. Right. So when you're kind of figuring out the budget, but then you kind of say, okay, this this is our plan planning for a year and two years. Because when we are building out the vision, it's a year to year and a three year where we want to be. And this is more kind of, uh, but then every quarter you have to come back and say, okay, uh, what what did we, uh, what did we assign for that? What were the lessons learned and how does it change our course for next three months, six months, one year and two years? Right. So you have to kind of continuously, uh, inform your strategy just to be relevant. Otherwise you'd be kind of aiming somewhere and building something else. Mhm. Yeah I agree I'm seeing a lot of trends with time compression like uh having a one year goal. But then you know really drilling it down into like 12 weeks, uh, you know, a 12 week plan like our iOS friends are, um, really doubling down on that. And, uh, there's a popular book out. Uh, recent book called 12 Week Year. Uh, really kind of focusing on the 12. And in software development, we, you know, we always had like sprints and, you know, we're very time compressed. And so I'm seeing a lot of folks revamp their annual planning for something that, uh, draws a little more urgency to the, um, to the, to the tighter time window. Right. That definitely I think that, uh, uh, the and, uh, as I was talking about when we build products like this, it's important to get feedback. And same thing with, uh, strategic planning is you have to say, okay, what did we learn? What did we learn from the different aspects, the sales operation and product, uh, and customer side. Let's take those inputs and see that there's those still matches with our assumptions that we made at that time. Right. Well, what lessons have you learned from tech initiatives that failed to deliver expected value? And I've had my share a share of failures. Right? It's kind of that one thing that I live by is if you have to fail, fail fast. And, uh, and that that's something that we do. One thing I would say is, uh, uh, if you if you're thinking of a business kind of a new revenue or anything new, it has to be profitable even in a prototype or you're doing something or only then you can scale, right? If you say that, we'll build it and then we'll become profitable, that does not work. So you have to think about the whole ecosystem as you're building out, even though at a smaller scale. And then once you build that out, otherwise you're building one component without knowing what the other, how would it all come together? So, uh, in my kind of that's something that I've learned is don't invest too much time on one concept. Test it out, test it out with the people who are using it, others and get their input. Uh, and then kind of, uh, one thing else that I would say is empowered the team to make the right thing. So you hire people for their skill set, use them for that. Right. So you have to sell your vision. You you just can't tell them and do this and do this because that's the vision you have to share the vision kind of empower them to say, okay, how do they contribute to the vision? And it's becomes a joint joint and everyone is excited for for it. Yeah. I've heard, uh, just recently checking out this, uh, three laws of performance, uh, book. And one of the, one of the things they talk about is, um, your vision is future based language. Like, people perform their best when when they use future based language rather than descriptive language about the current and, um, the your vision, like in order to create that feature based language, really it should be a collaborative effort with the team. So what is the future that we can all collectively envision so that it's not, um, because what you what you alone think the future could be is going to be far less than what a group of people might think the future could be in allowing those, um, aspirations of the entire group to set the vision, uh, is really powerful. Um, and so even not thinking that as a leader, you have to set all the vision you can, you can ask the question like, what is the future that we want to create together? Definitely. Totally agree. I think that's that's the that has helped me quite a bit in kind of inspiring, uh, people as well as kind of getting the best out of them, challenging the team and, uh, creating the best. Yeah, well, in this question, I'll go right along with that. How do you cultivate a culture of innovation and fluency within your organization? Yeah. So I think going back to that, empowering the team and then ensuring that with with how the technology is shifting, you have to ensure that they are they are set up in where they are learning and growing as well. Right. So it's just not what you have done. What you know is what you need to learn and learn. Learning happens in different aspects. So I know the one. One best way that in my experience, is when you talk to your customers and their challenges, those are the best way to kind of understand what they are going through, what their challenges and as a provider, what you're trying to solve. And and then the other aspect, obviously giving them some kind of, uh, uh, a learning system of whether they are whoever and everyone has a different style and ensuring just don't assign five courses to everyone in your team that does not work, but inspiring them that it. Let's try something else. Let's kind of, uh, experiment within within a compound. Right? This this kind of business has to be done as well. But giving them the space to grow and that growth mindset. Yeah. That's cool. Are there any practical ways that you've been able to, uh, to apply that? Yeah. So I think one of the key things that we have done is, uh, create a sort of we as I've, we had a lot of challenges that we, we, we cannot solve right away as a, as a feature or a product. Right. So we have kind of a big backlog. So we, we kind of created a hackathon. It's like okay, let's, let's say some time of X hours in this two week period and go for it. I did this other set of problems or any other problems that you may have been thinking about, and let's try and find a solution. And we found that at first it was very engaging. But people are facts of life. Even if they're not programming salespeople that have their challenges, they would come in, partner with others. So it kind of, uh, kind of helps with culture, but then also helps them from problem mindset. Right. So what are we doing? Get them involved. More involved into what the what the company is trying to do and how can they add more value. Yeah. Really cool. Um, cool. Well, um, what advice or shared experience would you give to, uh, to peers that are beginning their, you know, their career journey, their sales journey, or even their digital transformation journey? Yeah. So I would say as you're going through that, uh, the final partner or you already have a team, what who understands your business needs. Right. So transformation for the for the sake of transformation does not work. Uh, transformation is a long journey. You need to be totally bought in. It's not. You know, if you press a button and it's done, you need to understand, uh, what all components need to change. Which will have biggest impact. What will what will be the kind of the wave effect? Because everything will get impacted. Don't lose patience because things will go wrong. But then in the long run, it will be, uh, you'll be much better positioned and more capabilities and more scale. Yeah. Really cool. Well, cool. If people like what you've had this shared today, how could they? How should they connect with you? Uh, LinkedIn. LinkedIn is, uh, best way to connect. Uh uh uh, I don't know if uh, or, uh, well, I thought that would be the best way. Find me on. Okay, we'll make sure that gets in the show notes. Yeah. Awesome. Well, cool. It's been really great catching up with you and hearing about your journey and your, uh, the innovations you're engaged with, and I just really appreciate your time and being on the show. Yeah. Thank you. Benjamin. That's fun.