AI-Led Services Quoting for Salesforce

Carlos Ponce (00:12):

Good morning everyone. Welcome to another episode of Tech Leaders Unplugged. And today we are getting unplugged with Mahesh Baxi, the CEO and co-founder of Provus. And of course, as ever hosted, co-hosted by my fellow teammate Wade Erickson.

Wade Erickson (00:32):

Hello everyone.

Carlos Ponce (00:33):

Welcome to the show. Welcome, gentlemen.

Mahesh Baxi (00:37):

Thank you so much. Thanks for having me.

Carlos Ponce (00:40):

Absolutely. It's our pleasure. We look forward to this conversation, Mahesh. So I'd like to start off by you, tell us a little bit about you, well, us and the audience about you and Provus, what's, what's it all about. So, let's start with that, and then we'll continue with the topic. Thank you.

Mahesh Baxi (00:59):

Great. Absolutely Carlos and Wade Thank you so much for having me. Really pleasure and looking forward to this conversation. A little bit about me: within the industry for close to 30 years now. But there are really two key domains that I'm super passionate about and where I've spent most of my professional life. One is a domain called Code to Cash and Code to Cash kind of covers, you know, everything from your lead all the way to getting the cash or getting paid. And that actually covers all of the different spectrums, right? I mean, the core to cash has actually become sort of mainstream in the last 15 years. And I've worked in this industry you know, going back to 2001 starting with a CLM Contract Lifecycle management company, a pricing optimization company. Then I was the first employee of a company called Aptis, which is now known as Conga, which kind of defined this category called Code to Cash. And so super passionate about that, and I'll talk about pros and how it relates to code to cash. But the second domain is HR Tech. And I've done my entrepreneurial stance in the HR tech domain because I, I believe, you know, the technological advances have a lot of potential to change the HR tech industry. And so that's, that's what I did. You know, most of all, I love solving complex business problems for enterprise customers. That's really how I would define my professional career, and that's what I've done. Now you know, coming to Provus, Carlos, Provus is basically a service quoting automation platform, right? What we essentially do is we enable the quote to cash motion for the services. And when we say services, it's all kinds of services to name a few. It could be professional services you know consulting services companies. It could be asset-based services, pharmaceutical services transportation services, and so on, so forth. Y you know, the reason we started Provus, me and my co-founder started Provus is because there were a lot of tailwinds about the success of a product, CCP, QSS, and quote to cash when it comes to products like a physical touchy Philly product or software, subscription products. But you know, when, when we asked about 30 companies, this is two and a half years ago when we started pros, when we asked around to about 30 companies of all different sizes everyone was doing services quoting on Excel spreadsheets. And as we know, a lot of enterprise software products are built, to solve problems that are done on Excel spreadsheets today. So, we'll talk more about Provus, but you know at the end of the day, we automate the entire services quo process, right? From your scope discovery to estimation, to quote, to, you know, creating multiple different scenarios approvals, collaboration, output documents such as ss, o W, and of course, you know, all the of kind of northbound and southbound integrations as well. But that's what we do.

Carlos Ponce (04:06):

Thank you so much, Mahesh. So now let's move on to the topic as chosen by you. So we're going to be talking about AI-led services quoting, right? So, we're going to be discussing and elaborating on service-based organizations quoting automation for sales teams. Okay. First question that I have for you is, why did, why did you choose this topic? Why did you feel it was relevant for this day and age? Let's start there, please.

Mahesh Baxi (04:34):

Yeah, yeah. No, that's a, that's a great question. So, so the way I describe this journey and it's, it's like a 1.0 version and 2.0 version. What we are going to talk about today is 2.0. And most customers are still stuck on 1.0. I'll explain what I mean by that. So, the way we explain the services coding automation journey is, is in four different phases or four different ways, right? So, one is you, you have to acquire your data. Most companies, like I said, are on Excel spreadsheets. You would be surprised irrespective of the size of the companies’ public companies, billions of dollars of revenue and services. All of these companies are doing their entire services quoting on Excel spreadsheets, right? That's our biggest competitor if you will. And, and so that's, we, we are in the process of, you know, kind of retiring Excel spreadsheet-based processes and bringing them onto, you know, more modern way of doing the services quoting, but most customers struggle with acquiring the data that you need for your services quoting to be intelligent, to be smarter, and to learn from the historic you know, the data. The second phase we talk about is then you have to organize. Once you start acquiring this data, you have to start organizing that data in a meaningful way. The third one is really analysis, as we call it. The analysis is now that you have acquired and organized your data, when it comes to services quoting you can start analyzing, right? All of these three things, which are acquire, organize analyze are what I, what we call 1.0 journey, right? And most customers are still on the 1.0 journey. The 2.0 is now, which is what we call the fourth phase in the evolution journey the prediction, right? Mm-Hmm. <affirmative>. Now you want to start, you know, if, if you have done those three things really well in terms of acquiring, organizing, and analyzing those data, well then you are at a stage where you can advance to 2.0 journey and you can start predicting what's going to happen or start getting recommendations. Now, this is where the AI technologies kind of come in, right? And this is one of the areas. So, if you, if I step back and look at a lot of the, a lot of the processes in the, in the sales area, right? You, look at lead management, you look at opportunity management, you look at professional services automation, you look at ERP, you look at contract lifecycle, all of these processes have evolved over the last 10, 15 years, and they are at a, at an advanced stage where you can start applying the AI. But when it comes to service quoting, you know, you won't believe all of our customers. We ask that question, which is, can you give us data in a structured format that can be ingested into our AI engine so that you start getting recommendations? And guess what the answer was? No one actually has the data that can be ingested directly into the training modules of our AI engine, right? And that's the reality, right? So basically the 2.0 journey is, is something that we are super excited about, and I think that's one of the, when we say we enable the core to cash for services, this is one of the few areas left to be automated in the enterprise businesses, and AI is very ripe, and we just need to kind of fast forward the acquire, organize, and analyze pieces and get customers onto the 2.0 journey very quickly, because the advantages of that 2.0, which is something that we'll talk about as, as we go along, and if time permits is tremendously you know, useful for the enterprise companies when it comes to revenue maximization and margin optimization.

Carlos Ponce (08:27):

Great. Thanks. Thanks again. That was so enlightening. Wade, I know you have some questions, right? You want to go ahead and jump? You're on mute.

Wade Erickson (08:38):

Yeah, I was on mute. So yeah, so my experience, of course is that 1.0 version, which is the product CPQ that you talked about. And you know, given the tangible world is often easier to visualize than the intangible world of services, can you talk a little bit about some of those nuances, so folks like me who, that come from, you know, having complex bill of materials and those kind of things that are tied within the sales process as we're collecting maybe some of the environmental issues that need to be proposed to the proposal engine to come up with the structure, and then of course, the tie into the ERP and bill of materials. How does that translate into the intangible world of services and some of those kinds of handoffs and then, like you said, where the AI is kind of used to make that process smarter, if that Yeah.

Mahesh Baxi (09:33):

Makes sense. That's a great question, Wade. So I'll talk about that in two, two parts. One is the 1.0 parts, which is, which will explain, you know, the, the kind of comparable in terms of the bill of materials world, which is what we call the product CPQ, and, and we are basically services quoting or services CPQ. And, and so what happens, and the fundamentally the services quoting is different than your product CPQ or the bill of material world is because there, there's a concept called price waterfall, right? And price waterfall in the touchy-feely product is like, Hey, you start with a list price, you apply a whole set of, you know, discounts, tiers, you know, all sorts of stuff, and then you arrive at a price that you want to sell. You know it could be complex, but it's fairly straightforward and it's a price waterfall concept. When it comes to services, it's a multi-dimensional approach. And what I mean by multidimensional is the, the concept of price waterfall no longer applies. The, you are dealing with different dimensions on one dimension. You are dealing with very complex scope that you have to dynamically figure out with the customers, right? If, if you were to implement ERP, you have to, you know, you know how to sell ERP software, which is, hey, you know, this many users, this many subscriptions, this many, you know, three year contract per user per month while, and you apply a bunch of discounts and stuff like that, and you know how to sell the subscription, but because you are selling that subscription for a million dollar does not translate into your services being a million dollar, right? For you to say that, hey, it's going to cost you a million dollar to implement our e r P software for you. You have to go through the entire scope discovery. You have to figure out, okay, how many processes I am I going to automate? What are the integrations I'm going to do? What is the workflow process look like, right? So, you have to do all of that stuff. So that's just one dimension. The second dimension of that is the resources, and then resources could come from many different locations depending on the kind of company you are, you are, and where you offer those resources from. Then the resource mix, sometimes, you know, you can get away by 50% onshore, 50% offshore, but sometimes maybe you need 70% onshore because it's the kind of company or kind of project or customer that is resource mix. Like you can do, you know, a good mix of senior and junior resources to get the project done and, you know, all that kind of stuff. And then on top of all of this is, hey, how are you going to ramp up and ramp down your resources, which can still deliver your scope, right? So now you are looking at like, so many different dimensions as opposed to the price waterfall in the product world, and which is what makes the services quoting very, very unique if not more, it's equally complex as product C P Q, and if it's not bigger, it's equally big as the product CPQ, right? Because now you are talking about professional services companies, consulting services companies, asset-based services companies, all sorts of stuff. And each of them has very different nuances in terms of how I estimate how I code. And the fun thing Wade about this industry and, especially services quoting industry, is, and, and I'm preaching to the choir to two of you here, is like you, you create a first baseline quote, and I put that in front of the customer, and it's not like, okay, you know, where is the dotted line? I'm ready to sign. It never happens like that. What happens from that on is an extremely messy affair. What that means is customers will come back and say, well, I don't have a million-dollar budget, you know I have an 800K budget now. Yeah. I mean, if you're desperate to win that business, you can say, okay, I'll give you a, you know, 20% discount, and let's close the deal. But what you, unlike your product CPQ, if you extend a 20% discount in the services quo world with what happens is you are actually underselling your highly sellable, highly skilled resources because you are taking a margin hit across the board, right? But, you know and, and this is now I'm transitioning into phase 2.0 of the evolution, which is, until now everyone has been doing what I just described, which is like, oh, let's put the Excel spreadsheet together, let's just throw 20% discount to get the deal done. Nobody knows exactly how you sold the deal. Nobody knows exactly. You know, what happened through the negotiation of the deal was one of our enterprise customers told us the CEO of this company told us that they ended up with 55 different versions of Excel spreadsheet in the six months of negotiation. And he is like, I have no clue what I'm signing. I have no clue what has been considered. I just, you know, basically at that point in time, I'm, I just trust that the team has considered everything that possibly that can be right? But no one can figure out anything out of the 55 versions of the Excel spreadsheet, which is where our scenario modeling and some of the advanced features kind of come in, but transitioning into 2.0, this is where the fun begins. And this is where a huge opportunity is, is there in the industry overall for AI, is to actually change the way, the services quo works. Imagine you know; you have done hundreds of these projects. Let's say you have ERP implementation, in our example, you have done hundreds of these projects, you have sold these projects and you have executed these projects, right? So, we, at Provus, obviously know what your sole margins are. How did you sell? What was your work breakdown structure? How did you estimate, what were the resources? And then we actually integrate with professional services, automation tools, and we bring that data back and say, okay, now the AI engine starts working the magic saying that, hey, you have sold a hundred of these deals. You have executed a hundred of these deals. Guess what? If you want to get to 800K in a meaningful way because you know, you have sold at a 55% margin, but guess what? You have never realized a 55% margin; you have only gotten a 40% margin. Now, in an Excel spreadsheet, nobody can tell you, how I got to a 40% margin and what, should I do in the future. But this is where our AI engine can come and tell you that, hey, you know, in that integration phase that you're estimating a hundred hours, guess what? In a hundred projects that you have done, you have always spent a thousand hours, right? You have lost a bunch of margins there. Now you have two options. You can either bump up the integration phase to, you know, maybe a thousand hours so that you're not losing money on that. Or you can say, hey, customer, you know, this, this might be something that your team might be able to do, right? And we will be happy to help you, but why don't you guys take care of it, right? So now you can start imagining the possibilities. We talk about maximizing the revenue, and we talk about optimizing the margins. As you know, services companies of 1% of optimized margin have the effect of 12 to 15% top-line you know, bringing the top-line revenue, right? And with those kinds of cases, now all of a sudden our AI engine starts to put this sold data and executed data in a meaningful way and start recommending scenarios saying that, hey, for this industry, this customer, and whatever attributions that you want to assign to, like, how competitive are you? You know, how well placed are you all that kind of stuff system will start recommending saying, hey, here is the scenario. It should have this scope, these resources, this resource mix, this location. And you know, you are going, you are good with 45% margin, but you know, highly likely that you'll actually realize the 45% margin, right? So that's where the AI and 2.0 evolution starts coming in. And trust me when I say this, every customer large enterprise customer wants to start with 2.0 without realizing that, you know, they don't even have 1.0 in place. And, that's where we are trying to bridge that and say, hey, you are to go through the acquisition of your data organization, of your data. Start analyzing that data in a meaningful way, and then, you know, we'll, we'll come and, you know, start working with you on the prediction part.

Wade Erickson (17:15):

Yeah, that's a great point, because AI ultimately needs to learn from your data and not from somebody else's, because now you know, it's going to be basically implementing somebody else's concept of all of these things you just spoke about. Great response, by the way. I, that, that, that cleared it up for me quite well. Tell me a little bit about your background you know, as we pivot a little bit away. Well, first of all, let's talk about how your product works. Cause Obviously this is very integrated heavily with your, not only your CRM systems, where the information's obviously collected from the customer interactions, but then, you know, as it pulls in other data sources and other systems that support you’re the quote process. Tell me a little bit about how I use your system. How do I get access to it? What are the plugins and how is it pluggable to other things? And that kind of stuff.

Mahesh Baxi (18:15):

Yeah, absolutely. Great, great. So, we are built on the Salesforce platform, also known as force.com, right? But that does not mean that you have to be a Salesforce Sales Cloud customer to use the services quote, right? You, if we actually offer our I S V licenses as well as the O e M licenses, o e M licenses are for the customers who might be using other types of CRMs or other systems, but they do want, they do want to use the services quoting tool you know, of quotes, right? And, because we are built on force.com and that ecosystem is, is predominantly, you know, driven by Salesforce we are fully integrated, with opportunity management, for example. More often than not, the entire process starts with an opportunity where, you know, the sales team adds a whole bunch of line items like, what do I want to sell? But then they have to transition into all of, the details in terms of how am I going to do scoping you know what are the questions I want to ask? How do I get to the estimate and quote and scenario modeling and all that kind of stuff, right? So that's where the full seamless integration you know, kind of comes in. And then, as you go through the negotiation and, and through the automation process, we automate with all kinds of backend systems, including the PSSAs, right? The professional services automation tool. So, 95% of the time we end up integrating with the a of whatever customer has. It, it could be, you know, Kimball, it could be NetSuite. So, NetSuite is our official partner as well. And so, if someone has an open-air, it automatically, everything ends up in, in the open air and so on, so forth, right? So, the beautiful thing whereabout this is, you know, not only we are integrated on upward, like integration or, or the opportunity management, but downstream we are fully, seamlessly integrated with how you are going to start tracking your projects, how you're going to do invoice and billing. And now we bring that data back, and that's where our AI engine kind of works on top of that to provide you with a meaningful recommendation. So, we are uniquely positioned that way. You know, we are purpose-built for services quoting, which gives us a tremendous advantage in terms of you know, why we are probably the only company in services quoting, which is able to really solve this complex business problem and give predictions using the AI engines.

Wade Erickson (20:42):

Great. And the name, where did you come up with the name?

Mahesh Baxi (20:47):

Provus. That's, that's a good question. So Provus is made up of two Latin words Proventus and Opus. So, it's a combination of Proventus and Opus and what Proventus, and Opus Means is a successful business, right? And so, like I said, we at pros are super passionate about solving complex business problems for our customers. That's one of the values that you will see on our website as well. But when we say successful business, it's not about our successful business. What we are passionate about is to use our innovative technology and our product to solve that complex business problem for our customers so that they can be, you know, widely successful. That's really what we take pride in.

Wade Erickson (21:34):

Excellent. I love that when people use Latin. Because I've had some businesses and it's fun playing with Latin words to, to form these unique company names. So, thanks for that. Would like to pivot a little bit, you're a serial entrepreneur living in San Jose, most of your professional career. Can you talk a little bit about what drives you to start businesses and maybe a little bit of that history prior to pro and then you know, how has San Jose influenced your entrepreneurial spirit and do you see that still, obviously, you know, decades ago that was kind of crucial for our software industry to kind of be in Silicon Valley, but how, how maybe the landscape has changed a little bit?

Mahesh Baxi (22:21):

Yeah. that's lots of, lots of loaded questions in there, so I'll try to be as precise as I can be. Let's talk about, you know, what drives me to, you know, the entrepreneurial journey, right? I think and it's different for different people. I think what's, what's important from my perspective is, is really you, the domain knowledge, right? You ought to be passionate about the domain that you are going to solve the problems for. Obviously every company is solving one problem or the other based on you, you know, based on what the product you are, you are going to create can do for your customers. But I think, you know, when I talked about the provost, which is enabling the core to cash for services, like I said, I've spent 20 plus years in this domain and super passionate, super deep into, you know, when it comes to the, the code to cash domain, right? And then the second one I talked about was the HR tech. And I've been very, very closely working in the HR tech domain for, for most of my life. And, you know, again the, the domain knowledge in terms of what happens in that industry is, is really critical to be able to create the confidence with your customers and inject that confidence with your customers, right? So, if, if you are, if you're a entrepreneurial about to jump on an entrepreneurial journey, if you're thinking to start your company and I'm sure everyone has lots of ideas, I think my one recommendation would be to stay close to an idea, which is which can be backed up by your domain knowledge, whatever that domain might be, right? Because it, it brings a lot of credibility to your experience, to your product, to your customers, and all of that kind of stuff. So that's number one. Number two, I think, you know, I've been in Silicon Valley for close to 26 years now. I just landed here, it, it was coincidence maybe, and never left you know from, from Silicon Valley, but I think Silicon Valley is known to be really, you know kind of heaven for entrepreneurs, right? And, and it, there is a reason for it. I think one is really, you, you are surrounded by lot of entrepreneurs who are ready to help you, right? The, the entire ecosystem in terms of people who want to genuinely help is pretty large here. The failure is not considered as something that's taboo or, hey, you know, you should not talk about, talk about your failures and stuff like that. In fact, if you fail and if you're open to talk about it, I think there's a lot of learning that you can get from other entrepreneurs as well. And the third, which is absolutely critical in this journey is the entire VC network, right? I think the VCs, I mean, not to say that New York doesn't have VCs or Austin doesn't have VCs and all that stuff, the VCs are spread around, but the VCs here in Silicon Valley, in my experience, is really ready to take the risk with you. I mean, when you are talking about this kind of journeys, there are a lot of unknowns, there is a lot of stuff that, you know, you just can't plan for it. I mean, that you, you have to work hard towards the success, but doesn't mean that you know everything along the way and which is where you, you are surrounded by the VCs who are ready to take the risk with you, who are ready to pull you out of the weeds from a day-to-day stuff and say that, Hey, here is a larger picture. What you're doing is a real enterprise, you know, game, and you are solving a really complex enterprise problem. So, you know, it's okay, it'll take its own course, right? And those things are really important in this journey as you grow, you know, from startup to, to the next stage of the company. So that's why I love Silicon Valley, and, you know that's, that's really how I, I see it as different,

Wade Erickson (26:03):

The tribe lives there as, as they say, right?

Mahesh Baxi (26:06):

Exactly. Exactly

Carlos Ponce (26:07):

Mahesh, I have one more thing. I mean, we are approaching wrap up time and, and but I wouldn't want to end this conversation without asking you something specific to the entrepreneurial spirit. Let's, let's call it like that, right. Not necessarily about the topic, but more in a broader, broader sense. And I've seen, and through, through the course of the years, I've seen a lot of people starting businesses in the tech space, you know, and you have everything from those folks who think they all, they came up with the, with the next Uber, you know, for Uber for something, right? There's always Uber for something, right? And so, they have these great ideas, blah, blah, blah. And, but in this mindset of becoming an entrepreneur, thinking that you have the best idea or the next big thing in mind what would you tell these entrepreneurs who, in to maximize the, the odds of success? You know in other words, more specifically, how does innovation, what in role innovation plays in becoming successful amongst entrepreneurs?

Mahesh Baxi (27:25):

Yeah, that's, that's a great question. Carlos, you know, more often than not, the entrepreneurs stay focused on innovation, which is absolutely important and critical because, you know, you, you are innovating. You are basically, you know, creating a new product. Now, if you look at us, right? We are innovating through technology, but we are solving a age-old you know, problem, right? We, we have not created a new problem, or we are not solving a new age problem. The services quoting problem on Excel spreadsheet has been there for like 30 years now, right? And, and so you don't always have to like to find a very new edge problem, but what you solve and how you solve is important for the audience that you are going to look for. But my advice to really entrepreneurs is while you are focused on innovation and technology, there, there are really two key things that most entrepreneurs miss out. One is a, a customer validation early on, right? You, you have to make sure that what you are thinking is a great solution and a problem is actually a problem for the customers. And the number two that most people don't ask is this, which is, will you pay for this solution? Right? You know, if you provide something for free, everyone will consume it and you know, you will have more success, but that's not why you are establishing the business in the first place. But if you don't ask that question, like, will you pay for this? And how much will you pay for this? I think, you know, you probably might be fooling yourself and starting a business only to realize a few months or few years into it to say that, hey, you know, that the total addressable market wasn't as big as I thought it was.

Carlos Ponce (28:58):

Great. Awesome. That's a great answer. Thank you, Mahesh. I appreciate it and I'm sure that viewers will as well. Okay, well, we're up on time right now, but I have an announcement to make. Please stay with us as we go off the really quick. So, I just want to announce that tomorrow about the same time 9:30 PM am Pacific. We are going to be speaking with Srini Siddireddy, I hope I pronounce it correctly. And he's the CEO and founder of SportsPlus, the topic is going to be emerging demand for specialized digital ecosystems. So that's what we have another interesting conversation right here on Tech Leaders Unplugged. I look forward to this one. And with that being said, the only thing left for me to say, Mahesh and Wade, thank you for having been with us on the show. And folks, see you next time right here on Tech Leaders Unplugged.

Mahesh Baxi (29:56):

Thank you so much.

Wade Erickson (29:58):

Nice meeting you.