How Railsware CEO Yaroslav Lazor grew to $17M revenue with a 201 person team in 2024.

quick context this was recorded March 28th and 29th so a couple weeks ago at my live event SAS open.com we had a thousand software CEOs there if you missed it we hope to see at the next one September 5th and 6th in New York City SAS open.com but for now let's jump into the recording so my name is Yo I run company called reals where um we're we're doing a lot of stuff with data and then I'll show you the subtle part of it so I've been 23 years in a prot te so basically working for uh technology companies and money first ver wrote my first code when I was 10 years old uh engineer by heart uh the they they make us uh drop some numbers in here so um uh the company is like evaluated with 100 plus million and it's 200 people uh Al together a bit more than 200 people um we we grew five times in the last 5 years years uh specifically because of the data um the relevant experience is we uh one of the products that we run as s product is called coupler it helps you move your data around and figure out your data uh so that's where basically the information about this presentation goes from um there's some consultancy that we're doing including data consultancy as as the guy said before like it's really great to um onboard people into this thing because when you see a blank sheet and you're like go go do your data is is actually pretty hard um um the there's a practical approach how to kind of make you see what is it that you're working with with uh and then I'm going to share it with you um and then take your ideas that you think are happening within your business in a lot of different areas and map them with the reality and actually look at them all the time data is not about looking at it one time data is about doing it all the time and uh um share the lessons that that we uh had across the time I'm trying to figure out who who I'm speaking with so who's who's doing analytics uh who's working with data kind of on a daily basis can you raise your hand okay and then who who are the CFOs in here maybe or CEOs and Founders who's everyone else is it C cros okay good um okay so this is the team growth uh specifically when we were starting to tap into Data and uh pushing the gas uh in the last few years and this is the evaluation growth and I'll take it to my first part so my my data path I'm an engineer I was writing software I was super happy um until the time when uh it was the time to to raise people's salaries and I needed to know our revenue for sure at that time we were a consultancy company so our Revenue were supposed to be time multiplied by rate equals revenue and what happened is that I multiplied Time by rate it didn't equal Revenue we were like $120,000 short and uh um there was there was a lot bigan in the in the time when when we started we we were a much smaller company so I looked into the numbers and I was trying to figure out what happened and uh our um the finance accounting lady um did a sum of B2 to B4 rather than B2 to B5 so she skipped in one line and overall across all the invoices we we lost $120,000 at that day I I lost trust in humanity specifically in accounting people and finance people and people that do sums in excels like this is definitely not the way the software is being built and having it done in finances one of the most important functions that everyone is trying to stash away uh it's it's a really bad idea right and then at that day uh an analyst was born within me I was reborn and um uh we became a data company and uh probably a bit overly data company because now we have about 600 dashboards that we look into um then the the second thing was when our CFO was uh paying so we we remote company and we have people in 26 countries right now back then it was 20 countries it was super hard to pay the payr payroll to everyone and um she was paying it basically for 10 to 15 days every month and then she was getting sick because it was so frustrating and stressing so we we turned it into a data process we build up the data uh um data flows around it a dashboards something I'll tell you a bit more about and then and now we're doing it in 4 hours instead of 15 days um that was kind of a second big thing that pushed us into data and the third one was um it was very hard to figure out exactly where we stand when when you have a generic p&l where does every product stand how much profit does it have there's shared services that you have to split with processes it was it was really hard to figure that out and then we built a a hyper detailed pnl that actually showed all of that and uh I did it uh myself at at the time using uh kind of our product and some other products and that helped to uh to understand that you really need to understand your data if you are growing uh um a lot so that you can push the gas into the pedal you need to know where the uh you need to know where the floor is so we can floor it rather than underdo it or overdo it and kill your company right um and so those three things kind of pushed me into direction that you need to become a spider of your of of what is it that you're doing and and you need to uh understand um uh how your data work works like and we'll go into it in a sec and then the art of how to manage the data because it's it's great when you see all those dashboards but where do they come from how do you build them right and and we we're going to go into it so this is the payroll nightmare that happened it's she was spending like 12 hours per person and then after the automation it dropped into like five and three hours per person now we're a much bigger company we're just leveraging our automation much better um so basically I I did tell you about the 12K deal that that pushed into Data so everyone has those horror cases where you actually understand that you're going into a very different direction that that you were supposed to be going um and then basically you need to you need to from from that moment on uh it's better to create your own data we'll jump into that uh so we went through the the the the so basically pnl is a very interesting case so we had our PN was spread between uh the the payroll multiple we had multiple entities in multiple countries um multiple accounting software uh we were transitioning from one software to the other and it pays off to combine all of it together unify it and to create yourself a data that you can that you can trust uh in most of that is being done with the uh data analyst of course um and uh build a foundation model with which you can reflect of what's Happening uh like within your uh within your organization um uh and and have an ability to drill down and actually see uh kind of the insights of of of where you're at so this is um this is something I looked at every day this dashboard is basically uh it contains everything that I as a CEO look at uh and this is the dashboard that I built for myself this is my spider web uh that I kind of gain control through um it's a it's a spreadsheet uh and uh it gives you flexibility to you understand your own data everyone can do spreadsheets on some level and you can basically create a base model for what can be useful for you instead of um just working with analyst and we'll go into that in a sec um this is like a typical uh setup that I have uh where there's a lot of monitors you can step back you can and then you can see the correlations of what's happening within your business um uh round multiple uh uh dashboards of them but the main one uh you should have your main one that you refresh every day and then you'll get a sense of it um and and there's some more uh stuff as I said we have 600 dashboards I don't have 600 slides but um uh one of them is the employee employees satisfaction and the other one is uh time tracking and basically where do people what what is the quality of time tracking uh in the company um so how to become a spider of your own uh data so whatever you think is important to you you can you can break it down in using um uh uh extraction tools and and you have to place it in front of you you you need uh you need a place where your reality the the reality of your world is going to reflect uh it using some hopefully colorcoded uh data and it's actually very easy to start it's much easier to start than than everyone realizes and you should always redesign your data for your visibility if you're going to use uh data tools that you need to filter in order to answer some of your questions that you have you're going to lose yourself uh you will basically um uh go what your intuition tells you rather than follow the um uh the answers that that you might have if if you pack your data correctly um and all of your Executives need their own data so if someone if you have hat of product he needs to look at the product data he needs to look at aurn data activation data um uh everything important for the product if you have theyr people they need to look at how their funnel goes through and um uh what is happening within the funnel if they look at it every day they will get an intuitive sense of what's happening within under their part of the business um and uh basically then you can take the data from your exacts uh and combine it into to uh something that you look at every day and it'll it'll it'll create an intuitive sense for you on how how to run the business um it is actually easy to start everyone knows Excel and and spreadsheet as I said it's easy to start you just uh use data extraction tools like one of them is our product coupler uh there's a lot of them in the market uh depending on what you need uh and you're pulling somewhat um uh aggregated data into to your spreadsheet and then you just combine it in in in a way you want to see it and you place it spreadsheet is a great canvas it's like a drawing a picture so basically you take the data and you place it into a proper part of where is it that you want to see it and then you you add up to it and create a base model of what is it that you would like to see the next step is working with a data analyst so uh the very often what we see and mistake is that people start working with data analyst and none of them know what needs to be done um the data analyst doesn't understand fully you don't understand fully uh what you want and then but then you know and this combination of a pair is is somehow um explosive so um you're you're getting frustrated because you don't see what you want but um that's because you yourself don't know what is it that you're trying to extract yourself okay so and then the first it's better to go back to the first step and try to extract some of the data even dummy data and then drop it onto a um uh spreadsheet for yourself to look into it and to actually understand um uh the model that you would like to look at and then you can proceed with the analyst and uh basically work with him uh uh to do a long-term kind of stable uh Foundation that is built on something that you you wanted to build from okay and then um and then there's a trick uh that helped us a lot uh specifically in the spreadsheet it's called the 3D data it's when you you you have your numbers uh you don't you might not fully know where they come from but then you combine them into this kind of a exp uh just text within the spreadsheet and and we have a blog post about it how to do it this saved us a lot because when you combine your own data uh and then you show it uh you're able to um see the underlying uh information that came from this and you are able to parse it with your eyes quickly and again build the intuitive uh understanding of uh where where does it come from and what does it mean um and basically that's it uh so I'm seducing everyone not to I'm seducing everyone to go into building your own spider we uh into uh creating a a visibility for yourself of what is it that you need it'll take time you'll build it over time but um it it will become um something that basically you want to check uh either multiple times a day or just every day um uh the uh then always redesign your data for visibility so if the business changes your reality changes and then your priorities and interest uh also changes so um don't be lazy and kind of redo it in a way that you want that you get exactly what you want to see um and then um make your exacts do the same thing and and you know then all the every time you synchronize about something with an exact you're actually looking at reality and you don't spend time of going over um uh like slide decks presentations or or just agenda items that are that are not that important you look at the reality of your business that is being refreshed all the time um and then start with a spreadsheet and data extraction tools extract it and and play with it until you create a a basic model and then this basic model can then be extended with data analysts or if you don't have them in the company just some Freelancers um and use the the 3D uh data shape uh it's a bit tricky uh but if you scan the QR code uh and and send me a note if you're interested uh we're going to send you the blog post when it's out just just so that those spreadsheets are just easier to to start with um and that's it hey folks if we haven't met yet my name is Nathan ladka I launched and sold my first software company back in 2015 and went on to write a book about it which you guys made a Wall Street Journal bestseller purchasing over 30,000 copies thank you so much for that after the book I launched this show and went went on to create founder path.com I raised a large fund to do non-dilutive deals with B2B software Founders so far we've invested in over 400 software Founders totaling $150 million here in 2024 we're doing three to four New Deals per week so if you're looking for Capital and don't want to give up Equity go sign up at founder path.com for free to get your offer