Adam: Hello and welcome to Tech for Finance, where we help finance professionals leverage technology to support their ambitions as businesses and as individuals. I'm your host, Adam Shilton. And in this episode, we're going to be chatting with Jon Cowley, who is head of Studio and the senior visual effects supervisor for Fuse and the founder of What If I? Web. Jon started his career in visual effects before forming What If I, an intelligent forecasting tool that helps business leaders model and present strategic scenarios in a low code, easy to use environment? So thanks for joining me today, Jon.

Jon: Happy to be here.

Adam: Excellent stuff. So so we'll get into it. I'm going to ask the obvious question, which is how you got into modeling software with with maybe a bit of a finance focus after you've you spent your entire career in visual effects.

Jon: Short question, long answer. So here we go. I have twin boys that are eight. So when they were born, my wife and I started asking a bunch of advice so you can appreciate us. What if my wife goes back to work? She doesn't wait a year or two or three, but the kids in day care, nanny, all of that sort of stuff there. And thankfully, even though I'm in the visual effects and film industry, it is still a business. So I am, while I'm not a 11 level 11 Excel guru, I'm like a seven or eight in there. And what I'm capable of doing based on the complexity of what we're doing in the film industry. So I built the model. I think I ran into all sorts of challenges because I had so many different variables to run into, including what I thought was the biggest variable there, which was time being able to figure out the timing of these events. So I built the monster, monster, Monster monster spreadsheet. I wasn't sure it was correct because there were so many variables. And then I put it in front of my wife and there was just that blank stare of nothingness, because that just wasn't the way that she thinks or visualizes things. So I was kind of at that inflection point where it's like, Well, this isn't working for me. So the personal finance solution and then my aha moment was kind of going back to the way that we work in the movie industry, right? So the movie industry, whether we're talking about editing, right? So anyone who's edited the video, including yourself, putting these videos together, you know that time is that underlying factor. Time comes first. Whereas the challenge I ran into with Excel is the calculation came first and then I was trying to figure out how to apply that to time. Right? The second aha moment was some of the software we use in visual effects, and I probably do a bit of a screenshot track, something down for that for you there. It's this very sort of node based kind of software. Think of like a decision tree where you tether together and connect these pixel calculation events to create the images that you see in a movie.

Jon: Right? And my aha moment was, well, why can't I build my financial model that way? Why can't I build it visually with a house event and a mortgage event and a job event and these sort of things that are to why can't I put this in front of my wife? Why can't it actually calculate? So not just a visualization, but actually run calculations through those series of events? And then the joy to what we do in the film industry is we expect change. All right. So while most folks, when they're trying to build a model and I'm going to say this from the from the position that I'm not an FPA expert. So when I say most folks, people can disagree and maybe put in your comments down below, whatever it is, but most people start bottoms up where you're trying to get all these assumptions that are together. They're the joy of the way that we work in entertainment. There is we expect change. So the workflows are designed knowing that this is going to change and this is going to change and this is going to change there. So it's very robust and adaptable as opposed to the hard core model that someone has built over weeks and weeks and weeks. And then if someone decides to make some [00:05:00] unexpected sort of change is a bit of a house of cards that's in there. So that again, long answer, I promise you on that one long answer is the family issue. Trying to figure out our path inspired a ha moment where why don't I bring that technology in? We started personal finance, but a couple of years ago we sort of shifted more over to business where things seemed more opportunity for success. And a better return on our investment.

Adam: But thanks for that. And it's fascinating. And I love that you've used your your wife as a sounding board. Yeah. And I think my wife would be the same if I put something in front of her. No, don't understand. Start again. Again. You probably went through quite a lot of iterations, right?

Jon: Exactly. Exactly. And so the typical and I know for your group, I'm not sure whether they're finance first and tech second or a combination, too, but we followed a lot of the traditional tech startup sort of things. We built mockups, we built MVP's, if things minimal about products, did a lot of sort of design work there to try and figure out what this looks like, the user experience. And we still have work to do, but the user experience is just as important, if not more important, than making sure that one plus one equals two.

Adam: And that going back to that time element, there is a it is I wouldn't say a completely fresh way of looking at things, but it is definitely. Innovative, shall we say. And I totally understand because my probably seen the background with the guitars and the drums. My background is in music production and sound recording, and it's the same when you're mixing a music track, You know, the sound comes first, tied together, you know. So. So it was always in flux until the end of the track. But when you look at, I suppose. More traditional, I say traditional because financial modelling and that that predictive side of things is kind of more modern than what you do in a spreadsheet, right? When you look at some of these more basic modeling tools, you can do scenario planning, but it's quite static. So So you can you can set up a scenario to say, Look, here are my figures and then what's the event? So how does this scenario change if this metric went up a percentage? But what you are losing there is you're losing that concept of time because it will then apply that this is the percentage uplift according to an entire time frame over a year or two or whatever. And again, you know, more more than me on that. But that's where I see a bit of a differentiator between what I class as more of a standard modeling tool that plugs into Excel, for example, and something that, as you say, you can chunk it up and say, you know, we're predicting this amount of growth based on this year. But then I think I saw some screenshots on the site you had. This is when we plan to employ more people, you know, and that's a variable that we need to add in at this stage. So making that as easy as possible to sound really advantageous, I guess so. So thanks to that.

Jon: And then the other kind of component to that one as well. And so the the parent company is called what web, the software itself is called, if and that's very much about that. What if. Right. And the reality is, again, can you do some of these things in Excel? Absolutely. Are they easy to do as a matter of opinion? But what about the end customer? Right. The person that's at the end of the stack. And I think what happens in some of this right now is you have the uber professional domain knowledge that builds this. And then there's like the PowerPoint ish version of here's your option one option to option three. And for a lot of people and I get it, that's all they need. They just need to know what their three options are. But for a good chunk of people that are sitting at the end of that stack, whether it's the CEO or the CEO or a founder or something like this, they need to understand the levers more and they need to be able to, on the fly, do a bunch of these sort of what if things and what if we raise money in January? What if we don't get that money until June? What if it's 500 K? What if it's 700 K So the ability to see all those and dynamically do that on the fly. One of the things I like to sort of value prop, the problem that I'm solving is not the ability for a finance person to do their job, although I think I can support that one. I'm trying to also solve the ability for them to put the results into a framework and tell a story that their end clients can solve. And as that end client, the CEO, is that client, a fractional CFO who's supporting other companies, is in an incubator and accelerator that has cohort companies. The answer is yes. So it's also thinking about that piece. And I think some of the understandably, some of the resistance that we're seeing to some of these newer tools and I'm running to those as well, is if you come through the stack of the finance person that's [00:10:00] been using these current tools for so long, sometimes the end user gets forgotten about in that exercise there. And that's kind of where I'm leaning into is that end and experience. You're in a board meeting and the CEO says, Well, what if we do this? And the standard answer currently is, that's a great question. Bill, let me get back to you. And I think that's where it's broken and I think that's where there's opportunity to refine.

Adam: You're bring people into the story. And this this is kind of a hot topic at the moment. And and I don't know whether you listened to my interview with with Christian Frantz Hansen. It's one of my side. I check it out because that might inform some of the way you think about the way that you build moving onward. So his company is the Business Partner Institute, and a lot of what they do is around finance, business, partnering and then creating impact, which often involves a lot of storytelling. And if you speak to Christian, what he'll say is he's an introvert by nature. Yeah, So it's quite happy to his desk, get up his code and do all of that sort of stuff. But there comes a time where you've got no option but to present your findings, as it were. And in a world where there's more and more automation, there's more bots, people need to be focusing on those skills to differentiate and tell those stories, to get buy in from the wider business as opposed to separating themselves. So so what you're saying there is, is bang on. Any tool that makes it easier to tell that story to non finance professionals is going to give you an advantage because presenting a spreadsheet with rows and columns with what a finance team that spends their life in spreadsheets is going to present, it's going to be drastically different to even somebody like me. I have understanding of finance, but I don't have an intricate knowledge of modelling and I don't have that experience. So if you were to present me with a spreadsheet with some scenarios on it, I'd probably come away. A bit more lost than when I started, Right. So to be able to come back and say, Right, well, actually, instead of let me go away and spend another couple of days building that scenario into this Excel model, it might not be an Excel model. It could be another, as I say, more traditional forecasting tool to be able to say, Right, well, let's let's get it up on screen now, you know, and we're then going past the level. So if we thought of it in terms of levels, you're most basic level would be presenting a spreadsheet, which doesn't tell much of a story.

Adam: The next level. Then when you do start getting into the business, partnering and the storytelling is right, well, how do we visualize that? So are we creating a pivot table or are we creating a PowerPoint presentation with more imagery to make it more easy to digest? But what you're suggesting there, and correct me if I'm wrong, is we're then going a step further. Than that. And saying this isn't a tool that we need to to hold hold on to in a team and nobody else ever see what we're doing. This is a tool where in real time we can build these scenarios and actually have people tweak it on the fly and come back to your point. It's a great tagline, isn't it? What if I why don't we try it? Why don't we do it now?

Jon: Exactly. Exactly. Yeah, exactly. I think that's in my customer discovery. What's interesting and I know one of the questions you had in your sort of leading questions there for me is how I learned, How have I talked to what I did? More so is I started from the end customer end user experience more. I'm a start up myself running my own numbers, talking to other sort of companies. I've worked my way back up into sort of the fractional CFOs and consultants there, and then I worked my way up the stack now into talking to more to traditional professionals on that one. So coming at it from the end experience as opposed to from the blank Excel spreadsheet thing has given me a very different insight, I think, into how to do some of that. It's also one of my challenges because I'm talking in a language that this group doesn't see, because I think this group doesn't necessarily see the problem because they're not the end receiver. And I'm talking in absolutes here, and I know that's dangerous, but I think that's one of the challenges that's there. I've also talked to folks that are in a consultancy sort of space where they've spent the time building the model. They put it in front of their clients and the clients still don't do what they know they should be doing. What what the professional knows that the client should be doing there. They're not acting upon it. They're not doing it. And one of my thesis is there is that it's not a fault in the model, it's a fault in the storytelling and the almost like the evidence based version of that one. When you're asking someone to believe a sell and everyone wants to hear what they want to hear, they want [00:15:00] they want validation that their big grand ego driven business that they're building, that they're perfect. Someone comes along and puts a bunch of holes in it, puts it in front of them. I think the buy in piece, getting that in consumer to buy into the plan is a big, big part of that one. And if you can put this into a visual format and again, I would argue that 80% of the population is visual first and zeros and ones and numbers second there.

Jon: It needs to be in a language that they can buy into, that they can follow the journey, they can follow the logic and mentally poke holes in it, and then also say, no, that checks out, that checks that checks out. And if you also give them a little bit of play so you make them feel like some of the decision making is their decision so they can go in and change your term churn from 10% to 11%, or they can go and say, no, I think my cost per click could be this or this. Let's give them that sort of functionality there. Or no, we can pull that Chinese initiative up by six months. We can do that. Oh, we can't. As opposed to waiting for to go back to the cycle. And I think the the cycle is also potentially one of the dangerous things in there. I have the benefit and again, I'm fantastic at it that easy questions and long answers. So here we go. I have the benefit in this model too, where the my visual effects background, it is a multinational private equity backed company. I've been in the board meeting, so I've also seen the exercise of what goes through when you're talking about millions and millions of dollars of revenue running through an organization with 4500 people. So I've got the startup lens, I've got the sitting in the board meetings and understanding how the private equity firm and the questions they're kind of asking. And I'm watching the weekly or monthly meetings where everyone's spending all their time trying to build the model to figure out what happens if something they should have done four months ago finally happens today. But of course, you're not going to get the results until the next quarter. And it's really trying to tighten that stack up. So, again, I'm getting a whole bunch of bullet. Points there, but just I think we are so used to a way of doing things. And I'm not saying it's wrong, but I think there's some blinders on that there could be other ways of doing it. Yeah.

Adam: And to come back to your point there about almost putting some of it. In. Your audiences hands. It reminds me of. You've seen the film Inception, right?

Jon: Yeah.

Adam: One of my favorite films. Of course.

Jon: Of course. I know people that worked on it. That's part of my background. So.

Adam: Yes, very good. It might be a separate conversation about that at some point. But obviously, the entire premise of that film is that they are they're planting the seed of an idea in somebody's head for somebody to come to the realization by themselves. So when we when we start talking about influence arguments. Sometimes hold more weight. If they come from the other side. Do you see what I mean? Because sometimes you spend forever and a day banging your head against a brick wall, trying to convince somebody that this is the right thing to do. Actually planting a seed and allowing them to come to their own conclusions is often a less painful way of doing them. Now there is a risk that you give people a bit of play in that they, in your mind, come to the wrong conclusions. That is the risk. But again, coming back to the business partnering piece. Anything that you can equip yourself with that helps support the outcomes that are best for the business is is something that you need to invest time in, right?

Jon: I can only kind of lean into sort of specifics. So I'm working with a health care startup here in Vancouver. The CEO is the numbers guy. The CEO is the emergency room doctor, the brilliant visionary who wants to build software for the emergency room experience there based on all of his stuff. And the CEO is banging his head against the wall, trying to get the CEO to look at the numbers and understand the business model. He shared his spreadsheet with me, and it's this beautiful, monstrous sort of thing with everything in there. And I can fully appreciate while the why the creative, brilliant visionary isn't looking at the numbers because of the language with which the story is being told right there. So I'm working with him to try and put all this into a visual flow instead, with the hopes that that that collaboration is happening there and people are not talking in language that everyone can get.

Adam: That makes total sense. Makes total sense. So so coming on to use cases then. It'd be good to understand. So when we look at the makeup of a of a finance team, right. And it's always changing. It's a big thing at [00:20:00] the moment, right? How do we move from operational finance into and into strategic leadership? So I know you mentioned fractional CFOs. There's a lot of talk about CFOs in general, but actually a lot of the power now is and I'm reluctant to say junior, but in in the team that form the background analysis, right? So so you could have an analyst or you could have a financial controller or you can have, you know, fill in the gap. So what are you seeing? Are you seeing a lot of sort of the back office team that aren't the CFO is using these tools to build, or are you finding that it's equally people that are starting selling, that's telling the stories that are sort of more senior and in those CFO positions that are getting more value from from this?

Jon: I've had my success to date more from maybe there's another way of looking at it. I can answer your question with another longer answer. In software, there's a concept called category creation. Right. And a lot of software that is being generated, people can very easily say, I'm doing a here's this thing that allows me to do a differently, better ten x, 15, X, whatever it is on that one. And that is a very handy and easy business sort of strategy. Someone immediately sees the value. We're not asking them to learn something entirely different and they're just going to add this part onto their car and their car is going to go faster and use less gas. Wicked, right? But when we instead we say, Hey, we want to take away your car. Here's a boat. Good luck getting into Costco. Right. Like you're asking somebody to fundamentally change the way they work there. So that category creation, when you're doing something so different and I think that I'm in that space where my approach is very, very different, there's going to be a very natural and understandable barrier to entry for people that are seasoned with their particular way of working for years and years and years. So again, that's a long winded way of saying the CFOs, I think like, Well, I can do this, you know what I mean? It's working. They don't necessarily see that piece, and that's okay. It's part of my journey, working my way up the stack. What I'm finding is I'm having my success right now with folks there that have some knowledge, but they're not the guru. I'm not asking them to cut off the right hand and attach this new thing to it. It's like, no, you people that are in the bottoms up piece there, whether it is the CEO, I keep kind of going back to startups because that's sort of my go to market. But a CEO there who's trying to run their own books and trying to run some of their own numbers and figuring out some of their scenarios there. I've even got I have a gaming company here that I'm supporting. They've raised $7 million. They're building video games and they're trying to figure out their staffing models and all of this.

Jon: I'm having some success when it's kind of coming from. They're expecting someone to come in to a large organization and immediately switch to my tool to replace their current tools. Not a chance, right, to complement their tools. That's what we're building for. So we are building Excel integrations, we're building other sort of things so people can still keep their current toolkit and add some stuff on. So maybe it goes back to the, I can't remember what the quote is, But no one ever got fired for buying IBM, right? It's there's that sort of piece that's safe there. I'm not sure I answer your question there, Adam, or not, but it is I'm finding it's more people under the scenes there, people that are finding ways in startup tech, business, tech in general. You need to find your early adopters. And quite often that could be someone who's trying to work their way up the stack. So imagine someone who's maybe a junior analyst, maybe using the tool on the side there, someone asks a question and instead of that two day turnaround, it's like 30 seconds later, it's like, Here, what about this? Like, oh, and they can kind of almost use it as a way of working their way up. I think that's where we're going to have success working with people that aren't fully. Integrity is the right word here, but let's just say engage to say it is fully engaged in the current methodologies and are willing to try something new.

Adam: And we're finding as well and spoke about it briefly with with Paul on the last point podcast is this concept of Centers of excellence versus hybrid roles. And I think you touched on it there with your start ups being a good use case for the solution. In a startup, you've not got a ton of staff, you know, so people wear more than one hat, so it's going to be really useful for them if they've got a quick and easy tool to do that scenario planning without having to having yet having had years and years of financial expertise. Yeah, but likewise the Center of Excellence approach where you've got a business unit devoted to that, there's no reason to say that these tools won't be equally as useful right now. I think what you're saying there is that it's just a little bit more difficult for organizations that are a bit more embedded with the way that they've always done things which, which which I totally understand.

Jon: Yeah. Another buzz term I always talk about is go to market strategy, right? And if you try to boil the ocean with your business [00:25:00] sort of strategy, that's a pretty big ask. So you have to figure out where your biggest chances of success are and then expand your verticals out. So to your to your point, they're finding people that need the solution. So it's not just a nice to have where they truly have a problem to solve there. And then you expand your offerings as you develop your software. So in my dream version, yes, someone is sitting there at Amazon with Jeff Bezos and he's not there anymore. But Jeff Bezos says, Well, what if we do this right? And the answer is getting I know that probably scares the crap out of some folks, but the idea of actually scenario modeling that on the fly in the room there, that's my dream moment where you're in a Fortune 500 company and someone is indeed tweaking things and playing things on the fly. So.

Adam: To come back to your your work with startups then. So startups obviously work at an incredibly fast pace compared to well, there are some larger organizations that are still growing quickly, right. But there's a lot more quick decisions that need to be made in a startup compared to a larger organization. So based on your work. How. And you might not be able to answer this. It's fine. I appreciate this wasn't in my set of. Questions, but. How would a start up business? Use a planning tool differently to a more embedded businesses. Are you finding that the triggers are slightly different? You're finding that it's similar just on a different scale. Can you talk a bit more about that?

Jon: If I'm understanding the question how they're using it right now. So this kind of gets back into my thesis on how models should be could be built. Be careful about that one, how models could be built. And my thesis right now is that most models, especially when you get into the into larger organizations, it's very much a bottoms up approach where you're trying to think of all the levers, all the pieces, all the stuff in your aggregate aggregate aggregate and your work your way up to this, to this, the final Valhalla golden model there. And let's take a look at this thing there. And if depending on how well the model has been built, someone comes in with a what if or a question or something there. A It trickles beautifully through that. Or B, it's a bit of a house of cards and you've got to go and rebuild a whole piece. Case in point, one of my neighbors works for a fuel hydrogen fuel cell company here. They've got millions of dollars in revenue. This is this is this is a large company. This is not a startup. But in that model there, I use the analogy of a Chinese initiative. They were looking at opening up some operations in China and the CEO came in and said, what if we push this up by six months? And they tried to update the model on the fly there? And then the analysts spent all weekend rebuilding the model because that was a piece we hadn't thought of because of that sort of bottoms up approach there in that time kind of component. So coming back to your question and the answer here, I think there's a world where you can start top down. You can start with very basic assumptions there. Remember my my analogy about how software is designed for change in the visual effects industry. So build a very basic model there and then you can drill down and add flavor and color to some of these things as you need to. Right. So what's our revenue going to be? It's going to be 5000 bucks a month. How did you get that? I just made it up.

Jon: That's okay. For a startup or a company in that very first pass there. But that's probably like sacrilegious to anyone who's actually trying to funnel a large organization through that bottoms up approach. But my thesis is you can put these placeholders in, but then you can refine and you can build it up so you can replace that part of the model on the fly very, very easily with some of those assumptions on round two or round three or even do that dynamically on the fly. So what we're finding is the intimidation of the big model for companies that don't have a lot of domain expertise. This is a very scary thing. If you can give them something perceptually simpler to start with there and then add in complexity as you go and very quickly a complexity as you go. You can round up the model and you can also make them part of that journey as well, like they're understanding the levers, right? So when they have that 5000, but then they break it into a website, visitors to trial to pay to pro and different conversion rates and all this. They can see how that 5000 is made. Right. And what actually has that. And they realize that it's actually going to be 500 bucks and eventually get to 5000. But the curves. So I'm not trying to answer your question there or not, but that's kind of the idea. Right.

Adam: Absolutely. And again, I'm paraphrasing here, but what we're saying is obviously an established organization is likely to [00:30:00] have more complexity. And with a traditional approach, it's likely to take longer to build models because there's more variables. If you're starting at the bottom and trying to work up to an end result. Whereas in startup territory, there's potentially less variables that just happens faster. So it's easier to start at the top and say this is the end goal. You know, how do we work back? What what, what are the scenarios that will enable us to to achieve that essentially?

Jon: But I'd also argue you need to think of like a decision tree to write in a traditional larger organization. There's a lot of feeder information that works its way up and up and up and up to get there. So I talk about a bottoms up sort of model. You also have the marketing department putting their panel together and you've got the IT department putting their piece together, and all of these things are taking their weeks and weeks to kind of come together as well. I think that can also be built more. Morally and more quickly with the same sort of thought process that information funnels in and then calculations sort of funnel out. And if you can automate that flow, if you can remove the barriers and I think if you can remove the need for absolutes in a model and instead support the ability for the marketing department to have six or seven variables in their assumptions there. So instead of the marketing department giving you one singular budget and I know this sounds crazy, but they're giving you six, right? And all six are coming along because they're having a few different assumptions in there. There's two assumptions here and three assumptions there. There's your six there. Our technology supports multiple, multiple, multiple, what ifs running there. So those can all come through. And then in your your big meeting there in the boardroom, you're looking at 82 different potential outcomes for the company. And again, I know this seems like, whoa, that's too much. But now you can kind of go in and say, all right, from the marketing stuff, thanks for our best case, worst case here. We're going to lock in this particular piece here. What does that mean? So if we lock in this decision or option here, that trickles through in those 82 scenarios now become 41 and you start to decision and work your way down the stack to some of your answers. Again, very different way of thinking. But does that make sense?

Adam: I love it. I love it. And to anybody who's used to more traditional forms of budgeting, they they start panicking. Sometimes when we have conversations like this because budgets are so painful. So in a lot of instances, to get to one budget can take. Months and. You might still be working on the budget well into the start of your next financial year. And again touched on this was Paul in the previous podcast with his interviews. There has been discussions around the concept of how do we move beyond budgeting, which is kind of similar, similar to what you're saying there. Obviously you're mentioning multiple budgets according to whatever scenario you find yourself in. But it's not too much of a stretch to say, right. Well, if we can build this information quickly, why can't we quickly move to this scenario? Once, once we're there, we've already planned for it. It just more closely aligns to this budget with these expectations than this budget and these expectations. So it's a refreshing way to look at things. But again, coming back to a time there. An organization has got to be prepared to move at that speed. Do you see what I mean? So again, coming back to startup territory, it might be a bit easier if you were a leaner team, right? But but larger organizations might be a bit.

Jon: Of a I would it's going to require a certain level of visionary and I'm going to have to be able to prove a certain level of use cases there. But then I go back again to my experience in the film industry. So the company that I'm working for doing visual effects, we are the largest provider of visual effects in North America for television, episodic, working and all this sort of piece. They're massive company, 14 different offices. And at any kind of given moment, we may have 40 different projects all running through this infrastructure. And if you are only doing your audits, for lack of a better term, every month or every quarter, I consider those to be a post-mortem. You mean you're looking at did you survive or not? And what did you do right and what did you do wrong? But given the sheer volume of stuff that's kind of going through an organization like that, we have systems there that are by the day. We know how many people if a project awards tomorrow and they're going to give us footage on Tuesday, how many artists are we going to need to do the work? What's the time frame? All of this we built in real time flows there that give us sort of staffing and financial projections by the day. So I know it can [00:35:00] be done. It's just a way of sort of thinking about it and organizing the stuff that you're getting real time analytics into it. So again, spreadsheets, I know there's some work being done on trying to get integrations into these and some of these other sort of tools, but you should be able to pull in real time data every single day and know every single day in this sort of simulation environment what's changed, Right? So if your biggest client has disappeared on you on a Tuesday, you need to know the ramification Tuesday night or Wednesday morning. You actually need a notification that pops up in your CFO or CEO's inbox that says, hey, you know, we now are falling below this particular threshold. Now this particular KPI, because this piece has gone away based on this piece of information that needs to be real time. It's not a monthly report kind of thing.

Jon: I think the challenge is the complexity of these systems there and the need to hone in on these very specific numbers begets a long cycle, and it's in the long cycle that I think companies get themselves in trouble. If I known then what I knew now, I would have done something different. Let's make that answer now. Give you the information to make that better answer now. A bit of a rant there, but I know this is the benefit of of of not being a domain expert here in FPA, but seeing other models and then questioning that founders. There's a beautiful book. I'm trying to find the name of it here for everyone's interested. It's called Super Founders What Data Reveals about billion Dollar Startups. And the author is Ali Tam, and he's gone through and looked at all of these successful companies there and really analyze the properties of their founders that are there. And there's a lot of narrative out there about what a successful founder is, and we all think it is this domain domain expert who's had 25 years experience in a given sort of vertical there. They're this, this and this. And the reality is a good chunk, if not 50%, are successful. When someone with an entirely different line of thinking gets involved in another sort of space and starts asking some of those questions there, and why is this and why is this? And I'm not saying I'm going to be 100% right, but I'm asking the questions. Yeah.

Adam: Absolutely. And it reminds me of it. And it's and it's a bit of a tangent, but I've worked in a fair amount of different industries, but tech's always been at my. Core. And this particular industry was in commercial livestock. Yeah. So mass production of chickens, pigs, all that. Sort of stuff. And it focused specifically on welfare. And in a traditional setup you've got a farm manager. You checks the temperatures, right. You know, they check that the the animals are happy. But when you apply tech to that and start putting sensing equipment in and you start looking at the analytics, that's when the domain expertise from another industry has a tangible benefit on. And I know it was a totally random example, right? But it's a really good example of where that cross crosses over. And again, it's another hat tip to you, bringing a fresh perspective with you with your visual effect background. Right. So another question I've got for you, that's and it wasn't in the set of questions.

Jon: I'll take it.

Adam: But but because I've been I've been having a bit of a nosey because I've been nerding out a little bit with with this. So some of the examples and if you go to the website, what if I do, I know you'll see this straightaway, but of course you've got these visual workflow flows and you've got some milestones on your timeline that says what happens if there's a price increase here? What happens to Product A and B, if we were to do this, how does it affect our target margin and so on and so forth. Some of the other visuals you've got, you know what, if we add a new member of staff here and that sort of thing. What are some of the lesser. Known. Triggers? And again, there might not be any it might all just be standard stuff. But, you know, new staff members, new product launches, entering new territories, that's pretty standard stuff, right? But from your work, are there any more sort of neat? I'm just interested to hear, are there any sort of more niche trigger points that people might think about building into that scenario that might not be instantly old price increase or price decrease?

Jon: Yeah, the one we're getting into a lot more is capacity. Right. So it's it's one thing to say, great, we're going to make $1,000,000. But the question is how? Right. So one of the examples that we're building for right now is a use example, like a candle making company, right? So they have their seasonality and their seasonal demand. And again, can you do this in Excel? Of course you can. But is it kind of tied in with everything else there? And part of the flow, it's not normally. So you've got this this candle making company, we've got the seasonality and we know that Christmas is going to roll around [00:40:00] and the holidays and there's going to be a big run on candles. So when does that whole phase kind of go? But then also understanding the person that you have packing the boxes, how many boxes can they pack per day there? And are you going to have a bottleneck in your flow at a particular stage because you haven't got enough people there hired? And when you need to hire those people to monitor that piece? And maybe the the secret here is even though I have a visual effects background, a little bit of a spoiler alert, I also have an engineering background. So I did industrial engineering, which is really about systems and capacity and where do you put the slag heap and how many trips does the dump truck make? I mean, and how do you minimize these 1%, 2% costs there for operational efficiency? So some of this kind of falls into this kind of critical path piece there, but how do you model that out? So imagine if you can have a model that has not only who do you need to hire and have you have enough sort of staff there, but it's tied into all those other assumptions that you're doing there as well. And what if we launch a new product? Or what if we open up the office at a time, these sort of things? So capacity and the timing of these things, Right. Does that answer your question, Adam, or did I miss it?

Adam: Yeah, no, absolutely. And the reason I ask the question is. There are some systems and sometimes we have to bear in mind that not every business has got $1,000,000 to spend on software and that sort of stuff. Of course, we're getting to the point now with AI and emerging technologies and that sort of stuff that you can build in external events. So whether it be weather or something like that, that was the reason for the question is I'm always keen to understand are there things that we don't know about that we need to be bringing into our forecast? So capacity, Absolutely. That's one. It's the reason that I ask the question.

Jon: I have a vision and this one is a little or how things could kind of work on things there too. As I'm looking at some of my pricing models in the way that I'm bringing the software out. There's one version of this where the software is more or less free for a lot of companies to kind of use there. But the trade off in that piece is those companies are also offering up the anonymized data there to us. Right. So obviously there's lots of grey areas there about security and what's in there. So so imagine a system where your information feeds this larger piece of information there, too. So in a weird sort of way, I know every company just wants to protect their piece, but what if you could garner information from other similar types of cohorts of companies? So why right now does a company have to go out? Obviously, they have a track record, but maybe they're going in a new market and they're trying to figure out what the customer acquisition cost for X is currently, how to kind of go out and try and distill what that is. Why can't you have an artificial intelligence type of approach here where based on large cohorts of information, some of the blanks are getting filled out for you or they're kind of put in in some of these tolerances there as a result there so that you have access to that. Like we all go out to a website right now and you're trying to figure out what's the customer acquisition cost for health care, what's the customer acquisition cost for B to B? And there's all these websites that have this. But imagine that information was actually distilled in real time and available to you. So it's a it's a different way of thinking. It's an end game kind of concept there, but more of a. Cloud based collaborative system there where real time information funnels into these models as opposed to going out, researching something, clipping a number and placing in your model, let's funnel information into it. I've got a dream.

Adam: Absolutely. And it's the right dream because we are already seeing, not in your space, but different software vendors move into this territory. So. So SaaS is nothing new, right? Multi tenant infrastructure. Url login. You've got a piece of that that server where your software its, right. But now we're getting to the point with security and advancements in blockchain and all of those sorts of. Things. Whereby you can access data completely anonymized, but it could still be useful. And one of the terms that I've heard recently is the concept of an intelligent GL in inverted commas, so an account structure. So it's similar to what you're saying there. Can we jack into an environment where a lot of the information is already available based on data that already exists? In an intelligent GL, it is using AI and scraping data to present the best set up of, say, a back in finance system based on what works in a in a similar industry. So it's not a million miles [00:45:00] away. Still a little bit of a way off for it to be accurate and for it to be accessible to people. But we're getting there, you know, and it's exciting to see what's what's going to happen. And yeah, is a little bit scary at the same time that technology can do so much. But.

Jon: You know, I think it gets into and this is the shift that has to happen a little bit. There is I use the term metadata or context. We have to get to a place that when we see the number 500 somewhere, there's more information about that than just 500. Now, is that 500 days? Is it $500? Is it 500 cats, 500 customers? So really starting to create richer data around the numbers as opposed to and I know I'm going after Excel here and it's probably one of the most dangerous things to do. But right now those are cell in a spreadsheet that says 500. And next to that is a label that says cats, right? But if that's mislabeled, that was actually meant to be dogs, right? Like the whole system sort of falls apart there. The fact of that sort of storytelling piece. But if there was information embedded into that 500 that you had all the information about what that 500 is, then you open up a world of possibilities and what you can do with that, knowing what that 500 actually is and taking that a step further and back to the sort of node based decision tree type software we're building, if you could also keep track of how that 500 was created. Right. You know, our founder will send me a spreadsheet there and I'll click through all their formulas. And it's a beautiful I follow this, follow this, and then suddenly there's a cell that's just like copied and pasted a number in there and everything breaks down because I don't know how that number was generated, but if you had the metadata associated with it and how that number is generated, use in PowerPoints. Yeah.

Adam: I totally agree. So what we'll do, Jon, is I've got a couple more questions and then we'll conclude the audio part of the podcast. And then I don't know how you are for time, but maybe you can spend 5 minutes after we finish the audio piece just to show us a couple of bits.

Jon: Yeah, sure. Happy to. Happy to.

Adam: And that means that anybody who's listening on an audio device can just stop, whereas anybody who wants to switch over to YouTube to see they can do that. So so the first question was what do you think the future looks like in this space? And I think you've already answered that question. We're talking about completely integrated data know, and I'd agree. Is there anything else that you think's on the horizon?

Jon: I think I'm hitting on all the topics I think it's about. Simplifying things. So it's it's about building complexity in the systems and then trying to simplify access to it. I anyone who uses Canva right, to do any of their sort of graphic design work, I love to use that as an analogy where I think tech needs to go. Anyone can drop into Canada and anyone can build a brochure or this or that without having to read the manual or to do anything. But there are some limits you can only get so far with that one. If you want to do something highly customized, you can't. Or you can drop into Photoshop and you can try to figure out how to use Photoshop there, and in Photoshop you can do anything. I think there is a world of opportunity to create the canva of financial modeling and projections and all of this. They're horseshoes and hand grenades. Will it be close enough? Is the number going to be perfect? I mean, are we going to be off by a percentage or two? In some cases? That's a really, really big deal. The numbers need to be perfect, but I think there's a world where we can start thinking of this more as the canva of financial model and getting people to answers more quickly there. So I'm not sure that's necessary. Question Adam, But that's the piece that I see is is the approach more than we all know, that one plus one equals two. That's that's not the problem here. It's how we present that.

Adam: Yeah, I totally agree. Okay, cool. So, so the question that I ask every time is the podcast tech for finance. I'm a tech nerd. I love my apps a lot. My software for you, whether it's in your personal or professional life, is is there an app or a system or even a gadget that you use that if somebody took it, took it away, you'd you'd have a heart attack?

Jon: This might seem a little bit weird, but it's actually notion, notion. So notion is a I don't want to say it's a notes collection. It's really a whole ecosystem for documentation and tracking things. There it is cloud based. It's a it's a unicorn company right now. You can create pages, templates. I have all of my developers and all of their scheduling in there. Any thought idea I have, I put it in there [00:50:00] and it's part of this ecosystem of documentation there. People can come in and edit on it. It's basically to my menus passing the whole Microsoft system there for real time collaboration and keeping track of things. Maybe the second one I put in there really quickly would be Loom, from there and the ability to very quickly do a video of anything, whether I'm talking to my developers, any time I build a model, I'll do a Zoom video afterwards where I'm recording the screen and that I'm posting that up there for people to watch the video before they get to get into the model. I think those would be my two two things. I could not live without.

Adam: A third of notion. Yeah, so I'll drop the link in the show notes because I'm aware of it. I'm not used it, but maybe I should and I use loop. I'm using it right now. It's I'm not using it to record. I'm using it for the transcript.

Jon: Yeah, it's fantastic.

Adam: It's not perfect. But the thing I like about it going on a bit of a tangent here is it's got a filter. So. So me, I'm terrible. I add in lots of errors and ums and all of that sort of stuff is it will take out the filler words. It doesn't help for the repeats, but the ums and the ahs. It does a good job of getting out. So. So yeah, I love Loom and the automatic gif images and the share links and it's yeah, we're good. And it comes back to your point about simplicity, right? You know, anybody can sign up with Loom, you know, and immediately record a video and share it within the space of 2 minutes. So no, I totally agree. That's great. So before we switch over to your screen, do you want to tell people a little bit more about where they can find you? Where they can find what if I.

Jon: Yeah, absolutely. So website is what if I oh, where we are right now. We are in our early access phase so anyone can use the software right now. There certainly there are some limitations there. Part of what I talk about is my blue sky vision about where we are. But you can sign up right now, you can get a free account and you can dabble in play. We have a few limitations in there. You can only create so many scenarios and so many integrations, but enough to kind of get your head wrapped around it. Is there a learning curve? Absolutely. To expect people to drop in right off the bat and kind of get it know it's not going to be for everyone on that one there, But if people are really interested in it, I am doing the occasional webinar where I run through it and it's also as a startup, it's all about high touch, so I am happy to hop on and help anyone build out any model or start to wrap their head around the ecosystem there. And maybe as an addendum there too, I am also at the stage now where I am starting to look for more industry advisors and people that are tech centric that would be interested in in an advisory capacity going along for the ride, helping me figure out my next steps and where I go with it to support more and more examples.

Adam: So from an I.T. or a finance perspective.

Jon: Yeah, it's there are there's a concept of early adopters, right? And when you're doing new technologies only. Small percentage of people that will be game. A lot of people are waiting for their product to be entirely robust and fully functional there. So depending on where you are on that spectrum, if you are an early adopter, that's game to kind of give a new way of thinking a run. Perfect timing for us. But again, there's nothing preventing people from jumping in and exploring it. Desktop only. It's not a mobile application only for desktop users.

Adam: Fine. And your LinkedIn is just Jon. Jon Cowley.

Jon: I believe that's correct. Yeah.

Adam: Well, in the show notes as well. Fab Jon. All right then. Well over to you. Anybody that's listening, feel free to tune out and we'll switch onto to YouTube.

Jon: Thanks. I love this sort of stuff. I'm happy to. If you can give me screen sharing there, Adam, that would be wicked.

Adam: Remind me how I do that.

Jon: I think you go down to the bottom and there's a screen share icon at the bottom of Zoom there, and I believe it's probably a preference for property in there.

Adam: You can share all participants.

Jon: Right. And that's probably some of stuff you want to edit out while I get all this stuff up and running here or not. All right. Are you seeing my screen? Okay. Yes, we are. Okay. Now, depending on you, Adam, there's like, the demo that I normally do. I'm going to obviously pare it down. Otherwise we'll be here too long on things. I do sometimes run through a. Speaking of camera, I do sometimes run through a little bit of a conceptual deck where I talk about how the technology works. If you feel like I've covered that, I can just sort of skip to the juicy stuff. That's your call.

Adam: Yeah, skip to the juicy stuff. That's fine. But if you got if you got this as a slide deck.

Jon: Well, it's it's in Canva. So I could just sort of share it with you. But yeah, it's just sort of the this is my, my generally my presentation deck. When I'm doing a demo, I usually run through it so I can I can share it with [00:55:00] you later there. I can, even if you want to. I can. It's just tricky. It's not like a self serve thing where someone's going to look at it and just kind of get it. It's sort of a visual tool when I'm explaining how the tech works, but whatever, I can make it available to you if that's a value. Okay. And I'm going to I have a couple of different models, so I've got I'm going to defer to you. This is a software as a service customer growth model there, which is usually one I use for my kind of lightning demo on things there. Is that a decent thing to do somewhere? Okay, let's do that. All right. Wonderful. All right, So I'll get started. Okay. So right now you're looking at a real live version of the software here. Right now. There's a couple of very kind of key concepts. I imagine if someone's dropping in right now and taking a look at this. This isn't a spreadsheet. It is a very, very different way. And I acknowledge that right off the bat. So we've built this canvas, and this canvas is a calculation engine. And as you drop in these things we call events, you can create these financial models, right? Think of it like Lego. We built the green Lego board there, which is our calculation engine, and we built 2530 of these Lego pieces. And depending on how you assemble them, there's a lot of things that you can make from those Lego pieces. As we're working with companies, we're adding new Lego pieces to the model that allow you to build more and more complexity there. And we've also integrated in some expression languages that allow a more tech savvy person to even use Excel language like logic in our flows. So it's almost like having your own 3D printer where you can build your own Lego blocks in there at the same time too.

Jon: So just some key things there. So these are these events and this is a software as a service customer growth model. Could you build this in a spreadsheet? Absolutely. But hopefully you sort of stick around. You'll sort of see why I think we can offer some extra value to this one. These are events. So here I've got a customer event, I'm funneling into my first option or decision. There's a growth and then a different sort of growth model. I've got churn customer acquisition costs, I've got pricing revenue, I've got KPIs at the end of the stack. And I also have this thing called a modifier, which I'll circle back to, but this is actually my incredibly powerful event that I have here. So speaking of events and interrupting each stage, Adam, if you have some questions, but speaking of events, we have a whole library of them. So for example, I have debit, credit, income, banks, loans all inside the stack. Think of these as being the business logic that would be involved in building something like this in a spreadsheet. We've sort of pulled that out and made it its own standalone module. If you're looking at a small, medium sized business module here we have an employee event. How much are you paying them? When are you paying them? What's their tax zones? All of that logic is buried into it in many respects. We're almost an accounting program smashed together with Excel, smashed together with a decision tree software customers, customer growth, churn transfer. What if I'm transferring 10% customers month over month, converting from my paid plan to my pro plan? I'd like to show, for example, the contract event, just to kind of give a sense of the level of granularity that can be in there. So I may have a contract. It starts in November. It's a big old number here. I'm going to have a 10% down payment. My net payment terms are going to be 14 days. Put it into milestones in so you can truly model it in granularity if you want to the cash flow from this particular contract and when the money is going to be actually in.

Jon: So whether you can kind of make payroll. So some of our events are granular like that, some are very high level. Okay. So in this flow, what our algorithm does is it runs through every single possible branch. We call them threads every single day and calculates everything. And I'll kind of get to what that means. So here I'm establishing my customer cohorts. So I've got two customer cohorts, one with 50 customers. Again, the dates were the important and one with 200 customers. And again, the dates are really important that funnels into my first decision here. I'm saying, well, what if all of my customer cohorts grow 10% month over month? All right, or I can say, but what if customer. Core one girls 15% and one off court. Number two has a dynamic growth rate. Things actually change over time. Those two funnel back into a churn event, three and a half percent customer acquisition costs. Here's my pricing. Here is product number one. It's $40 a month. And keep in mind, this 40 is going to be important in the second or. Here's my product number two. And I've also baked in my cost of goods sold for that particular product. So I have that level of granularity if I want it there, that funnels into a revenue event where multiplying my customers every month by those pricing products that are there and that funnels into KPIs where I'm calculating the cocktail TV ratio or the RPU or whatever it is I want to be able to have for this particular model. We have a growing list of kind of KPIs. Any questions there? I'm so far.

Adam: That makes.

Jon: Sense. Sorry, I just. [01:00:00]

Adam: Muted for a second. I had a screaming child.

Jon: So I'm good. I'm good. So what that does is we calculate, we go through every single one of those threads and we calculate those values here as we kind of run through. So I'm able to take a look at all of these threads here. And when I talk about calculating everything, I could look at customers, for example. So you're sitting there with the CEO or a division manager or something. It's like, Well, if this model happens, how many customers are we going to have so cumulative over time? This model, this thread, we're going to have 85,000 customers, whereas this one is going to be 10,000 customers. And traditionally we can pop this up here, we can throw it onto a graph, we can see what these things look like because our number 500 has metadata associated with it. I can look at it as through the lens of customers, or I know that something is my cost of goods sold and I can see my cost of goods sold values and what those are over time. You just have that sort of insight. Of course, I've got spreadsheets in here, so if you need to see a traditionally, you can look at every single one of these accounts and all the values that would play out in each of these scenarios that are here to. So I still kind of give that level of comfort. You can also spit this out to a CSV file afterwards and take it back into the tools that you want to. So core concepts, you connect these together to create these what ifs, the on the time sort of real time. Part of it is the ability to rapidly test some things. So I'm going to duplicate this model here. All right. And now I have a clean version of this here. What I'm doing now is I could very easily say, well, great, 10% growth. What if it's 20% growth? Right. And again, this is a very low level version of it. But take this kind of an expanded up to anything there. So I'm going to take this event. I'm going to copy it. I'm going to paste it into here and drop this in.

Jon: I'm going to open this up and I'm going to change this to be 20%, for example, and I'm going to relabel this 20. Just for clarity on that. I'm going to drop it into the flow. I'm going to reconnect it into the rest of the flow. And now as it's calculating, it's going to take a little bit of time because we are screen sharing. You're going to see there's going to be three scenarios. So we just asked and answer what if scenario here in real time, Right. Taking that one step further challenge right now in a traditional model And again, can you do all these things? Yes, you can. My thesis is about robustness and also about telling the story. I would argue that I could drop this in front of you right now, walk away and say, tell me what's going on. And you could probably figure out the model without me having to hold your hand. Right. But here I can do something like say someone says, What if we raise our prices 25% on our $40 a month product? That's a scenario. What if we do that again in a spreadsheet? If you haven't built for that scenario, if you haven't built that into your model, it's going to take a little bit of time to sort of figure that out. We have this concept of what's called a modifier, and a modifier allows you to go in and modify anything upstream in that calculation flow at any point in time. So I'm saying I want to point to that pricing event. I want to point to that product number one, that's $40 and I want to increase my prices by 25%. But I want to do that July 1st of 2023. That's that time piece that's really, really important. Right? So now what's happening? I have a bypass right now, but I'm going to toggle that on and now everything's going to recalculate with that 25% price increase there. But of course, what I could do very easily is I could also test different theories. So let's turn this back to being profit right now. So I'm looking at my profit and obviously there's dependencies.

Jon: It's not so simple. You just raise your prices and demand stays the same. So we have that built into our logic. But on a really low level, I'm going to add another option in here. All right. So add this event in and I'm going to do two things. I'm going to put in a null, which means no change. All right. So the data just flows through as if it hasn't been modified. I know I'm already getting a little nerdy here, but, hey, that's what founders do. All right. And in a second, we're going to have six scenarios, these three different growth models and also two different pricing models, all running concurrently at the same time. So you can picture that boardroom experience there. Someone would probably build this model in advance, kind of come in with some of that and then we play with it. So I now have six scenarios that are all calculating in real time. I sought those based on profit. This is my most profitable scenario, obviously the highest growth rate and that. But sometimes some of these levers will kind of counteract each other there because maybe there's a cost associated with some of those. So I'm able to see all these models in real time. I'm able to pop them up. I'm able to look at them all here concurrently. But what I'd also like to do is I want to drill down. I want to understand this $46 Million scenario better. So I'm going to drill into this [01:05:00] one singular thread right now, and I want to understand the levers. I want to I don't only want to know the answer, I want to know why. So let's look at this through the lens of customers. And I want to understand how did I get to 8400 customers in this model? Because every one of these calculations have these natural breakpoints, right, that you go through. It's very easy to step through the calculations and understand the levers. So I'm going to switch here to something called cumulative mode. And here you see I have no customers. All right. Here's the first event where I establish those two customers cumulative here.

Jon: So you're seeing my 250 customers I established. Now I'm additively adding in the next step and the next step. So here's my growth, right? 365,000 customers. Wicked. There's my churn, right? What's happened? I've lost 50,000 customers. So I can now drill down into just each individual event. There's my 54,000 customers I've churned, so I was able to add 365,000 customers. But our churn. So now in part of the decision making process, you can start to understand which levers are making the biggest difference. Maybe ask some new what ifs on the fly there and add those to the model in real time. So the ability to look very large and look very granular on things on the fly in that model and then maybe moving forward, we've decided that we want to have the assumption that the safest thing to do is maybe this model here. I'm going to lock in the 15% growth in the dynamic churn. Everything's going to recalculate. These other threads are now filtered out, right? So it's a decision making tool. And I'm back down to two decisions now. Do I raise my prices or do I not raise my prices? Does that.

Adam: Logic is it's just the speed of it, isn't it, Jon? And I know you're a pro, right? Because you built. But. But at the same time, you know, to get to that, there's not been what I've not seen is is 1,000,000,001 clicks.

Jon: And that's the that's the idea And we're at the stage now too and that's that's the thesis is being able to do those very, very quickly. I'm at the stage right now that I can import in all your QuickBooks data. So all your stuff is coming in. So if you want to refresh your books on a regular basis, you can do that. I'm in a stage right now with CSV importing that. If you have a pal that you want to bring in, you don't have to build a model. If you've built that your budget for 2023, let's import it in, have that as a baseline and then let's play with, well, what if we increase our travel budget or what if this or what if that you can all do that dynamically on the fly. So it's really meant to, to your point, be fast and iterative, expecting change, not trying to be perfect on day one and then struggle to adapt.

Adam: And if I got my hands on this, I'm going to resist the temptation. I probably lose weeks.

Jon: Because.

Adam: You you could keep on going. You could keep on going, wouldn't you? And it's almost at the point where you want to continue adding those what if scenarios and when you were going through that that story you where of the customers come from, where's the churn according to to what my projections are they're. But just just thinking out loud, you could add in another event before that, couldn't you? So. What if we employed another customer service exec know that meant that we reduced churn by 5%? Does that justify the cost of a customer service?

Jon: We're working with a company right now here in Vancouver that has an outbound sales model. They're supporting restaurants there and they have sales people going out in the field there. So they're trying to model. And again, can you do this in a spreadsheet? Yes, you can. The templates exist for it. I just argue they're not as robust. What's the average sales time? How many deals can a junior salesperson close in a month? What's the lead time as an enterprise sales there? So if I hire five sales executives, that and then that kind of dependency series of calculations that are there and what does that look like? All of that is possible. So again, anything that can be done with a formula can in theory be done in our world. Some of those we support today right off the bat, some of those Lego pieces we're building out to support that. And then some of these things you can build yourself, like at a certain level of domain knowledge, you're not hindered by what we've prebuilt. You can build your own there with that learning curve. Yes, I'd argue it's a steep but short learning curve, and once you get the concept, you can move much more quickly.

Adam: And I saw a couple of the events from the from the the menu there. You had some that were up and coming. So I saw inventory in there. I saw those cogs. One wasn't there. Yeah, they.

Jon: Get all of that. All of that is as we build back to the Lego example, as we build up more and more of these. So we have a sort of niche use cases that we're working with now. And a lot of that is just about velocity and back to partnering with people that are interested [01:10:00] in building out for other sort of use cases that are there. So yeah, that's what we can do, helping people rapidly ask and answer questions in real time and to tell a story, the journey of the money in a way where all of your stakeholders are able to see and follow along. No. One. Again, I'm not trying to knock a spreadsheet. It is the most successful software product of all time there. So it's it's definitely is incredibly powerful tool, but I don't think anyone would want to receive someone else's spreadsheet and say, Hey, go, best of luck. Whereas here I can click on this. I can say share scenario and I can send this to you right now and you could open on your desktop and play with this model. 12 seconds.

Adam: And just just before you go, because I appreciate we're we're over time. You've got a decision engine slider at the top. Right. You don't have to show it, but you can explain how it works if you like.

Jon: Yeah. So here's another sort of thesis and this is a bit of a rollover from when we started in personal finance. If my wife and I are looking at making decisions in life, the most profitable decision is for us to sell our house, move into a basement apartment with an hour and a half for my job, and that's the most profitable decision. But there are other levers that are involved in making decisions. So we have the ability in here. It's still in its early infancy, but to weight sentiment data, Right. So what do you want to do? Right. So maybe there's some initiatives there. Like I can look at opening offices in China, I can look at opening offices in Beijing or in Brazil. There I can look at the cost factors to all of those. But then I can also add another dimension to it, which is sentiment weighting sort of almost a star rating type thing. So as you're looking at your 82 different scenarios, what do you want to do? So you can weight some of those and sort them based on sentiment data or sort them based on financial data or somewhere between the two and they'll reorder because if this list gets very large, it gets quite daunting. And the idea is back to a decision making, you may choose to make a emotional decision for lack of a better term there. So if you choose to do that now, you can kind of rebalance and say what made the emotional choice? And I've locked in this particular event. Now we see the numbers. Now I better get back to making some financial choices there because I can't afford to make any more emotional choices. The idea of building models that take into account other dimensions, we can extend this in time to be eco friendliness or carbon footprint or other sort of things. There any kind of weighting factor, the one in there to be able to reorder some of these threads? That's your question?

Adam: Yeah, it did. And the little light bulb there.

Jon: Sorry. Which one?

Adam: The little light bulb on the right and the. The. Yeah.

Jon: Well, this is. This is kind of gets into our knowledge base. Right. So just got access to all of that charts graph what's. Think of it like a planning and strategic planning tool that has both financial and strategic decision making functionality inside of it. So as I'm talking about category creation earlier, the challenge is figuring out which box do we put ourselves in, what are people looking for and how to position ourselves. It is one of the challenges when you were doing something different there and figuring out where you are, where your positioning is good.

Adam: Now if that's been fab Jon, you know, I can think of a handful of people that will love to jump into this straightaway. So. So as I say, I'll. I'll get this up on the YouTube channel. What I'll do is for anybody that wants to skip to the end, you can add a link in you in the description so that they can they can go straight here if they want to pick up.

Jon: They can. They can hop to the website. I can also send them directly to it. And again, as a recap, there is there is a learning curve. So I'm happy to walk people through it at this stage of evolution there and help them kind of get off to a great start, but they're welcome to play at the same time.

Adam: Yeah, that's Megatron. Really appreciate that. It's fabulous.

Jon: You're welcome. Well, thanks. Thanks for coming on the show. Thanks for having me.

Adam: Maybe we'll have a round two in a couple of years when you know, you've made an absolute beast of a solution and you've got, you know, 250,000 customers.

Jon: That's a fantastic moment in time. And then Intuit comes knocking. It'll be great. Absolutely. All right.

Adam: Thanks so much, Jon.

Jon: Thank you, sir. Bye.