Why hiring won’t fix your quality problem

John Rebello: Every aircraft was getting close to a thousand issues that would then have to get dealt with. If we're finding this problem, you know, at assembly station eight, but I know it's happening in assembly station two, all I'm going to do is move my inspection point. We saved, I think it was close to $100 million for this assembly line in a year.

Victor Wong: Welcome to Owners & Experts. Look, if you're running a business and trying to make it from 5 million to 20 million, you already know what got you here today won't get you to where you want to go tomorrow. In fact, what got you to five million, it's almost certain to break on the way to 20. Top line strategy sounds great in pitch decks, but the devil is in the details, and those details come down to daily execution. So whether you're coming from other CXP content, or you found us looking for real help to scale your business, you're in the right spot. I'm your host, Victor Wong. I was employee 21 and COO and CFO of a venture-backed tech startup in Toronto called Flipp. We grew that business to north of 100 million US in revenue with 30% EBITDA margins, and I had a successful exit to private equity in 2023. And now, together with John Ling, another early operator from the Flipp team. We're here to share the exact experiences and hard-earned lessons from our journey direct with you, the operator looking to scale. That's why we built the show. It's a peer-to-peer teardown, no fluff, no polished PR stories, just real operators breaking down what actually happened behind the scenes when you scale. Which brings us to today's episode. So when a business starts hitting real momentum, your sales are up, existing accounts are expanding, and on paper, everything looks great. But internally, the demand is completely overwhelming your team. So now your quality is slipping, your delivery gets a little delayed, maybe a lot delayed, and your first standard executive reflex is we gotta hire more people. You just need more bodies in in the building, and this will fix things. Now, in this episode, we're gonna tear down why adding headcount is not gonna fix the process and it's just a band-aid. And why embedding in a continuous improvement mindset is actually the real fix. So as you can imagine, when you first encounter a situation, you're like, okay, well we need to fix this with people. So then you start a job rec, that'll probably take a week. You then start sourcing candidate. You might actually need to hire a recruiter, that'll probably take another month. And then you have to go through interviewing candidates, which you know maybe another month or so. Interview candidates, wait for them to leave their jobs. Maybe they don't have a job right now, so you could get an immediate fix. But that entire process itself for just hiring, it's already three, three months, four months in. And then there's training time involved. So you're looking at almost six months before this quote quote unquote magic fix, and it's not really a fix at all, is actually going to impact the business. So, this is why we're looking at a continuous improvement process, and this is what we've done at Flipp. So, our main takeaway tool for you today is something called a KPI tree. Now, we're going to walk you through how to map your downstream operational drivers, isolate root cause bottlenecks, and fix quality issues before you open that head count requisition. So, joining us today to break this down is John Rebello. John wore many hats at Flipp. One of the most important impactful hats that he did was his first. He was our director of continuous improvement at Flipp, where he spearheaded operational process improvements that allowed us to scale efficiently without just throwing headcounts at the problem. So John, welcome to the show.

John Rebello: Hey, Victor, how's it going? Thanks for having me.

Victor Wong: Maybe give some context to the operators listening. How did you first end up in operations and what pulled you towards continuous improvement early on?

John Rebello: Yeah, so I can start off with a little bit of my story, but it kind of started for me at university. I studied mechanical engineering and there it was exposed to, you know, the process of design of designing processes and then also improving them. So it went through, you know, a lot of the theory operations research and manufacturing. I don't know if any of the operators out there read the book, The Goal by Eli—

Victor Wong: Great talk. Great talk. Yeah.

John Rebello: Yeah, Eliyahu Goldratt, but I kind of think I read that in university as part of a course and it kind of it opened my mind to, okay, there's opportunity and there's really you need a unique way of looking at processes in order to improve them. So if you guys haven't read that, definitely recommend picking that up and having a quick read. It's a pretty easy read and kind of changed how I looked at things. So first I was in engineering kind of exposed to the theory of lot of continuous improvement and process design. And then when I left university, my first job out of school was at General Motors at the assembly plant here in Canada. there, that was a GM at that time was kind of losing market share year over year to the Japanese companies. I had been doing so for decades. And they had realized at that point in time, of what the Japanese companies, one of the things they're doing better than, you know, GM was that continuous improvement playbook. know, Toyota, Honda, all those companies are famous for having built in place a continuous improvement mindset, you know, from the CEO right down to the guy putting tires on on the car. So at that point in time, when I entered GM, they were kind of going through. You know, that change in their process and in their mindsets. And I got access to some very good tools that they had developed or, know, to be honest, they had stolen from Toyota and and I was able to get to use them on, you know, an assembly line and, you know, at an assembly line, you have a car coming off the end of the line every minute. You know, every time you can shave seconds off of the process, you're saving millions of dollars across the company for the year. there is. A lot of focus and a lot of opportunity. And so I getting access to those tools and then being able to use them both at GM and then across its supply base really opened my eyes and said, okay, well, this is pretty cool. I got to go into all sorts of processes I had never seen or learned and talked to a lot of very interesting people. You people had been doing things for 30 years and work with them to figure out, what's the best way I'll go back to, you know, to put the tire on the car. Or how do we get the gas to go into the car faster? So it was all very like hands-on and concrete stuff. And so that really opened my eyes and you're really able to have an impact. And it kind of brought me into that continuous improvement mindset. And then once you get good and you're able to actually have an impact and the company allows you to do that kind of work. You get to go into places where there's problems and you're helping people that have been in those places fix things. I mean, you get to meet so many people, you get to see so many new things. A lot of times you go into the situation knowing nothing about anything. So there's just so much learning and continuous improvement, which is really what made me, what makes me, continues to make me interested in that type of work. Like you can have a real impact on people's lives and you learn so much and you get to meet so many interesting people. And so I continue to love doing that work.

Victor Wong: Yeah, no, absolutely.

John Rebello: And, and you know, Victor, going back to your preamble, you're talking about a startup that's gaining momentum. Things move so fast in that environment. And the organization is still small enough where you can do things and you can pivot and you can get everyone on board. when your momentum becomes, you know, when you get to a certain size and your momentum is still going and then you bring in sort of that continuous improvement mindset to the organization, what you'll find is because the startup happened so quickly, there's going to be so much opportunity of things that.

Victor Wong: Yeah, yeah, for sure.

John Rebello: Happen, right? Like, I mean, we the experiences we went through, it was, people didn't have time to think about continuous improvement because everything was moving so fast. So if you can then, you know, once you get to the right size, which is not that big, you take a breath and you just have to look around and, you know, think a little bit, think in a structured fashion and you'll be able to identify those opportunities to really change things and that promise you'll be able to solve. Problems that will be of a greater effect to your business than going out and hiring, you know, more people for sure.

Victor Wong: Yeah. Yeah. I know absolutely. Absolutely. So maybe to to crystallize this for the operators listening, like maybe take an ear as through an early moment in your career where before us, so maybe in the GM, because that those are always interesting stories. when you t what you tell when you told me in the moment as we're chatting at flipp, but like before our startup states has really helped you learn, help shape how you learn to fix spoken processes.

John Rebello: Yeah, I mean, so there's a ton of examples, obviously, through my career at GM, but also the one I'll talk about here is when I left GM, I did a few different jobs and lived in different parts of the world. But eventually I ended up at Bombardier, an aircraft manufacturer I'm sure that people are familiar with. And there, what I was hired to do was to start a continuous improvement team on the manufacturing. Assembly line for the aircraft. And so what I had found or what we found with the aircraft as it was getting built, every time a quality inspector found an issue with the aircraft, they would write what's called the snag. So this is basically something that would need to get fixed. And as the aircraft moved through the assembly line, when I first started there, we were finding that they were getting close to a thousand snags on every aircraft. So something wrong could be, you know, something minor as a, there's a cosmetic issue on, on a seat in the cockpit or, you know, it could be something more major where, you know, the, aircraft, there's a fuel leak or something like that. So as it went through the assembly line, the aircraft was, yeah, every aircraft was getting close to a thousand issues that would then have to get dealt with. And this had been going on for years. And the aircrafts, when I started there, the aircrafts were behind schedule. They weren't able to deliver to customers on time. They were all over budget. They were paying, the aircraft mechanics just over time after over time to to to build and try to get these aircrafts out on time. And we were still failing. But what I found was like, OK, we have all this nonstandard work that's happening. There's like a thousand events every aircraft and like every event you need someone to inspect it, then they have to write it up that there's a problem. Then someone needs to come fix it. Then it needs to get inspected again. And then the documentation needs to get filled out because there's a lot of documentation that happens in aerospace. And so all that extra work was what was a main contributor to what was, you know, killing this assembly line and not being able to deliver aircraft on time. We were getting to the point where we were, you know, I can't remember the exact time. I want to say like six months to a year behind schedule. you know, customers ordering a $80 million aircraft and they're expecting to get it in January and it comes, you know, October at the end of the year, they're still, you know, still haven't been able to fly in their aircraft. it was a big problem for Bombardier. But all we did was we looked at those a thousand or so snags per aircraft and built a KPI tree basically out of that database, right? So there were hundreds of aircrafts, there were thousands of snags each. So then it was, okay, we just went through the data and this was the reason why it hadn't been done before was all of this paperwork was actual paper. So it wasn't digital. So we had to hire someone to do data entry and to put it into a spreadsheet, identify, okay, what are the biggest contributing problems? And then it was just a matter of, okay, if we're finding this problem, you know, at assembly station eight, but I know it's happening in assembly station two, all I'm going to do is move my inspection point so that it happened. The inspection happens in assembly station two. So right away you've taken. The problem from, let's say, station number eight and moved it back to where it's actually happening, and that can happen right away, right? And then once now you have the problem being found, fixed and contained in assembly station two. Then it's about, okay, who's doing this? What's the problem? Why is it happening? And then you can put in place the root cause. But what you would find is assembly station eight would find the problem, but assembly station two was causing it, but they never even knew about the problem. And no one had ever done that work to go back and first start finding it in assembly station two and then fix it so it doesn't happen again. And so honestly, we were able to do that. Analysis and that work. there were, you know, there was, kind of led the team and then we had three other people across this, you know, this facility where that was employing 10,000 people. was like a billion dollar assembly line. We were able to then cut snags down to like, it was probably close to about 75% of them, we were able to eliminate and it just changed the whole complexion of this assembly line. And, and, know, we, all we did was really like, the main thing we did was, what are the biggest problems? How do I take it from number eight and put it back into number two? And what we actually found was once it was in number two, there was a, you know, a team in number two. And if they knew that they had to find it in number two, very quickly, like we weren't even typically involved in finding out where it was happening because the inspector in number two would just know where it was. And he would go tell, you know, hey, Jimmy, stop doing that. You're causing us problems. Because now number two is kind of accountable for the problems that they were causing. And so that sort of activity and just forcing those conversations, it really changed the whole assembly line. we, yeah, it was a great experience and amazing. We saved, I think it was close to $100 million for this assembly line in a year.

Victor Wong: Wow. That's that yeah, I didn't I even I know I know obviously your your your your work history, but didn't didn't know that story. I mean it's this the w the acronym snag sounds like it's a play on words too, right? It's like the the process hits a s hit a snag, it sounds like. Yeah. Yeah. Yeah. No, that's that's

John Rebello: Yeah, I hit a snag. Exactly.

Victor Wong: great. That that story high is ex exactly why kind understanding the root cause really matters because I can foresee and maybe it actually happened in Bombardier 'cause you can say from an executive level, let's hire more people because we got these volumes of snags that we need to remedy. And the easiest metric put them for potentially is one person equals like ten snags resolved in a week or something like that, right? So it's it's a various easiest thing versus putting that inspection station up to station two, fixing the actual problem before it moves downstream. And I'm sure By the time it gets downstream too, a lot of probably like cross impact or negative impact probably have happened after from station two to all the way to station eight as well, right? So yeah.

John Rebello: Yeah, yeah, and I mean, effectively, what we were doing before this next move was we were fixing it with overtime, right? And so that's the equivalent of hiring more people. Right. So it's crazy.

Victor Wong: Right, yes. Yeah. So that's that yeah, yeah. No, absolutely. So so you so you mentioned just why do companies look at only top line vanity metrics? I know obviously for us at Flipp when at it's always been revenue and always was daily active users, monthly active users, some sort of user metric because that was the consumer side of our app. So so why is that? Like why why doesn't anyone break that down into its actual drivers?

John Rebello: Yeah, I think a lot of the companies at the leadership level, those are the metrics and the KPIs that they need to report out. If it's a public company, it's what they need to report out for their calling or their earnings. Even private company or smaller companies, need to be accountable to the board. And once you get to a certain level of management, you need that visibility to understand, how are things going? So, you know, typically the leaders, they're really good, I would say, like acting like owners and they want to know how things are going. But I think typically one of there's kind of two things. One is like bandwidth, right? At some point, you can only look at so many things and revenue, it obviously is a very important driver for any business and costs. So there's typically get looked at very closely, right? And monitored. But I think, so that's kind of one thing and leaders don't really have the bandwidth to go, okay, what's that next level down? So what you need to do is actually just put in place the process where you may not necessarily need to look at those drivers yourself, but you need to have that structure in your company to be able to ensure that the right people are looking at the right KPIs and the KPIs are linked, you know, both vertically. So I'm supporting my managers' KPIs, who's supporting their managers' KPIs. And then you also need to make sure they're linked horizontally. So like my KPIs are not conflicting with a different teams' KPI. So like I'll go back to a manufacturing example, but a lot of times you'll have, there's a productivity KPI where it's like, okay, how quickly can I pump these things out? Which would be in sort of tension with the quality KPI. Because the faster I can go, I can go faster, but it might compromise quality, right? So it's about how do you find that balance horizontally where there will be tension in the system between different departments or different units. And that's not necessarily a bad thing, but it's how do I make sure they're all driving to support that top level KPI, right? And so to do that, especially at the onset, like the initial rolling out of that, it takes a lot of work, right? You need to have the right people in the right rooms to get aligned on, okay, yes, we are going to this KPI and make sure everything's aligned and you have agreement and buy-in from everyone. So I think that sort of is one of the reasons that it doesn't necessarily get driven down through the organization. And then the second thing too is the reason is leaders By the time they get to the leadership level, they may not actually be in the trenches and doing the work that is driving that KPI. you know, they're most, I don't know, I wouldn't say most of the time. Well, probably most of the time they don't have the level of knowledge that, you know, the marketer who's sending out the, you know, campaigns on how things are doing and looking at those results. They may not know at that level what is actually impacting that top level KPI. So I would say those two reasons are things, know, are reasons why companies kind of stop at the top, but then they don't go down and drive down and make sure every team has its own KPI, right? That then drives up to the top one.

Victor Wong: Yeah, I I I laugh a little bit because yeah, I laugh a little bit, John, because I I feel like you're describing our relationship back at Flipp where I was so so entrenched in with both of my hats looking at at both the revenue metric and then obviously our our quality metric, but really at the top top level. and that there wasn't another true understanding, although I grew up in the organization and helped develop some of the processes. At the time that you joined, like th those processes were like way beyond my comprehension because it the company scales so so large at that moment. So continuing with that that train of thought, like I'm I'm now interested. Like what's the stuff that you guys were fixing at the at the at the team level and the operational level that you were kind of hiding, not hiding necessarily, but like stuff stuff that I wouldn't necessarily see that you guys were were working on.

John Rebello: Yeah, so I think that's sort of the beauty of the KPI tree and how it gets rolled out through the organization. It really like it really drives visibility and transparency on how each KPI is doing and sort of what's changing, you know, month over month or year over year, day over day, depending on how you're reporting out on things. And so, a, I'll call it in a good KPI tree organization, the people that are down, the people that are running one part of the business that is causing the problem, they should actually be able to see the problem before it bubbles up to the top level KPI. So if I use Flipp as an example, we were always monitoring sort of our users, right? How many users we were getting every week, et cetera, et cetera. And so we had set up in a KPI tree fashion where every week we would pull, what is our user base? And we would then be able to identify, okay, it looks like in, and we split that up into different regions, right? So we were then able to identify, look, like last week in Arizona, our user base just fell off the cliff, right? I don't know why. At the outset, but that then being able to see, there's a KPI about Arizona users. You can then identify that something statistically significant happened there and look at it and deal with it before it actually impacts the overall user number for the entire app. Because maybe that week while Arizona was doing bad, you know, something happened in Ontario, whereas like, yeah, our user base went up significantly and those two sort of offset each other. If you're just looking at the top level KPI, you don't even know what happened and you miss that, that learning that you could figure, okay, what happened in Arizona? How can I, what can I do to make sure this doesn't happen again?

Victor Wong: Yeah, that that was definitely the case 'cause it w it would be like the two geographies would net each other out. You're it's flat this week. Where yeah, everything's fine.

John Rebello: Everything's fine, right? So you miss that opportunity and then you don't learn from it and you don't get better, right? And so being able to sort of keep a pulse on things and it's not like you want the leadership team looking at the Arizona users, but you want the Arizona team looking at the Arizona users or however it's split up, right? Yeah, and I would think the other thing too is the KPI tree when you like I would encourage, you know, the operators out there. When you first put it out, it's not going to be right, like it's not going to be perfect, right? So it's more about like just get it out there and then by monitoring it and understanding things, you'll see. You know, right away, hey, like I thought x times y would give me that z KPI, but now I see x is fluctuating all over the place. It's not doing anything for z. So I need to then investigate, why did I think x was a contributing factor towards z and what am I missing, right? And all of a sudden your x could become whatever the next letter is a, and it's a times y equals z. So it becomes a... Evolving system that is self-correcting, right? If you have a team that's engaged on it. So I'll give you, and I can give you an example from, from Flipp, Victor. One of the early, earlier things when I joined was I believe we were getting maybe about 30,000 or so CX tickets every, I can't remember if it was every week or every month where customer, like users, users were like, in the app, there was a feedback button. So they would give feedback. And there was a whole product team or there was a portion of a product team looking at those tickets and trying to figure out, what can we do to the application to make them better? And so, OK, when I came in, it's like, OK, let's fix this. How do we take that 30,000 tickets and reduce them, analyze, build a KPI tree? And so when we went to get the data from the product team, we were finding they were only seeing like 3000 or so tickets every month. And so, okay, well, something's not adding up here, right? Right away, just by looking at the data, you can see. And then what we found was there were two types of tickets. There were product-related tickets where it was like, I don't like the search function, or I don't like how this widget looks on the application or whatever. And then there were content-related.

Victor Wong: Yeah.

John Rebello: Tickets where it's like, hey, I want to see the Loblaws flyer for today, or I want to see the Kroger flyer and it's missing. And so the product team, because they had determined, well, we're not involved with getting the content for the app. We're going to work on the product tickets. And we had spent, then we're spending resources on fixing 3000 tickets. So let's say they get rid of everything. We're still going to have 27,000 tickets coming in from unhappy customers. So right away it shows like, this is not making, this is not how we should be doing things. And then, we were able to say, okay, let's go after these 20s, like let's eat the elephant in the room, right? And not just keep our narrow lenses on our area of the business. And we were able to quickly like, okay, let's, we're missing content, let's go get it. And we got it and we were able to reduce. So was just by setting up that KPI tree. And then asking the right questions and looking at the data, you're then, this is obvious what we should do next. And what we're doing right now makes no sense. And at the end of the day, we were then able to have a meaningful impact on the data, on the numbers, on the KPI.

Victor Wong: Yeah. Yeah, no, absolutely. So before we jump into telling telling the operators how to build up this KPI tree, there's another related, directly related topic where you talk about metrics and things like that, executive levels, because everyone wants a dashboard. Everyone wants a dashboard, everyone wants real-time dashboards that gives every single possible metric. So any any kind of words of advice or any rules that you can share with the operators listening on dashboarding?

John Rebello: What I found, especially at Flipp and I imagine this is similar across a lot of tech startups is those dashboards are sold as like, we always like paint like. The company ends up paying a lot to get these real-time dashboards that are flashy. And there are dashboard vendors that will come in and say, hey, we can take your data and then give you the flashiest, the UX looks great.

Victor Wong: Your red, yellow, greens, right? So

John Rebello: Yeah, it's, we can send out alerts and notifications and do everything. The tech is all there. And a lot of companies will buy into that and pay for those types of dashboards. And unless the teams engage with that actual KPI from a, you know, it's from like a cultural and behavioral perspective, a lot of times, and this is what I've seen, that dashboard will get paid for and then kind of never used or looked at. Right. And so. You know, when I go back to my manufacturing days, the most effective dashboards that we've had were, you know, data that was kind of plotted by pencil. You know, every day you would go to the chart, you would say, OK, how much further along are we? And so I think a key thing about the the KPI tree and the dashboards is you need to make sure that the team and, you know, people are. Engaging with the actual data. So I can have, you know, the most effective tech solution and a dashboard, send out notifications, but if no one's ever looking at it, it's kind of useless, right? And so you, it's more, it's less about what is the dashboard that you're using and more about what is that process and that culture you put in place that ensures people are looking at it, understanding the results. And then fixing things and getting better based on those results. And so I'm not suggesting that we all need to go back to a pen and paper and update things with highlighters every day. I think there are good technical solutions out there that can save a lot of time and a lot of work, but you need to make sure that it's being engaged with and looked at. know, had at Flipp, we had one central sort of dashboard that was on, it was an Excel sheet, right? But everyone in the organization knew about it. Everyone, you know, if they wanted to know, okay, how many users are we getting every week or every month or whatever, it was there and everyone in the company knew where to go. And that was because we built the culture around that spreadsheet, where it's like, we're gonna go back here every month. This is what we said we were gonna do. This is how we did it. This is how we're doing. We, you know, we didn't meet our KPIs a lot of the time, but it was, okay. Everyone can go and see and understand exactly how we were doing basically at all times, which I think drove that behavior. Okay, and what can I do in my team to impact those KPIs, right?

Victor Wong: And then the other one too from from what we talked about in in terms of Operators looking for the latest and greatest tools. And now everyone promises like this real-time stuff, right? This real time, like once you plug in the data, once you have clean data that you plug into this dashboard, everything becomes real time. You get live updates and all that stuff. Sometimes your business just doesn't move that fast, right? So if you're looking at this revenue metric and you're like, why is it looking at it like every single hour? You're like, or like our monthly active users or daily active users, like, why isn't this going up? Well For us, for Flipp, it's it's a retail technology based on the weekly ad. So just logically, you can't have a daily metric move up because new content gets released every week. It's a weekly it's a weekly play. So that hence we trend changed our our metrics to weekly active users at some point. Monthly active users was more of a metric to compete with competition, just a general standard market. But yeah, the weekly active users, it it was was what we looked at just because of how our business runs. So there's a there's a contextual piece to how often dashboards gets gets updated, gets looked at. But again, I don't think anyone should miss your point. It's like don't put this together, don't buy that software just because you have a bunch of metrics that you want to lay out. Is it important? Can people impact it? And how do they impact it to better the business? What's that five to ten minute exercise they can get started on this concept that we've been talking about, KPI tree? How would you suggest people go about using it right away and getting some immediate results and and seeing some real impact to their their business by implementing this this exercise?

John Rebello: Yeah, so I would say typically as an operator, especially if you're listening to a podcast like this, you're going to have a multitude of problems to go after. I think before you go into the KPI tree, it's really trying to think about which of your problems is the biggest that you can go after. And then understanding, okay, what are the different variables that then build or contribute to that KPI or that problem that you're experiencing? What are the different factors that you can go after that will drive that KPI to change? So it's spending some time thinking about, what are... Yeah, what are the different things that can drive that? So one of the examples I can use is sort of like a lot of companies obviously with that revenue, right? If we think about revenue, then you can break that down into, okay, what are the different factors that drive that? So if you're a manufacturing company, it's kind of like, okay, what are the widgets sold times the price, right, that you're charging for that widget? So then right away you've got the revenue is broken down into two factors. Then you can look at widgets sold. Okay, what are the things that drive widgets being sold? And it's kind of a mix of, okay, how many can I build? What's my supply? And then how many can I sell? So what's my demand? So now you have the widgets sold quantity, like widgets sold quantity into two more KPI's. And so it's sort of doing that exercise and going down to whatever level you think is appropriate. And then at that point, it's about getting the data, right? You need to be able to understand, okay, can I actually see how many widgets did we sell last month? And what you'll find is as you go down the key, down the tree, it will become harder and harder to get that information. So this is where sort of the art of the KPI tree comes in. You need to understand, okay, is this level five of that KPI tree, is it... A big enough portion of the problem for me to go and try and get data around it. Maybe I don't need to know what my widget demand is in what's a small country like in the Canary Islands because I know I don't sell a lot there and I don't need to go get that data. But how many widgets I sold? The United States or how many widgets I sold in China, those are more important because I know that's a potential market that if things change, it's going to impact my top line. Right. And so it's finding that balance between getting the information, the effort to get the information versus, you know, is what's the likelihood of it being a problem for me? Yeah.

Victor Wong: Impact to the to the top to the top goal. Yeah. Yeah.

John Rebello: And so even at this point, we haven't set KPI. Like we had maybe have a KPI for the top ball, but now I'm just getting data, right?

Victor Wong: Hmm. Yeah.

John Rebello: And if you have a problem now, typically you may not have had a problem in the past. And so something's changed. And so this is where the real value of getting the data comes in is you can then look, you know, month, whatever is that frequency of your business, right? Is it weekly? Is it monthly? Whatever it is and whatever, you know, frequency of data you have, can then look at, okay, I was okay from a revenue perspective, you know, last year at this time, this year, I'm not, what's changed, right? And I was like, my factory in Kansas got hit by a tornado, right? Or

Victor Wong: Mm.

John Rebello: the demand in China just fell off a cliff because the competitor moved in, right? And so it's about understanding or by by looking at that data and how it changes over time, a lot of times you'll see what has changed to cause a problem. And then that's where you go attack to fix things. And so that's very, you know, at a very high level, how you build a KPI tree. But as your organization gets bigger, the real magic comes when, now that we have, we understand how things build up to that top level number, you need the teams. That are responsible for those lower KPIs and lower levers to buy into. Yeah, I need to monitor this. I need to understand how it's performing. I need to look at this on a regular basis. And I need to trigger when things are going. You want to do both. You want to trigger when things are going off track. And you also want to trigger when things are doing really well and better than expected because those are both learnings, right?

Victor Wong: Yeah, and how to do more of it, right? Yeah.

John Rebello: And if you're doing that in China, it's like, hey, maybe I can do that in the US or I can do that here in Canada or wherever. And and so if you can identify those events and then learn from them and then share the learnings across all the relevant areas, you then take that, you know, without a KPI tree, that opportunity is gone and nothing happens with a KPI tree. You can then fix it, but then also share it and the growth can be exponential as a result.

Victor Wong: But it's like if I'm an operator on the ground floor, I'd be like, Okay, well, I walk into the I walk into the office, I don't know how like I see the revenue goal, I or I see the revenue metric, I'm not sure how I impact it. And I think this tree also helps kind of share that so people understand where where they're at. So yeah.

John Rebello: Yeah, I mean it gives like it gives people a scoreboard right so it's it's like I forget what book I read this from but it's I mean if you just think about I'll think about myself like if I'm playing sports or like basketball or whatever Things change once then when there's a scoreboard Right. And I'm playing against the team. So as soon as I know what I need to do and I can see that, I have scored a bucket. My behavior will change. I'll get a lot more buckets. Right. And so the KPI tree can have that effect on the team, too. Whereas if you don't have that scoreboard, like I'm just in the gym, I'm kind of shooting around. I don't know. I might get a couple in the bucket. I might, you know, stand off in the corner and just kind of, you know, wait or. If I'm playing defense and you know, there's no scoreboard, I may not, you know, jump as high to whatever, you know, bad basketball analogy, but like the scoreboard does make a difference and it makes things clear. And then when the scoreboard is wrong and you're in a, you have the right culture, you can then have the, you know, the point guard on the team and say like, Hey, you're not counting, you're counting fouls. You're not counting buckets. What we want is buckets, right? And so it just, a good KPI tree, you really want to unlock the knowledge of the people that are in the trenches, like people that are doing the work. And so you put this out and have them look at it and be like, that's ridiculous. It shouldn't be that, it should be this. you'll see, you just need to enable people to do that. without that KPI tree, you know... The easier path is just to be silent and be like, okay, I'm just going to do what I do every day. And I don't know if it's contributing or not, right? But if you tell people like, I'm going to score you on this, it changes things significantly. No problem, Victor. Thanks a lot. Take it easy.