How managers use data analytics for marginal gains

Paul: You've got to be ahead of your game, you've got to be ahead of your competition, and you've got to be innovating and continuing to innovate if you want to even be on the grid.
Jimmy: Welcome back to the Ways of Working Podcast, your weekly dose of practical tips for senior leaders who are looking for a performance edge without burning themselves or their teams out. Today, we're talking with managing consultant and former F1 performance specialist who is an expert in bringing performance insights to organisations all over the world, Paul Teasdale. Hey Paul, how are you?
Paul: It'd be speaking with you, Jimmy, as always.
Jimmy: Fantastic. I'm so pleased to have you on the podcast and genuinely excited to dig in today to the world of Formula One and how that applies in business. So let's get straight to it. First question, why is it important to have an edge in Formula One?
Paul: The long and short of it is your competition are, and if you don't have that edge, you're going to be at the back of the grid, as simple as that. There's such a high pace of innovation in the world of Formula One. Everybody's doing it and they're doing it at such a high standard and such a high pace that if you take your foot off the pedal even a second when it comes to that driving your business forward, then you're going to be at the back of the grid definitely. There's all sorts of facts and figures around to start with a car at the start of the season. That car has changed by at least 70% by the end of the season. There are so many different parts going on that car, different designs happening, different changes, just small little tweaks here and there, and you've got to be ahead of your game. You've got to be ahead of your competition, and you've got to be innovating and continuing to innovate if you want to even be on the grid, never mind win.
Jimmy: And what I'm hearing is there's there's a lot of echoes or mirrors into the business world, and and I can't wait to dig into some of that. But how did you end up as an F1 performance specialist? Tell us a little bit about that.
Paul: My background has always been about helping people perform, in one way or another. Funnily enough, I've got a background in food manufacturing. I worked in uh international shipping and dairy export, which is where we met many years ago, and banking, as well. So I've applied the the thinking in different organisations and different setups. And I found myself when we were looking to move back home to the UK from uh our time in New Zealand, looking for that exciting role that may give me the passion to move back. Luckily had a a connection who worked in the simulation team uh McLaren uh was reaching out to various people and he said, "Oh, I'm sure they're looking for people who do your sort of thing, whatever that is, and looking to do that with McLaren." And got in touch, had a conversation, jumped on a plane for an interview, flew the other side of the world, had an interview, jumped on a plane, went back home again, and was lucky enough to uh be offered a role there. And yeah, it's an amazing setup and an amazing company that's got so much going for it. And uh yeah, I was able to bring a different perspective on the way in which they take their methodologies, and some of their technologies, but their methodologies and their ways of working, out to other organisations. And that was my role.
Jimmy: That's fantastic. And I like the way that you kind of taken bits of various careers and put them together in terms of how do you help people perform? And we'll come back to that a little bit later on. What was it about the world of Formula One that you found exciting, that you found inspiring, that you've been now able to take away and support other businesses with? What was the thing that attracted you to that world?
Paul: Funnily enough, it wasn't because I was an F1 fan. And I don't consider myself an F1 fan. I'm a big fan of the performance and the approach that um that those businesses take. And I'm a big follower of McLaren still ongoing now. But uh it's one of the things I said in my interview, for instance, like if you want an F1 fan, I'm not your person. And yeah, I'm I don't bring that to the table. And it's like, "We've got plenty of those. Plenty of people with the specific experience. We're looking for that different mindset." And this is one of the things that really attracted me is that in all sorts of different roles and positions in that organisation, you had people that when you found out about their history, and you found out about their training and things like that, yeah, how have you ended up here? You know, there was a a young lady who was a strategy role. Actually making the calls as to whether or not you're going to pit the car or not. Multi-million-pound calls at times, you know. You get that wrong, it can cost literally millions of pounds. And I believe she was a lawyer by trade. And it's that approach that McLaren were taking that says, "What do we need for this role? What's the capability, not necessarily what's the experience, and what you know, you've done this before?" And this is one of the things in wider organisations I've always had a bit of a gripe with is, experience of doing that role does not mean you're the right person to come in and do the role somewhere else. It's capability, it's desire, it's coachability, all those sorts of things that go along with it.
Jimmy: And I think what you've described beautifully is is diversity as well, in terms of, obviously we focus a lot on how do you build a high-performance team culture. And part of that high-performance team culture comes from getting different ideas from different backgrounds, different experiences. And sometimes, it comes from throwing what would you say, new people into old problems or old people into new problems, to spark the creative juices. So let's talk about the Formula One and that performance edge that so many of our listeners will be thinking, "How do I do this for my business?" How does a Formula One team get a performance edge?
Paul: Well, the first thing they have to do is get the basics right, and get the basics right all the time. So that's something that a lot of people forget. They look at the shiny shiny, they look at the mission control, and they see the new tools and the technologies that are there, and they're brilliant, and they provide a performance edge, but only on top of the basics. You've got to get the basics right for your organisation, and you've got to be able to do it right every time. And that comes with being purposeful about what you're doing. It's about making sure that people are clear about what their role is in that whole space. And it's about giving people the opportunity to practice or to try things out and do something new in safe environments. And then once you've got that stuff nailed, you can start to add on the 1%s. You know, quite often, not very often, but sometimes you get the big step-changes in in innovation, but, actually, most of it is the 1%s.
Jimmy: Tell us more about 1%s, what's that?
Paul: This is the concept of, Sir Clive Woodward was a sort of real proponent of this, is actually just firstly get the basics right and then add on the 1%s. It's one thing that's slightly better today than it was tomorrow. And if you look at the numbers, I'll see if I can remember the numbers off-hand, but if you take your the starting point of one for your year, and you take a massive project, and you go, "Right, I'm going to 50% improve my performance. I'm going to invest all throughout the year. I'm going to do this." At the end of the year, I've got a 1.5. That's the maths behind it, you know? If you start with one and you get a 0.01 increase tomorrow and you compound that, and you compound it 365 times, you end up with 37.8, I think the number is, or something along those.
Jimmy: Bang on, 37.8, correct.
Paul: And so it is streets ahead. Absolutely streets ahead. But if you don't You've got to start with the one to begin with. You've got to have those basics. But once you do, you chip away those little things. And it can be the technology, but it can be the methodologies, your processes, your people, the way in which you communicate. Communication's key in Formula One. And if you can get 1% better at communicating what you need, when you need it, how you need it, then that can have a real compound impact on the the rest of the organisation. So it's just finding those bits that, "How can I be better today than I was yesterday?" And it doesn't have to be streets ahead, it can just be that little bit better. And that comes through experimentation and things like that that is such a proponent of yourself.
Jimmy: Absolutely. 100% playing in that space. And it kind of reminds me of McKinsey three horizon modelling anyway is of the role of the senior leader in an organisation and those three horizons being: the first horizon is run the business, the second horizon is optimise the business, and the third horizon is disrupt or innovate the business. And I my suspicion is that a lot of senior leaders are very focused on the long-term game, the how do we disrupt and innovate to survive, when, actually, the big opportunity area is in the optimisation space. And it's not optimisation from a Lean Six Sigma perspective, but it's actually drilling down and talking to your people about where are there little 1% opportunities that we potentially have overlooked or we might have missed, and what that looks like. Have you got an example of where you've taken some of this F1 knowledge and skill set that you've accrued, and plus all the other things you've done, and where you've taken that to a non-F1 business and helped them with the processes that they were working on? And I think what's important as a senior leader is the decisions that they're making and the decision quality. Can you walk us through something you've done there?
Paul: Yeah, so decision-making is crucial. Absolutely crucial. And, ultimately, that's one of the things that a Formula One team McLaren are particularly good at. They've invested time and money in the technology. Sure, there's some great technologically assisted elements to what's going on, but it all centres around the human. It's like, how do you help people, all of their technologies are to help people make better decisions? And that's about providing them the insights, and a lot of time like predictive analytics. It's like, what would happen if I did this? And the number of organisations we've spoken to which is, they're actually, what would happen if you could understand, if you made this decision now, what would the impact of that be going forward? And just, "Oh, well, you know, that means we could invest in the right places. We could understand if it's worth spending any money in that space or not. What impact does it give us?" And it doesn't have to be accurate in any way, shape, or form. If you understand the quanta of what's going on, we worked with a supermarket chain, for instance, on supermarket shelf stacking. You couldn't get any further away from Formula One than that. That's what I moved back, by the way, when I've moved from
Jimmy: Unless you're on Dale Winton's Supermarket Sweep, and then that's like the equivalent of Formula One in a supermarket, right? But yes, I hear what you're saying.
Paul: But I I moved from working on the dockside, on the harbourside uh Auckland with all that beautiful weather, and the right next to the sea, and all the rest of it, and working in a brand new building with the bank that I worked in, to move over the other side of the world to join McLaren to work out of a windowless office in Woking on the problem of supermarket shelf stacking. You know? Living the dream sometimes. But no, it's the fact that, you know, in labour alone, at an organisation at that level, I think the numbers were close to £1 billion a year just in terms of paying for the people to put stuff on the shelf.
Jimmy: So a few 1% incremental improvements in a billion pounds, we're talking serious bottom line impacts.
Paul: Precisely. Yeah. The challenge that that organisation was facing was when we our people take stuff to the shelf, or go to the shelf with a you know, you've seen these big trolleys or the racks that on wheels that people have, and they're bringing all of this product to the shelf. And some of the time, they get to the shelf, and actually, "I've got all of these boxes of cornflakes or tins of soup or whatever it is, and, actually, the shelf's full still." So, I don't need to do that, and actually I just need to move those out the way in order to get to the next things. I'm spending all of this time and effort on this. And sometimes, you get the the shelf, and it's empty, and you look on, "Oh, I haven't got that. I'll have to go back and get that stuff," because uh the systems don't talk to each other. They're based on data that that wasn't quite right and accurate, and not pointed in the right direction. So, actually, how could you build a simple model, relatively simple, yeah certainly not the levels of some of the F1 simulation pieces, but a simple model that says, "If you were to make a change, what could you do? What what impact would that have? And, actually, how big is the problem at the moment? Because we just don't know." And so you can take the data, do some analytics, point people at the right question, and that was a big part of my role is point these really smart people who knew what to do in terms of analytics and modelling, and point them at the right challenges. And if you can point them at the right challenges, they can go, "Ah, actually, if we build a model and we did something in the virtual space you could never do in reality, we'll make the shelves infinitely big. We'll make the trolleys that you bring out, they'll have everything on them. We'll just make that happen in, you know, few clicks of a of a button, bit of code. What's the impact of that?" Because what that means is, whenever there's a gap in the shelf, I'll have product to put on it. So it's like the perfect world. And so you can do that and you can compare the two, and you go, "Well, how much money are you spending here? How much money are you spending here?" And it was hundreds of millions of pounds that could be saved if you got all of that. But, actually, you're never going to get to all of it, you know, but if you just got a portion of that, you can start to, "Well, if I can get tens of millions, just by making some better decisions, some uh some information in the right areas to help my people make better decisions, then, actually, that decision as to whether or not in to invest in those technologies becomes a lot easier." And that's where at a high level at that um that boardroom level is like, "If I'm going to be investing a lot of money in technologies and a lot of money in people and insights, is it going to be worth it?" And every seller of IT systems and software will tell you, "Oh yeah, it'll save you millions." How can you prove that? How can you get that to understanding to understand, yes, it's worth investing or not?
Jimmy: So I'm hearing a few different decisions there that leadership teams need to make on their way to realising these huge, potentially financial, potentially people-focused impacts. Number one is the decision of: what is the problem here? What's the problem we're trying to fix? Because, often, we can go off down rabbit holes of solving for the wrong thing, which might seem sexier or shinier as you say, or it might just be it feels like an easier problem to solve, so we'll go there first. Then there's the problem of: what do we know, and what do we not know about this problem so far, and so deciding what information we want to gather? And and then the third one is: what's our decision around our solution and how much we want to invest in order to realise a gain? Because, as you say, if we invested in an infinitely sized shopping trolley, essentially a supermarket within a supermarket, it'd be a significant investment, and we get all 100% of our gain, but then there's some parameters. So what I'm hearing is there's a bit of a theme here around the usage of data. And I know that you had some great experience with McLaren around why data comes last. There's a little bit of a, what's the word, a dissonance in my mind of surely we start with data, right?
Paul: It's one of those areas where you think, particularly in the world it's one of the biggest insights that I had when going into McLaren, because in a Formula One race, in that weekend, there's more data flying around the world for all the different teams and everything than any other data experiment that's happening on Earth. There's load it's so much in that short space of time being generated, transmitted, analysed, yeah, modelled and simulated all the way through. It's crazy. So you would think that the more data the better, and also you start with, "Well, we'll get more data. We'll get more data." But the interesting insight for me was, actually, data has a cost. You can't get data without a sensor and some telemetry, and some way of transmitting that data back and forth. And, actually, that cost in a Formula One car is weight. So if you want to put a sensor on a car, it's going to weigh something. They haven't invented anything yet that doesn't weigh anything. And so even if it's a small amount, actually, that's going to have an impact on your car. So you've got to understand, is that extra weight worth it? So how do we go about understanding whether that data is going to be worth it or not? And if you start with the data, if you start with, "Oh, let's get more data," we had examples of uh large factories investing millions of euros and and pounds in generating more data only to come back and go, "What do we do with this now?" And if you take this other approach, which is to put data last, what you can do is make sure you have the smallest possible data set. Because if you take that example of weight for a Formula One car drags down performance, well, how does that translate into the business world? Well, data and information, all this reports and additional data that you're giving to all of your people, that takes up head space. People are flooded and you know you the term 'infobesity', you know? There's so much information out there. You don't know what to do. You're consuming it, it's like properly drinking from the firehose stuff, you know, and managers are lost.
Jimmy: Mhm. That's great.
Paul: And you know as well as I do that when when that happens, when you've got so much data, you can't make good decisions. Once you get to that stage of of sort of blindness into a panic mode, then you can't make effective decisions. So what we want to do is put data last on the list so that your managers are having the smallest possible data set to help them with their decisions.
Jimmy: And I think you've described something that is probably the situation a lot of execs and leaders find themselves in is: let's get a team of consultants in who can do lots of analysis, who maybe track some big spreadsheets, we'll use big data because that's important, and actually, you're saying that's not the best route to start. So let's get the expert's opinion. Where should we start?
Paul: Just to clarify as well, big data can have advantages, and if you have access to that, you can look at big data and you can find patterns, and that can be useful. But it's a little bit like shooting in the dark. You don't know what you're going to understand, and you could misinterpret big data in a in many many ways. So where I encourage people to start is I encourage them to start with results. What are the results you're trying to drive? What are those things that you've got in front of you at a high level for the organisation, and then you can drill down and do like a results hierarchy for your organisation? And that includes not only the what you want to achieve, so I use the the F1 example, championship points. Championship points is what you're after for the season, but, actually, that's if you only as as well if you're putting the season timeframe in your mind. If you're talking about the race in front of you, more operational view, then it's actually the race points, the race position. But when you stand back and you take that third view of, what about in 2026 when there's new regulations coming in or something like that? Well, actually, it's not championship points I'm I'm looking at there, it's more about my position compared to my competition and my longevity with them. So you've got to pick a timeframe that works for you in the first place, but understand results in terms of what you're trying to achieve and how you want to do that. And when I say how you want to do that, I don't mean like the the nitty-gritty of, how am I going to deliver that on a day-to-day basis? I'm talking about some restrictions or some guidelines within that, you know. So I want to be doing that in a a regulatory compliant way. I want to be doing it in a way that supports our key strategic objectives. So the McLaren example, I want to achieve championship points, it's got to be within the F1 regulations, and it's got to align to our key strategic themes or some of our key strategic themes, such as sustainability and sort of viewer uh and fan engagement.
Jimmy: And it's got to happen by the end of this year, presumably, by the end of this season.
Paul: Yeah, so you've got those timeframes in mind, and then and so you start with those results, understand that what those results are, be crystal clear at the top level and how it cascades to the individual teams. And then you can start to look at actions. So this RAPID model that I've uh have developed, you know, starts with the results for the R. A is for action. What are the levers that you have at your disposal to push and pull that have an impact on those results? In Formula One, you'd be talking about straight-line speed, power, grip, you know, those key things that that lead to the ability to deliver what you're trying to deliver, but also human performance and other various bits that go along with that. You bring that into an organisation, you've you've got all sorts of actions you can take. You can change your own policies, you can change the processes, you can change your people, your organisational structure. You can do things on a day-to-day basis, change where you prioritise your resource. That's a lever at your disposal and it's going to have an impact on the results you're trying to drive. So the next level, the P, is for people. Who are the people involved in making the those decisions as to what actions to take, and also the people involved in putting them in enacting those, as well? So truly understanding your people, you know, understanding what drives and motivates them, the diversity of thinking. How do you get the best team possible supported in the right way so that they can make the best decisions for those actions? And then the next level down, this is where it starts getting into the nitty-gritty, is insights. What are the insights that those people need in order to make the best decisions? And then from insights, it's data, the smallest possible data set. And just for clarity as well, because uh quite often, people get a little bit confused in this area, data, in my mind, is the what. It's the raw facts and figures of what's happening. Information is where you start to put a bit of structure around that, so reports and uh, you know, quarterly reviews, and they're all bits of information where you've taken the data and you've presented it back to people. Insights take that to the next level and they help people to make a decision. They support a decision to be made. So you might present that data in a way that combines multiple bits of information with some prioritisation views, it might be more visual, it supports them, it's presented in a way that helps them with the decision that they've got at hand so that they you're taking that cognitive load off in terms of processing all that information. The great example that of this was uh did some work in a hospital. And sitting in this room and there's all of them came to the monthly review of cancer patients. And they were saying, "Right, Patient A, this gentleman was born in 1972, and uh, you know, he's got this, this, and this." And then you could look around the room and everyone was going, "1972? He must be about 50, 51." And all that time for, you know, however many people in that room, everyone was going, "How do I translate that date into something that means something to me?" And you could just change that to, "It's a 50-year-old man," or, "A man in this bracket," because that actually makes a difference. That supports the decision, because whether that person was young, old, middle-aged has an effect on the decision they're trying to make as to what treatments or priorities and things like that. So, actually, present that in a way that helps people that doesn't require additional cognitive load. If you can understand those insights, you can just ask that question: what's the smallest possible data set I need to generate that insight?
Jimmy: That's great. So the model is RAPID, R-A-P-I-D. Start with the result you want. Look at the actions that drive those results. Talk to the people who are going to be making the taking the actions and impacted by the actions and doing the actions. Look for the insights that are going to help you decide which people should be involved and what they should be doing. And from those insights, work out what data you need to get your insights. So it As you say, it actually makes real sense when you think about it from back to front in a way. I just find this absolutely fascinating. Can you give us an example of where this framework has, maybe where you've gone into an organisation where they've been a little bit sceptical about this, they're maybe drowning in data, and you've taken them through this process to get to the result they want, because presumably you kind of go through RAPID and then come back again to get the result? Can you walk us through how you've seen that actually work?
Paul: Yeah, let me give you an example from a public sector company I worked with, and having a global reach, and a problem with recruitment and selection. And at a high level in the organisation, their problem was: where do I plan and prioritise my resource? Because I've got a shortage of resource everywhere in the organisation. A shortage of lots of roles that haven't been filled, lots of gaps in the market, but also I've got shortages of resource to plug those gaps. I haven't got enough recruiters, I haven't got any So, actually, when I've got that limited resource, where do I prioritise my people from a resourcing perspective, from a recruitment perspective, so that I plug the right gaps at the right time? And so people are trying to pull all this data together and pull reports and all the. Stop, right. What decisions do you have in front of you when you are looking to make those sorts of decisions? What information do you have? Well, it's about where in the world those things are, because actually that has some elements of criticality from a security perspective, or from an availability of resource in the market, for instance. But, also, it's about what are those roles? Are those roles key roles within the organisation? They're critical to moving forward. We have to plug them, we have to plug them within a specific timeframe. Are they just nice-to-haves? Are they are you backfilling, are you covering? All those things go into supporting the decision as to where to prioritise your resourcing capability. So actually, working backwards from there, it's actually: how do you pull those insights together and present them to a senior team, preferably in a visual way, so it helped people move that? And so it's, you know, we've got a map map of the world. So instead of having a a report and with numbers and facts and figures, people are good with facts and figures, but not everyone can visualise that. And when it comes to prioritisation, bits and pieces, you get a few reports with a bit of red, amber, green on them, and things like that, but, actually, showing the map of the world and going, "Right, actually, it's not only these parts here that are critical. If you look at them, they're all towards Africa or or Asia, whatever it might be. So actually, instead of focusing just on the one specific area, or in let's say Asia I've got one critical part, and it's in Southeast Asia is a real problem, but in Africa, I've got seven critical parts that are Individually, they're small, but actually if you group those together, and you go, 'Right, well, what if I brought in some senior teams to focus on Africa as a whole versus just ploughing everything into Southeast Asia?'" Actually, visualising that and putting it up on the wall helps with those elements of where do I prioritise my resource, and having the facts and figures in front of you supported by insights that help people. Visuals help here.
Jimmy: That's incredible. And so you took this business from scrabbling around, desperately trying to recruit to plug any gap, every gap, to what situation?
Paul: To a state where they were confident with where they needed to focus their efforts. Still all the challenges that go along with that in terms of we still don't have the resource, the market is still a difficult one to make. What they were able to do is start to go, "Right, well, what's stopping us from bringing people from this area that's nice and secure, and it's got very few problems? Actually, we could bring in somebody Oh, you can't because of our internal policies. Or we'd need to train for that, or we'd need to get some Okay, let's take some action in those areas. That's a lever that we can push and pull." And it's helping generate those insights for people to say, "It's those bits that are stopping us from achieving success." And then you can start to question: why are we putting those restrictions in play? What is it about our systems? What is it about our processes and our policies that stops us from achieving what we want to achieve? Therefore, where do we need to focus our efforts in terms of improving our processes or our systems or our policies?
Jimmy: I think that's genius. I genuinely do, because, essentially, what you're doing is helping them uh we go back to the the point we were talking about a little bit earlier, are we focusing on have we made the decision on what is the problem we're actually trying to solve? And it could be, well, the problem we're trying to solve is not actually a recruitment problem. Actually, it's a resource allocation challenge, or it's a policy challenge, and if we could just change that one policy, we could all of this stuff would just fade into the background. So I think there's a real clarity moment that came for me, and I'm sure other people have had the same thing, was this is about deciding what to decide on.
Paul: It can get fairly meta, but you can also use
Jimmy: Some sort of inception moment right now.
Paul: But you can also use it at a small scale, as well, you know. It doesn't have to be that. I've used it um helping people, individuals, who are trying to make a a career decision, for instance. Very simply it's it's like almost like using the GROW model from a coaching perspective. It's like, what's the results you're trying to drive from this career? What's success for you? In what areas, and let's not just talk about money, but actually it's all those elements of a role. And then, okay, what actions have you got? You can speak to people, you can go on courses if you need to plug gaps in your capabilities. You can network, you can go do all sorts of things. Actually, but I could do all of that, what should I do? Right. Now let's think about the people. Who have you got in your coaches, and people you can speak to, friends, family? You can help They can help you with a decision by giving you different insights. People in the role already, previous managers, also. And so and then you work down to: what insights do I need to understand where I prioritise my efforts? If you're applying to 50 different roles, this happened to me when I left Fonterra, I think I had about 27 different roles in my spreadsheet that I was tracking, and, "I can't put the same amount of effort into all of these. Some of them are more bigger priorities than others." And so going through this kind of a process, unbeknown to me at the time, look that uh good on reflection, but it was like, "Right, these are the top three." It's a prioritisation piece. These are the top three that I'm going to really put the effort into. I'm going to, you know, maybe throw a couple of darts this way and see what happens and maybe I can then follow that up if if new insights come into play. And, therefore, if those are the insights you need, what data do you need? And data And this is where data doesn't have to be systems-driven, ones and zeros, and all this facts and figures, it can just be, the data I need is: what's the salary range? When was the last time that someone was promoted from that? Because, actually, if that's a big part If those are the the bits of data that I need, I can go out and I can get them one place or another, or I can at least ask the right questions that give me an indication of that data. So it it's all sorts of applicability, but seeing that obviously the big impacts come from big organisations making big decisions.
Jimmy: From the big projects. Yeah. What I'm hearing, though, is the RAPID and the framework could become an organisational decision-making ecosystem.
Paul: Yeah.
Jimmy: And, actually, one of the things we see in organisations that do really well is where there's a consistent ecosystem of anything. And it's not about limiting parameters and stopping creativity and stopping exploration, but actually just going, if we all think and talk in the same language, and it's why Lean took off and Agile took off, as if we're all thinking in terms of starting with the result we want, and then we're working backwards from that, and we're minimising data creation, and what was it, infobesity, I think you said? Yeah, I think there's a real commercial opportunity to slow down the pace of some of the work that executive teams, leadership teams, management teams, and even employees are buckling under right now, because they're trying to do all the things based on actually not having clear decision points on what are we actually trying to solve.
Paul: No, you're right. I mean that cultural aspect of, like, if you want to move forward as an organisation, having common language, having standard systems in place, like, it's why things like the GROW model works so well when you're trying to have a coaching organisation. You know, you've got a simple model people can follow, you can train people in it, you can build them up their skills and expertise, you can try new things, and you everybody knows that when you're going to face a challenge like this, I know how it's going to be presented back to me. If somebody comes up to you and says, "Right, we've got this big idea." "Okay, what are the results you're trying to drive? What are the actions that you that are applicable in this area? Who are the people involved? What insights do you need and that do those people need to make best decision? And, therefore, tell me about the data. Have we got any data gaps? It might well be you've got all the data available right now."
Jimmy: But it might be choosing which bit of data to go and focus on from your gigantic spreadsheet CSV file that you don't know where to start. No, I think there's some genius in this, Paul. You've obviously taken this framework and you fully you like it's yours, you fully own it. How can people connect with you, find out about you, get in touch with you if they're interested?
Paul: I do a lot of work on LinkedIn. You'll find me on LinkedIn, it's Paul J Teasdale. I'll make sure I've got all the links for everyone. I've got my website, paulteasdale.co.uk. And on there, you'll find a a button for a just to set up a chat, a half-hour chat. No obligation, just so we can talk about what are your challenges, what are your opportunities right now, and how applicable is this? What would we need to do in order for this to move forward for you and your organisation? So, more than happy to have those conversations with people. Just want to give some value back to folks. If it takes us anywhere from there, all the better, but uh you know, it is just about adding value back to people. So get in touch through the website, or catch me on LinkedIn. And I I post a few bits on Instagram, as well, so we'll put that link in as well.
Jimmy: Fantastic. And I believe there's a beginner intro course programme that um if leaders are just wanted to just go, "Is this the right decision-making structure for our organisation? I want to dig a dig a bit deeper." Can we share the link to that with uh the show notes?
Paul: Yep, so that's in the website as well. It's connected to that website, but if you want to go straight there, it's rapid.paulteasdale.co.uk. And I'll even put in a a little special for guests of this, so uh if you the the coupon code will be in with the show notes, and we'll make that so you you get a nice little discount for all your your listeners as well.
Jimmy: Fantastic. Paul, thank you so much for joining us today on the Ways of Working Podcast. Really appreciate your time, the insights you've shared, and making F1 performance secrets suddenly seem a whole lot more achievable, attainable, and something that we can use in our own businesses. I'm I'm really excited about that. Thanks once again for your time. If you enjoyed this podcast, please take a moment to subscribe and drop us a review on whatever platform you listened on. It helps others to know what you think, and also to share any ideas, insights, or comments with the incredible guests that we have on the show. We also genuinely appreciate any contact or any support through Instagram or LinkedIn if you are interested in the show, or you want to find out more. Have a wonderful day. Speak to you all soon.
Jimmy: That's a wrap for this episode of the Ways of Working Podcast. If you enjoyed the episode, make sure to hit the subscribe or follow button on your podcast platform so you don't miss our upcoming episodes. And if you have a moment, please leave us a review with your thoughts on Apple Podcasts or your favourite podcast app. Your feedback helps us improve and grow our community of senior leaders seeking a performance edge. Thanks for listening, and we'll see you on the next episode.