77: From Data to Direction: Building a No Limits Culture with AI

In this episode of No Limit Leadership, I sit down with Jim Stevenson—founder and CEO of the Bletchley Group, a global growth consultancy helping organizations align strategy, culture, and technology.

We dive into what most leaders get wrong about data, why OKRs (not KPIs) are the key to alignment, and how AI is transforming leadership in real time. Jim shares how to create psychological safety, drive clarity, and build teams that win.

If you’re a growth-minded leader who wants to future-proof your organization, this conversation is your blueprint.

 What You’ll Learn:
• The difference between data and useful data
• Why OKRs are more than just goals—they shape culture
• How to build teams that adapt and execute at speed
• What limits real growth—and how to remove them
• How AI is reshaping leadership, communication, and trust
• Why psychological safety is a performance multiplier

Chapters:
00:00 – Intro & why this episode matters
01:05 – The origin of Bletchley Group & purposeful tech
04:00 – Breaking limits and AI’s next frontier
10:00 – Superintelligence, free will & leadership
17:03 – What makes data actually useful
23:00 – OKRs vs KPIs: what leaders get wrong
29:30 – The 70% rule: unlocking high performance
32:20 – Incentives: unleash or destroy greatness
36:00 – What elite teams do differently
37:33 – Culture: the real transformation
41:54 – Creating psychological safety
44:00 – Red team thinking & decision ownership
48:39 – Eliminate blockers. Uncover your strategy.

Guest: Jim Stevenson
Founder & CEO, Bletchley Group
🌐 Website: www.bletchleygroup.com
🔗 LinkedIn: https://www.linkedin.com/in/jimstevenson/

executive coaching, leadership development, team accountability, coaching culture, middle managers, high-performing teams, leadership communication, onboarding systems, questions for leaders, leadership podcast, self-leadership, culture-building, lead yourself first, Ken Proctor, Sean Patton, No Limits Leadership

Transcript

Sean Patton (00:02)
Welcome to the No Limits Leadership Podcast. am your host, Sean Patton, and I am so excited to have Jim Stephenson with us today. He is the founder and CEO of the Blakes League Group, a renowned international growth consultancy with over 24 years of expertise in strategy, transformation, and growth. He established the Blakes League Group with a fundamental belief that while technology is powerful, it should always serve a meaningful purpose. Jim's unique value stems from his diverse background, having worked in numerous roles.

across a wide array of companies. This experience has provided him with a valuable bird's eye view of business operations, enabling him to identify common mistakes made by businesses. So Jim, it is awesome to have you on today. I'm excited for this.

Jim (00:47)
Thanks, Sean. I'm really excited to be here, actually. I'm looking forward to this.

Sean Patton (00:51)
Yeah. And we, you know, we hit it off so well in the pre-call and then you just dropped another, ⁓ you know, pun intended bomb on me about the name of your company, ⁓ Blatley group. So why did you, why'd you call your company?

Jim (01:05)
Okay, yeah, I I like the story, but I'm slightly biased. I created the company on the basis of Bletchley Park, which was a kind of like the US NSA or GCHQ in the UK before those organizations existed. So it was a Second World War code breaking outfit for the UK government.

And it was where Alan Turing, the guy who created the Turing test in 1938-39, he went to work for the UK government during the war to break the German Enigma code. And I just loved the basis. It was where we got the, what we talk about, the first modern computer. So the basis of programmable computing. And it was built, the entire technology was built to break the German Enigma code. And I don't know a better purpose than that. So.

the using technology for a business purpose, it just all seemed to gel. And I liked it so much, I named the company after that, Bletchley Link.

Sean Patton (02:03)
Wow. I like that. That's awesome. And it's yeah, what are, you know, it's there's so much that came out of that time in terms of technology. And I have to say, you know, outside the scope of this prod podcast, probably, ⁓ one of the most interesting classes I had when I went to the military Academy at West Point was, ⁓

military history, not necessarily because of the history part, but because of you see how out of necessity, these different conflicts and technology being leveraged in these violent ways or in geopolitical strategy, the role that technology plays in the power struggle between nations and ideologies and how it drives those different things. And we still see it today, right?

Jim (02:52)
Hmm. ⁓

Sean Patton (02:59)
with quantum computing and AI and all these new things coming up and the battle between Chinese developers and US developers. mean, it just continues, you know?

Jim (03:09)
Completely, mean, and going back to the name of the podcast, No Limits, I mean, for me, going back to Alan Turing, the computer didn't exist in that form before. And rather than being constrained by the limits of his time, he broke through those and created something that has been revolutionary for the last 70 years. Now what we're actively seeing, and there is the Paris Summit, there was a...

subcommittee in the US Senate in December talking about weaponizing AI, things like that. We're in a whole new era, but it's still born out of that same influence of let's not be constrained by limits. Let's see where we can go. Let's see where technology can take us. Let's see where society will let us take the technology. China's deep seek of making that open source while open AI was still paid for.

That's a game changer because suddenly you've decriminalized all of that technology. I have DeepSeek running on my laptop locally. I still pay for OpenAI. But the fact that I've got access to both, the fact that can actually interact with one with the other, and just in a completely personal thing, taking this away from anything that is business related, but I still find it mind-blowing. My mother is

home alone most of the time. So I gave her access to OpenAI, ChatGDP essentially. And she talks to it every day. She now has a friend that's AI and sitting in the computer. And I mean, just society changes, technology changes. And again, I love the no limits. don't think, constraints are always there and we always need to break through them to move forward and progress. So I love that.

Sean Patton (04:37)
Wow

Hmm. Yeah, that, that is so, I appreciate that. And it is so interesting. do believe that, ⁓ you know, the key to our next evolution as, know, an individual human, as well as organizationally is always by punching through, ⁓ what are essentially self-imposed limits, right? ⁓ and how we break through those to become the better vert, the greater version of ourselves so that we can lead more.

Uh, effectively and inspire others to do the same. And I think you're doing that in this space and man, the, on the AI thing that is so interesting. think, um, I think it was, I was here opening our Elon Musk talking about how. You know, I wanted that with my, I have a new son. He's we were talking about before the podcast five weeks old, how all the school kids are basically going to have, you know, AI. Bots with that software or like a robot hardware.

basically assistant, like following them around at all times, like an AI buddy. You and I had, we had our invisible friends, but didn't have access to the world's information.

Jim (06:01)
Yeah,

yeah, mean, just before we go into that, but going back to your no limits of self-imposed limits, I love Leonardo da Vinci. And by all intents and purposes, he invented a helicopter when the technology didn't exist to create a helicopter. So yeah, there are limits, but there's no limits to your thinking. There's no limits to where your creativity can go. And you can set something up that you're limited today because there isn't a material, there isn't a...

capability. The other one just to digress slightly that I loved, I read about 20-30 years ago an invention that NASA had created which was an elevator to space. So you would literally jump in an elevator on probably on the ocean so it could move geopositionally with the space station but you could have an elevator that went up but the limit of it was the weight of the core that to take it

but they still invented this elevator and it's like, we can't do it yet, but hey, that's pretty cool. But yeah, no, I agree. The other thing that I have discussions about is whether you should have a mobile phone in the classroom. And I kind of, I feel like I'm out there on my own at the moment. I don't believe you should have a phone in the classroom for kids that are kind of like five, six, seven, eight. But I think when you, because I think that part of education is about socializing.

playing, learning, being creative and those types of things. But I don't view a phone as a phone. I view the phone as a learning device, a communication device. So if you want your kids to learn how to work in the real world, how to operate and be normal members of society, you shouldn't be excluding the phone from the classroom because that's not how real life is. You should limit it.

and you should tell them how to use it and how to use it responsibly and how not to use it and do things like that. But yeah, I think what you see, an imaginary friend, that's now your mobile phone and it's connected to the world and you've got everything you want and you can talk to it rather than typing into it. It will respond to you in a language that you can understand. Yeah, I'm very bullish on where the future is going with technology and society and how we're getting there.

Sean Patton (08:17)
That's interesting because I think what we hear so much is that we hear that the sky is falling, it's going to be a Terminator and Skynet is going to come take in and take over for us. So it's interesting to hear. I agree with you. I'm optimistic on, I think, just the potential of mankind and our ability to overcome challenges, technological or other ways.

But not without, it's not gonna be without our hiccups though, right?

Jim (08:43)
Can I take a kick?

Oh, completely. Absolutely. mean, nothing does. There's always a step back before you go a step forward or several steps forward. But I read an article just as a side again about 10 years ago, and I found it fascinating. It was essentially predicting the future, but it was 10 years ago. So we're now so we're just getting into where it was predicting. But the thing about it was it was explaining as the start of this article that you can take a monkey and put him into Manhattan.

and the biological brain power of a monkey says he will know that a building exists, but he doesn't have the biological brain capacity to know that a human being built it. So your biology is a limiting factor here. When you get into AI and coming very soon, the predictions are within the next five years, I think it's gonna be sooner than that, two or three, we're gonna have artificial super intelligence. And at that point, our biology, our brain just cannot compute.

what will happen after that point is very much an inflection point for society. That there will be this artificial intelligence and it doesn't matter who you are, you do not know what happens beyond that point because our brain, our biology just won't allow us to understand it. I think that's fascinating. And yeah, it could be Skynet. I don't think it will be. I'm optimistic. I'm keen. I'm looking forward to it.

Sean Patton (10:11)
Yeah, it's interesting. Almost like, yeah, it's in like a computing event horizon, right? That we're like approaching. Yeah, that is.

Jim (10:20)
But I mean,

imagine this super intelligent has access to all the data in the world, because it probably will have, whether we give it to it or not, it will just hack through every system that we've got and give itself access to everything. And it starts relating unknown study of 300 people in Thailand with a study of cancer in America with another study in Brazil. And it starts to pull all those pieces together.

No human being can do that today, even with the data analysis stuff that we do at the moment, it just can't. But suddenly you've got a fundamental shift in how you approach disease, how you approach climate change, how you approach any technology advance, how we get to Mars and beyond. Is space rockets the way to go or do we want to teleport there in some futuristic, we just don't know. And that super intelligence is that inflection point that you mentioned, it's an event horizon.

I'm keen to get beyond that. I genuinely am. And if it means that a computer's gonna kill me, then do you know what, that's fine. I can live with that. It's a not bad way to go.

Sean Patton (11:31)
I was like, it's inevitable. It's going to happen anyway. But you know, that's interesting. ⁓ you know, one concept that, ⁓ I'm fascinated by, and also I kind of love the fact that I, and we will get to, I have like a prep document for our pre-conversation and we're nowhere near it right now, but that's cool too. That's cool too. I like, I like this, ⁓ hope for the hope for the audience does too. But, ⁓ the concept, the concept of, ⁓ determinism versus free will. And there is a,

Jim (11:33)
Yeah.

Yeah, I one of those.

Yeah, let's go.

Sean Patton (12:00)
there's an old thing called, I forget the philosophy that came up with it, but Laplace's Demon. Are you familiar with that at all? So it was these philosophical arguments over whether there's free will or whether there's determinism. And there was this idea that Laplace, who I think was a French, I'm guessing, basically came up with the concept that it's just, don't have all the information that like everything has cause and effect, right? So it's just,

Jim (12:07)
I'm not, no.

Sean Patton (12:29)
The idea that if you had super intelligence, if you had every data point that could happen, you could then accurately predict the future. And if you could do that, that basically would mean that free will doesn't exist. That we're all just reacting to our environment in a predictable manner. And they call it Laplace's demon. And so it's just, it rings to me there of, ⁓ if we have super intelligence that can.

maybe get up to or at the point of basically having every data point of the whole universe or anything, something close to that.

How accurately will it be able to predict the future? And then how does that interact with, can human will break that? Because if it can't, we sort of maybe solve this determinism versus free will debate.

Jim (13:26)
I love that, it's a really bizarre example, but the only one that popped into my head was, even if a super intelligence has access to all the data in all the world, I remember, do remember when the Challenger blew up in 1986, I think it was, that was caused by a freeze overnight that took one O-ring on a booster, froze it so that when it heated up again, the metal itself had been jeopardized.

So when they put the heat into it, it expanded and it blew up. I wonder whether superintelligence will have that level of detailed knowledge to know that O-ring was made with this material and it can only go down this far in temperature before it. That seems a level of randomness that I think even superintelligence would struggle with, at least in my lifetime. yeah, hopefully there's still a bit of...

Let's hope not spaceships blowing up. I hope there's still a bit of randomness in life that makes life exciting.

Sean Patton (14:26)
Yeah. And does it have access to it? It almost reminds me of, ⁓ like quantum quantum physics and the fact that like how you react, how something, how you interact with something changes its fundamental state. like it may know all the information right now and be able to predict the next thing. But if something in a human being's head knows it knows the next thing can then we gen change the variables in our own head. And it doesn't know that in time.

Jim (14:56)
What? Yeah.

Sean Patton (14:56)
So then that

proves free will, right? So it'd be just be interesting one way or the other, know, because already you see, I see things with like the accuracy of certain sports betting, it'd be an example, right? How that's changed now with all the analytics and AI we have and versus before you'd be like, don't know, horse looks fast to me, Bob, you know, but now it's they've got all the data and they run it through these algorithms and.

Jim (15:04)
completely.

Yeah exactly.

Sean Patton (15:25)
they're able to, you know, predict with so much more accuracy, ⁓ outcomes, but you know, is there, is there, what's the, what's the word I'm looking for? like, what's the, what was the limit? Yeah. What's the limit on that? Like how, how, how close can we get to that? And when, when do we hit, ⁓ or do we hit a edge of can human beings break it with, with.

Jim (15:29)
completely.

limo.

Yeah.

Sean Patton (15:53)
with just our own ideas and thoughts.

Jim (15:56)
I'm going to say we can break it. I'm going to go down that route because I don't know what I'm having for lunch. So if a super intelligence knows what I'm having for lunch, then that's great. But the whole data, the sports betting thing, I remember watching Moneyball back in the day. And that was what got me hugely into it. It didn't get me into it, but it got me to understand the true value of data and analyzing data and understanding it.

And that's huge. For me, going forward, superintelligence or any AI, we've got two big challenges that will slow us down. One is chip manufacturing, of the number of chips that we need. Another one is power. I think we're going to have a severe problem with power to make all this happen. And even if we choose today that we're going to run all of our AI on nuclear power or something like that, a nuclear power station is 20 years to build.

So it's how do we get enough power into this thing in the next few years to actually make it sustainable. So it's not without challenges, but, man, I just get so excited by this stuff. I really do. It seems to be a game changer for everything.

Sean Patton (17:03)
Well, it's interesting. You mentioned to segue here, the data and having all this data to make decisions. And, you know, one conversation that, that we had before that I love to get into is how do companies and companies you work use data and find the right data to make decisions. So when you look at a company and your, experience, whether it's through MNA or through some sort of change management, how do you start to determine what data you need to make decisions?

Jim (17:33)
I think the problem with any kind of data is the fact that you don't know what's useful until you need to use it. So it's like everything else. You start at the outcome you're trying to achieve. And as you go through that outcome you're trying to achieve, you start to identify the data that you need to get there. So I think the philosophy of if you have a piece of data, keep it, store it, label it, reference it.

you probably will need it at some point in the future. And I think it would have moved away from, well not moved away from, but the focus has definitely moved away from traditional machine learning algorithms, which were fantastic even two years ago. And it was all over the raise two years ago of having a machine learning algorithm that could do your customer recommendation and predictability of your supply chain, things like that, into large language models.

I have no idea how a large language model works, but I know it takes every piece of data it can possibly find to analyze it. So we've shifted from being selective in what we need as data into just store everything and let the large language model understand it, interpret it, use it, and then you get something fundamentally different out of it. So I don't think you can identify what data is useful at this point. I think you keep everything you have.

which then takes us onto a whole new different world of blockchain and decentralization and things like that. at the moment for corporates, if you have a piece of data, then hang on to it. It will become useful. The one thing I would say, and this is a big thing that I have in my head, I've actually just written an article about it yesterday, it's still to be published. I think where corporates and companies generally are getting it wrong is they're viewing their data as a piece of data.

what you need to view is an accurate piece of data. You need to have some integrity around about it. You need to know where it came from, what it means, what that actual piece of data means so that you can use it properly in the future. I've gone into so many companies in the past whereby they've got all access to all this data, but they can't do anything with it. I remember one company I worked with.

they wanted to create a recommendation engine that every day when the customer came back onto their website and e-commerce website, they would get a list of recommendations. It's not an unreasonable request, it's not an unreasonable function to have, but to move the data to allow the recommendation to work to them 20 hours. Well, you can't do that if you want a 24-hour answer. And it wasn't, I mean, it was a really cool company, it was doing really well.

But just that lack of foresight on the data, how you're storing it, where it's stored, how you're moving it, and being that their infrastructure was completely incapable of allowing them to run a 24-hour process to recommend a new product to a client because the data took 28 hours to move. And it's like, OK, well, we can make it every two days. They'll get a different recommendation. Now you're impacting on your customer engagement, your customer satisfaction, your profitability, your revenue, because if

if it's the same thing, I'm getting recommended twice, I might not come back until next week. So all of these things impact on it. So how you store your data, where you're storing your data and making sure that it's available is key until, in fact, it's not until it's now. So that as you start moving into more and more AI, more and more usage of your data, you can actually use it. The other thing that I included in the article was actually sovereign cloud. And I like the word sovereign even though it's...

talks about nation-state as opposed to enterprise cloud. I like sovereign cloud because it has an extra level of security in it. So I like the idea of a sovereign cloud for a company, an enterprise, because you can get access to all of the publicly available data, but your data, your competitive advantage is within your own sovereign cloud. No one else can access it, but your AI can. If you have DeepSeeker, Lama, or any one of the open-source models that you can use,

You can run that against the public data that you have, but you can also run it against your own corporate competitive advantage data. But you can only do that if you've got your data in the right place, it's in a secure environment, you know how you're doing it and you're setting yourself up today. Because in fact, you should have set yourself up a year ago when everyone started talking about it, but hey, we're here today. So you need to set that up today so that you can access it next year.

Sean Patton (22:05)
So then it becomes all this data, all the large language learning models. how do we use that? How do we turn all that data information into clearly articulating to one of our employees? Here's what we need you to work on, right? Here's your objectives. Here's your key results. Like here's where I want you to do.

in translating that and communicating that so someone can effectively use it to drive them forward. So how does, how do we, how do we move from recommendations and, ⁓ what this with AI and what are, what is the data saying and compute that into someone and say, here's what we need done this quarter. Here's the actionable, ⁓ direction we need you to head as an individual employee.

Jim (23:01)
Yeah, now you're talking about the secret sauce of every business's success. And I think this is fundamental to any success. I think there's two things that make companies, and there's lots of things that make companies successful, but two key things in this context. One is the ability to say no, and the other one is to focus on what you're actually doing and where you're going. And they're both related. If you say yes to everything, you're not focusing on anything.

So it's what are you focusing on where you're going next? I personally love it, assuming that you know where you're going, assuming that you've got a strategy, you know what you're trying to achieve. And that isn't always the case, but hopefully you do. How you go about implementing that? I love the OKR framework, although so many companies get the OKR framework wrong. They use the OKR.

Sean Patton (23:49)
But you want to explain,

pretend like you're taught, you're explaining this to someone who's never heard the term OKR before. What is an OKR?

Jim (23:56)
Okay,

okay, so OKRs were created as part of a book. The book was Measure What Matters by John Doar. So it's probably 10 or 15 years old now, maybe a bit longer than that. And essentially, what it says is, there you go. The man's got the book. And essentially what it says is, it's way of figuring out what it is your objective is, but then make your objective measurable.

Sean Patton (24:13)
It's on the bookshelf, buddy.

Jim (24:24)
And the thing that, or the subtleties that people occasionally get wrong, are OKRs are targets. It's something that you're going for. Your metrics, your KPIs, they're lagging metrics. They're what you've done. They're what you achieved. So OKRs are future thinking. KPIs are actuals, if you like. OKRs forecast, KPIs actual results. But the OKR framework allows you to actually

go in and say, is my objective. This is how I will know when I've achieved it. So if your OKR is expanding to Europe, say, then your key result could be half, 30 % of my revenue in Europe in two years. Suddenly it's more measurable. Two years later, is 30 % of your revenue coming from Europe? You can tell that you've met your objective. And the beauty of that is,

your objective or your key result, 30 % of my revenue comes from Europe, it's no question. It's not subjective. You can tell it's binary. We did it, we didn't do it. And it's not to say that 28 % of your revenue coming from Europe is a bad result, but the KR, the key result, is very, very binary in that regard. So everyone knows what they're doing. Everyone can align to it. Everyone can understand it. And because of that, it's a really cool thing.

Far too many people use it though as a way of trying to drive a target that isn't aligned to the objective, isn't aligned to the company's overall strategy. And there's a disconnect as you go down the organization structure from what the company's trying to do to what Bob in accounting or Janet in customer service is actually delivering for you. And the OKR framework aligns all of that. So it's very clear to see me working in my department within this big corporation or any company for that matter.

I can see how what I'm doing today helps the company achieve its objectives for the next two years, three years, five years, whatever that period is. I like to do these on annual basis, just because it's a nice time. I like to have quarterly targets, because I think that's something that's good enough. And if you aren't getting where you want to get to within a quarter,

you've got three other quarters to pivot to change to move what you're trying to achieve to still get to where you wanted in that annual basis. And on the same basis, I like to review everyone on a two weekly basis so that in one quarter, I have six opportunities to pivot what individuals are doing to achieve that quarter's objectives. And on a company-wide basis, I've got four chances to pivot to achieve that annual result if I need to change that annual objective.

So the whole thing is a cascading process. The one that most people get wrong though is they start to align people's bonuses to success. And I'm not for one second saying do not align bonuses to success and outcome and achievements, but your OKR is meant to be a challenge. If you're achieving 100 % of your OKR, you're putting limits on your people. So the name of the podcast has no limits. So OKRs for me are designed

that you should be achieving 70 % of your OKRs on a regular basis. But that extra 30 % is where the no limit comes from. How can you give your employees, your teams, the freedom to go away and go above and beyond? How do they know what above and beyond looks like? Because the OKR is telling them they've got to expand into Europe and 30%. They don't get to 30 % in Europe and just stop and say, oh, we've achieved it.

get them to get to 35%. If they can, why not? Keep them going. So OKRs for me are very often used as a replacement for KPIs with a, let's look at where we're going next. And it limits people because their bonus is 100 % of the objective they're trying to achieve. Whereas they are much more effective if what you can do is actually plan for 70 % success.

Make it an environment, a culture, that 70 % of success in your key results is actually okay. That's not a failure, you're doing well. But if you can get to 75, 80, 100, then that's amazing. And by designing your OKRs, that way you're taking away the limits in your organization. And who doesn't like that? As an owner of a business, as the CEO of a business, having teams that are all out there, driving you towards your objectives.

Sean Patton (28:56)
Mm.

Hmm. Yeah.

Jim (29:12)
know what good looks like, know that 70 % is enough because that's how you've designed them, but they're all capable and hopefully on occasion achieve more than that 70%. That is a fundamental shift in your business progress and your acceleration and your growth.

Sean Patton (29:30)
It reminds me of this concept called the Pygmalion effect, where is basically a psychological principle that whatever standard expectations you set for people, which is just an important concept for leadership, whatever expectations, more often than not, people will achieve that, but they almost never, very rarely go above and beyond, right? If you set someone say, here's your commission rate.

A lot of people are going to hit that commission, like once they hit that, unless there's again, some sort of, uh, incentive beyond it, no one's like, you know, I'm going to go ex I'm going to work extra hard, you know, once I've hit whatever standard you set, um, and, they prove this with like teachers in classrooms where, know, if you set, if you set the standard at whatever low for the same, for students, they'll generally hit that, but not going above it. You could take the same students set a higher standard and a vast majority of them hits this higher standard. Um,

again, creating this sort of upper limit problem. I love, I love how you're sort of applying that with this 70 % rule when it comes to OKRs to give them and to have them stretch and facilitate them pushing beyond. But not, you know, causing what we're seeing with burnout and things like that where you're seeing these unrealistic expectations or sales commissions that only 50 % of the people hit or something like that.

Jim (30:49)
Yeah.

Completely, and sales commissions are a really good example of it. The one that always got me was when you were looking at sales commissions, it was, want your sales target to be half a million dollars a year. at half a million dollars, I'll give you X percent of them as a commission. And that's great. But if you've got above half a million, then your commission is reduced. And if you've got above a million, it's reduced. And if you go above two million, because the number that your commission is in hard terms is higher.

So I don't want to be paying you a 400 grand a year salary because you had 2 million sales this year. That's too much to pay anyone. Why would I pay that? So you'll get a commission and then the commission goes lower and lower to reduce the amount of money I pay you every year in real terms. And it should be the opposite. If you're capable, either I've set the target wrong, which is very common, or it should be the opposite. If you go above your target, I should be paying you more.

because it gets more money coming into the business, I can do it cheaper, the economies of sale increase, and you're achieving. So why am I limiting you and what you're doing to make me more successful? I've never quite understood that. And it is a slightly different mindset, but taking away that limit from people. In the right way, I mean, you don't want to have it completely open. There needs to be some guard raising about all of these things. But why would I limit you being successful that then limits me being successful?

That does not make sense to me.

Sean Patton (32:22)
Yeah. Or limit the, uh, or discourage, you know, uh, excellence, right? Discourage a going above and beyond. And, and you point the economies of scale. I just had this conversation in one of my other businesses. Um, I, uh, I own, uh, I don't know we talked about this before, but I co-own some Brazilian Jiu-Jitsu martial arts gyms. And we're talking about, uh, compensation for one of our general managers based on, uh, bonuses and profitability of that individual location.

Jim (32:28)
Yeah.

Sean Patton (32:51)
And we had my business partner had the same conversation, like, you know, up to X number 10%, this number, that number we're at 15. And then, you know, anything above that is going to be 20%. So we're elevating as they go up because it becomes, you know, a win-win. And you see that all the time with sales. My wife is in sales, right? And you'll see it when you structure the comp plan, way you, you see it or the way you mentioned, ⁓ where it decreases. What do we see all the time? Right?

They're not making the final sale call. They're holding over till next month. They're resetting the comps. They're doing it again. So you're missing out on potential sales now because your sales who are going to react to the incentive system that you have set up for them.

Jim (33:21)
Yeah. Yeah.

Completely, completely. And it's one of those things that is counterintuitive, but so many people do it, so many companies do it. It's like, I can't have a salesman who's paid more than I am. Well hang on, if a salesman's bringing in all the sales, then he's earning it, he's doing it, he's entitled to get paid substantially for what he's doing, and the company's getting better, and everyone's growing, so what's the relationship between what he's getting paid and what you're getting paid?

It kind of is none. Your compensation is probably an equity that you'll get in five years time and it'll be substantially better because the salesman's been successful. It is, yes.

Sean Patton (34:07)
Yeah, I think on a salary

and commission basis.

Jim (34:10)
you

Sean Patton (34:11)
know, salespeople should be some of the, you know, depending on the model, right? I mean, not every business model is the same, but in a lot of models, it should be the most. know, ⁓ I had this really cool opportunity when I was still in the military actually, it was my last year and I was in like the only staff job I ever had. I, got, I got to command like frontline soldiers for eight, nine years. And then the last year they put me in a staff job for one year and I got out. That's kind of what I did. But, ⁓ in that job, I had a really cool opportunity where I got to lead. was me and.

Jim (34:16)
Hmm.

Sean Patton (34:40)
small team of Green Berets. We actually got to go to General Electric Appliances in Louisville, Kentucky, and basically did a two week consultancy. They called it a joint business exchange training. And they basically just had a bunch of Green Berets go in and look at their systems and solve problems. And it was usually in the manufacturer, in the plants, right? And I was one of the first ones, I got to go with the sales and marketing team. And, you know, they had this

conversation about how these, you know, PhD engineers would get upset because, know, the sales person with no college degree was making, you know, 250 K and they're making 150 and they were all upset and they're like, well, all well you want to go, you want to fly to Chicago today and make a sale call? And they're like, no, like that's, that's why you don't get paid because they're, got to go, you know, we know how sales is you're going to get, not many, not very many people want to go and get told to know or some explicit and then know afterwards.

Jim (35:25)
Yeah.

Yeah.

Sean Patton (35:38)
every day at their job. And so that's why they get comp that way.

Jim (35:40)
Yeah, it's a tough job. Yeah,

it's a tough job. You need resilience for it. But I mean, you've highlighted there, I very often don't talk about individuals and companies. I like to talk about teams, because a salesperson is irrelevant if you've got nothing to sell. PhD that's got some chemical scientific background is irrelevant if he's built the best thing in the world and no one's out there selling it. It's not about individuals, it's about teams.

And so you're example of special forces. I love special forces because generally they're given an objective. They're not told how to get there. They're not told you've got to kind of do this, this and this. This is the objective. So back to the OKR conversation. We'll know you're successful because there's a very clear key result. We want a Samah bin Laden in a box or brought back to the US, whatever that is. It's very clear. There is no ambiguity in that. And then you allow the team with different skill sets.

some commonality but predominantly different skill sets to go away and actually achieve the objective for you. And that is through every successful high performance team, whether it was skunks works back in the day, whether it's a special forces team with a specific objective or whether it's just some of the best run companies in the world. That is how they do it. That is the secret sauce. Trust in your team, create teams that are phenomenal, create teams that are...

They've got self-healing, because every team will have a challenge, let them fix their own problems, give them the autonomy and the skills and the resources and the environment to be successful in, and then just watch them be successful. And that's a beautiful thing, watching a team be successful.

Sean Patton (37:20)
I agree for leaders that want to set up their teams like that, what are the keys for them to be successful in creating that type of culture?

Jim (37:33)
wow, the culture itself is huge. I've kind of gone into companies and done transformations and it's called everything. We've been digital transformation, we've been this transformation, the realities, they're all cultural. Every transformation is a cultural one. The culture though is very much one where curiosity is key, transparency is key, ownership is key. I very often talk about healthy tension.

where you and I can have a genuine disagreement. But because we know that we're both trying to get to the same objective, we will come to a compromise whereby you're kind of happy, I'm kind of happy, but we know it's the best thing you do to get us to that objective. And so that little healthy tension of having that in there. The culture, though, is very much top down. You don't berate people for failure. Failure is a learning opportunity.

I didn't actually prepare a full list, so making this up off the top of my head. One of the best cultures I had was the Guardian newspaper because it was created by a lady called Tanya Cordray and she was just fantastic. But it was very much one of those, we're going to make mistakes, that's fine, but we all know what we're trying to get to. We're all going to learn. Don't be embarrassed about your mistake. Share your mistakes so other people can learn from it, not just you.

We had a very clear set of objectives that we're all trying to get to. We had clarity in how we were kind of going to get there as teams. Teams, the other one actually that plays into this is you've seen the rag status for team performance, so red, amber, traffic lights. Where if you're reporting, and I kind of like the subtlety, if you're reporting everything's green, if you've got a problem, it becomes amber.

Sean Patton (39:13)
Great.

Jim (39:24)
And if you've got a real challenge, everything's gone wrong, you're And in most organizations, red means failure. We change that. Red does not mean failure. Red means that within the confines of your team, you can no longer influence things sufficiently to be successful. So it's not a failure. It's a failure within the constraints I have. But if someone in the leadership team comes along and says, man, what you need is two extra people.

Yeah, that's cool, we'll put two extra people in your team. You're all good, let's go away and be successful again. And it took away that kind of reluctance to raise anything as a red flag because it was no longer a failure, it was a request for help. So those subtleties in your culture are what makes high performance teams. It gives them the environment to be high performance because you're no longer scared of that failure, no longer scared of the implications of failure and the impact of failure on you. So you can go away and actually do things.

openness, sharing. I've screwed this thing up, me a compa, but here's what I did, here's what I did wrong. Actually, another example to The Guardian. I remember sitting in a hotel in New York, we'd just launched The Guardian in America back in the day, and the whole world blew up for us. Something had happened, the website had gone down, it was just terrible.

And the guys in London were fantastic. One guy particularly, a guy called Grant, he was amazing. He kind of went through the whole thing, came back to us and said, man, you'll never believe what we did. Essentially in simplistic terms, we did a denial of service attack on ourselves, internal to the network. it's like, man, how could you do that? And it was done as a, okay, well we'll learn, let's not do that again next time. And to be honest, it wasn't Grant who did the problem, he was the one that found the problem. But it was kind of like,

disaster for the website for five hours or something like that. But it was a learning experience and if you can't create an environment where people are free to learn, free to make mistakes, free to be open about those mistakes, you're just going to keep doing the same stuff. You're process driven and if the process isn't working for you, if the process isn't allowing you to grow, if the process isn't allowing your teams to grow, you're going to stay in the status quo forever.

So you've got to break out of that and allow teams to grow, fail, learn, move forward, try something that doesn't work.

Sean Patton (41:54)
How do leaders, how do we know if we've created a culture of psychological safety so that people on our team feel safe to openly share failures, to openly share when they have a question or they think something's wrong or to question even our decisions. Like, how do we know that

We're creating space for that as leaders.

Jim (42:27)
I think the only way to know that is the results. So again going back to OKRs, it's the key results. Are people actively coming up and saying to you, I don't understand why you made that decision? Are people coming up and saying, do know you could do that differently if we did this? And that's a difficult thing for a leader to accept, and especially in corporate world because generally the corporate world is driven by the Peter principle. We're all promoted to a level of our own incompetence.

Therefore, it gives us a level of self kind of confidence that isn't always always warranted. So being open, asking for people's advice creates that willingness for them to give you what they think. And then taking that the next step is they're coming in and offering advice. I think the challenge with this is and it's a subtle learning experience and we've all done it, we've all got it wrong, we've all kind of closed conversations down too soon or allowed them to go too long.

I don't think you can have that collaboration forever. In one topic, you've got to kind of say, I've heard you, I know what you're saying, but this is where we're going. And I think the true mark of a leader is if that person you've just said, but this is what we're doing, if they go, got your boss, hear you, I'm off. I'm a weird, I don't understand why we're doing that. I don't agree with it. We're often doing it anyway because you've listened to me. I've been heard.

There's obviously something happening that I'm unaware of and you can't tell me today. Hopefully you'll tell me tomorrow or next week, but I believe in you. So we're off and running. And I think that's probably the single biggest thing for me when you can tell you've got a really good culture. People willing to challenge you, but when the decision's made, they go away and do it anyway.

Sean Patton (44:17)
I love that. You know, it really takes me back to my military days. used to say, that's the job of the commander is to decide when the, when the good idea fairy time is over and, uh, you know, all right. And then, and then make the decision and, that's the way it is on a, in a well-run, you know, elite military organization as well. Right. Everyone says, okay, cool. And this is now the plan and they run with it and just like it's their own. Um,

And I had, you know, kind of two thoughts here then I want to, I want to wrap, but one is I have this opinion that as leaders, there's two sort of roles that we can never delegate and we just covered both of them. So I think it's so cool. It's decision-making the end of the day, the leader, that's your responsibility to make the decision. can't pass the buck to somebody else and to creating culture. Like that's a leader's job to create culture to your point that has to be top down. So I'm loved you brought up those two points.

And the third thing that just made me think of what you just mentioned, this is something I may have to explore in the future more is, you know, when we're doing mission planning on a, on a special forces team, we always have someone play we call red team. And I don't know if you've seen this, have you seen that in business planning or, or in corporate or board environments? Cause I wonder if that would be a really interesting way to help you want to talk about help assuring psychological safety, you know,

Jim (45:34)
Yeah.

Sean Patton (45:46)
pick a really talented, pick your CFO and be like, all right, your job is to play devil's advocate. How are you gonna break our plan? How are we wrong? And assign someone the responsibility to be the contrarian and challenge to help establish that culture. know. I just had that idea that, cause that's a really key part of how we do our mission planning. Have you seen that? Have you seen that played out in the corporate environment at all?

Jim (46:08)
not

I've not, the only time I've seen that played out was actually in the TV show newsroom, I think it was, where they were trying to launch a big kind of news article and before they did it, they wanted to make sure they were buttoned up. I've never seen it done in corporate world, but there's two things in there. One is, how often have you seen organizations fail because the business leader is unwilling to make a decision and by default, he's forcing someone lower down

the organisation structure who doesn't have all the information, who has to do something today because he can't not do something, it's happening, I need an answer now, that person has to make a decision without all the information because a business leader procrastinated or something else. so, yeah, but taking on your red team, I've never seen that done in an organisation, although I would love that it is done more often, especially at a strategic level. Do some scenario planning and then stress test the scenarios.

as opposed to just getting a team of five people in a room and them coming out and saying, this is what we're doing for the next five years. Which is all too common. But I do have this other thing, and man, I've said it like so often in the last couple of weeks and I've not got it right yet. You're aware of Sherlock Holmes, the fictional character, very popular. He has a saying that whenever you eliminate everything that is impossible,

Sean Patton (47:25)
Yes.

Jim (47:34)
no matter what you're left with, no matter how improbable must be the truth. I've converted that to being business speak. Whenever you eliminate anything that is gonna be a blocker to your success, whatever remains must be your path to success. So if you focus on the negative in your business, take away everything that's gonna kill you, everything that's gonna block you, everything that's gonna take away your successful. By definition, what you're left with is the path to success.

So I very often talk about not creating strategies. You uncover a strategy. You remove everything that isn't getting you towards your objective. And it's like, that's not gonna get me there. Or it's not gonna get me there quick enough, it's not gonna get me there. It's 10 billion and I don't have 10 billion to make this work. So that's not the answer that I'm looking for. This isn't the answer I'm looking for. That's not it. So the only thing I have left is with the constraints I have with what we're objective is this is our path to get there in the most effective, cost effective.

speedy time, whatever it is, by removing all the blockers to your success gets you to success.

Sean Patton (48:39)
Oh, that's awesome. And Jim, this was great. I feel like we could do this for hours, man. I really appreciate the conversation. Really enlightening. And we did take a few side quests, but I think they were entertaining, at least for me. So that's what matters, I guess.

Jim (48:44)
Yeah.

I enjoyed them as

well. hope the audience did too, but hey, I enjoyed them, so that's cool.

Sean Patton (48:57)
that's awesome, Jim. If people are trying to find you, where do they go?

Jim (49:01)
LinkedIn is probably the best answer, so Jim Stevenson, LinkedIn.com or Bletchleygroup.com

Sean Patton (49:10)
Awesome. And we will definitely put those links in the show notes so people can find you. Thank you so much for your time, man. It was great talking with you.

Jim (49:17)
Absolutely loved it. Thanks, John.