"How Earlobes Can Signify Leadership Potential." It's phrenology of management, so it's really important for executives to have the right size earlobes. So I'm going to talk about strategy from my own personal perspective when I was CEO of a software company called Fotango. We'd been bought out by Canon. We built a number of different services, online photo services, several million users, et cetera. And we were doing fine, revenue all good, and we were profitable. But we had a problem and the problem was me. Because rather than being a chessmaster of strategy like CEO, I was making it up as I went along. I was a fake CEO. It was all– well, I had all those things like vision statements. "Our strategy is customer focused. We will lead an innovative effort of the market through our use of agile techniques and open source." And that sounded good, except for I'd pinched it from someone else because I really had no clue what I was doing. But what I did do is I used to go around listening to other CEOs talk about strategy and I started to record the words they said, looking for what I call Business Level Abstractions of a Healthy Strategy, or BLAHS, for short.
And I do this every couple of years and this is my recent set of common BLAHS that people talk about. Things like digital business, big data, disruptive, innovative, collaborative, competitive, advantage, ecosystem, open source, et cetera, et cetera. And then, what I normally do is get all these strategy documents, pile them together, and generate a Blah template. "Our strategy is Blah. We will lead a Blah effort of the market through use of Blah and Blah to build a Blah." And then I combine the Blahs and the Blah template and also generate a whole bunch of different strategies at random. So I thought I'd go through some. Strategy number one, total random gibberish. "Our strategy is customer focused. We will lead a disruptive effort of the market through our use of innovative social media and big data to build a collaborative cloud based ecosystem." Strategy two, again, total gibberish. "Our strategy is innovative digital business. We will lead a growth effort of the market through our use of customer focused competitive advantage." You get the thing.
And then I send them around to people and I normally get responses of three basic types. "This is more or less the exact wording from our business plan." "I've seen two of these used already." And my favorite is, "Are you for hire?" By the way, a friend of mine has put this all online. This is strategy as a service. So if you ever need a strategy, just type in the URL. This is the one I did earlier. Well, I did it yesterday. You just type In the URL. If you don't like it, just press refresh. "Our strategy is collaborative. We will lead an open effort of the market through our use of big data and social media." Anyway, so there I was in 2005, CEO of this company, not knowing a clue of what I was doing. I was like, oh, oh, dear. What shall I do? So I went back to basics. Sun Tzu. Anybody know what Sun Tzu wrote? "Art of War," fantastic. Sun Tzu talked about five factors that mattered in competition. One, understand your purpose, your moral imperative.
Two, understand the landscape that you're competing in. Three, the climactic patterns that impact that landscape. Four, your doctrine, and then you're into leadership, which is context-specific gameplay. Then I came across John Boyd. Anybody know what John Boyd wrote? AUDIENCE: OODA. SIMON WARDLEY: OODA. OODA loops. A US Air Force pilot. John talked about, you have the game. The first thing you do is observe the environment, so that's the landscape and the climatic patterns. You orientate around the game. And then you decide what you're going to do. That's the context-specific play. And then you act. Now often, people will say, well strategy's all about the importance of why. Well, that's fair enough, but there are two whys. There's the why of purpose, as in, I want to be the best online photo service. And the why of movement, as in, why do I make this move over that move? So if you think about a game of chess, you've got the why of purpose, which is to win the game, and then you've got why of movement.
Should I move that piece or should I move that piece? And it's through movement that we do learning. So we move that piece, it gives us a tiny bit of advantage, not much of a great deal. But if we move that piece, checkmate, you see? So much better. So if I go back to Fotango, I had my purpose, online photo service. Here we are, 2005, very profitable. The next bit is, how do I understand the landscape? How do I observe the environment? This led me into a topic known as situational awareness. And to explain this, I'm going to use three examples. Vikings, chess, and Themistocles. Vikings, a very fearsome race. The way Vikings did navigation is they used stories. Things like, "From Hernam, head due west towards Hvarf, and you will have sailed north of Hjaltland, so that you just glimpse it in clear weather." That, actually, is just that. A much simpler translation. But the question I have to you is, what would you use to navigate? A visual map or a verbal story? What do you think?
Map? Story? AUDIENCE: Story. SIMON WARDLEY: Story. Map. A map. OK. What do we use in business? AUDIENCE: Stories. SIMON WARDLEY: Stories. Super. Right. Excellent. The next example is chess world. I want you to imagine you live in a world where everybody plays chess, but no one's ever seen the board. All you've ever seen are these characters on a screen. And you play the game very simply. You press a button, your opponent counters, you press a button, they counter. And the game goes on for ages until somebody wins or it's a draw. Now, what will happen is people will take these sequences of many games and feed them into their, I don't know, big data systems and come up with magic secrets of success. So if you press queen, I should respond with king, pawn, or whatever. And we'll write articles about that, a bit like earlobes. Then what will happen is you will play a game of chess against somebody who will see something truly magical, the board, but you won't know this.
And so you'll press a piece and they'll counter. And you'll press a piece and they'll counter and you'll have lost. And your first– you'll be there, what the fiddlesticks happened there? All right. The first thing you're going to do is scribble down that sequence as though it's some sort of magic sequence which you're going to try and use yourself. And you'll still lose. And then you'll start thinking, well, maybe it's the speed at which they pressed the button. Then you'll start going, is it cultural? They're a happy sort of person. Maybe that's why they beat me. They beat you because you exist in a low level situational awareness environment. So what would you use to learn, by the way? Secrets of success? Or context specific game play? What do you think? [INAUDIBLE] SIMON WARDLEY: Excellent. What do you think we use in business? AUDIENCE: Secrets of success. SIMON WARDLEY: Secrets of success. Excellent. Super. Right. The next example is Themistocles, ancient politician, Greek general.
Had a problem. The Persians were invading. Had choices. Defend around Athens, defend around Thebes. What he decided to do was to block off the Straits of Artemisium, force the Persians along the coastal road into Thermopylae, narrow pass, small number of troops defend against a larger force. So about 170,000 Persians, 4,000 Greeks, including 300 Spartans. Fabulous. So I want you to imagine you're a member of the Athenian army, so part of the Greek states. It's the eve of battle. Themistocles is in front of you. He's giving you purpose, a moral imperative. We must defeat the Persians. And then he says to you, I don't understand the landscape. I don't understand the environment. I have no map. But have no fear, for I have created a SWOP diagram. [LAUGHTER] Strengths. A well trained Spartan army, a high level of motivation not to become a Persian slave. Weaknesses. The Ephors might stop the Spartans turning up. Sorry, a truckload of Persians are turning up. Opportunities.
Get rid of the Persians, get rid of the Spartans. We're Athenian, we actually hate the Spartans. Threats. The Persians get rid of us and the Oracle says a really dodgy film might be produced a few thousand years later. OK. So what would you use to communicate and determine strategy in battle? Position and movement described by a map or some sort of magic framework? What would you use in business? [LAUGHTER] SIMON WARDLEY: Excellent. [? CPAV, ?] right. You're getting the point. So here I've got chess, here I've got alchemy. Navigation, learning, and strategy. In chess, it's all visual, contextspecific. It's all about position and movement. It's what we call a high level situational awareness environment, a bit like the military. If you ask a general, why did you bomb the hill? They won't say, because I read an article in "General Weekly" that 67% of generals bombard hills. They won't tell you, because it would make a good story. Or that's what Uber would do.
But over here, this is alchemy. This is all about storytelling, secrets of success, magic frameworks. It's all low level situational awareness environment. And so that's where I was as the fake CEO, desperately hoping that no one would rumble that I didn't know what on earth I was talking about. Anyway, I explained this to a couple of my peers and they said, oh, don't worry, it's all about execution. Well that's interesting because that's one of those memes, "I'd rather have a first-rate execution and second-rate strategy." I tend to like data, though. So I went around looking– I to 160 Silicon Valley companies, looked at their level of strategic play, situational awareness from low to high, and the use of open– as in open source, open data, open APIs– as ways of manipulating the market. The bigger the bubbles, the more companies in that group. Now, if execution ruled, these would be doing well. If strategy ruled, those would be doing well. And that's what it actually looks like.
Market cap changes over a seven-year period, positive, more negative. It turns out both are important. Strategy actually matters. So Dimon's doctrine, as Professor Martin said, is about "as flawed as it is popular," which is a bit of a shame. So I would explain that to people and they would go, but we're successful, getting– it was my fat cat getting a little bit angry here. Which is fair enough, if you're fighting against others. It's OK to be hopeless at this stuff as long as everybody else is because then no one gains an advantage. And there's this wonderful study by Fitza, "Use of Variance Decomposition in the Investigation of CEO Effects," which basically says those are no different from random chance. So you can just get someone off the street. At which point, people get really angry at me. We're not stupid! Well, that's fair enough. But there is a difference. You don't have to be daft to be blind. So the Vikings themselves, they didn't see the environment.
They had stories, it was their way of communication. They didn't use maps at all. Doesn't mean they were daft. And the difference turns out to be maps. But what do we mean by maps? Well, maps have certain characteristics that are really important. They are visual, context-specific, battle at hand. You have the position of pieces relative to some anchor. In this case, a compass. And you can see consistent movement and, obviously, you have components. It's the same with the chessboard. Visual, context-specific. You have position of pieces relative to an anchor, the anchor being the board itself, and you have movement. And that's what a map has. So what did I have in business? Well, I had systems diagrams, network topologies, which are not maps. They don't have those navigation characteristics. Or I had things like this. Business process maps, which turn out not to be maps either. In fact, I had loads of diagrams which call themselves maps and didn't have any of the characteristics of a map.
So that was my problem, 2005. How do I create a map? So I took one of my network topology diagrams. I said, right, I need an anchor. We're going to have to start somewhere. So I took the customer and the user need. That was my anchor at the very top. Great. Now we need position. Well, I had lots of components, which were basically in a chain of needs. So things like, the customer wanted print, print needed a website, website needed a platform, platform needed compute, compute needed power. So I could create a chain of needs. Now I've got position and an anchor. Good. But I still have no movement. Well, that's a problem. Because if you look at somebody like Nokia, it was a paper mill, plastics manufacturer, telecommunications company, something else today. It's changing. So I need to describe movement. So I took power. I thought, well, power. We start off with a Parthian Battery, 480 AD. Somehow, we end up with utility provision, 1886, Westinghouse, Tesla. So how do we go from there to there?
My first idea was diffusion curves, Everett Rogers's work, made famous by Geoffrey Moore. Have you heard of "Crossing the Chasm"? Yes? So adoption over time. Geoffrey Moore does it as the non-cumulative form. Everett Rogers, the original work, is the s-curve shape. Geoffrey, very valuably, added this chasm, the thing you have to jump over, from the early market to the mainstream market. I thought, well, this is going to be simple, isn't it? Because what I'm going to do is I'm probably going to get something up here and we'll get custom built examples, and then probably products and commodity. And I just have to find the right percentages and, oh, that's wonderful. That'll be easy. Except for– unfortunately, I like data. So I looked at things like– well, take this, the smartphone. Right. Who thinks the smartphone is a commodity? Hands up. There's quite a few of you who don't. OK. And what percentage of people in the US do you think have smartphones?
65%, 70%, 80%, 90%? OK, fine. Right. Gold bars. Who thinks gold bars are a commodity? Is there somebody here who doesn't think a gold bar is a commodity? OK, fine. What percentage of the population have gold bars? All right. The problem is, a whole bunch of stuff wasn't commodity when 70%, 80% of the population had it. But a whole bunch of things were commodity when only 1% of the population had it. So I can't really use adoption as a measure of change. Turned out that things appeared and would evolve through multiple diffusion curves over different time frames and different applicable markets. So I can actually use adoption or time to measure change. So I was a bit stymied at that point. And then I noticed something. When looking back through the history of telephones– this is diffusion of multiple improving forms of telephones. In the earlier stages, I noticedS we wrote manuals like this. "The Telephone and How to Use It." How to hold it, how to speak into it, et cetera.
And I thought, well, we don't do that anymore. And then I discovered things like this. "This room is equipped with Edison Electric Light. Do not attempt to light with a match. Simply turn key on wall by the door." And so I started to look into publications. And what happens is something appears and we have publications talking about the wonder of it. The wonder of radio. Then that gets overtaken by publications talking about how to build something. Building construction awareness, how to build your own crystal radio set. Then that gets overtaken by publications, which talk about operation, maintenance, and feature differentiation. And finally, you get publications which talk about use. So things like the wonder of radio, crystal radio sets, how to build one, my radio is better or worse than your radio. Followed by, here's the radio times, what's good on channel whatever at 4 o'clock? And so there was increasing certainty about the thing. So what I did was I took this point, where the publication types changed, went back and looked and found the applicable market, then measured ubiquity against the applicable market against certainty, that point of stability, and discovered this pattern.
What happens is things appear novel and new, the genesis of new acts like the first ever telephone, the first computer, the Z3, 1943, the Parthian battery. Then, through demand and supply competition, it evolves and you get custom built examples. Then you get products. So computers, you got things like the IBM 650. Improving products, rental services, time-share, commodity hardware, and eventually, utility services. And that is movement. So I was able to take my value chain, flatten that evolution curve at the bottom, add in movement, and suddenly, I had a map. Quick recap. I started off as this fake CEO, no clue what I was doing because I hadn't gone to the right courses. No one had taught me how to do this stuff so I had to invent my own way. I realized I was competing against others. I was completely blind, totally depending upon stories, secrets of success, and magic frameworks. So I thought, well, hang on a minute. I want to be over here. That means I need to understand, A, that strategy's a cycle.
That I need to observe the landscape, learn about climatic patterns, orientate around it, and then get into context-specific play. Which means I need to first understand the landscape with a map. A map needs an anchor, so that was users and user needs. I need position relative to an anchor, so that's my value chain. I add in evolution. I now have a map. It is 2005. And I went to other people and said, look at this, isn't it exciting? And they went, so what? Well, now I have a map. I can start to observe climatic impacts. These are the roles that influence the game. The first one I noticed was that everything evolves. Due to supply and demand competition, it's all moving from left to right. The next one is the characteristics change as it evolves. It starts off in this uncharted space, where it's chaotic, uncertain, poorly understood, changing, different, exciting, and a source of future worth. And over an unknown amount of time, it becomes industrialized, ordered, standard, stable, measured, dull, boring.
This is known as the Salaman and Storey Innovation Paradox of 2002. So the next thing I noticed was that, because characteristics change, there's no such thing as a one size fits all method. Agile in-house was very strong on the left, very weak on the right compared to things like Six Sigma, which was all about reducing deviation, and very weak in the middle compared to things like Lean Enterprise because they're all focused on learning and reducing waste. So there's no such thing as one size fits all. Which was great, because in 2002– sorry, 2001, we'd gone all Agile, as in XP. And then by about 2003, 2004, we were discovering it wasn't working everywhere. So now, we– 2005, we understood why. We also realized that our purchasing methods were not singular. We needed time, material, VC based here, outcome based here, COTS and fixed, and utility. That's good. Then we learned another pattern. As things evolved, they became more efficient, like electricity. But that enables higher order systems to appear.
Electricity enabling computing, radio, television. So if you think about the nuts and bolts, used to be a home made cottage industry. Then Maudslay introduced the screw cutting lathe. Suddenly, you get an explosion in standard nuts and bolts and suddenly, an explosion in machinery. And those higher order systems create new sources of value and new sources of worth. So as electricity became a utility, enabled television, and television became a new industry. Of course, all this stuff is uncertain on the left. So you didn't know whether the box in the corner showing pictures was going to be the future success or whether it was the refrigeration blanket. Personally I would have gone for the blanket, but it turned out to be the box. So things evolve, new things appear, they evolve, they enable new things to appear. And so what you get is a line of the present in a constant sea of moving components. And then you learn more patterns. That we have inertia to change because of past success.
So if you take somebody like Blockbuster, Netflix, who was first with a website? Blockbuster. Right. Who was first with video ordering online? Blockbuster, yay. Who was first with experimenting with streaming video online? Blockbuster, yay. Who went bankrupt? [LAUGHTER] Right. So anybody who says, you don't want to be uninnovative like Blockbuster, well, actually, they pretty much out-innovated most people. Their problem– do you know what their problem was? Late fees. Hence the stores. Late fees, they were addicted to late fees. For those of you who don't remember, you would get a video, it's a cassette thing which you'd get from the shop, go home, forget to take it back the next day, and get charged a fortune. So now we have some basic patterns, we can anticipate, communicate, and challenge. So I took my map of online photo service, I knew the computing platform was evolving to a utility. I knew that we would have inertia to the change. I knew that this would enable higher order systems to appear and that some of them were new sources of value or worth and we would get a new line of the future.
So there we were, sitting in the boardroom. I had IT, I had business development, finance, operations, marketing. We're all sitting around discussing, around a map, how our world is changing. A bit like, in the military, a marine needs to call in air support. They can use a map to do so. You don't phone up– oh, sorry, or call in on a radio and get somebody from air support, the Air Force. And they turn around and say, do you know how to fly a jet? No. Well, we can't support you then. But interestingly, we do that in business. You may have noticed everybody in IT thinks everybody else should learn IT. And everybody in finance thinks everybody else should learn finance. And so we didn't have that problem. That was nice. And then we learned about weak signals. Weak signals. A friend of mine used to run a hedge fund, greed is good, all that sort of stuff. They wanted to use social networks to look at where their companies were possibly thinking about acquiring others. And I explained, that's not the way you do it because CEOs don't tend to like each other on Facebook or whatever, especially not prior to an acquisition.
But what they do like is private jets and the tailplane numbers are public and so are the flight plans. So what you can do is just map the movement of all the private jets, looking for disturbances in the pattern. This was 2008. They're very good at leaking information. Everything must be secret. We jump into our jet and we leak information because it's all public. Anyway, the point is, you can use weak signals with this stuff. So we knew compute would evolve to a utility. We knew people would have inertia. We knew that would enable higher order systems to appear. And this sort of change is known as a punctuated equilibrium. It's a non-linear form of change. Now this is part of a cycle known as Peace, War, and Wonder. It goes at both a local and a macroeconomic scale. What happens? You get big vendors in this space, whatever it happens to be. They all have inertia to change because of past success. New entrants, unencumbered by a preexisting business model, move in, like a bookseller for hardware.
That causes an explosion of higher order systems, the wonder out of which new industries form, and of course, all the people stuck behind the inertia barriers, they disappear off the cliff. And this occurs at both a local and a macro scale. At the macro, we call them ages, so Age of Electricity didn't start with the Parthian battery. It started with industrialization of electricity preexisting at Tesla and Westinghouse. Same as the mechanical age– Machine Age. Didn't start with the formation of nuts and bolts. That was long before. It started with industrialization, that shift from product to more commodity. The point about this is, this is the trigger, the shift from product to commodity. And that's based upon that evolution curve, which comes from this, which comes from those publication types. So you can actually use the publication types and variants within them as a weak signal for when these changes will occur. And that's the last time I did a weak signal analysis.
It's 2014, so it's three years old. And what you've got is big data is just entering the war, 2015, which basically means you've got loads of big data product vendors running around saying we're the future. You've got about 10 or 15 years before they're all disappearing. It's already moving into utility space. That's already happening. Platform, we're in that space. Center as a service, a bit further away. But anyway, that comes from the data. And the point about this is you know that these points of industrialization are approaching, so you can at least plan for it. A quick recap. I wanted to be over here, not over here. I hadn't done an MBA. This is obviously the stuff they teach people at MBA's, but I had to invent it because I couldn't afford an MBA. I started off with the strategy cycle. Understand, observe your environment and landscape climate, orientate with doctrine, then you're into leadership. It's a cycle, it's an iterative process.
Key for this is understanding your landscape, your map. It has some basic characteristics. You start with user needs, understand position, understand movement. Once you've got that, you can start to learn climatic patterns, like everything evolves, characteristics change, no one size fits all, efficiency enables innovation, higher order systems create new sources of value and worth, past success creates inertia, economy has cycles, and you get things like punctuated equilibriums. And that enables you to do amazing acts of fairly obvious prediction. This stuff is going to a utility and it's going to enable other stuff to appear. OK. Now I get into doctrine because once you've learned the map and you start to learn climatic patterns, you start to find universal approaches. By universal, I mean they're useful everywhere. So things like if you're in a military campaign, you get things like flanking movements, which depend upon where your opponents are. But there's useful things like soldiers learning to shoot a rifle before a battle.
It's not much use going, oh, we should flank the opponent. You better all run off and start learning how to shoot a rifle for the first time. There is universal stuff that happens before. So these are universally applicable principles, regardless of context. So things like, focus on user needs, turns out, is universally useful. Reduce duplication. One of the beauties about maps is, if you share maps– like immigration, borders police, UK government– you share maps between departments, you suddenly start discovering we're building the same things elsewhere. Now, I used to think the government was bad at duplication and waste, then I started looking at the private sector. It's amazing. So I thought really bad would be having six examples of the same system in an organization. No one would ever beat that. Then I found a national bank with 14 CRM systems. European corporate, 22 rules engines. I had 118 workflow systems registering prisoners into prisons. We had to do it 118 times.
Then I found a global technology vendor, 170 Cloud projects all doing the same thing. A global pharma company, 300 separate teams all building enterprise content management systems and five global efforts, none of which knew the others existed. A global energy company, 380 teams building customized versions of the same ERP system. And then I found a bank with 1,000 risk management systems. And they were all sitting there going, we can't innovate. And you just go, I think I know why. Anyway, if we take something like HS2, heavy engineering, high speed rail. We used to try and organize things with box and wire diagrams. This is actually a map of them building the entire railway in a virtual world because it is actually much more sensible to dig up a virtual world and go, whoops, we got it wrong, than in the real world. But you've got a map and now what they're do is, we check. Have we got systems elsewhere? Are we using the right sort of method? We're going to outsource that stuff on the right, build off-the-shelf product– oh, sorry.
Yeah, use off-the-shelf products in the middle, build agile in-house techniques on the left. This is 2011, 2012. Point is, we started using, now, multiple methods. That's another form of doctrine, using appropriate methods. In the past, we do things like take out topographical– sorry. A box and wire, a network topology diagram, and go and ask things like, should we outsource this without a map? And we'd make a decision. And of course, if you map that version, what you find is that some bits are actually suitable for mapping– for outsourcing, I should say– and some bits, on the left-hand side, are novel and new. So you wouldn't outsource them. If you do, you'll just incur excessive change control costs because they will change all the time. So you don't take a whole bunch of things like this, get a big specification to outsource, because you will just end up with huge overruns. But that's what we'd done in the past. And then we'd have fights with the vendors.
And then somebody, some Muppet, would come out with the, well, we need better specification in the future. Well, that's never, ever going to work. To give you an example of this, I thought I'd do an experiment. Do you know what a world perception server is? No? OK. It's part of a self-driving car. And what I've done is, I've translated the network topology diagram all into Elvish. So I'm going to pretend you're all finance. And IT is all Elvish to finance people. So here is the network diagram in Elvish. And so I'm going to say, should we outsource or build our own A, should we outsource or build our own B? What do you think? This is the sort of decision processes that we go through. Anybody? OK. What I'm now going to do is I'm going to convert it into a map. Exactly the same diagram, but it's now a map. Should we outsource or build our own A? OK. Wow. What about B? Fantastic. And of course, now, translate it back into English, GPS, and world perception server.
But the point is, we make these decisions about outsourcing contracts not using– well, using those sort of box and wires. Anyway, you get to the point of now you're using appropriate methods. And then we get onto things like FIST, fast, inexpensive, simple, and tiny. US Air Force, Lieutenant Colonel Dan Ward. It's an approach of breaking down large complex systems into small pieces. It's used by Special Operations Command. What you do is you've got your map, you're using the right methods. Now you think small. You're building small teams. Amazon now calls that two-pizza, Hire has its own cell base structure. It's the same thing. And then what you discover is that attitudes are different. So engineering over here is not the same as engineering over here, and it's not the same as engineering in the middle. Same with finance and marketing. So you start building structures which cope with evolving attitudes. You have pioneers, settlers, and town planners. And you create, from that, structures which are constantly evolving, cell based, considering attitude.
We don't have time to go through that. But GCHQ, that's our intelligence services, very kindly open-source Boiling Frogs, which is a document which talks about how you use structure around constant change. OK. Quick recap. Strategy cycle. Purpose, landscap, climate, doctrine, leadership. Very basic, very simple. It's iterative. It's all about the why of purpose and the why of movement. So observe your environment, then orientate and decide in that. To start with, you need to have a map. A map has a number of basic characteristics, context-specific, position, anchor, and movement. Once you've got that, you can start to learn climatic patterns, things like everything evolves, characteristics change, no one size fits all, efficiency enables innovation, higher order systems create new sources of worth. That we have inertia caused by past success, the economy has cycles, there are things called punctuated equilibriums. In fact, what you discover– prepare yourself for horror– there are 27 different common economic patterns.
And so you get to– it's like rules of the game. You get to learn these and then you can more effectively anticipate. And you can just take your map, you can describe the likely points of change, you can start using weak signals to refine on that. Then you get into doctrine. We now have an idea of what's in our landscape, where it's going. So how do we organize ourselves? You think about, well, I've got to focus on user needs. I'm going to reduce duplication using multiple maps between different groups. Use appropriate methods, think small, think aptitude and attitude. Design for constant evolution. Prepare yourself for shock. There's about 40 common forms of universal doctrine. Really useful stuff. Actually, this is quite useful looking at competitors because you get an idea of just how bad they are. To which people then go, ah, this is complex. And it is. That's why we like stories. That's why we like secrets of success. That's why we like magic frameworks.
It is complex, I'm afraid. Then we get into the leadership bit, which is all about context specific forms of gameplay. So you have your map. You can anticipate where things are going to go because you've got those climatic patterns. Not everything is perfect, but you can do a reasonable job. And now you're going, where do I attack? And this is the why of movement. Why here over there? Do I want to build the first platform, the first compute environment? Do I want to modify the online photo service? You also learn where not to attack. Where to leave it, all the stuff stuck behind inertia barriers. And then you start to learn you can manipulate the environment. So you can use open approaches to accelerate, you can slow things down with fear, uncertainty, and doubt. Pattern plays. There's about four or five different forms of ecosystem models. There's all sorts of constraints that you can manipulate. Horror. There's about 68 different ways of manipulating the market.
3D printing, mobile phones as cameras, and this utility computing thing. That's not the future. The future is 3D TV. So shut it all down and spend a billion on 3D TV. By the way, who owns a 3D TV? Who uses mobile phone as a camera? Who uses Cloud? 3D printers? I don't like American strategy consultancy firms. Anyway. Anyway, anyway. So I went to a company called Ubuntu. Heard of Ubuntu? Yay. So in 2008– Mark's a friend of mine. We mapped out the environment, determined where to attack. I also mapped out Red Hat and Microsoft, and specifically, with Red Hat, looked for points of inertia and how we could play the game against them, et cetera, et cetera. Particular things like where their salesmen had inertia to change and how we could exploit that. So we exploited that, and basically half a million– 18 months later, we went from 2% operating system market to 70% of Cloud. Wee. That wasn't too bad. And then I went to government, wrote something called the "Better for Less." Well, sorry.
I worked for a research organization called the Leading Edge Forum, where I did a lot of work with Liam Maxwell and with the government. And this was for Francis Moore before the coalition got into power. So that led to lots of things like spin control and changes in the UK government. So a quick summary. Strategy's actually cycle, not a linear path. It's an iterative process. It's like chess. It's a game you have to learn, it takes time. It helps to understand the board. One of the key things is, acting movement is the mechanism of learning. Really important to understand the landscape, as well, to observe it. So it's all about small steps, understanding the environment, being adaptive. Which is basically what crossing the river by feeling the stones, Deng Xiaoping, is all about. Now if you're all going, gah, that mapping, I don't understand any of it, don't worry. It's all Creative Commons. You'll find wardleymaps.com has– I've got a Medium account.
You can read all about it on there. And there's a group called Map Camp setting up to teach people how to map, as well. And that's me. Thank you. [APPLAUSE] OK. Future things to think about. I had to charge through all of that because I just wanted to get to this point. I assume– how many of you– actually, I should have asked that question. How many of you map? There's only a few of you. Hey! Well, there's some of you, anyway. There's three other topics I can quickly cover. A serverless ecosystem and MAGA. That's actually a spelling mistake. It should be MAGBA, Make America Great Britain Again. Anyway, sorry. Or quick questions. Do you want me to go through these? Yes? OK. So serverless and co-evolution. Right. So our platform, really interesting point of war again. 2014, we're in it. It's shifting into that utility space, code execution environments. Right. Let's wind back a little bit, talk about infrastructure. So compute. When compute was a product, we built applications which used emerging architectural practices based upon compute as a product.
And these were all based upon the idea of high MTTR. So I had a server and if my server went bang, it would take me weeks to get a new one. So I had architectural practices like scale up, capacity planning, n+1, disaster recovery test. And do you all remember those? Yes? Yes. Great. Super. And so they evolved and became best practice applications built with best architectural practice for use as a server as a product. And we would mock people who didn't do capacity planning and all that sort of, oh, you silly person, et cetera. And then, of course, what happened is, computer evolved, became more of a utility. And so you've got a new set of emerging architectural practices based upon the characteristics which are low MTTR. So what happens is your server goes bang, takes you seconds to recover. So you've now got things like distributed systems designed for failure chaos engines. And that evolved and it's become good practice. And that's DevOps and that's legacy. So when we talk about legacy, we're talking about applications built with best architectural practice for product world.
And that is legacy. And DevOps is applications, good architectural practice for utility world. OK? And of course, what happens is, people go, make my legacy cloudy, i.e., they want to have all the benefits of efficiency, agility, and all that sort of stuff. So I want to take that stuff, but I don't want to re-architect. And so somebody sticks their legacy on something like Amazon. Amazon has an outage and they run around going, the end of cloud is nigh. To which you go, shouldn't our architecture evolve, as well? And they go, burn him. Evil. And get her, get her. A heretic, witch, or whatever they say. Right. So the point is, it's those people, their best architectural practice, they have inertia to this change and I don't like this, it's uncertain, et cetera, et cetera. Anyway, if you move up the stack into platform, we've got this shift going on from very much a product space– I've got a LAMP stack or whatever it happens to be– much more to a utility execution environment.
I just write code, et cetera, I deal with these functions. And you'll get a co-evolution of practice. So a whole set of new financial development practices will come out, particularly things like functional billing. It changes the way you operate, how you invest in things, refactoring all this sort of stuff. And that'll spread. And so you should be investing in those two places. Of course, you're going to get resistance from people, best architectural practice for how you build LAMP stack of whatever, legacy environments. And you're always going to get resistance from the DevOps people because they're now below the line. So they don't matter as much. They're going to become less visible. And they're not going to like that. So they're all going to give you inertia. OK. So you'll go out and say, how about no Ops, and they're like, burn you, heretic, and all the rest of it. It's tough. That's the way it goes. Ecosystem. If you look at this game, if you look at somebody like Lambda, of course there's [INAUDIBLE] functions and Google Cloud functions, as well.
Make some noise for it, please. If you look at somebody like Lambda, Amazon is very good at a particular eco– well, it's very good at ecosystems play. At this point, I have to be careful. Because we cannot say how they play the game, but I'll show you an example of how you might play the game. So it's a game play called ILC, innovate, leverage, commoditize. It's a decade old. It's 11 years old, this one. I know, because I wrote about it in Zimki. It's very simple. You take an activity, you commoditize it to a component service, provide it as a utility. Everybody builds new things on top, componentization effects. They act as your free research and development department. Thank you very much. [? My ?] metadata to identify new components, which you provide as utility services. The group over here grumble, oh, he's eating my business model. And that enables new higher order systems to appear and everybody thinks you're brilliant. And so what you've got is others innovating for you.
That's your entire ecosystem. And you're mining metadata to find future patterns and you've got an ever-growing platform of commodity services, which everybody is building on. You normally show it in this form. You take something from the ecosystem, turn it into a utility service, expose in the API, everybody builds on top. Use that to identify new patterns by leveraging the data, metadata, consumption data, not their actual data. And then you use it to build new services. And the net result, it's very simple. Again, it's a very old model. Your apparent rate of innovation, customer focus, and efficiency now all simultaneously increase with the size of the ecosystem. So do you know a company which seems to be getting more innovative, more efficient, more customer focused every year, which other people say, they've eaten my business model over? Anybody got any ideas who that might be? Right. So if you are that company and you're playing that utility game, what's going to happen is– let us suppose they are providing a code execution environment with all those benefits of functional billing.
Then certainly soon, you're going to have a marketplace with functions you can buy from others, a CPAN-like repository where you can get code functions from others, and suddenly, you discover the level of duplications in systems is nothing in comparison to the level of duplications within systems, particularly within code. And you'll get into a world where, suddenly, everybody is building entire trading applications in a day and a half. I know, I built one in two days, but that was 2006. So that's the power of ecosystems. So really watch out. Be careful if you discover that somebody is playing a utility code execution game against you with functional billing and is very good at ecosystems. Because that's a very dangerous competitor and somebody you have to react to. Right. MAGBA. Do you want to hear about MAGBA? We've only got a few minutes left. Right. MAGBA. Right. Compared to what? Make America great again compared to what? OK. Self-driving cars, because I like elves and self-driving cars.
I did a piece of work years ago on the automotive industry. You start with consumers want to go from A to B. They want comfort, affordable. You've got a pipeline of cars. They also want status because they want to look good in their car. And underneath that, you've got things like entertainment systems, IS screens, location based services, IoT, power supplies, assembly, sensors, a whole bunch of things. And what's interesting, of course, is that if you roll it forward, that's 2015– hm, 2014– but you roll it forward to 2025, you find it's a lot more commodity and all that sort of stuff. Very interesting. And you find new links. And what it basically means is we're heading into a world which is all much more self-driving cars, immersive, you won't own a car. You'll have a digital subscription. You might have gold, I might have silver, which means when I'm puttering along in my car, it'll get out of the way as you zoom past me and all that sort of stuff.
But it's really exciting. Not really. It's all fairly obvious. From a government point of view, of course, it impacts things like driving licenses and and you have to think about that sort of stuff. But what's interesting is now, if we start looking at the points of war– these points of heavy industrialization– and then we start looking at which governments are good at investing, as encouraging industries prior to those points of war, you find China's brilliant at this stuff. It's gotten really, really good. So we all run around going, the future's Uber, Google, whatever, within self-driving. Well, it may be. But actually, more like [? DD, ?] et cetera. So the problem with the whole "make America great again," it's not really your choice alone. You are in competition with other nations. And if we start looking at the different value chains and game play that's going on, there's some real skilled game play. You start going, well actually, there's some really fierce and capable and skilled competition.
There's some truly amazing Chinese companies. But anyway, people run around with it and say, we've got to do this. And so there's huge obstacles. And I've been trying to find what the biggest obstacle is. And I think it's economic thought, bizarrely enough. I took about 160 odd economists and various people in the economic field and asked them a bunch of questions. So US-centric people, US-centric economists, I asked them, on a scale of centrally planned to laissez faire, to place a bunch of economists. They had Marx, Keynes, Smith, Hayek, Friedman. OK? And they were like, this is the less effective communist model. This is the more effective capitalist model. And that's how they thought the US operates, very much Smith, Hayek, Friedman. And that's very much how China operates. That's interesting because then I went, and I kept within Western philosophy, and asked a bunch of European economists exactly the same question. What we got is Marx here, Keynes, Smith, and Hayek in the middle, Friedman right on the right.
So they are very much– this is more of a social capitalist type model. And that's where the US is. And this is where China seems to be operating. And so you're talking Europe and the impression is that China is actually operating as the world's largest venture capital firm. But of course, if you're talking to people in this sort of frame, that doesn't make any sense to them. So I think part of the problem is, A, it's a question of whether you understand the actual landscapes that you're competing in. What patterns are actually played? But it's also the economic processes of thought. It's really difficult. You sit there with US economists and say, oh, no, it's a VC firm. They operate like the world's largest VC firm, incredibly skilled. And it's like, people just have difficulty getting that. Anyway, it's not a zero sum game. The one piece of advice I actually would have is there's an awful lot of learning from China. There are some really skilled companies now who have extended beyond many of the management practices we have in the West.
Anyway, that was it. Thank you very much. [APPLAUSE] [MUSIC PLAYING]
Deng Xiaoping once described managing the economy as crossing the river by feeling the stones—in other words, have a direction, but be adaptive. But in a world of constant change, how do you determine the right thing to do? Which pebble to tread on? How do you understand where you’re going and where you need to go? How do you know if your strategy is right? Is there even such a thing? Simon Wardley examines the issue of situational awareness and explains how it applies to the world of open source. Using examples from government and the commercial world, he explores how you can map your environment, identify opportunities to exploit and learn to play the game.
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