[MUSIC] In this segment, we're going to put together all of the ideas that we've been kicking around for the last two, two modules. This slide shows the, the kind of the orienting slide that we'll be using all the way through, in a slightly different way. What we're doing here is we're saying that, take the top two dimensions of management. How we coordinate activities, how we make decisions. We're calling those the means. And then we're taking the bottom two dimensions, how we motivate employees, how we set objectives. And we're calling those the ends. And if you think about it, we can take those two dimensions, means versus ends, and we can kind of split those apart and create a simple two by two matrix. So you'll see in this chart here the two by two matrix, where we've got the means on the horizontal axis. These can be tight or loose. In other words, we can have very traditional means around coordination and decision making, which are based around hierarchy and bureaucracy there's a tight means. Or we can have very lose means, which is these principals of emergence and collective wisdom. Then you take the vertical dimension in terms of the ends, the objectives, and again we can take loose versus tight, the tight objectives, tight ends, is around essentially the old principle of linear alignment and the old principle extrinsic motivators. Or we can take very loose ends, which is the principles around obliquity and the principle of intrinsic motivation. Put them together and you create, conceptually anyway, these four generic types of management models. And what we're going to do in this segment is we're just going to really talk briefly through one example of each of these types, and then we going to show how they kind of link together. And, and, and how maybe one evolves into another. We'll take the bottom-left corner first. We'll call this the planning model. This is really the, the traditional way of managing any large organization. I've taken McDonald's as my example. I could have easily taken Walmart. I could have taken ExxonMobile, BP, any number of traditional hierarchical companies which, for very good reasons, operate by this planning model. So remember what I said. This is tight, tight. In other words, we have both very tight rules around how we do things. Hierarchical bureaucratic systems. And we've got much, very, very tight also objectives in terms of what we're trying to achieve. And so I don't want to say much more about it. I think we, because this is kind of the classical model, I think everybody intuitively gets it. We're going to be fairly regimented about what we do and about why we do it. So that's the planning model. Let's move now to the science model. This one's a bit more unusual. So this is the, the top left corner, whereby the ends are loose and the means are tight. What do I mean by that? I'm going to give you an example just to help us understand it. There's there's a UK based engineering consultancy called OVE ARUP. Nowadays typically known as ARUP, and they're responsible, for example, for Sydney Opera House. They're responsible for the, for the millennial bridge, Millennium Bridge in London, which you see in the image here. They're responsible for designing the, the Bird's Nest stadium that was used in the Beijing Olympics. Very, very well regarded company. They are a bunch of very clever, often PhD level engineers, who work together in ARUP because they want to design interesting stuff. And so a large number of ARUP engineers do stuff, not because it's necessarily profit making, but because it's exciting, and challenging, and worthwhile. So, in terms of these schematic we've got here, their objectives are really very loose. In other words, they are very much in the kind of this oblique principle world. And their employees are very much driven by what you might call intrinsic means engineers. At least in the UK, aren't particularly well paid. They're not badly paid, but they're not paid anything like as much as, as bankers and, and consultants and so forth. So they have very, very loose ends, objectives. But they actually have to some degree quite tight means. In other words, they have professional standards and mechanisms and, and, and systems that they all have to adhere to. If you are an engineer, if you're trained as a civil engineer, there are extremely explicit codes around how you design and develop a bridge or a stadium or whatever it is. So they actually by virtue of their training, this is why I call it the scientific method because science is all about conforming to certain principals of a professional or, or a way of working that guide their work. So they're fairly tight in terms of means. It's actually remarkably bureaucratic in terms of what steps you have to go through when you're going through the design over, you know, a large football stadium. And yet, strangely enough, it's also an organization that's driven very much by these sort of loose, intrinsic motivations. So that's what I'm calling the science model. And that's the second of the four.