Open course ware

[AUDIO LOGO] RICHARD DE NEUFVILLE: And so we have basically two topics for today. And the first one is the concept of the value of information. And we're going to end up with two ways of thinking about it. I am going to present in some detail the procedure for the definition of the upper bound on the value of information, the EVPI, which stands for Expected Value of Perfect Information. At the end is a supplement for your interest if you want to is the calculation of the exact value of EVSI, which is a interesting, probabilistic exercise. But I personally don't think that it's very valuable in practice. But it's part of standard curricula, and it's there if you want to go for it. It will not be part of a quiz or anything like that. I think you should know about it, so you can appreciate the other aspect I will be focusing on, so methods. And then I want to stand back from this and talk about information gathering as a basis for having a flexible strate...

[AUDIO LOGO] RICHARD DE NEUFVILLE: So I'm going to explore this basic trade-off between big versus small from an economic point of view in this short presentation. And it's all based on an old analysis from a simple case. And the real situation is more complex. But this analysis leads you to some simple, intuitive understanding of the trade-offs, which is what I want to use. And by the way, this was built upon the experience of building steel plants in India back half a century ago. So here's the picture when it all comes out to. Let me explain the picture first, then let's talk about the explanations. So I have on the horizontal axis is this alpha, which I've been talking about. And he ran the numbers because it's a simple analysis actually, which I'm not going to repeat. You can look it up. But it's not a crucial to the understanding. So that from our purposes, the economy of scale factors is in the range between 0.6 and 100. And so this ...

[SQUEAKING][RUSTLING][CLICKING] RICHARD DE NEUFVILLE: Right. Richard de Neufville here again. Pleasure to talk with you, and for this session, I'm going to talk about porcupine graphs. It's all part of this topic of the forecast being always wrong, not every single time, but in general, we can't count on it being right. And we just expect it, the reality that we face during the-- our project lifetime is not what we anticipated. Now, what's a porcupine graph? Well, let me first describe what a porcupine animal is in case you don't know it or haven't seen it. The porcupine is a North American animal. It maybe exists elsewhere also. I think it does, but I'm not an expert in the area. But the important thing about a porcupine is that it is an animal, four-footed, small, about the size of a small dog, and it has a lot of spikes on it that go up from its back. And as you can see in this example here, they go all back in a variety of ways in many diff...

[AUDIO LOGO] RICHARD DE NEUFVILLE: There's something important about this title. And it is that I'm talking about preferred projects. I'm not talking about best projects. And this is very much on purpose. Basically, when we think about a system, a system which has lots of different performance characteristics, which has numbers of stakeholders who are thinking about it-- there's a financial side, there's a technological side, there's the human relations side, there's environmental sides, et cetera, different criteria for performance-- it is basically conceptually impossible to talk about the best. We may talk about what we think is our preferred choice, what is, in some ways, in our minds, the best. But in terms of an optimization, it's difficult. And I think that we ought to recognize that and use optimization techniques to sort through dominated solutions, a concept I'll come to by the end of the class, but really focus on that we...