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Hello everyone. Welcome to the 5 Minutes Podcast. Today I'd like to talk about Minimax strategies in project management. And I know that every time I talk to you about the Minimax strategy, the first thing that comes to your mind is game theory. It's John von Neumann's algorithm that is almost 100 years old. And you think about AI, and you think about tactical games or connecting four games, how you play against the machine, and how machines behave when playing in a zero game, zero-sum game. What is a zero-sum game? It means if I win, you lose. And what I want to share with you, I don't want to talk about algorithms here. It's not the intent of this episode. The intent of this episode is to explain philosophically and psychologically what this strategy is. So the Minimax strategy, the name, answers everything to us. Minimax means to minimize the max the maximum possible loss resulting from your decision. So you need to make decisions in a project every single minute. And what do you want? Do you want to minimize your maximum loss? For example, you want to minimize the tragedy. And you don't want to protect because it's just impossible to protect your project against absolutely everything. But what you need in your prioritization of how you answer to uncertainty you need to understand which kind of uncertainties I really need to monitor to avoid the maximum possible loss.
And this is the meaning. It's a very key thing for you to make decisions under uncertainty. Let me go one step back and talk about, for example, a normal game or tactic, though. You put the X, and you put the circle in every step. Of course, you want to win the game, but why do you use Minimax? Because sometimes I know, look, if I put an X here in the next round, I will win. But there is a problem. If I put my X here. I will not have the next turn because my opponent will win the game. So I need to block my opponent to create the maximum damage in what is the maximum damage on this game is to lose the game, right? This is why, for example, when you put very, I would say, strong machine learning algorithms to play against each other in this kind of tic tac toe game, what happens? It's all draw. Nobody wins because they always use minimax and because they are a limited amount of possibilities. There is always pretty much always a tie. And this is exactly what I'm suggesting you do and not look for a tie. But imagine now that you don't have an opponent in your project, but your opponent in your project is uncertain.
And this is why you do risk management. This is why you plan. This is why you try to forecast, I would say, what is potentially coming. And then you need to defend yourself and need to prepare yourself by saying that. Let me give you another example. Let's suppose you need to make a decision. Should I buy or not? Insurance for my car. A very simple example. Before you make this decision, you need to understand what the maximum is. The possible loss I will have. Okay. It's to lose my car, and I can lose this car by two things. By crashing the car or, for example, by having the car stolen. Okay. And let's suppose that you look and you see that based on statistics of crime and accidents, there is a higher possibility for you to lose your car by being stolen. So what do you do? You say which kind of strategies I can take on this to minimize these losses. Then you put a lock. Then you put an alarm. Then you park your car in a garage. Then you do a series of actions aiming to minimize. And if you do that, maybe you will decide not to hire or not to buy the insurance because you are minimizing the maximum possible loss. Another example, let's suppose you have a project that is 100 days, okay? And this is the deadline.
Most of the time, people are focused on delivering on these 100 days. But let's suppose that something happens to you. You notice in your contract that if you deliver the project later than 120 days, it means not 100, but 120 days, you will have a penalty or a fine. That is huge. That is incredibly high. So what is your minimax strategy? Your minimax strategy is not to put in the effort to deliver the project in 100 days. It's how I can avoid that penalty, how I can avoid that penalty of 120. So you work, and you create all your mitigation plans. You create all the changes in your scope to minimize because you say, look, if I deliver in 103 days. It's not a big deal. But if I do not deliver in 120, it is a big deal. So you're minimizing the maximum possible outcomes. Remember, you don't have money. You don't have time to answer everything, right? Because otherwise, you would say, oh, I want to answer all possible uncertainties. This is impossible. So this is why the Minimax strategy helps you to focus on really what is the biggest, I would say the biggest, enemy of your delivering your project. Another thing that is interesting. In another case, it's what is called maximum. Sometimes it's exactly the opposite. It means minimax. You minimize. You minimize your own maximum possible loss.
Maximum. It's what you want to maximize. The other size is the smallest gain. This is extremely helpful. The concept of Maximin and Minimax, for example, when you were handling contractors in your project, because there is this process of claims, for example, if you are in infrastructure work. So the contractor wants to raise claims about unpaid work, and you want to minimize. So what is the strategy for you? For you. It is to maximize your contractor's smallest gain as small as possible. This means you may lose, but you will lose the smallest amount. This is one relevant strategy that many times we use in procurement. We use contracts to reduce our uncertainty related to the behavior, for example, of your client. If you are a contractor or your contractor, if you are on the client side. So it's a good point for you to think about because you cannot answer and try to minimize every single loss because it's just impossible. It's unfeasible. So you need to understand which losses are the maximum ones. And this is exactly how you should prioritize your answers. So think about that. There are a lot of videos on YouTube about this. Take a look. You'll see that the psychological and philosophical meaning is super nice. I hope you enjoyed this podcast, and see you next week with another 5 Minutes Podcast.