Decision under uncertainty

Managers who follow this approach analyze the size and nature of the risk involved in choosing a particular course of action.

Decision under uncertainty

Decision under uncertainty

The worst thing you can do is nothing. This is especially true in situations where we are trying to decide something based on the external environment—market trends, customer needs, or competitor reactions.

During my time at McKinsey, we were often called on to advise a client to make an important decision without the benefit of a lot of data.

Decision under uncertainty

A good example was when a client asked us to evaluate whether it should move into an adjacent, but new, market.

As McKinsey consultants, we were trained in how to make decisions and recommendations in just these types of situations. Below are some of the tools we used to make decisions with incomplete data. How you develop your hypothesis is a combination of good problem solving skills, pattern matching, and intuition.

But the expectation was that within your first day on the project, you should come up with your early hypothesis about the right decision to make. Then, you can always gather additional data to refine your hypothesis over time. You should be open to changing your hypothesis as you gather additional data, but you should start out with a hypothesis on Day One.

Roger Pielke Jr.'s Blog: Five Commandments of Decision Making Under Uncertainty

The reason why this approach is helpful is that after Day One, you always have a decision that you can stand behind at any point in time. You may try to gather additional data, but based on the data that you have already reviewed at that point in time, your current hypothesis is your current decision.

Directionally Right, Same Order of Magnitude. A lot of times, people get hung up on making a decision because they want to make sure they get the right answer.

Decision making under uncertainty

This is especially true when you are trying to get to some numerical value: If we decide to do this, how much revenue can we expect in year 1, year 2, and year 3 after we do it? Without having complete data, you will never be able to get to a precise value.

Instead, you should strive to make sure your answer is directionally right. Will we be revenue positive, neutral, or negative if we make this decision? And you should strive for getting the order of magnitude right.

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So strive to be directionally right, and the same order of magnitude. Suppose we were trying to decide whether to enter a new market, and one of the key drivers of our revenue estimate was what our market share would be in three years.Scope of this book This book is about decision theory under uncertainty, namely asking how do people, and how should people, make decisions in sit- uations of uncertainty.

Nov 20,  · In our everyday life we often have to make decisions with uncertain consequences, for instance in the context of investment decisions.

To successfully cope with these situations, the nervous system has to be able to estimate, represent, and eventually resolve uncertainty at . Decision theory (or the theory of choice) is the study of the reasoning underlying an agent's choices.

Decision theory can be broken into two branches: normative decision theory, which gives advice on how to make the best decisions, given a set of uncertain beliefs and a set of values; and descriptive decision theory, which analyzes how existing, possibly irrational agents actually make decisions.

Sep 09,  · These are “Five Commandments” of decision-making under uncertainty. That description is apt. Like disease detection, frisbee catching, sports prediction and stock-picking, living a moral life is a complex task.

An introduction to decision making under uncertainty from a computational perspective, covering both theory and applications ranging from speech recognition to airborne collision avoidance. Many important problems involve decision making under uncertainty—that is, choosing actions based on often imperfect observations, with .

Sep 09,  · These are “Five Commandments” of decision-making under uncertainty. That description is apt. Like disease detection, frisbee catching, sports prediction and stock-picking, living a moral life is a complex task.

Decision-Making under Certainty, Risk and Uncertainty