SafekipediaDecision analysis is a special way of thinking and planning that helps people make important choices. It brings together ideas from philosophy, methods for studying problems, and ways that professionals can help with big decisions. This field helps break down complicated choices into smaller parts that are easier to understand.
In decision analysis, experts use tools and steps to look closely at all sides of a decision. They help show what each choice might lead to and what the chances are for different results. By using a rule called the maximum expected-utility axiom, they can suggest the best action to take based on what seems most helpful or valuable.
The goal of decision analysis is not just to find an answer, but to give clear information to the person making the choice and to others who have a stake in the outcome. It helps everyone understand the decision better and why one choice might be better than another. This can be useful in many areas, from business to everyday life, making tough decisions a bit easier to handle.
History
In 1931, Frank Ramsey introduced the idea of subjective probability to describe personal beliefs about uncertainties. Later, in the 1940s, John von Neumann and Oskar Morgenstern created a way to express personal preferences when outcomes are uncertain. In the 1950s, Leonard Jimmie Savage developed another method for making decisions under uncertainty.
The term "Decision Analysis" was first used by Ronald A. Howard from Stanford University in 1966. Books and teachings about decision analysis became more common, helping people learn how to make better choices, especially when they have to balance different goals. Over time, decision analysis became a respected field used in many industries, like medicine and oil, where big, risky decisions are often needed.
Methodology
Framing is the first step in decision analysis. It helps define the problem, set boundaries, and identify success measures and possible actions. Sometimes people think decision analysis always needs numbers, but many decisions can be made using qualitative tools like value-focused thinking without needing numbers.
The framing process can lead to tools like influence diagrams or decision trees. These are graphical ways to show choices, uncertainties, and how well goals might be met. They can also help build quantitative models when needed. In these models, uncertainties are shown with probabilities, and the best decision is chosen based on what gives the highest expected value. Quantitative methods can be used for many types of decisions, even those that seem hard to measure.
Main article: Influence diagram
Main articles: Decision tree, Objective
Further information: Bayesian inference, Optimal decisions, Subjective probability, Multi-attribute utility functions
Decision analysis as a prescriptive approach
Prescriptive decision-making research focuses on making the best possible decisions based on clear rules of logic. It helps people think through important choices carefully. However, sometimes people make decisions that don't follow these rules, especially when they are under pressure or rely on their instincts instead.
Some critics say that using formal decision analysis might make people feel less responsible for their choices. But studies show that when people have time to think, using special methods can lead to better results than just going with their gut feeling. Even though people can make mistakes, training and feedback can help improve decision making. There is also concern that spending too much time and money on decision analysis might slow things down, but there are ways to avoid this problem.
Applications
Decision-analytic methods have been used in many different areas, such as business, including planning, marketing, and negotiation, as well as in management, environmental remediation, health care, research, energy, and exploration. One early example was a study done in the 1970s about whether to seed hurricanes to change their effects.
Today, big companies use decision analysis to help make very important choices, like spending huge amounts of money. For example, in 2010, Chevron received an award for using decision analysis in its big decisions. People also use these methods for personal choices, like planning for retirement or deciding on medical treatments.
Decision analysis has helped in many specific fields:
- Energy. It was used to organize energy goals for Germany.
- Entrepreneurship. Ideas from decision analysis helped create better ways to fund new businesses.
- Health Care. It has been used in medical decisions about breast cancer, thyroid cancer, and lung cancer.
- Insurance. It helps figure out the best ways to buy long-term care insurance.
- Litigation. Lawyers and mediators use it to understand possible outcomes in legal cases.
- Portfolio Management. It helps improve how money is allocated in investments.
- Military Planning. It has been used in deciding about closing military bases.
- Radioactive Waste. It helped evaluate where to store radioactive waste.
- Research and Development. It aids in choosing which research projects to fund.
- Terrorism and Homeland Security. It supports decisions to keep people safe.
- Projects. It helps predict costs, schedules, and risks in projects.
Software
Main article: Decision-making software
Decision-making software helps people analyze important choices. Some well-known tools include Analytica for creating influence diagrams, DecideIT and Logical Decisions for making choices based on many factors, and Eperoto for decisions related to legal cases. These tools make it easier to think through complex situations.
This article is a child-friendly adaptation of the Wikipedia article on Decision analysis, available under CC BY-SA 4.0.