Decision Analysis (DA)

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What is decision analysis (DA)?

Decision analysis (DA) is a systematic, quantitative and visual approach to approach and assess the important choices that companies are sometimes faced with. Ronald A. Howard, professor of management science and engineering at Stanford University, coined the term in 1964. The idea is used by large and small businesses when taking various types making, including management, operations, marketing, capital investments or strategic choices.

Understanding decision analysis (DA)

Decision analysis uses a variety of tools to assess all relevant information to facilitate the decision-making process and integrates aspects of psychology, management techniques, training and economics. It is often used to assess decisions that are made in the context of multiple variables and that have many possible outcomes or goals. The process can be used by individuals or groups who are trying to make a decision regarding risk management, capital investments and strategic business decisions.

Key points to remember

  • The decision analysis is a systematic, quantitative and visual to make strategic business decisions.
  • Decision analysis uses a variety of tools and also incorporates aspects of psychology, management techniques and economics.
  • Risk, capital investments and strategic business decisions are areas where decision analysis can be applied.
  • Decision trees and influence diagrams are visual representations that facilitate the analysis process.
  • Critics argue that analyzing decisions can easily lead to paralysis of analysis and, due to information overload, the inability to make decisions.

A graphical representation of alternatives and possible solutions, as well as challenges and uncertainties, can be created on a decision tree or influence diagram. More sophisticated computer models have also been developed to facilitate the decision-analysis process.

The objective of these tools is to provide decision makers with alternatives when trying to achieve business goals, while highlighting the uncertainties involved and providing measures of how the goals will be achieved if the final results are achieved. Uncertainties are generally expressed in the form of probabilities, while frictions between contradictory objectives are considered in terms of compromise and utility functions. In other words, the objectives are considered according to their value or, if they are reached, their expected value for the organization.

Despite the useful nature of decision analysis, critics suggest that a major drawback of the approach is “analysis paralysis”, which is excessive thinking about a situation to the point that no decision can be made. outlet. In addition, some researchers who study the methodologies used by decision-makers maintain that this type of analysis is not often used.

Examples of decision analysis

If a property development company decides whether or not to build a new shopping center in a location, there are several things they could consider to help them with their decision-making. These may include traffic to the proposed location on different days of the week at different times, popularity of similar shopping malls in the area, financial demographics, local competition, and people’s favorite shopping habits. of the region. All these elements can be integrated into a decision analysis program and various simulations are run to help the company make a decision concerning the shopping center.

As another example, a company holds a patent for a new product that is expected to sell quickly for two years before becoming obsolete. The company faces the choice to sell the patent now or manufacture the product in-house. Each option presents opportunities, risks and tradeoffs, which can be analyzed with a decision tree that takes into account the benefits of selling patent verses making the product in-house. Within these two branches of the tree, another group of decision trees can be created to take into account, for example, the optimal selling price of the patent or the costs and benefits of producing the product internally.

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