Constructing Decision Models
1. Constructing Decision Models
In this video we'll learn how to construct decision models to optimize the decision-making-process.2. Decision Models
Decision modeling is a systematic approach to represent, analyze, and optimize the decision-making process. These models formalizes decision problems by breaking them down into elements, such as objectives, alternatives, uncertainties, and constraints. To formalize a decision problem, decision models use graphical representations, mathematical operations and computational techniques.3. Decision modeling techniques
Decision modeling techniques empower decision-makers to make informed decisions. Some examples of modeling techniques are: Decision Trees: A representation of a decision that involve choices, alternatives and potential outcomes.4. Decision modeling techniques
Influence Diagrams: A graphical model to represent factors that influence a decision and their relationships.5. Decision modeling techniques
Lastly, Probabilistic Models: A representation incorporating probabilities between variables and decisions. These techniques can be applied collectively in a decision-making-process to optimize the results. Let's now take a closer look into them.6. Decision Trees
A Decision Tree provides a visual representation of sequential decisions and their potential outcomes. The rectangles in this model represent Decision Nodes. These are points in the decision-making process where a decision must be made.7. Decision Trees
The chance nodes shown as circles represent uncertain events or variables that may influence the outcome of a decision.8. Decision Trees
The leaf nodes, displayed as triangles, represent the final outcome associated with decisions and uncertainties.9. Decision Trees
Lastly, the lines represent the possible actions or outcomes in a decision. Let's see these in an example:10. Applying a Decision Tree
In this example, the model describes the decision to have an outdoor picnic. The weather, is the main decision node. This node branches into three alternatives: Sunny, Rainy and Cloudy.11. Applying a Decision Tree
Instantly, we conclude that a Rainy weather will lead to an unsatisfactory outcome.12. Applying a Decision Tree
However, A Sunny weather will lead to another decision factor: Humidity. Low and High Humidity also lead to dissatisfaction, Medium humidity will be perfect!13. Applying a Decision Tree
Lastly, the wind on a cloudy day is also a point of decision. High winds will lead to a bad outcome. However, Low and Medium winds on a cloudy day are perfect for a picnic! Now let's take a look at another type of Decision Model: Influence Diagrams.14. Influence Diagrams
An Influence Diagram displays the factors impacting a decision. Every decision can be broken down into Objectives, Alternatives, Information and Data, Risks and Uncertainties, and Constraints. An influence diagram explores the relationship among the decision factors using mainly these four symbols: The rectangle represent the decision problem. The oval-shapes are the unknown or uncontrolled variables. The diamond represent the outcomes and the rounded rectangles represent the calculated variables. Let's explore this model further in an example.15. Applying an Influence Diagram
The Millers are getting married! They are considering a beach wedding at sunset. What variables can influence this decision? Centrally, in this influence diagram, we can spot the decision problem. In this case, having a beach wedding.16. Applying an Influence Diagram
The outcome is connected with the objective, represented by two things: Bride's happiness and satisfaction of the guests.17. Applying an Influence Diagram
The calculated functions are things that need arrangements for the objective to be reached. These are Budget, Invitations, Outdoor Environment and Infrastructure.18. Applying an Influence Diagram
Lastly, we see the uncertainties. Things like Weather, Flights, Accommodations and the number of attending guests are unknown factors that may influence this decision. Remember that every decision model is a live organism! Elements should be added or removed as things evolve in the decision-making process.19. Let's practice!
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