Farhan Hassan Al Shammari*
Risk and Uncertainty in Decision-making

Decision-making is essentially chosen from the available options.

Decision-making is going sometimes through some steps such as making choices by identifying a decision, gathering information, and assessing alternative resolutions.

Using a step-by-step decision-making process can help you make more deliberate, thoughtful decisions that by organizing relevant information and defining alternatives. 

Here we will discuss the risk and Uncertainty in decision-making and how to overcome this kind of obstacle by scientific steps as below.

As known that an analytical and scientific framework for decision implies the following systematic steps

1. Defining the problem.

2. Establish the decision criteria.

3. Formulation of a model.

4. Generating alternatives.

5. Evaluation of the alternatives.

6. Implementation and monitoring.

In risk and uncertainty situations, information about the decision variables or the outcomes is probabilistic. Below are some of the techniques used in this situation:

1. Statistical analysis: 

• The use of probability.

• Probability distribution, 

• Estimation and tests of hypothesis, 

• Bayesian statistics. *

• Decision theory. **

• Correlation.

• Analysis of variance

Bayesian statistics

It is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event. 

The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event.

Decision theory

Can be broken into two branches: normative decision theory, which analyzes the outcomes of decisions or determines the optimal decisions given constraints and assumptions, and descriptive decision theory, which analyzes how a person make the decisions.

2. Queuing theory: 

The analysis of queues in terms of waiting-time length and mean waiting time  are useful in analyzing service systems, maintenance activities, and control activities.

3. Simulation: 

Computer simulations are valuable tools for the analysis of investment outcomes, production processes, scheduling and maintenance activities.

4. Heuristic methods:

 Heuristic methods involve set of rules, which facilitate solutions of scheduling, layout and distribution problems when applied in a consistent manner.

5. Network analysis techniques:

 Network approaches include decision trees, CPM and PERT methods can identify alternatives of action and controlling the activities.

6. Utility theory:

Utility theory or preference theory allows decision-makers to incorporate their own experience and values into a formalized decision structure.


Farhan Hassan Al Shammari

Twitter: @farhan_939

E-mail: fhshasn@gmail.com

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