OR utilizes modeling as a way to recognize the problem and then ultimately solve the problem. From recognition to the decision; the OR process is made up of eight distinct phases:

Recognition of a Need: This phase is defined as the perceptions of needing some sort of resolution or need for improvement.

Problem Formulation: This phase takes the problem, defines it, and assigns inputs to be used in the next phase. These inputs are variables, parameters and constraints.

Model Construction: This phase takes the variables, parameters and constraints and constructs a mathematical representation of the problem defined in phase 2. The purpose of this phase is to create the best model so that the variables can be changed and observed.

Data Collection: This phase utilizes the model and the different inputs to the model, which reflect actual problem conditions. Data that is hard to collect include: preferences, opinions, and quality. These items are known as soft data.

Model Solution: This phase actually utilizes the input data and mathematical algorithms to produce results.

Model Validation and Analysis: This phase is a self-checking phase. It makes sure that the first four phases are free of errors and that the model accurately represents the problem hand. If there are errors in any of the processes, phase 2 to phase 5 must be redone.

Interpretation of Results: This phase is concerned with examining the results and makes sure that the solution is the optimum or best solution. Tradeoffs can occur and this is known as sub-optimization.

Decision Making and Implementation: Once a project reaches this phase, the OR is done and a decision must be made. The outcome of the decision may not directly be related to the results. Other existing external factors play a part in the decision process. These factors can be personal, ethical or political. Whatever the reason, the OR process has been accomplished and this gives management another tool for making a decision on the problem.