The Analytic Hierarchy Process (AHP) enables decision makers to structure decisions hierarchically with the overall goal of the decision at the top of the model, strategic objectives in the higher levels, evaluation criteria in the middle levels, and alternative choices at the bottom. The AHP provides a structured framework for setting priorities on each level of the hierarchy using pair-wise comparisons, a process of evaluating each pair of decision factors at a given level on the model for their relative importance with respect to their parent. The consistency of the judgments is tracked using the rigorous math analytics behind the AHP to validate the decision process. In cases where inconsistency is above 10% it is recommended that the criteria and judgments be revisited. Decision makers are then able to create a model of their priorities where the weight of the decision is distributed from the goal downwards. If a user increases the weight of a criterion, the alternatives that performed well on that criterion will always get higher scores. This sensitivity analysis is portrayed graphically in the Decision Lens software products and is extremely valuable for testing the impact of changing priorities on alternative business decision choices.
In Decision Lens, the AHP is integrated with a genetic algorithm that is integrated into the decision engine for programming optimizer to enable decision makers to define business rules for budget allocation. They can then allocate resources across investment alternatives to maximize business value. Using this optimization capability, organizations can effectively manage investments in projects and people using a true portfolio-based framework rather than a project-based framework.