Analytic Hierarchy Process
The Analytic Hierarchy Process (AHP) is a powerful decision-making technique that helps organizations prioritize options and make complex decisions with precision. By breaking down decisions into a structured hierarchy of criteria, AHP enables you to weigh alternatives and achieve consensus, ensuring that your choices align with strategic goals.
Build Consensus and Buy-in on Decisions!
Definitive Pro uses the Analytic Hierarchy Process (AHP), which is the world’s leading technique for multi-criteria decision-making.
- The Analytic Hierarchy Process (AHP) is a structured decision-making technique that helps in ranking and prioritizing options when making complex decisions involving multiple criteria. Developed by Thomas L. Saaty in the 1970s, AHP allows decision-makers to model a problem in a hierarchy, breaking it down into its constituent parts. This hierarchy typically consists of the goal at the top, followed by layers of criteria and sub-criteria, and finally the decision alternatives at the bottom. AHP uses pairwise comparisons and a scale of relative importance to assign weights to each element, allowing for a comprehensive evaluation of each alternative’s potential to achieve the overall goal.
- In the context of project portfolio management, AHP is particularly valuable because it provides a systematic framework to evaluate and prioritize projects based on multiple, often conflicting, criteria such as cost, risk, return on investment, and strategic alignment. By applying AHP, organizations can objectively assess the relative importance of these criteria and use that information to rank projects within the portfolio. This helps ensure that resources are allocated effectively, aligning the selected projects with the organization’s stratsegic goals and maximizing the overall portfolio value.
Our use of AHP in Definitive Pro:
- Removes group think and reduces bias and noise;
- Eliminates blind spots by supporting use of cross-functional teams to learn from each other;
- Measures the consistency of judgments for each participant and by the team;
- Measures the degree of consensus on each pairwise comparison;
- Offers the use of AI personas as participants to augment the team;
- Supports any use case involving multiple criteria, alternatives, and decision participants.