When running tens of projects in parallel, you’re sure to face colissions. It is usually about resources, of course. How to resolve them? Man in charge might feel what needs to be done in such cases, but it’s not easy to communicate the decision without a proper explanation as every project manager, resource manager and business manager has his or her own view. This is where decision support systems come into play and Analytic Hierarchy Process (AHP) as defined by Thomas L. Saaty in the 1970s is one them.
AHP is a typical divide and conquer solution to tackling complexity. The idea is to divide a complex decision into smaller, manageable evaluations, which are then recombined into the final metric, which helps you make a decision.
This is not a one way process. AHP might propose a different solution than you expect and it enables you to backtrack the calculation to help you understand the model by which the solution was proposed. You can then either agree with the model or correct it, to better reflect the real situation.
As written on Wikipedia, AHP provides a comprehensive and rational framework for structuring a problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions.
An interesting article appears on Robust Decission: Why pairwise comparisons are a waste of time for finding criteria importance. David G. Ullman presents a faster approach, especially usefull with more criteria.