Definition of AHP: “Analytical Hierarchy Process (AHP) is an approach to decision making that involves structuring multiple choice criteria into a hierarchy, assessing the relative importance of these criteria, comparing alternatives for each criterion, and determining an overall ranking of the alternatives”, as defined by DSS Resources.
The concept of AHP was developed, amongst other theories, by Thomas Saaty, an American mathematician working at the University of Pittsburgh.
What is analytical hierarchy process (AHP)?
By organizing and assessing alternatives against a hierarchy of multifaceted objectives, AHP provides a proven, effective means to deal with complex decision making. Indeed, AHP allows a better, easier, and more efficient identification of selection criteria, their weighting and analysis. Thus, AHP reduces drastically the decision cycle.
Benefits of the analytical hierarchy process (AHP)
AHP helps capture both subjective and objective evaluation measures, providing a useful mechanism for checking the consistency of the evaluation measures and alternatives suggested by the team thus reducing bias in decision making.
AHP allows organizations to minimize common pitfalls of decision making process, such as lack of focus, planning, participation or ownership, which ultimately are costly distractions that can prevent teams from making the right choice.
Prescription of the analytical hierarchy process (AHP)
AHP is very useful when the decision-making process is complex, for instance, by being unstructured. Indeed, when the decision cycle involves taking into account a variety of multiple criteria which rating is based on a multiple-value choice, AHP splits the overall problem to solve into as many evaluations of lesser importance, while keeping at the same time their part in the global decision.
Steps of the analytical hierarchy process (AHP)
- The goal is to structure the problem into humanly-manageable sub-problems.To do so, iterating from top (the more general) to bottom (the more specific), split the problem, which is unstructured at this step, into sub-modules that will become sub-hierarchies. Navigating through the hierarchy from top to bottom, the AHP structure comprises goals (systematic branches and nodes), criteria (evaluation parameters) and alternative ratings (measuring the adequacy of the solution for the criterion).
Each branch is then further divided into an appropriate level of detail. At the end, the iteration process transforms the unstructured problem into a manageable problem organized both vertically and horizontally under the form of a hierarchy of weighted criteria.
By increasing the number of criteria, the importance of each criterion is thus diluted, which is compensated by assigning a weight to each criterion.
Assign a relative weight to each criterion, based on its importance within the node to which it belongs. The sum of all the criteria belonging to a common direct parent criterion in the same hierarchy level must equal 100% or 1. A global priority is computed that quantifies the relative importance of a criterion within the overall decision model.
Score alternatives and compare each one to others. Using AHP, a relative score for each alternative is assigned to each leaf within the hierarchy, then to the branch the leaf belongs to, and so on, up to the top of the hierarchy, where an overall score is computed.
Compare alternatives and select the one that best fits the requirements.
Web resources about the analytical hierarchy process
- Fundamentals of Decision Making and Priority Theory With The AHP or Analytic Hierarchy Process
by Thomas L. Saaty, “The father of AHP”
- HIPRE Decision making, systems intelligence and decision support
- AHP or The Analytical Hierarchy Process: A Step-by-Step Approach
by Dr. S Tom Foster & Dr. Gerald LaCava
- Decision Support Tools
from University of Cambridge :: Department of Engineering
- Excel Spreadsheet for AHP (Analytical Hierarchy Process)
- Improving the Faculty Selection Process in Higher Education: A Case for AHP or Analytical Hierarchy Process
by John R. Grandzol, Bloomsburg U of Pennsylvania