?? Prioritizing complex project portfolios just got easier!

?? Unlock the Power of Prioritization with Analytic Hierarchy Process (AHP) ??

The Analytic Hierarchy Process (AHP) is a game-changing decision science solution that can help you make informed decisions and maximize your project portfolio's success!

?? AHP allows you to break down your goals into individual components and determine their relative importance through a pairwise approach. This structured methodology ensures you consider all the factors and make well-informed choices.

This process of decomposition makes the decision-making process less overwhelming and more manageable. What's more, AHP uses a unique scale of relative importance, known as the Saaty scale, to assign numerical values to each alternative based on its comparative importance.

This allows the conversion of empirical data into mathematical models, a distinctive feature of AHP. Once all comparisons are made and relative weights are assigned, AHP calculates the numerical probability of each alternative. The higher the probability, the more likely it is that the alternative will achieve the desired goal.

?? Perfect for large organizations, AHP bridges the gap between strategy and execution. It emphasizes structured collaboration and group decision-making, enabling your team to align their priorities and work towards a common goal.

?? The University of New South Wales has identified AHP as one of the best models for prioritization, surpassing other alternatives. Its effectiveness lies in enabling data-led decisions and handling risks.

AHP helps project managers prioritize projects in a portfolio by comparing them pairwise concerning a goal and assigning them relative weights. AHP also helps reduce human errors, such as bias and inconsistency in the decision-making process.        

• the limitation of the AHP at the end of the article

Story:

Samera was a project manager at a software company that had several ongoing projects. She had to decide which projects to allocate more resources and attention to, based on their :

• strategic importance,
• customer satisfaction,
• technical feasibility, and
• profitability.

She decided to use the Analytic Hierarchy Process (AHP) to help her with this task.

She first defined the goal of her decision, which was to select the best projects for the company. Then, she identified the four criteria that she mentioned above and assigned them relative weights based on her judgment. She used a scale of 1 to 9, where 1 meant equal importance, and 9 meant extreme importance. She compared each pair of criteria and filled a matrix with her ratings.

For example, Samera rated

• strategic importance as 5 times more important than technical feasibility,
• and customer satisfaction as 3 times more important than profitability.

She then normalized the matrix and calculated the weights of each criterion.

She found that strategic importance had the highest weight (0.46), followed by customer satisfaction (0.26), profitability (0.16), and technical feasibility (0.12).

Next, she listed the six projects that she had to prioritize: A, B, C, D, E, and F. She repeated the same process of pairwise comparison for each project with respect to each criterion. For example, she rated project A as 7 times more preferable than project B in terms of strategic importance, and project C as 4 times more preferable than project D in terms of customer satisfaction. She then normalized each matrix and calculated the weights of each project for each criterion. She found that Project A had the highest weight for strategic importance (0.38), project C had the highest weight for customer satisfaction (0.36), project E had the highest weight for profitability (0.34), and Project F had the highest weight for technical feasibility (0.32).

Finally, she aggregated the weights of each project by multiplying them with the weights of each criterion and adding them up. She obtained the overall scores and ranks of each project. She found that Project A had the highest score (0.28) and rank (1), followed by project C (0.24, 2), project E (0.19, 3), project F (0.14, 4), project B (0.09, 5), and project D (0.06, 6).

Samera was satisfied with the results of the AHP method. She decided to allocate more resources and attention to projects A, C, and E, as they were the most aligned with the company's goals and values. She also checked the consistency of her comparisons and found that they were within acceptable limits. She thanked the AHP method for helping her make a rational and transparent decision.

To use AHP for project prioritization, you need to follow these steps:

1. Define the goal and the criteria for selecting projects
2. Create a hierarchy of the goals, criteria, and projects
3. Collect pairwise comparison data from experts or stakeholders
4. Calculate the relative weights of the requirements and projects using a mathematical formula
5. Aggregate the weights and rank the projects according to their scores
6. Check the consistency of the comparisons and revise them if needed

AHP is a useful tool that can help you make informed decisions about your projects. However, it does require some expertise and effort to use it correctly.

There are software tools and online calculators available to assist you with the AHP calculations.

Some limitations of AHP are:

1. Getting pairwise comparisons from experts or stakeholders is hard and time-consuming, especially with many criteria and alternatives.
2. It can be subjective and inconsistent, as the judgments depend on the personal preferences and knowledge of the decision-makers.
3. It is important to note that even small changes in the comparison matrix can have a significant impact on the ranking of alternatives. Therefore, it is crucial to exercise sensitivity and caution while making any modifications to the comparison matrix.
4. It can be affected by rank reversal, which means that adding or removing an alternative may change the order of the existing options.
5. It can be challenged by complex scenarios, such as dynamic, uncertain, or non-linear problems, that require more sophisticated modeling and analysis.