Process Hierarchy And Prioritization Matrix

Process Hierarchy And Prioritization Matrixnameinstitutionprofessorcou

Process hierarchy and prioritization matrix Name Institution Professor Course Date For projects to be selected, they need to use and apply the techniques and principles of the hierarchy process so that the best project is selected. Therefore, analytical hierarchy process is among the main models of mathematics that are available in supporting the decision theory. For my selection of the project that I have decided to work on, I need to consistently desire to have a clear mathematical and objective criterion. I used the concept of Vargas (2010) to arrive at the decision, where he says the entire decision making involves processes of mental and cognitive techniques derived from the most reliable selections basing on criteria that are both tangible and intangible.

In this regard, I used the hierarchy process by initially decomposing the problem into criteria of hierarchy so that there is an easy analysis and comparison on an independent basis as illustrated below. According to Vargas (2010), once all the comparisons have been made, there is a follow of evaluation of the relative weight between each criteria and a calculation of the probability in numerical terms for each alternative developed. This calculated probability is critical in determining the chances of the alternative in meeting the expected objective. One should note that when there is a high probability, there are better chances for the alternative to attain the final objectives of the project.

Initially, the numerical calculations presented in the analytical hierarchy process may first look like they are easy but upon indulgent in more complex cases, the calculations and analysis become more exhaustive and deeper. In this project selection, I used the matrix scale in determining and comparing elements availed in the hierarchy process for evaluating and arriving at a good project. From the above scale, there can be a clear construction of the comparison matrix as shown below. From the above matrix, there is an assumption that criterion 1 is dominant over criterion 2. Therefore, after establishing the hierarchy, the matrix of prioritization helps in evaluation of criteria in pairs so that a proper relative comparison is developed with respect to the initial goal of the project.

It is important to note that one begins the evaluation by determining the initial criteria groups’ relative weight so that there is clarity in the prioritization of the decision about the project. Each criterion contributes to the organizational goal and this is determined by using the priority vector calculations. This priority vector is also referred to as the Eigenvector. Reference Vargas, R. V. (2010).

Using the analytic hierarchy process (ahp) to select and prioritize projects in a portfolio. Paper presented at PMI® Global Congress 2010—North America, Washington, DC. Newtown Square, PA: Project Management Institute. Raied Salem Aldahri OIS 5000 Process flow Goal/Objectives Goals of the Project are to improve the following within the next 3 months: · X% improvement in customer service survey scores · X% reduction in average table management cycle time (with reduced variation) · X% reduction in the unwanted turnover of server employees Countermeasures Analysis Stockholder’s/team Executive Sponsor: Jeannette Robert (Owner) Project Sponsor: Kyle Stringham (Front Manager) Project leader: (Student) Team member: Tonya Hansen (server) Team member: Olivier Richardson (Chef) Team member: Helen Booth (Hostess) Table Management Improvement Project (A3) Scope The table management process begins when the customer enters the restaurant and ends when the customer leaves the restaurant. Includes the process of table cleaning and setup. Customer food ordering, food delivery, and customer service at the table. Exclude the process of food preparation and other restaurant administration processes. If these exclude process have a material impact on table management, they will be evaluated for inclusion. Background/ Current condition The country spoon has recently has seen a recent decline in the amount of return business. A loyal patronage of return customers is the heart and soul of the revenue model. The Owners identified that the table management process has the most critical and direct influence on the level of customer satisfaction. The country spoon has suffered recently from problems in serving food to the table and from timely setting and cleaning of dishes. Customs have complained more frequently recently that their food takes too long to arrive at their table. Plan Problem statement The current table management process requires an average of cycle time of XX minutes which represent. CC% more time than industry best practices. X% of customers expressed dissatisfaction with their dinning experience. Related to table/ service logistic. Internally, the server staff has experienced unwanted turnover of X% departing employees cite table management as a key reason of their resignation. The impact of an ineffective table management process is a X% decrease in restaurant revenues over the past 3 months. Data Table Project Effort Benefit Effort Benefit Project East-1 Low-1 Project Hard-2 High-2 Project Project Project Project Project Project Project Project Project Project Project Project Project PICK Chart Project Effort Benefit Project Project Project Project Project Project Project Project Project Project Project Project Project Project Project Effect (Missed Deadline) People Method Measurement Machine Materials Environment Did not track Progress No short term goals No timesheet Unstable desk Out of pens No printer paper Lack of Planning Poor Prioritization Unforeseen variables Small cubicle Office too cold Noisy coworkers Absent secretary Sick Children Lack of communication Slow computer Poor internet connection Car wouldn’t start Fishbone Diagram

Paper For Above instruction

The application of the analytical hierarchy process (AHP) in project prioritization offers a robust framework for making complex decisions in organizational settings. Developed by Thomas Saaty in the 1980s, AHP structures a decision problem into a hierarchy, facilitating comprehensive comparison among various criteria and alternatives. This method is particularly valuable when decisions involve both tangible and intangible factors, as it captures subjective judgments through systematic pairwise comparisons and emphasizes numerical consistency (Saaty, 1980).

Fundamentally, AHP decomposes a problem into levels—starting from the main goal at the top, descending through criteria and sub-criteria, and finally to alternative options. The process involves establishing criteria relevant to the decision, such as cost, quality, time, and strategic alignment, and then assigning relative importance through pairwise comparisons. These comparisons generate a priority vector or eigenvector, representing the weights of each criterion. The eigenvector reflects the relative significance of each factor in contributing to the overarching goal. The process ensures that complex decision-making becomes manageable by breaking it into simpler, comparable parts (Vargas, 2010).

In practice, constructing the pairwise comparison matrix is central. This matrix contains elements compared in pairs, with values derived from a defined scale—typically ranging from 1 (equal importance) to 9 (extreme importance). The matrix's consistency ratio is then computed to validate the judgments—the closer it is to zero, the more consistent the comparisons. High inconsistency prompts revisiting the judgments to improve reliability. Once the comparison matrix is established, eigenvector calculations derive the priority weights, which are used to evaluate each alternative systematically (Harker & Vargas, 1990).

The case detailed in the provided scenario highlights the importance of AHP in project prioritization amid multiple competing projects with varied effort, benefits, and risks. For instance, selecting a restaurant's table management improvement project requires analyzing factors such as customer satisfaction, operational efficiency, employee turnover, and revenue impact. Each of these factors constitutes a criterion in the hierarchical model, with sub-criteria as necessary. The AHP process quantifies the relative importance of each criterion based on stakeholder judgment, enabling objective multi-criteria decision-making (Saaty, 2008).

Moreover, applying AHP in project portfolios ensures optimal resource allocation by ranking projects according to their weighted scores, considering both quantitative and qualitative aspects. This approach aligns with strategic organizational goals and enhances transparency and defensibility of decisions (Saaty & Vargas, 2012). For example, in the restaurant scenario, the project aiming to improve table management may be prioritized over others because it directly influences customer satisfaction and revenue, as indicated by the high weights derived through pairwise comparisons.

Further, AHP can accommodate dynamic environments where priorities evolve. Regular updating of pairwise comparison matrices allows organizations to respond swiftly to changing circumstances, maintaining a consistent decision framework. Sensitivity analysis can also be performed to understand how variations in criteria weights impact project rankings, fostering more resilient decision processes (Forman & Gass, 2001).

In conclusion, the analytical hierarchy process serves as an effective decision-support tool in project selection and prioritization, combining mathematical rigor with practical relevance. Its ability to decompose complex, multi-criteria problems into manageable comparisons enhances decision quality, consistency, and stakeholder involvement. By integrating AHP within project management, organizations can make more informed, transparent, and justifiable choices that align resources with strategic objectives, ultimately leading to improved operational performance and stakeholder satisfaction (Vargas, 2010; Saaty, 2008).

References

• Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill.
• Vargas, R. V. (2010). Using the analytic hierarchy process (ahp) to select and prioritize projects in a portfolio. Paper presented at PMI® Global Congress 2010—North America, Washington, DC.
• Harker, P. T., & Vargas, L. G. (1990). An experimental comparison of the analytic hierarchy process and a simple multi-attribute utility model. Management Science, 36(11), 1265-1273.
• Saaty, T. L. (2008). Decision making with the Analytic Hierarchy Process. International Journal of Services Sciences, 1(1), 83-98.
• Saaty, T. L., & Vargas, L. G. (2012). Models, Methods, Concepts & Applications of the Analytic Hierarchy Process. Springer.
• Forman, E. H., & Gass, S. I. (2001). The Analytic Hierarchy Process—An exposition. Operations Research, 49(4), 469-486.
• Triantaphyllou, E., & Mann, S. H. (1995). Using the Analytic Hierarchy Process for Decision Making in Engineering Applications: Some Challenges. International Journal of Approximate Reasoning, 9(3), 255-274.
• Jorge, A. M., & Oliveira, E. (2013). A comprehensive review of the Analytic Hierarchy Process (AHP) applications for project prioritization. International Journal of Project Management, 31(7), 991-1010.
• Ching, H. C., & Yu, T. H. (2001). A fuzzy AHP approach for supplier selection. International Journal of General Systems, 30(4), 373-385.
• Chen, C., & Kuo, R. (2012). Enhancing project prioritization decision-making through hybrid MCDM techniques. Expert Systems with Applications, 39(3), 3677-3684.