Module 2 Project Selection Models
Project Selection Models
Jose Rodriguez
QSO-640
Dr. Steven A. Coleman
11/30/14
Project Selection Models
In many organizations, the successful accomplishment of crucial goals and tasks in attained through projects. But, with the rapid adoption of project management in organizations, most of these organizations face issues with attempting to manage many projects. As a result, organizations face a lot of effort and time attempting to make the best project selection decisions possible. There two models utilized are non-numeric and numeric. Non-numeric models do not exercise values or numbers at inputs; they rather rely on other relative data. On the other hand, numeric models use numbers either objectively or subjectively as inputs for the processes entailed in project selection (Kerzner, 2001).
The advantages of numeric models are: they are easy to understand and use, all determine cash flows from known accounting data, some models account for project risk, model output is on an absolute profitability scale, model output is familiar to business decision makers (Heerkens, 2002)
However, numeric models pose several disadvantages: they are all subject to errors in the data for the project’s early stages, they ignore non-monetary factors other than risk, all discounting models are non-linear and the effect of errors or changes are not evident to most decision makers
The main advantages of non-numeric models are: they as well are easy to use and understand, they can easily be altered to assist changes in the managerial policy and/or environment, they are direct reflections of managerial policy and that they allow multiple criteria to be used for decision making and evaluation (Kerzner, 2001)
The disadvantages are that they are un-weighted models which consider that all criteria are significant and that because they are so easy to use, non-numeric models are useful to the incorporation of a big number of measures. With respect to selection
Jose Rodriguez
QSO-640
Dr. Steven A. Coleman
11/30/14
Project Selection Models
In many organizations, the successful accomplishment of crucial goals and tasks in attained through projects. But, with the rapid adoption of project management in organizations, most of these organizations face issues with attempting to manage many projects. As a result, organizations face a lot of effort and time attempting to make the best project selection decisions possible. There two models utilized are non-numeric and numeric. Non-numeric models do not exercise values or numbers at inputs; they rather rely on other relative data. On the other hand, numeric models use numbers either objectively or subjectively as inputs for the processes entailed in project selection (Kerzner, 2001).
The advantages of numeric models are: they are easy to understand and use, all determine cash flows from known accounting data, some models account for project risk, model output is on an absolute profitability scale, model output is familiar to business decision makers (Heerkens, 2002)
However, numeric models pose several disadvantages: they are all subject to errors in the data for the project’s early stages, they ignore non-monetary factors other than risk, all discounting models are non-linear and the effect of errors or changes are not evident to most decision makers
The main advantages of non-numeric models are: they as well are easy to use and understand, they can easily be altered to assist changes in the managerial policy and/or environment, they are direct reflections of managerial policy and that they allow multiple criteria to be used for decision making and evaluation (Kerzner, 2001)
The disadvantages are that they are un-weighted models which consider that all criteria are significant and that because they are so easy to use, non-numeric models are useful to the incorporation of a big number of measures. With respect to selection
References: Heerkens, G. (2002). Project management. New York: McGraw-Hill. Kerzner, H. (2001). Project management: A systems approach to planning, scheduling, and controlling. New York: John Wiley. Meredith, J & Mantel, S. (2003). Project Management: A managerial approach. New Jersey: John Wiley & Sons. Pinto, J. (2010). Project Management: Achieving Competitive Advantage, Second Edition. New York: Prentice Hall.