PPMP20012 Unit Portfolio: PM Application Systems for Project Execution

This portfolio for PPMP20012 examines the critical role of project management (PM) application systems in achieving both internal and external project objectives. It covers various project selection methods, including cost-benefit ratio, economic models, payback period, discounted cash flow, and net present value, emphasizing the importance of selecting the most suitable method. Furthermore, it discusses how PM application systems contribute to effective knowledge management and decision-making, compares manual and electronic systems across PM knowledge areas, and explores how these systems aid in performance monitoring and change management. The portfolio also proposes appropriate PM application systems for successful project execution across different industries and discusses contemporary developments in their use.

(Insert Student Name) / (Insert Student Number) - PPMP20012 Unit Portfolio for Week 1
Week 5 Topic: 5. Explain the importance of appropriate selection of project management (PM) application
systems in regards to meeting the internal and external objectives of a project
Reading samples Learning
outcomes
of the unit
Learnings from your weekly study, experience, this and
prior unit readings and assignments
Supporting
documentation
including any
prior learning
 SEBoK
 Part 3: Systems
Engineering and
Management: Knowledge
Area: Systems
Realization;
 Part 3: Systems
Engineering and
Management: Knowledge
Area: Systems
Deployment and Use;
 Part 3: Systems
Engineering and
Management: Knowledge
Area: Systems
Engineering
Management;
 Part 3: Systems
Engineering and
Management: Knowledge
Area: Product and Service
Life Management;
 Part 3: Systems
Engineering and
Management: Knowledge
Area: Systems
Engineering Standards;
 Kerzner (2013) Chapters
5. Explain the
importance of
appropriate
selection of
project
management
(PM)
application
systems in
regards to
meeting the
internal and
external
objectives of a
project.
The project management framework is comprises of different knowledge areas
such as resource management, cost and time management, quality
management, scope management, procurement management and risk
management. Each of these knowledge areas are required to be checked by the
project associates to ensure success or failure of the project. It has been learnt
that success and failure of any project is dependent on the project selection
approach.
The manager, stakeholders and project team members re required to choose
the most suitable project selection method to meet the objectives and goals
that are primarily set by the organization. In order to meet the external and
internal project objectives manager should also focus on project component
integration, scope management, time and schedule management,
communication management, resource and human resource management and
stakeholder management.
While manage any project successfully the project manager and team members
are required to select the most suitable project selection method among the
above mentioned. This week learning discusses different project selection
methods such as cost benefit ratio, economic model, payback period, discount
cash flow and net present value.
Therefore, it can be said that the manager should select the most suitable
project selection method among these mentioned. Apart from this, Internal Rate
of Return (IRR), is the other project selection method that is helpful for project
success.
PPMP20012 lecture
notes
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(Insert Student Name) / (Insert Student Number) - PPMP20012 Unit Portfolio for Week 1
Reading samples Learning
outcomes
of the unit
Learnings from your weekly study, experience, this and
prior unit readings and assignments
Supporting
documentation
including any
prior learning
23;
 AS/NZS 15288:2015
Annex E
Optional Readings
 AS ISO 21504:2016
Web Sites
YouTube: What is Portfolio
Management vs. Project
Management?
References
Gür, Ş., Hamurcu, M., & Eren, T. (2016). Using analytic network process and goal programming methods for project selection in the public institution. Les
Cahiers du MECAS, 13, 36-51.
Liu, F., Chen, Y. W., Yang, J. B., Xu, D. L., & Liu, W. (2019). Solving multiple-criteria R&D project selection problems with a data-driven evidential reasoning
rule. International Journal of Project Management, 37(1), 87-97.
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