PROJMGNT 7024 : Complex Project Management

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PROJMGNT 7024 : Complex Project Management

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PROJMGNT 7024 : Complex Project Management

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Course Code: PROJMGNT 7024
University: The University Of Adelaide

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Country: Australia

Is the methodology of parametric estimating appropriate to projects in the non-engineering domain, such as welfare projects? Is so then how is that the case? If not then why is that the case?

This report is going to discuss about the methodology that is described by Terry Cooke-Davies in the book Aspect of Complexity. The main objective of this report is to discuss about the parametric estimation in non-engineering fields (Brockwell & Schlemm, 2013). Parametric estimate is calculated by calculating the time and cost required per unit. The approaches that are estimated with the parametric model will be discussed in the report.
Parametric Estimation in Non-Engineering:
Parametric estimation is used to analyze the time and the cost required for building and completing a project (Cespedes & Sun, 2014). This helps in calculating the time and money faster than other projects. The variables are being used in the parametric estimation for critically analyzing the cost required for completion of the project and the estimated period. The book Aspect of Complexity describes different aspect of parametric estimation in non-engineering field. The main aim of parametric estimation is to determine the cost and time (Heess, et al., 2015).   Many approaches are made in the parametric model for estimation, this are as follows:

The predicted limitations of parametric estimation model
The cost and the time required are being calculated and the value is returned to Return on Investment (ROI)
The data and all the information necessary and related to this projects are being addressed , so that it can help while data designing ,scheduling the project and cost estimation.
Data after collection are normalized for determining the  quantity, finances, manufacture rate, and for unit capacity.
Some variables are related to cost and are independent of the factors. On the basis of this variables, theory is formulated.
In order to analyze the significance, the theory is being tested.
Cost is being estimated for further changes that are likely to be made in the future.

From the article given, it can be said that the parametric estimation is used in the projects that involves some sort of technical work. Several technological development models are used in the parametric estimation. However, the main discussion in the article is that parametric estimation can be used in the non-engineering projects.
In the above discussion, it is clearly described that in non-engineering projects also parametric estimation can be used. The non-engineering project can use the parametric estimation method for fulfilling their requirements. There is a estimated time for every project and the cost analyzed for each project is being assumed from the beginning itself , so that it can help the manager to understand the feasibility (Babadi & Brown, 2014). For evaluating the cost, the method of estimation is being used. Whether the project is engineering one or a non-engineering one, the cost estimation is necessary and time evaluation is also necessary. There is a minimum requirement for every project , such as time and money and the basic materials for planning the project. The parametric estimation will become easier If the project is having these data then the , if the time and the money is involved in the project is being analyzed from the beginning itself (Guo., et al.2014) . After knowing all the requirements , the method will start normalizing the data according to the requirement. For analyzing the collected data hypothesis is made. The hypothesis evaluates the growth of the project that is directly associated with the revenue incorporated in it and the time required in completion.
There is a fixed budget maintained by every projects based on the period, even in the non-engineering projects like welfare project. There is a huge difference between both the projects.  Mainly the engineering project contains technical tasks and evaluation whereas, the non engineering tasks contains less number of technical work (Cooke-Davies, 2011). Time and the requirements are more or less same for both the projects. Irrespective of the project type the material providers and the stakeholder remains same. According to the author Terry Cooke, the major problem that arises while dealing this type of projects are with the technologies involved in it , as the technologies are mature enough but  do not have the ability (Matzke, et al., 2013). Parametric evaluation helps the non engineering projects to achieve and deal with the requirements. There are some limitations to this and based on this assumptions is made. Normalization is done based on the requirements. The parametric estimation is useful in non-engineering projects for these factors.
From the above report , it can be concluded that parametric estimation is needed for non engineering projects. This helps the non-engineering project to easily calculate the cost and time evolved in the project. The factors on which the parametric estimation works are more or less same in the both projects. The cost drivers are being used in the reports. Basically the report aims at giving a idea on the use of parametric estimation in non engineering projects.
Babadi, B., & Brown, E. N. (2014). A review of multitaper spectral analysis. IEEE Trans. Biomed. Engineering, 61(5), 1555-1564.
Brockwell, P. J., & Schlemm, E. (2013). Parametric estimation of the driving Lévy process of multivariate CARMA processes from discrete observations. Journal of Multivariate Analysis, 115, 217-251.
Cespedes, M., & Sun, J. (2014). Adaptive control of grid-connected inverters based on online grid impedance measurements. IEEE Transactions on sustainable energy, 5(2), 516-523.
Cooke-Davies, T. (2011, August). Aspects of complexity: Managing projects in a complex world. Project Management Institute.
Guo, X., Liu, H., Mao, X., Jin, J., Chen, D., & Cheng, S. (2014). Willingness to pay for renewable electricity: A contingent valuation study in Beijing, China. Energy Policy, 68, 340-347.
Heess, N., Wayne, G., Silver, D., Lillicrap, T., Erez, T., & Tassa, Y. (2015). Learning continuous control policies by stochastic value gradients. In Advances in Neural Information Processing Systems (pp. 2944-2952).
Matzke, D., Dolan, C. V., Logan, G. D., Brown, S. D., & Wagenmakers, E. J. (2013). Bayesian parametric estimation of stop-signal reaction time distributions. Journal of Experimental Psychology: General, 142(4), 1047.

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