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Published in: Information Systems Frontiers 3/2008

01-07-2008

Team performance and information system implementation

Application of the progress curve to the earned value method in an information system project

Author: Malgorzata Plaza

Published in: Information Systems Frontiers | Issue 3/2008

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Abstract

Although the Earned Value Method (EVM), a multi-dimensional project control system, has been widely used since 1960, there has been little research focused specifically on its application in IS implementation. The management of IS projects—including the accurate forecasting of project duration—is complicated by the strong impact of the learning curve on the effectiveness of EVM. This study makes new contributions by advancing formulas for the accurate prediction of project duration, and by developing a decision support model in which the learning curve is fully integrated with EVM, and performance changes due to learning are isolated from other factors affecting project duration. The study makes three contributions to the understanding and use of EVM in IS implementation: (1) It provides an extended version of EVM, (2) it provides an illustration of the application of EVM to a real project situation based on empirical data from an ERP implementation project, and (3) it provides a theoretical basis for empirical studies of IS project control techniques. The decision support model can be used to determine both the learning curve coefficient and the project completion date during the early stages of a project, and it thus offers a significant practical contribution to the management of IS projects.

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Appendix
Available only for authorised users
Footnotes
1
Assumption 1 is used by various PM methodologies to assess duration of the project and its individual activities (Project Management Institute Standards Committee 2000).
 
2
On the majority of industrial projects, the team consists of fully trained and experienced members, no initial training is required, and the performance of the team will remain at a relatively stable level. Therefore, the impact of LC category factors can be neglected and SPI 1 can be used to accurately predict the project duration variance.
 
3
Note from our previous discussion that the L-curve represents the performance changes for a project resembling the situation at the educational institution and will most likely be selected for a project with significant in-house training during which team integration has occurred and a start-up effect will not be observed during the early stages of the project.
 
4
If the maximum error possible using the approximation cannot be higher than 5% of kT 1 then based on the Alternating Series Estimation Theorem \(\left| {\frac{{\left( {kT_1 } \right)^3 }}{{3!}}DT^3 } \right| = \frac{{\left( {kT_1 } \right)^3 }}{6}0.001 \leqslant 0.05kT_1 \), which gives kT 1 ≤ 17.3. Therefore, if for example, k is estimated as higher than 1.4 and the project is scheduled to take longer than 12 months, then the model will provide the required level of accuracy for DT < 0.1.
 
5
Note that the project manager can use Method 1 only if he is able to isolate the EM factors (see the discussion at the end of Section 4.3).
 
6
In EVM, instantaneous learning is assumed and the learning curve is depicted as a step function. In the EVM/PC model, the L-curve approaches the step function if PRI is close to 1, but is never equal to it. Therefore the results of EVM and EVM/LC model are close in the cases where the learning effect can be neglected or PRI approaches 1, but they will not be the same. Performance can be depicted as a step function in some projects, but since the very steep learning curve would still be a better approximation to reality, the results derived from the EVM/LC model are a closer approximation to the duration variance than those from EVM.
 
7
We provide the range for the assessment in order to test the sensitivity of the model.
 
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Metadata
Title
Team performance and information system implementation
Application of the progress curve to the earned value method in an information system project
Author
Malgorzata Plaza
Publication date
01-07-2008
Publisher
Springer US
Published in
Information Systems Frontiers / Issue 3/2008
Print ISSN: 1387-3326
Electronic ISSN: 1572-9419
DOI
https://doi.org/10.1007/s10796-008-9080-9

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