Earned Value Management (EVM) has been a well-known methodology used since the 1960s when the US department of defense proposed a standard method to measure project performance. This system relies on a set of often straightforward metrics to measure and evaluate the general health of a project. These metrics serve as early warning signals to timely detect project problems, or to exploit project opportunities. A key aspect of EVM is to estimate the completion cost of a project by considering both cost and schedule performance indices. However, good performance of cost and schedule performance indices does not necessarily guarantee cost effectiveness of the project regardless of the overhead costs. The reason is because, in most project-based organizations, overhead costs constitute a significant proportion of the total costs. However, EVM indices are usually calculated in the absence of the so-called overhead costs. This paper, first, seeks to remedy this problem by proposing a practical procedure of allocating overhead costs in project-based organizations. Then the traditional EVM indices are revised by consider-ing the allocated overhead costs. Finally, a case study demonstrates the applicability of the proposed method for a real-life project.

As the need for software increased, the number of software firms and the competition among them also increased. The software companies in developing countries like India can no longer survive based on cost advantage alone. The firms need to deliver competitively priced quality software products on time. This can be achieved through quantitatively managing the different phases or sub processes in software development process. But quantitative management of a process consisting of a set of interlinked sub processes or stages with the output of one sub pro-cess influencing that of subsequent stages and final output is not easy. The process performance models developed for quantitative management of software development process often model the final outcome in terms of factors from various stages together or focuses only on quantitatively managing a particular sub process independently. In manufacturing and other engineering indus-tries, the processes with multiple sub process are monitored and controlled using multistage pro-cess control methodology. This paper is an application of multistage statistical process control for managing the software development process. The suggested methodology is a combination of process performance models and control charts. The proposed methodology can be easily im-plemented for controlling various types of software projects like development projects, incre-mental development projects, testing projects etc. The methodology also provides the project manager the opportunity to tighten or relax the control at various sub processes based on the pro-ject team’s strengths and still achieve the goal on the final outcome.

In the era of technology, the demand of the software development increases at a very high speed, as software has touched the human’s life in all aspects. The better quality software development acquiring minimum development time leads to the team work in which a group of people has been formed that work together in a team for the software development. One of the most significant issues in effective and efficient teamwork is the team leader selection because the team lead-er is the person in any team that is going to handle all types of managerial activities such as leadership, motivation to others, etc. The team leader selection process may be dependent on numerous conflicting selection indexes that make it a Multi-Criteria Decision Making (MCDM) problem. In the present research, an MCDM approach namely, Euclidean Distance Based Approximation (EDBA) which is based on the calculation of the composite distance value for each alter-native from a hypothetical optimal point is presented. The result of this study provides a comprehensive ranking of team leaders that leads to the right selection of team leader in information technology (IT) sector.