Research Article Predicting Defects Using Information Intelligence Process Models in the Software Technology Project Manjula Gandhi Selvaraj, 1 Devi Shree Jayabal, 2 Thenmozhi Srinivasan, 3 and Palanisamy Balasubramanie 4 1 Department of Computer Applications, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu 641 014, India 2 Department of Electrical and Electronics Engineering, Coimbatore Institute of Technology, Coimbatore, Tamil Nadu 641 014, India 3 Department of Computer Applications, Gnanamani College of Technology, AK Samuthiram, Pachal Post, Namakkal District, Tamil Nadu 637 018, India 4 Department of Computer Technology (PG), Kongu Engineering College, Perundurai, Tamil Nadu 638 052, India Correspondence should be addressed to Manjula Gandhi Selvaraj; krishnasmgjv@gmail.com Received 16 April 2015; Accepted 28 April 2015 Academic Editor: Venkatesh Jaganathan Copyright © 2015 Manjula Gandhi Selvaraj et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. A key differentiator in a competitive market place is customer satisfaction. As per Gartner 2012 report, only 75%–80% of IT projects are successful. Customer satisfaction should be considered as a part of business strategy. e associated project parameters should be proactively managed and the project outcome needs to be predicted by a technical manager. ere is lot of focus on the end state and on minimizing defect leakage as much as possible. Focus should be on proactively managing and shiſting leſt in the soſtware life cycle engineering model. Identify the problem upfront in the project cycle and do not wait for lessons to be learnt and take reactive steps. is paper gives the practical applicability of using predictive models and illustrates use of these models in a project to predict system testing defects thus helping to reduce residual defects. 1. Introduction A project is temporary endeavor with defined objectives. Project management involves managing the project through- out the life cycle. Project life cycle includes initiation phase, planning phase, executing phase, monitoring and control phase, and finally closedown phase. e challenge lies in understanding and meeting the project goals with the defined project constraints. Every project is unique and needs to be planned well. A project has a defined start and end date. Project management is applicable across industries like production, information technology, and textile to name a few. In the information technology industry, project man- agement plays a crucial role. Industry experts have high- lighted the importance of project management. 20%–25% of IT projects fail due to poor project management. Project management principles need to be understood well by the technical managers. Proactive management is the key for success of any project. Ability to predict project outcomes and take preventive actions will determine the success of the project. e focus on shiſting leſt in the project life cycle is vital. Self et al. [1] highlighted the importance of customer satisfaction measurement. Johnson and Gustafsson [2] and Peppers and Rogers [3] studied how customer satisfaction can be improved and customer relationship managed using strategic frameworks. McConnell and Huba [4] discuss how loyal customers become a volunteer sales force. Shiſt leſt approach is one of the approaches where the focus is to concentrate on the upstream activities. e intent is to reduce the defect leakage upfront such that there is less impact on downstream activities. is approach is applicable for any type of industry. In a soſtware development project, the shiſt leſt refers to section of quality management concerned with prevention planning. Designing the shiſt leſt strategy is important. Focus should be to improve overall operational efficiency and ensure early defect detection while Hindawi Publishing Corporation e Scientific World Journal Volume 2015, Article ID 598645, 6 pages http://dx.doi.org/10.1155/2015/598645