The proposed research tackles the problem of planning the scope of product releases over time. Determining the scope of work (SOW) of each release involves both features as well as development activities. This problem is frequently encountered in planning continuing technology development projects (CTD projects), and especially hardware and/or software R&D. Here we aim to formulate a cluster analysis approach that generates the SOW by associating the developed components to releases based on similarity between their features such as common functionalities, tasks, and activities. This innovative algorithm will also incorporate another type of distance measure based on competition for common resources as well as the complementary or dissimilar nature of the features.
Current project scheduling methodology focuses mainly on the concept of a project as a one-time concentrated effort. However, CTD projects are the building blocks of a continuing activity divided into several intermediate projects leading to product Releases. Each release is composed of several new features, and the development of each feature requires a set of activities (some may overlap with activities of other features). Today's planning methodologies fail to cope with the unique characteristics of the CTD projects; in particular the fragmentation into releases is overlooked.
The goal of the CTD project scheduling goal is to cluster features in the most cost-beneficial manner, so as to balance the need to expedite feature completion and prepare the ground for future releases, subject to limited resources. The scheduler determines the components of each release (i.e. features included in release) based on the expected benefits from the implementation of the new feature and the efforts and the resources needed to implement the required activities as a whole. This presents a complex problem, as each project task is related to several features, and also competes for the same resources.
This project proposes a new methodology for the overall planning problem, by clustering the components into releases. The similarity of any two features is based on the weighted sum of efforts, resources and benefits related to their overlapping as well as distinct activities.
The research innovates in two ways:
§ It is the first methodology to tackle the planning and scheduling of product releases in a CTD project. This includes the determination of new features as well as the scheduling and release timeline. So far, this problem has been left solely to intuition, because there is no valid decision making process. This project will provide a decision support tool to answer key questions such as what to include/exclude in the next release and what benefits can be gained by postponing a release.
An adaptation of cluster analysis methods to the field of project management that calculates the cost-benefit tradeoff of features and components for upcoming releases.
