David Housman

FireAnt Project Engineering Plan

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Excerpt from Task 2 from “Process and Project Management” composed by Team “Time Boxer”, Rob Black, John Lee, Abhishek Shiroor, and myself.

Course taught by Professor Sheryl Root. Part of Master of Science in Software Management curriculum, Carnegie Mellon University, Silicon Valley.

Executive Summary

FireAnt is a highly innovative project set to take place in an organization with very little relevant maturity. The Application Lifecycle Management tool market is expected to be lucrative, feeding expectations of new entrants to the market. This plan recommends Extreme Programming (XP) be used for the FireAnt project. Even without tailoring, XP is a fairly good fit to the FireAnt project. XP also tailors well to the context of the FireAnt project: an early Spike, Remote Pair Programming help overcome the limitations of an unstable architecture and distributed team. Further, the team will be adjusted to meet the needs of the project and methodology by asking the Software Architect to don the hat of a Senior Developer.

This project should be carried out in four phases: the Minimum Viable Product, High Number of Instances, Application Administration, and Power User Features. Given current estimates and projected velocity, it is expected that the project will take approximately 16 weeks to conclude. This estimate is subject to several project risks; the most severe being architectural difficulties resulting from NDSS’s lack of experience in large scale, distributed software development.  Another large risk is related to story duration estimates.

NDSS’s FireAnt initiative is a foray into the uncharted territory of the commercial, enterprise software industry. The opportunity may seem vast and within easy reach. This may be the case. In all likelihood, it is not. The proposed FireAnt project is beset with risk. Some of these risks can be controlled- others cannot. Looming most heavily is that of time; a delay comes with huge penalties in opportunity and staffing costs. Improvements due to mitigation and tailoring aside, the residual exposure of this endeavor is substantial. The recommendations in this paper are an optimization of limited resources in the context of grand problems.

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