Date of Conferral
1-1-2011
Degree
Ph.D.
School
Management
Advisor
David Gould
Abstract
The worldwide software project failure rate, based on a survey of information technology software manager's view of user satisfaction, product quality, and staff productivity, is estimated to be between 24% and 36% and software project success has not kept pace with the advances in hardware. The problem addressed by this study was the limited information about software managers' experiences with data-driven decision making (DDD) in agile software organizations as a tool to improve software development productivity. The purpose of this phenomenological study was to explore how agile software managers view DDD as a tool to improve software development productivity and to understand how agile software development organizations may use DDD now and in the future to improve software development productivity. Research questions asked about software managers', project managers', and agile coaches' lived experiences with DDD via a set of interview questions. The conceptual framework for the research was based on the 3 critical dimensions of software organization productivity improvement: people, process, and tools, which were defined by the Software Engineering Institute's Capability Maturity Model Integrated published in 2010. Organizations focus on processes to align the people, procedures and methods, and tools and equipment to improve productivity. Positive social change could result from a better understanding of DDD in an agile software development environment; this increased understanding of DDD could enable organizations to create more products, offer more jobs, and better compete in a global economy.
Recommended Citation
Brown, Mary Erin, "Data-Driven Decision Making as a Tool to Improve Software Development Productivity" (2011). Walden Dissertations and Doctoral Studies. 1075.
https://scholarworks.waldenu.edu/dissertations/1075
Included in
Business Administration, Management, and Operations Commons, Databases and Information Systems Commons, Library and Information Science Commons, Management Sciences and Quantitative Methods Commons