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Data-Driven Decision Making as a Tool to Improve Software Development Productivity

By Mary Erin Brown

Abstract

The worldwide software project failure rate, based on a survey of information technology software manager\u27s 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\u27 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\u27, project managers\u27, and agile coaches\u27 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\u27s 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

Topics: business administration, management, and operations;management sciences and quantitative methods;databases and information systems;library and information science, Business Administration, Management, and Operations, Databases and Information Systems, Library and Information Science, Management Sciences and Quantitative Methods
Publisher: 'IUScholarWorks'
Year: 2011
OAI identifier: oai:scholarworks.waldenu.edu:dissertations-2074
Provided by: Walden University

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