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Title: Estimating the value of decisions relating to managing and developing software-intensive products and projects
Authors: Mendes, E
Turhan, B
Rodríguez, P
Freitas, V
Keywords: Value-based decision making;Software product and project management;Bayesian network;Value-based software engineering
Issue Date: 2015
Publisher: ACM
Citation: Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering, Beijing, China, 21 October, pp. 1-4, (2015)
Abstract: The software industry’s current decision-making relating to product/project management and development is largely done in a value neutral setting, in which cost is the primary driver for every decision taken. However, numerous studies have shown that the primary critical success factor that differentiates successful products/projects from failed ones lie in the value domain. Therefore, to remain competitive, innovative and to grow, companies must change from cost-based decision-making to value-based decision-making where the decisions taken are the best for that company’s overall value creation. Our vision to tackle this problem and to provide a solution for value estimation is to employ a combination of qualitative and machine learning solutions where a probabilistic model encompassing the knowledge from different stakeholders will be used to predict the overall value of a given decision relating to product management and development. This vision drives the goal of a 3-year research project funded by the Finnish Funding Agency for Technology and Innovation (Tekes), with the participation of several industry partners.
ISBN: 978-1-4503-3715-1
Appears in Collections:Dept of Computer Science Research Papers

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