Using Bayesian Network to estimate the value of decisions within the context of Value-Based Software Engineering
Emília Mendes, Mirko Perkusich, Vitor Erick Cardoso Freitas, João Pedro Nunes · 2018
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 to value-based decisionmaking where the decisions taken are the best for that company's overall value creation. This paper details a case study where value-based decisions made by key stakeholders to select features for the next sprint of an Internet of Things (IoT) project, stored in a decisions database, were used to build and validate a value estimation model. This model's goal was to estimate the overall value contribution that each feature being discussed during a decision-making meeting would bring to the company, if selected for implementation. The estimation technique employed was Bayesian Network, and validation results were quite positive.