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Early Value Argumentation and Prediction: An Iterative Approach to Quantifying Feature Value

  • Aleksander Fabijan
  • Helena Holmström Olsson
  • Jan Bosch
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9459)

Abstract

Companies are continuously improving their practices and ways of working in order to fulfill always-changing market requirements. As an example of building a better understanding of their customers, organizations are collecting user feedback and trying to direct their R&D efforts by e.g. continuing to develop features that deliver value to the customer. We (1) develop an actionable technique that practitioners in organizations can use to validate feature value early in the development cycle, (2) validate if and when the expected value reflects on the customers, (3) know when to stop developing it, and (4) identity unexpected business value early during development and redirect R&D effort to capture this value. The technique has been validated in three experiments in two cases companies. Our findings show that predicting value for features under development helps product management in large organizations to correctly re-prioritize R&D investments.

Keywords

Continuous experimentation EVAP QCD Data-driven development Customer-driven development 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Aleksander Fabijan
    • 1
  • Helena Holmström Olsson
    • 1
  • Jan Bosch
    • 2
  1. 1.Faculty of Technology and SocietyMalmö UniversityMalmöSweden
  2. 2.Department of Computer Science and EngineeringChalmers University of TechnologyGöteborgSweden

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