Early value argumentation and prediction: An iterative approach to quantifying feature value
Paper i proceeding, 2015

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.

EVAP

QCD

Data-driven development

Customer-driven development

Continuous experimentation

Författare

A. Fabijan

Malmö universitet

Helena Holmström Olsson

Malmö universitet

Jan Bosch

Chalmers, Data- och informationsteknik, Software Engineering

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

03029743 (ISSN) 16113349 (eISSN)

Vol. 9459 16-23
978-3-319-26843-9 (ISBN)

Ämneskategorier

Data- och informationsvetenskap

DOI

10.1007/978-3-319-26844-6_2

ISBN

978-3-319-26843-9

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Senast uppdaterat

2018-02-22