Data-Driven Persona Retrospective Based on Persona Significance Index in B-to-B Software Development

Yasuhiro Watanabe, Hironori Washizaki, Yoshiaki Fukazawa, Kiyoshi Honda, Masahiro Taga, Akira Matsuzaki, Takayoshi Suzuki

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Business-to-Business (B-to-B) software development companies develop services to satisfy their customers' requirements. Developers should prioritize customer satisfaction because customers greatly influence agile software development. However, satisfying current customer's requirements may not fulfill actual users or future customers' requirements because customers' requirements are not always derived from actual users. To reconcile these differences, developers should identify conflicts in their strategic plan. This plan should consider current commitments to end users and their intentions as well as employ a data-driven approach to adapt to rapid market changes. A persona models an end user representation in human-centered design. Although previous works have applied personas to software development and proposed data-driven software engineering frameworks with gap analysis between the effectiveness of commitments and expectations, the significance of developers' commitment and quantitative decision-making are not considered. Developers often do not achieve their business goal due to conflicts. Hence, the target of commitments should be validated. To address theseissues, we propose Data-Driven Persona Retrospective (DDR) to help developers plan future releases.DDR, which includes the Persona Significance Index (PerSI) to reflect developers' commitments to end users' personas, helps developers identify a gap between developers' commitments to personas and expectations. In addition, DDR identifies release situations with conflicts based on PerSI. Specifically, we define four release cases, which include different situations and issues, and provide a method to determine the release case based on PerSI. Then we validate the release cases and their determinations through a case study involving a Japanese cloud application and discuss the effectiveness of DDR.

Original languageEnglish
Pages (from-to)117-146
Number of pages30
JournalInternational Journal of Software Engineering and Knowledge Engineering
Volume31
Issue number1
DOIs
Publication statusPublished - 2021 Jan

Keywords

  • Data-driven personas
  • data-driven software engineering
  • release planning
  • requirement engineering

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence

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