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Based on the large amounts spent by software companies to develop new and existing software systems, we argue that an evidence-based approach that focuses on a software portfolio as a whole should be in place to support decision-making. We developed EBSPM as an evidence-based, practical model to support software companies to actively steer at optimization of their software delivery portfolio. We evaluated the model in case studies and surveys in industry, to demonstrate its strengths and limitations in practice. This lead to the following results:
• We analyzed - from a portfolio point of view - the characteristics of best performers and worst performers, in a dataset of 352 software projects, resulting in 7 success factors and 9 failure factors.
• We found that a release process that performs above average on cost and duration, satisfies stakeholders through fast response and direct value, even when the reliability and availability of the actual system are weak.
• A statistical, evidence-based pricing approach for software engineering, as a single instrument, can be used in the subject companies to create cost transparency and performance management.
• We found significant differences between the EBSPM-repository and an ISBSG-subset. Practitioners and researchers alike should be cautious when drawing conclusions from a single repository.
• We found that a focus on shortening overall project duration and improving communication and team collaboration on intermediate progress is likely to have a positive impact on stakeholder satisfaction and perceived value.
Based on the findings, we conclude that it is wise for software companies to collect and analyze their own historic software portfolio data because cross-company large differences in performance are found. We obtained a better understanding of the differences and equalities between effort and cost of software deliveries. Additionally, we studied the effects of pricing of software deliveries, giving us a better insight into ways to support decision-making. Based on the results of ongoing research, we expect that automation of the measurement and analysis process, based on statistics to calculate strong relationships, is a direction in which the analysis of software portfolio (software analytics) is the to develop strongly in the coming years.
Original languageEnglish
QualificationMaster of Philosophy
Awarding Institution
Supervisors/Advisors
Award date16 Feb 2018
Print ISBNs978-94-028-0932-9
DOIs
StatePublished - 2018

    Research areas

  • Evidence-based software engineering, Evidence-based software portfolio management, Software Analytics, Software Economics, IT governance, Metrics, Perceived value, Stakeholder satisfaction, Project performance

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