Chapter 19 - Analytical Product Release Planning

https://doi.org/10.1016/B978-0-12-411519-4.00019-7Get rights and content

Abstract

As part of any incremental and iterative development, release planning is the process of assigning features to upcoming releases (or iterations) such that the overall product evolution is optimized. Analytical product release planning refers to the application of analytical methods in this process, thereby utilizing the diversity of data available from internal and external sources of information. In this chapter, information needs for release planning are outlined and a taxonomy of release planning problems is given. The paradigm of Open Innovation is introduced as a new way to elicit and gain access to relevant data related to product objectives, features and their dependencies, customers and changing priorities, as well as product values and market trends. Analytical Open Innovation (AOI) is the integration of Open Innovation with (a portfolio of) analytical methods which could be used in different problems of a semi-wicked nature such as planning and design. This chapter studies the usage of AOI in the context of release planning (RP). The respective approach called “AOI@RP” is taking advantage of gathering and generating data and relating data into well-defined aspects of the problem and combining analytical methods to address the solution. The usage of AOI is studied in more detail for two of the concrete release planning problems given in the taxonomy: (1) Release planning in the presence of advanced feature dependencies and synergies detected from morphological analysis; (2) continuous what-to-release planning in consideration of ongoing trial feature evaluation. An illustrative case study is used as proof of concept to the proposed solution methodology.

References (0)

Cited by (21)

  • Towards participatory cross-impact balance analysis: Leveraging morphological analysis for data collection in energy transition scenario workshops

    2022, Energy Research and Social Science
    Citation Excerpt :

    Moreover, the morphological field presented visually facilitates qualitative data collection more expediently in a participatory scenario workshop. Morphological analysis can help identify, structure, and investigate possible relationships involved in the complexity of energy transitions [67]. For participatory CIB, as proposed in this article, we combined morphological analysis and CIB analysis into a coherent scenario development process.

View all citing articles on Scopus
View full text