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P334 - 1st International Conference on Software Product Management

https://dl.gi.de/handle/20.500.12116/41773
Auflistung nach:

Auflistung P334 - 1st International Conference on Software Product Management nach Autor:in "Bosch, Jan"

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  • Konferenzbeitrag
    Software Product Management: from opinions to data-driven experimentation
    (1st International Conference on Software Product Management 2023, 2023) Bosch, Jan
    With the digitalization of industry and society, product management of digital technologies such as software, data and AI is rapidly becoming critically important. Digitalization offers new tools for product managers to increase the return on investment of R&D including DevOps, DataOps and MLOps. These fast feedback loops allow product managers to adopt a much more experiment- and data-driven approach, e.g. using A/B testing and other experimental approaches. Product management is at the transition point from “what to build” to “what outcomes to accomplish”. The keynote addresses this transformation, the challenges that one has to address while transitioning, the benefits as well as the new techniques available. The talk will share numerous examples from industry based on our research in the context of Software Center (www.software-center.se), a collaboration between 15 international companies and 5 Swedish universities focused on accelerating the digital transformation of the European software intensive industry.
  • Konferenzbeitrag
    What Got You Here Won’t Get You There. A multi-case study on the challenges in the transition from traditional towards continuous data practices in the embedded systems domain
    (1st International Conference on Software Product Management 2023, 2023) Olsson, Helena; Bosch, Jan
    For decades, product data has been collected and used for quality assurance, for post-deployment defect detection and for informing the next generation of products. Across industry domains, and with the online domain leading the way, companies have adopted experimentation and data driven practices such as A/B testing to evaluate product performance, customer behaviors and for determining what adds value to customers. However, with the rapid changes that new digital technologies bring, companies are moving towards continuous value delivery and monetization models in which they offer their products as-a-service or offer services to complement and extend their existing products. In this transition, the traditional way of post-deployment data collection and use is no longer sufficient. While companies realize this, they experience difficulties in making the changes they need to transition towards continuous practices and new ways of working with data. As a result, companies risk wasting development efforts on functionality that have little or no customer value and they lose out on the competitive advantages that come with insights derived from continuous collection and use of data. In this paper, we explore the challenges companies experience in the transition from traditional towards continuous practices and the implications this shift has on their ways of working with data.