P334 - 1st International Conference on Software Product Management
Auflistung P334 - 1st International Conference on Software Product Management nach Schlagwort "Digitalization"
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- KonferenzbeitragPerception of Social Costs of Digitalization: Profiling Top Managers, Middle Managers, and Front-line Employees(1st International Conference on Software Product Management 2023, 2023) Bogodistov, Yevgen; Schwaiger, Antonia; Beimborn, DanielAlthough information technology has become advanced in profiling users, we often offer this knowledge to marketing and forget that profiling is needed for information technology implementation itself. If digitalization is introduced in a firm, it may encounter internal resistance. Top managers, middle managers, and front-line employees may have different expectations with regard to digitalization initiatives in their firms. Having different visions of what digitalization is about may result in conflicts with regard to digital solutions selection and implementation and, consequently, lead to digitalization failure. In this paper, we look at differences in digitalization cost perception using a Discrete Choice Experiment. Based on our findings, we propose to approach firms by profiling top managers, middle managers, and front-line employees.
- KonferenzbeitragWhat 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, JanFor 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.