In today's world, the users of software-based products demand a lot. They want the systems to offer the needed functionality, show high performance and, at the same time, be usable and trustworthy. Especially consumer products should also offer joy to the user. The success of a software-based product strongly depends on how well the product fulfills these user expectations. Therefore, considering the users' expectations should be an integral part of modern system engineering activities. This paper shows an approach that was designed to appraise and measure the users' (future) satisfaction in an early phase of system development: the requirements engineering phase. In this phase little systematic guidance exists on how to evaluate the effects of features on user satisfaction early on, and on how to contribute the results to the development process. AMUSE (appraisal and measurement of user satisfaction), the approach presented in this paper, closes this gap. It helps requirements engineers and product managers to select the most promising features, i.e., the ones that will satisfy the user the most, already in the requirements phase. The approach uses a standardized user satisfaction measurement device (questionnaire), a feature appraisal and prioritization methodology, and tool support. This approach was developed and piloted in cooperation with Siemens AG, Germany.

Explicit risk management is gaining ground in industrial software development projects. However, there are few empirical studies that investigate the transfer of explicit risk management into industry, the adequacy of the risk management approaches to the constraints of industrial contexts, or their cost-benefit. This paper presents results from a case study that introduced a systematic risk management method, namely the Riskit method, into a large German telecommunication company. The objective of the case study was (1) to analyze the usefulness and adequacy of the Riskit method and (2) to analyze the cost-benefit of the Riskit method in this industrial context. The results of (1) also aimed at improvement and customization of the Riskit method. Moreover, we compare our findings with results of previous case studies to obtain more generalized conclusions on the Riskit method. Our results showed that the Riskit method is practical, adds value to the project, and that its key concepts are understood and usable in practice. Additionally, many lessons learned are reported that are useful for the general audience who wants to transfer risk management into new projects.