Purpose: Due to the complexity of digital services, companies are increasingly forced to offer their services “in permanent beta”, requiring continuous fine-tuning and updating. Complexity makes it extremely difficult to predict when and where the next service disruption will occur. The authors examine what this means for performance measurement in digital service supply chains. Design/methodology/approach: The authors use a mixed-method research design that combines a longitudinal case study of a European digital TV service provider and a system dynamics simulation analysis of that service provider's digital service supply chain. Findings: With increased levels of complexity, traditional performance measurement methods, focused on detection of software bugs before release, become fragile or futile. The authors find that monitoring the performance of the service after release, with fast mitigation when service incidents are discovered, appears to be superior. This involves organizational change when traditional methods, like quality assurance, become less important. Research limitations/implications: The performance of digital services needs to be monitored by combining automated data collection about the status of the service with data interpretation using human expertise. Investing in human expertise is equally important as investing in automated processes. Originality/value: The authors draw on unique empirical data collected from a digital service provider's struggle with performance measurement of its service over a period of nine years. The authors use simulations to show the impact of complexity on staff allocation.

Resource pooling is known to benefit performance through reduced congestion, but primarily in settings with homogenous demand. In settings where demand is heterogeneous, pooling can be counter effective. The effects of pooling of staff when demand is heterogeneous and dependent are not known. We present a simulation model based on a service supply chain that delivers Interactive TV to customers. Customers expect high performance in terms of innovativeness and reliability. Based on the results of simulation analysis, we find that when target innovativeness of the service is increased, pooling outperforms not pooling, but the delays that are involved with pooling will make the system and hence its performance unstable. Stable and high performance can be realized through “unbalanced” hiring. This means that a target performance increase in the upstream stage of the chain (innovation), is accompanied by hiring staff in the downstream stages of the chain (QA and operation).

During SimEx2018 the large-scale field exercise was augmented with a digital environment. This digital environment consists of the digital presence of role-players on social media, the use of modern web technologies and the involvement of the Digital humanitarian Network (DHN). In SimEx2018 the DHN, specifically the Standby Task Force (SBTF) was activated and collaborated closely with UNDAC team. The value of DHN involvement was well recognized and proved to contribute to the response operations during the exercise. This report highlights the setup of the digital environment of SimEx, the activities executed prior and during the exercise, the management of SimEx digital environment and the lessons learned / reflections for future exercise and DHN development.

Simulation exercises as a training tool for enhancing preparedness for emergency response are widely adopted in disaster management. This paper addresses current scenario design processes, proposes an alternative approach for simulation exercises and introduces a conceptual design of an adaptive scenario generator. Our work is based on a systematic literature review and observations made during TRIPLEX-2016 exercise in Farsund, Norway. The planning process and scenario selection of simulation exercises impact directly the effectiveness of intra- and interorganizational cooperation. However, collective learning goals are rarely addressed and most simulations are focused on institution-specific learning goals. Current scenario design processes are often inflexible and begin from scratch for each exercise. In our approach, we address both individual and collective learning goals and the demand to develop scenarios on different layers of organizational learning. Further, we propose a scenario generator that partly automates the scenario selection and adaptively responds to the exercise evolvement.

Aid workers increasingly face risks when working in crisis regions. In order to improve effectiveness and safety of humanitarians, it is of great importance to provide a well thought out real-time socio-technical support. Thus, new policies and innovative technological solutions need to be developed and integrated into humanitarian workflows. For the requirements elicitation process to realize this aspiration, we employ a board game approach that confronts players with situations aid workers experience in the field. From the first game session, we learned that the game is a valuable tool. It raises awareness to important challenges and trade-offs that humanitarians face. In addition, it is an effective catalyst for initiating a discussion on which system requirements are needed. Future work will include an update of the board game as well as sessions with the target group of practitioners to inform the development of a socio-technical system for humanitarian aid work.