Evaluation and control of the value provision of complex IoT service systems

Abstract

The Internet of Things (IoT) represents an opportunity for companies to create additional consumer value through merging connected products with software-based services. The quality of the IoT service can determine whether an IoT service is consumed in the long-term and whether it delivers the expected value for a consumer. Since IoT services are usually provided by distributed systems and their operations are becoming increasingly complex and dynamic, continuous monitoring and control of the value provision is necessary. The individual components of IoT service systems are usually developed and operated by specialized teams in a division of labor. With the increasing specialization of the teams, practitioners struggle to derive quality requirements based on consumer needs. Consequently, the teams often observe the behavior of “their” components isolated without relation to value provision to a consumer. Inadequate monitoring and control of the value provision across the different components of an IoT system can result in quality deficiencies and a loss of value for the consumer. The goal of this dissertation is to support organizations with concepts and methods in the development and operations of IoT service systems to ensure the quality of the value provision to a consumer. By applying empirical methods, we first analyzed the challenges and applied practices in the industry as well as the state of the art. Based on the results, we refined existing concepts and approaches. To evaluate their quality in use, we conducted action research projects in collaboration with industry partners. Based on an interview study with industry experts, we have analyzed the current challenges, requirements, and applied solutions for the operations and monitoring of distributed systems in more detail. The findings of this study form the basis for further contributions of this thesis. To support and improve communication between the specialized teams in handling quality deficiencies, we have developed a classification for system anomalies. We have applied and evaluated this classification in an action research project in industry. It allows organizations to differentiate and adapt their actions according to different classes of anomalies. Thus, quick and effective actions to ensure the value provision or minimize the loss of value can be optimized separately from actions in the context of long-term and sustainable correction of the IoT system. Moreover, the classification for system anomalies enables the organization to create feedback loops for quality improvement of the system, the IoT service, and the organization. To evaluate the delivered value of an IoT service, we decompose it into discrete workflows, so-called IoT transactions. Applying distributed tracing, the dynamic behavior of an IoT transaction can be reconstructed in a further activity and can be made “observable”. Consequently, the successful completion of a transaction and its quality can be determined by applying indicators. We have developed an approach for the systematic derivation of quality indicators. By comparing actual values determined in operations with previously defined target values, the organization is able to detect anomalies in the temporal behavior of the value provision. As a result, the value provision can be controlled with appropriate actions. The quality in use of the approach is confirmed in another action research project with an industry partner. In summary, this thesis supports organizations in quantifying the delivered value of an IoT service and controlling the value provision with effective actions. Furthermore, the trust of a consumer in the IoT service provided by an IoT system and in the organization can be maintained and further increased by applying appropriate feedback loops.