Browsing by Author "Sommarberg, Marko"
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Perustieteiden korkeakoulu | Bachelor's thesis(2013-12-16) Sommarberg, Marko - Industrial Value Drivers from Internet of Things
Perustieteiden korkeakoulu | Master's thesis(2016-08-24) Sommarberg, MarkoCustomer value creation is an important source for competitive advantage for firms to differentiate products and services from competition. On the other hand, Internet of Things (IoT) is an emerging phenomenon that enables firms to enhance their value creation to industrial customers. It is also an important topic from the customer value standpoint. In short, IoT means connecting world’s myriad of machines and appliances through Internet to introduce widely new possibilities in machine usage and system efficiency in different fields and industries. It is predicted to bring new efficiency gains and incremental revenue to industrial firms across different industries. Altogether the global impact could be enormous. However, the adoption is still lacking behind the hype. To address this issue this study focuses on increasing knowledge about the customer value IoT can generate to industrial customers. The objective of this research was to identify most important IoT value drivers in industrial applications. This was achieved by using qualitative research method where four industrial firms and their outlooks on IoT were studied. Altogether 21 semi-structured interviews were carried out with the operational managers of the case firms to investigate the elements where IoT could create most value to industrial customers. In addition, value drivers and development in the early IoT adoption were studied in the interviews. After the interviews the qualitative data was analyzed in multiple steps using qualitative research software where data was structured and concrete findings were synthesized in different levels of abstraction. Findings suggest that IoT could create substantial value to industrial customers around four dimensions: data utilization, operations improvement, knowledge sharing and gradual adoption. Industrial customers seem to already possess vast amounts of underutilized process data which should be better utilized before adding new data. However, industrial customers appeared to have limited data analysis capabilities which implies need for external support. Furthermore, predictive maintenance enabled by IoT could improve operations planning, recovery from disturbances and avoidance of disturbances altogether. Moreover, production optimization opportunities arising from IoT should be focused on monitoring and understanding critical equipment better to optimize industrial processes. In addition, IoT offers opportunities to improve factory knowledge sharing by cross-department collaboration and external support from suppliers. Lastly, industrial IoT adoption seems gradual according to the findings.