In general, at smaller companies, decisions are based on the intuition of their experts within their respective areas. The decision processes are dependent on several aspects, such as assumptions and context, and some on data. Over the last year, the increase in data flow has enabled SMEs to make a decision in a systematic and planned process referred to as data-driven decision-making(DDM). Small-medium enterprises (SME) companies have been affected by enabling aspects. However, research shows challenges for SMEs trying to develop their DDM. To address these challenges, this thesis aims to propose a process to assess and develop data-driven decision-making in an SME within the manufacturing industry. The study has been made with a qualitative approach. In addition, a case study of an SME within the manufacturing industry has been done to study the phenomenon in a real-life situation. The data collection was conducted by a literature review, interviews, and planned and unplanned observations. The literature review showed that different aspects affect the development of DDM. The aspects discussed were the decision-making process, technology and organisational factors such as general change, organisational culture, resistance to change, management and the last aspect, Data quality. A maturity assessment model was discussed to introduce the ability to assess a company's current state. The empirical data discussed two main aspects: the current state and the desired future state. The empirical findings showed that there were three main levels of decision-making in the current state: Operator level, Production level, and Management level. The desired state discusses data expectations, which provides a view of the company's perception of what data is and how it is used. In the analysis, there were two main challenging aspects identified from the empirical and theoretical data, and these were organisational and technological factors. The challenges related to technological factors were identified, such as digital adaptation, technological uncertainties and data quality. The challenges related to Organisational factors were the decision-making process, adaptation to change, organisational culture and data quality. Based on these challenges and the evaluation of the maturity model and application process, a different proposed application process was created to help organisations develop their DDM. Some of the challenges identified within the SME company connect to the challenges found in theory, and they bring future support that these challenges are present in real-life situations. An aspect that was identified as both a technological factor and an organization is the need for data quality and evaluation of it within the organisation. It shows that this is a critical aspect that must be considered when developing DDM.Keywords: Data-driven decision-making, Techno

Purpose - The purpose of this study is to investigate how the challenges of Internet of Things that manufacturers can influence can be overcome. Theoretical foundation - This study conducted an extensive literature review to identify and understand the challenges to Internet of Things and actions to overcome them. 11 technical challenges, 13 organisational and 6 resource availability challenges were identified. 4 actions were identified. Method - To fulfil the purpose, an embedded multiple case study at a global Aerospace manufacturer was conducted. 7 unstructured interviews, 12 semi-structured interviews and a survey were conducted. Respondents were picked due to their experience in Internet of Things projects and relevant technologies. The survey was conducted to evaluate the challenges’ relevance to high-technology manufacturers, on a 7-point Likert scale. The semi-structured interviews aimed to find actions to overcoming the challenges relevant to high-technology manufacturers. Findings - The evaluation of the challenges relevance to high-technology manufacturers resulted in 10 common, 9 occasional and 2 uncommon challenges. 12 actions to overcoming the challenges and their tasks were identified. Theoretical contribution - The study provides a comprehensive list of potential challenges to Internet of Things. It evaluated the challenges’ impact on high-technology manufacturers, thus challenging and validating Internet of Things challenges presented in literature. It provides a set of actions and a framework which aids in overcoming challenges that impact high-technology manufacturers’ Internet of Things initiatives, thus contributing to digital change management. Finally, it aids in the progress towards concretising Industry 4.0 and its trends toward connectivity, intelligence, and flexible automation. Practical contribution - The study provides an increased understanding of potential challenges of Internet of Things, and recommendations to how high-technology manufacturer can overcome the challenges. A framework is provided which gives an overview of which actions, and subsequent tasks, to take to overcome a specific challenge.