Applying Operational Business Intelligence in Production Environments

Operational Business Intelligence (OpBI) discusses a possible support of production-specific decisions by integrating and analyzing production data. The discussion of OpBI focusses thereby rather on common applicability aspects than on certain implementation strategies. This is however less conclusive for a functional reliability of OpBI in production environments and for associated efforts. Therefore, we introduce an OpBI framework to integrate and analyze data of production processes automatically. Following principles of design science research, framework evaluation refers to real-world data from a rod and wire rolling process. In conclusion, our OpBI framework improves information quality perceived by end users analyzing a steel’s rolling behavior

Business Intelligence in Industry 4.0: State of the art and research opportunities

Data collection and analysis have been at the core of business intelligence (BI) for many years, but traditional BI must be adapted for the large volume of data coming from Industry 4.0 (I4.0) technologies. They generate large amounts of data that need to be processed and used in decision-making to generate value for the companies. Value generation of I4.0 through data analysis and integration into strategic and operational activities is still a new research topic. This study uses a systematic literature review with two objectives in mind: understanding value creation through BI in the context of I4.0 and identifying the main research contributions and gaps. Results show most studies focus on real-time applications and integration of voluminous and unstructured data. For business research, more is needed on business model transformation, methodologies to manage the technological implementation, and frameworks to guide human resources training

Manufacturing Value Modelling, Flexibility, and Sustainability: from theoretical definition to empirical validation

The aim of this PhD thesis is to investigate the relevance of flexibility and sustainability within the smart manufacturing environment and understand if they could be adopted as emerging competitive dimensions and help firms to take decisions and delivering value

La création de valeur des données de l’Industrie 4.0 : une étude empirique dans les manufacturiers québécois

Abstract : Manufacturing companies in developed countries face a digital transformation that is meant to improve their productivity, but also produces a large volume of data. This data will go to waste if it is not valorized by using it to gain actionable insights, for example with business intelligence and analytics. This master’s thesis presents a systematic literature review and a multiple case-study on the subject of Business Intelligence in manufacturing companies. The first article, “Business Intelligence in Industry 4.0: Research opportunities”, present a literature review. Results show a lack of studies on the impacts of business intelligence activities on manufacturing small and medium enterprises. The strategic impacts should be studied, since they are often neglected in favor of the operational impacts such as quality improvement and operating costs reductions. The second article, “Business intelligence value creation: A multiple case study in manufacturing SMEs”, presents an exploration of the factors influencing strategic and operational business values of business intelligence. Results show the limit of the traditional models based on the Resource-Based View of the firm, which overlooks organizational factors that might be more important in smaller organizations. Contingency factors, such as organisational learning, leadership style, and the role of the owner, should be included when studying small and medium enterprises, as in these smaller organizations the lack of resources and the simpler structure affect business value of business intelligence and analytics systems differently than in larger firms. There is an interesting potential for the model suggested in this master’s thesis to understand the factors linked to business value creation in smaller organization, which should be empirically tested with a larger and more diverse sample in a future study.Ce mémoire présente les travaux réalisés dans le cadre de ma maîtrise en Stratégie de l’intelligence d’affaires, de l’École de Gestion de l’Université de Sherbrooke. Il consiste en deux articles. Le premier est une revue de littérature systématique ayant été soumise et acceptées à la 51e édition de Hawaii International Conference on System Sciences, qui a eu lieu du 3 au 6 janvier 2018. Il est présenté intégralement au chapitre deux. Le second article, présenté dans sa version longue au chapitre trois, a été soumis à la 7e édition de International Conference on Information Systems, Logistics and Supply Chain qui aura lieu du 8 au 10 juillet 2018. Les notices d’acceptation seront envoyées après la date de dépôt de ce mémoire. Toutes les preuves de soumissions sont présentées dans les annexes de ce mémoire. Les articles ont tous été rédigé par moi, Fanny-Ève Bordeleau, qui a également réalisé toutes les prises de données et les analyses, assistée de mes co-directeurs, les professeurs Elaine Mosconi et Luis Antonio De Santa-Eulalia