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Implement a BI solution using the soft system methodology approach: A use case in a resource-constrained non-profit association

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Resumo(s)

Non-profit associations (NPA) have concurrently faced the bottleneck of having an overload of manual tasks, potentially hindering their efficiency and motivation to work. Different methodologies are pursued to achieve the most efficient solution to each institution. The soft system methodology is being paved a way for innovate methods to streamline NPA´s volunteers processes. This project investigates the effectiveness of implementing this methodology in a resource-constrained non-profit association in order to develop a business intelligence (BI) solution by following itsseven different stages within a non-formal association led by nine volunteer leaders. After identifying the problems, a centralized data structure was created as a solution by developing a website to enable more automated and detailed tracking of membership and financial management through a BI model. Despite the association's nonprofit focus, unlike private organizations, the implementation resulted in increased process efficiency. The SSM proved effective due to its iterative and cyclical stages, leading to a final solution that aligns well with real-world outcomes while considering the environmental constraints of limited knowledge and investment. The use case presented can be seen as a viable solution for associations or even small businesses that don´t have the amount need to invest in an implementation and maintenance of a data warehouse. In future research it would be viable to arrange a way of measure the real impact of efficacy and efficiency of the adoption of the soft system methodology.

Descrição

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence

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Soft System Methodology Non-profit association Business Intelligence SDG 4 - Quality education SDG 5 - Gender equality SDG 8 - Decent work and economic growth

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