Analysis of a Business Intelligence process based on Lean Office principles

Authors

DOI:

https://doi.org/10.15675/gepros.v16i1.2545

Keywords:

Business intelligence, Business Analytics, Melhoria de processos, Lean Office

Abstract

Purpose – Business Intelligence (BI) is the company's ability, through the use of technologies and methods, to transform data from external and internal environments into information to improve performance. Capture, management and transformation can be understood as processes and these can present problems and need for improvement. This article presents a case of applying Lean Office in a BI process in a service large company. The goal is to identify BI process-related waste and propose improvements through Lean Office tools and principles.
Methodology – The research was developed through a case study. Three data collection instruments were used: participant observation, document analysis and documented interviews. The analyzes were conducted based on the data collected and tools identified in the literature were applied that helped in conducting the analysis of the information transformation process.
Findings - The article presented two main results, the detailed presentation of BI activities that are little explored in the literature, especially in developing countries, and the contribution of Lean Office's philosophy and tools for improving the management of a BI process.
Originality/value – It contributes to a better understanding and creation of a common vision about the BI process between researchers and practitioners, and with a case that exemplifies the potential of the Lean Office to identify waste, analyze causes and improve the performance of this process.
Keywords - Business intelligence. Business analytics. Process improvement. Lean Office.

References

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Published

2021-03-14

How to Cite

Lizarelli, F. L., Tonissi, L. F., & Toledo, J. C. (2021). Analysis of a Business Intelligence process based on Lean Office principles. Revista Gestão Da Produção Operações E Sistemas, 16(1). https://doi.org/10.15675/gepros.v16i1.2545

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