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Crossing Human Factors Research and Business Intelligence

Crossing Human Factors Research and Business Intelligence

Cláudio Miguel Sapateiro, Rui Miguel Bernardo
Copyright: © 2020 |Volume: 16 |Issue: 3 |Pages: 15
ISSN: 1548-1115|EISSN: 1548-1123|EISBN13: 9781799805038|DOI: 10.4018/IJEIS.2020070106
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MLA

Sapateiro, Cláudio Miguel, and Rui Miguel Bernardo. "Crossing Human Factors Research and Business Intelligence." IJEIS vol.16, no.3 2020: pp.78-92. http://doi.org/10.4018/IJEIS.2020070106

APA

Sapateiro, C. M. & Bernardo, R. M. (2020). Crossing Human Factors Research and Business Intelligence. International Journal of Enterprise Information Systems (IJEIS), 16(3), 78-92. http://doi.org/10.4018/IJEIS.2020070106

Chicago

Sapateiro, Cláudio Miguel, and Rui Miguel Bernardo. "Crossing Human Factors Research and Business Intelligence," International Journal of Enterprise Information Systems (IJEIS) 16, no.3: 78-92. http://doi.org/10.4018/IJEIS.2020070106

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Abstract

Starting from business intelligence (BI) reference models, this work proposes to extend the multi-dimensional data modelling approach to integrate human factors (HF)-related dimensions. The overall goal is to promote a fine grain understanding of the derived key performance indicators (KPIs) through an enhanced characterization of the operational level of work context. HF research has traditionally approached critical domains and complex socio-technical systems with a chief consideration of human situated action. Grounded on a review of the body of knowledge of the HF field, this work proposes the business intelligence for human factors (BI4HF) framework. It intends to provide guidance on pertinent data identification, collection methods, modelling, and integration within a BI project endeavour. BI4HF foundations are introduced, and a use case on a manufacturing industry organization is presented. The outcome of the enacted BI project referred in the use case allowed new analytical capabilities regarding newly derived and existing KPIs related to operational performance, providing insight into the value of the BI4HF framework.

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