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Authors
Advisor(s)
Abstract(s)
Starting from Business Intelligence (BI) reference models, this work proposes to extend the
multi-dimensional data modeling approach to integrate Human Factors (HF) related dimensions.
The overall goal is to promote a fine grain understanding of 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,
modeling and integration within a BI project endeavor. 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.
Description
Trabalho apresentado em 11th INEKA Conference, 11-13 junho 2019, Verona, Itália
Keywords
Human Factors Data Modelling Business Intelligence
