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Conference Papers Year : 2017

From Indicators to Predictive Analytics: A Conceptual Modelling Framework

Soroosh Nalchigar
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Eric Yu
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Robert Wrembel
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Esteban Zimanyi
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Predictive analytics provides organisations with insights about future outcomes. Despite the hype around it, not many organizations are using it. Organisations still rely on the descriptive insights provided by the traditional business intelligence (BI) solutions. The barriers to adopt predictive analytics solutions are that businesses struggle to understand how such analytics could enhance their existing BI capabilities, and also businesses lack a clear understanding of how to systematically design the predictive analytics. This paper presents a conceptual modelling framework to overcome these barriers. The framework consists of two modelling components and a set of analysis that systematically (1) justify the needs for predictive analytics within the organisational context, and (2) identify the predictive analytics design requirements. The framework is illustrated using a real case adopted from the literature.
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Dates and versions

hal-01765243 , version 1 (12-04-2018)





Azadeh Nasiri, Soroosh Nalchigar, Eric Yu, Waqas Ahmed, Robert Wrembel, et al.. From Indicators to Predictive Analytics: A Conceptual Modelling Framework. 10th IFIP Working Conference on The Practice of Enterprise Modeling (PoEM), Nov 2017, Leuven, Belgium. pp.171-186, ⟨10.1007/978-3-319-70241-4_12⟩. ⟨hal-01765243⟩
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