TY - GEN
T1 - Advanced Business Simulations: Incorporating business and process execution data
AU - Drobek, Marc
AU - Gilani, Wasif
AU - Redlich, David
AU - Molka, Thomas
AU - Soban, Danielle
PY - 2015/5/31
Y1 - 2015/5/31
N2 - Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.
AB - Key Performance Indicators (KPIs) and their predictions are widely used by the enterprises for informed decision making. Nevertheless , a very important factor, which is generally overlooked, is that the top level strategic KPIs are actually driven by the operational level business processes. These two domains are, however, mostly segregated and analysed in silos with different Business Intelligence solutions. In this paper, we are proposing an approach for advanced Business Simulations, which converges the two domains by utilising process execution & business data, and concepts from Business Dynamics (BD) and Business Ontologies, to promote better system understanding and detailed KPI predictions. Our approach incorporates the automated creation of Causal Loop Diagrams, thus empowering the analyst to critically examine the complex dependencies hidden in the massive amounts of available enterprise data. We have further evaluated our proposed approach in the context of a retail use-case that involved verification of the automatically generated causal models by a domain expert.
KW - Business Dynamics
KW - Business process simulation
KW - Business Simulations
KW - Key performance indicator predictions
KW - Process performance parameters
UR - http://www.scopus.com/inward/record.url?scp=84946417122&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-20052-1
DO - 10.1007/978-3-319-20052-1
M3 - Conference contribution
AN - SCOPUS:84946417122
VL - 220
T3 - Lecture Notes in Business Information Processing
SP - 119
EP - 137
BT - Business Modeling and Software Design
T2 - 4th International Symposium on Business Modeling and Software Design, BMSD 2014
Y2 - 24 June 2014 through 26 June 2014
ER -