TY - JOUR
T1 - Strategic business modeling
T2 - Representation and reasoning
AU - Horkoff, Jennifer
AU - Barone, Daniele
AU - Jiang, Lei
AU - Yu, Eric
AU - Amyot, Daniel
AU - Borgida, Alex
AU - Mylopoulos, John
N1 - Funding Information:
John Mylopoulos University of Trento, Italy. John Mylopoulos holds a distinguished professor position (chiara fama) at the Uni- versity of Trento, and a pro- fessor emeritus position at the University of Toronto. He earned a Ph.D. degree from Princeton University in 1970 and joined the Department of Computer Sci- ence at the University of Toronto that year. His research interests include conceptual modelling, requirements engineering, data semantics and knowledge man agement. Mylopoulos is a fellow of the Association for the Advancement of Artificial Intelligence (AAAI) and the Royal Society of Canada (Academy of Sciences). He has served as programme/general chair of international conferences in Artificial Intelligence, Databases and Software Engineering, including IJCAI (1991), Requirements Engineering (1997), and VLDB (2004). Mylopoulos was recently awarded an advanced grant from the European Research Council for a project titled “Lucretius: Foundations for Software Evolution”.
PY - 2014/6
Y1 - 2014/6
N2 - Business intelligence (BI) offers tremendous potential for business organizations to gain insights into their day-to-day operations, as well as longer term opportunities and threats. However, most of today's BI tools are based on models that are too much data-oriented from the point of view of business decision makers. We propose an enterprise modeling approach to bridge the business-level understanding of the enterprise with its representations in databases and data warehouses. The business intelligence model (BIM) offers concepts familiar to business decision making-such as goals, strategies, processes, situations, influences, and indicators. Unlike many enterprise models which are meant to be used to derive, manage, or align with IT system implementations, BIM aims to help business users organize and make sense of the vast amounts of data about the enterprise and its external environment. In this paper, we present core BIM concepts, focusing especially on reasoning about situations, influences, and indicators. Such reasoning supports strategic analysis of business objectives in light of current enterprise data, allowing analysts to explore scenarios and find alternative strategies. We describe how goal reasoning techniques from conceptual modeling and requirements engineering have been applied to BIM. Techniques are also provided to support reasoning with indicators linked to business metrics, including cases where specifications of indicators are incomplete. Evaluation of the proposed modeling and reasoning framework includes an on-going prototype implementation, as well as case studies.
AB - Business intelligence (BI) offers tremendous potential for business organizations to gain insights into their day-to-day operations, as well as longer term opportunities and threats. However, most of today's BI tools are based on models that are too much data-oriented from the point of view of business decision makers. We propose an enterprise modeling approach to bridge the business-level understanding of the enterprise with its representations in databases and data warehouses. The business intelligence model (BIM) offers concepts familiar to business decision making-such as goals, strategies, processes, situations, influences, and indicators. Unlike many enterprise models which are meant to be used to derive, manage, or align with IT system implementations, BIM aims to help business users organize and make sense of the vast amounts of data about the enterprise and its external environment. In this paper, we present core BIM concepts, focusing especially on reasoning about situations, influences, and indicators. Such reasoning supports strategic analysis of business objectives in light of current enterprise data, allowing analysts to explore scenarios and find alternative strategies. We describe how goal reasoning techniques from conceptual modeling and requirements engineering have been applied to BIM. Techniques are also provided to support reasoning with indicators linked to business metrics, including cases where specifications of indicators are incomplete. Evaluation of the proposed modeling and reasoning framework includes an on-going prototype implementation, as well as case studies.
KW - Business intelligence
KW - Business model
KW - Conceptual modeling languages
KW - Goal
KW - Influence diagrams
KW - Key performance indicators
KW - Situation
KW - Strategic planning
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U2 - 10.1007/s10270-012-0290-8
DO - 10.1007/s10270-012-0290-8
M3 - Article
AN - SCOPUS:84903452705
SN - 1619-1366
VL - 13
SP - 1015
EP - 1041
JO - Software and Systems Modeling
JF - Software and Systems Modeling
IS - 3
ER -