Business Intelligence and Strategic Decision Simulation
The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.
[1] Balaceanu, D. (2007). Components of a Business Intelligence Software
solution, Informatica Economicˇa, vol. 42, no. 2, pp. 69-73.
[2] Becker, J. (2010). Prozess der gestaltungsorientierten
Wirtschaftsinformatik, in: H. Österle, R. Winter, W. Brenner (Ed.),
gestaltungsorientierte Wirtschaftsinformatik, pp. 13-18.
[3] Bohanec, M. (2001). What is Decision Support, in Proceedings of 4th
International Multi-conference Information Society (IS 2001),
Ljubljana, Slovenia, pp. 86-89.
[4] Bonabeau, E. (2001). Don-t Trust Your Gut, Harvard Business Review,
vol. 81, no. 5, pp. 116-123.
[5] Chang, Y. and Makatsoris, H. (2001). Supply Chain Modelling using
Simulation, International Journal of Simulation, vol. 2, no. 1, pp. 24-30.
[6] Crawford, I. (1997). Marketing Research and Information Systems,
Rome: FAO Regional Office.
[7] Fazlollahi, B. and Vahidov, R. (2001). Extending the Effectiveness of
Simulation-Based DSS through Genetic Algorithms, Information and
Management, vol. 39, no. 1, pp. 53-65.
[8] Ingalls, R. (2008). Introduction to Simulation, in Proceedings of the
2008 Winter Simulation Conference, The United States of America, p.
1726.
[9] Kellner, M., Madachy, R. and Raffo, D. (1999). Software Process
Simulation Modeling: Why? What? How? Journal of Systems and
Software, vol. 46, no. 2/3, pp. 1-18.
[10] Kemper, H.-G. and Baars, H. (2009). From Data Warehouses to
Transformation Hubs - A Conceptual Architecture, In: Proceedings of
The 17th European Conference on Information Systems (ECIS 2009),
Verona.
[11] Kopackova, H. and Skrobaekova, M. (2006). Decision Support Systems
or Business Intelligence: What Can Help in Decision Making? A
Scientific Paper of the University of Pardubice. [Online]. Available:
http://dspace.upce.cz/bitstream/10195/32436/1/CL585.pdf.
[12] Kossik, R. (2007). White paper on dynamic simulation and supply chain
management. A White Paper by GoldSim. [Online]. Available:
http://www.goldsim.com/downloads/whitepapers/scmpaper.pdf.
[13] Li, W., Li, B. and Zhang, Y. (2008). Container Terminal Scheduling
and Decision- Making Using Simulation Based Optimization and
Business Intelligence, in Proceedings of 2008 IEEE International
Conference on Mechatronics and Automation, Takamatsu, Japan, pp.
1053-1058.
[14] Mintzberg, H., Raisinghani, D. and Theoret, A. (1976). The Structure of
Unstructured Decision Processes, Administrative Science Quarterly, vol.
21, no. 2, pp. 246-275.
[15] Mitchell M. and Jolley J. (2010). Research Design Explained. The
United States of America: Cengage Learning.
[16] Power, D. (2001). Supporting Decision-Makers: An Expanded
Framework, in Proceedings of Informing Science Conference, The
United States of America, pp. 431-436.
[17] Power, D. (2004). Specifying an Expanded Framework for Classifying
and Describing Decision Support Systems, Communications of the
Association for Information Systems, vol. 13, no. 1, pp. 158-166.
[18] Power, D. and Sharda, M. (2007). Model-Driven Decision Support
Systems: Concepts and Research Directions, Decision Support Systems,
vol. 43, no. 3, pp. 1044-1061.
[19] Sein, M. K., Henfridsson, O., Purao, S., Rossi, M. and Lindgren, R.
(2011). Action Design Research, appears in MIS Quarterly, vol. 35, no.
2.
[20] Silva, A. D. and Botter, R. (2009). Method for Assessing and Selecting
Discrete Event Simulation Software Applied to the Analysis of Logistic
Systems, Journal of Simulation, vol. 3, no. 2, pp. 95-106.
[21] Vercellis, C. (2009). Business Intelligence: Data Mining and
Optimization for Decision. United Kingdom: John Wiley and Sons.
[22] Watson, H. (2009). Tutorial: Business Intelligence Past, Present, and
Future," Communications of the Association for Information Systems,
vol. 25, no. 1, pp. 487-510.
[23] der Zee, D. V. and der Vorst, J. V. (2005). A Modeling Framework for
Supply Chain Simulation: Opportunities for Improved Decision
Making, Decision Sciences, vol. 36, no. 1, pp. 65- 95.
[24] Zhang, J., Creighton, D. and Nahavandi, S. (2008).Towards a Synergy
Between Simulation and Knowledge Management, Cybernetics and
Systems, vol. 39, no. 7, pp. 768-784.
[1] Balaceanu, D. (2007). Components of a Business Intelligence Software
solution, Informatica Economicˇa, vol. 42, no. 2, pp. 69-73.
[2] Becker, J. (2010). Prozess der gestaltungsorientierten
Wirtschaftsinformatik, in: H. Österle, R. Winter, W. Brenner (Ed.),
gestaltungsorientierte Wirtschaftsinformatik, pp. 13-18.
[3] Bohanec, M. (2001). What is Decision Support, in Proceedings of 4th
International Multi-conference Information Society (IS 2001),
Ljubljana, Slovenia, pp. 86-89.
[4] Bonabeau, E. (2001). Don-t Trust Your Gut, Harvard Business Review,
vol. 81, no. 5, pp. 116-123.
[5] Chang, Y. and Makatsoris, H. (2001). Supply Chain Modelling using
Simulation, International Journal of Simulation, vol. 2, no. 1, pp. 24-30.
[6] Crawford, I. (1997). Marketing Research and Information Systems,
Rome: FAO Regional Office.
[7] Fazlollahi, B. and Vahidov, R. (2001). Extending the Effectiveness of
Simulation-Based DSS through Genetic Algorithms, Information and
Management, vol. 39, no. 1, pp. 53-65.
[8] Ingalls, R. (2008). Introduction to Simulation, in Proceedings of the
2008 Winter Simulation Conference, The United States of America, p.
1726.
[9] Kellner, M., Madachy, R. and Raffo, D. (1999). Software Process
Simulation Modeling: Why? What? How? Journal of Systems and
Software, vol. 46, no. 2/3, pp. 1-18.
[10] Kemper, H.-G. and Baars, H. (2009). From Data Warehouses to
Transformation Hubs - A Conceptual Architecture, In: Proceedings of
The 17th European Conference on Information Systems (ECIS 2009),
Verona.
[11] Kopackova, H. and Skrobaekova, M. (2006). Decision Support Systems
or Business Intelligence: What Can Help in Decision Making? A
Scientific Paper of the University of Pardubice. [Online]. Available:
http://dspace.upce.cz/bitstream/10195/32436/1/CL585.pdf.
[12] Kossik, R. (2007). White paper on dynamic simulation and supply chain
management. A White Paper by GoldSim. [Online]. Available:
http://www.goldsim.com/downloads/whitepapers/scmpaper.pdf.
[13] Li, W., Li, B. and Zhang, Y. (2008). Container Terminal Scheduling
and Decision- Making Using Simulation Based Optimization and
Business Intelligence, in Proceedings of 2008 IEEE International
Conference on Mechatronics and Automation, Takamatsu, Japan, pp.
1053-1058.
[14] Mintzberg, H., Raisinghani, D. and Theoret, A. (1976). The Structure of
Unstructured Decision Processes, Administrative Science Quarterly, vol.
21, no. 2, pp. 246-275.
[15] Mitchell M. and Jolley J. (2010). Research Design Explained. The
United States of America: Cengage Learning.
[16] Power, D. (2001). Supporting Decision-Makers: An Expanded
Framework, in Proceedings of Informing Science Conference, The
United States of America, pp. 431-436.
[17] Power, D. (2004). Specifying an Expanded Framework for Classifying
and Describing Decision Support Systems, Communications of the
Association for Information Systems, vol. 13, no. 1, pp. 158-166.
[18] Power, D. and Sharda, M. (2007). Model-Driven Decision Support
Systems: Concepts and Research Directions, Decision Support Systems,
vol. 43, no. 3, pp. 1044-1061.
[19] Sein, M. K., Henfridsson, O., Purao, S., Rossi, M. and Lindgren, R.
(2011). Action Design Research, appears in MIS Quarterly, vol. 35, no.
2.
[20] Silva, A. D. and Botter, R. (2009). Method for Assessing and Selecting
Discrete Event Simulation Software Applied to the Analysis of Logistic
Systems, Journal of Simulation, vol. 3, no. 2, pp. 95-106.
[21] Vercellis, C. (2009). Business Intelligence: Data Mining and
Optimization for Decision. United Kingdom: John Wiley and Sons.
[22] Watson, H. (2009). Tutorial: Business Intelligence Past, Present, and
Future," Communications of the Association for Information Systems,
vol. 25, no. 1, pp. 487-510.
[23] der Zee, D. V. and der Vorst, J. V. (2005). A Modeling Framework for
Supply Chain Simulation: Opportunities for Improved Decision
Making, Decision Sciences, vol. 36, no. 1, pp. 65- 95.
[24] Zhang, J., Creighton, D. and Nahavandi, S. (2008).Towards a Synergy
Between Simulation and Knowledge Management, Cybernetics and
Systems, vol. 39, no. 7, pp. 768-784.
@article{"International Journal of Business, Human and Social Sciences:58922", author = "S. Sabbour and H. Lasi and P. von Tessin", title = "Business Intelligence and Strategic Decision Simulation", abstract = "The purpose of this study is two-fold. First, it attempts to explore potential opportunities for utilizing visual interactive simulations along with Business Intelligence (BI) as a decision support tool for strategic decision making. Second, it tries to figure out the essential top-level managerial requirements that would transform strategic decision simulation into an integral component of BI systems. The domain of particular interest was the application of visual interactive simulation capabilities in the field of supply chains. A qualitative exploratory method was applied, through the use of interviews with two leading companies. The collected data was then analysed to demonstrate the difference between the literature perspective and the practical managerial perspective on the issue. The results of the study suggest that although the use of simulation particularly in managing supply chains is very evident in literature, yet, in practice such utilization is still in its infancy, particularly regarding strategic decisions. Based on the insights a prototype of a simulation based BI-solution-extension was developed and evaluated.
", keywords = "Business Intelligence, decision support, strategic decisions, simulation, SCM.", volume = "6", number = "1", pages = "124-8", }
