Abstract
The risk management over a supply chain has to be founded on the management controls in each of the partner companies in the chain. Inevitably, the business relationship and operations dependence bind the control efforts of partner companies together. This proposes challenges for supply chain risk management and at the same time for the BI application. In this paper we analyse the management control situations where business intelligence technology can be applied and describe the concepts of systematic risk analysis to improve the management controls, based on causal analysis of business exceptions. The analysis process is driven by diagnostic drill-down operations following the equations of the information structure in which the data are organised. Using business intelligence, the analysis method can generate explanations supported by the data. A “risk template” is provided to assist analysts to fully comprehend the risk scenario in the practical business setting, so as to evaluate and re-design the existing controls, and to apply BI for management improvement.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Rushton, A.: International Logistics and Supply Chain Outsourcing: From Local to Global. Kogan Page Publishers, London (2007)
Christopher, M., Lee, H.L.: Mitigating supply chain risk through improved confidence. Int. J. Phys. Distrib. Logist. Manag. 34, 388–396 (2004). doi:10.1108/09600030410545436
Bartlett, P.A., Julien, D.M., Baines, T.S.: Improving supply chain performance through improved visibility. Int. J. Logist. Manag. 18, 294–313 (2007). doi:10.1108/09574090710816986
Peck, H.: Drivers of supply chain vulnerability: an integrated framework. Int. J. Phys. Distrib. Logist. Manag. 35, 210–232 (2005). doi:10.1108/09600030510599904
Hulstijn, J., Overbeek, S.: International Logistics and Supply Chain Outsourcing: From Local to Global. Advanced Information Systems Engineering Workshops, pp. 351–365. Springer, Berlin (2012)
Lee, G., Kulkarni, U.: Business intelligence in corporate risk management. AMCIS (2011)
Davenport, T.: Competing on analytics. Harv. Bus. Rev. 84, 98–107 (2006)
Sodhi, M.S., Tang, C.S.: Managing supply chain disruptions via time-based risk management. In: Wu, T., Blackhurst, J. (eds.) Managing Supply Chain Risk and Vulnerability, pp. 29–40. Springer, London (2009)
Lund, M.S., Solhaug, B., Stølen, K.: Model-Driven Risk Analysis: The CORAS Approach, 460 pp. Springer, Berlin (2011). doi:10.1007/978-3-642-12323-8
Rizzi, S.: Collaborative business intelligence. In: Aufaure, M.-A., Zimányi, E. (eds.) eBISS 2011. LNBIP, vol. 96, pp. 186–205. Springer, Heidelberg (2012)
Van Baalen, P., Zuidwijk, R., van Nunen, J.: Port inter-organizational information systems: capabilities to service global supply chains. Foundations and Trends® in Technology. Inf. Oper. Manag. 2, 81–241 (2009). doi:10.1561/0200000008
Hofman, W.: Compliance management by business event mining in supply chain networks. VMBO (2013)
Das, T.K., Teng, B.-S.: Between trust and control: developing confidence in partner cooperation in alliances. Acad. Manag. Rev. 23, 491–512 (1998)
Tomkins, C.: Interdependencies, trust and information in relationships, alliances and networks. Acc. Organ. Soc. 26, 161–191 (2001). doi:10.1016/S0361-3682(00)00018-0
Laurier, W., Poels, G.: Invariant conditions in value system simulation models. Decis. Support Syst. (2013). doi:10.1016/j.dss.2013.06.009
Turetken, O., Elgammal, A., van den Heuvel, W.J., Papazoglou, M.: Enforcing compliance on business processes through the use of patterns. ECIS 2011 Proceedings, Paper 5 (2011)
Milliken, F.J.: Three types of perceived uncertainty about the environment: state, effect, and response uncertainty. Acad. Manag. Rev. 12, 133 (1987). doi:10.2307/257999
Von Wright, G.: Explanation and understanding. Annu. Rev. Psychol. 57, 227–254 (1971). doi:10.1146/annurev.psych.57.102904.190100
Vasarhelyi, M.A., Alles, M.G., Kogan, A.: Principles of analytic monitoring for continuous assurance. J. Emerg. Technol. Acc. 1, 1–21 (2004). doi:10.2308/jeta.2004.1.1.1
Bay, S., Kumaraswamy, K., Anderle, M.G., Kumar, R., Steier, D.M.: Large scale detection of irregularities in accounting data. In: Sixth IEEE International Conference on Data Mining, 2006. ICDM’06, pp 75–86. IEEE (2006)
Caron, E.A.M.: Explanation of Exceptional Values in Multi-dimensional Business Databases. Erasmus University Rotterdam (2012)
Caron, E.A.M., Daniels, H.A.M.: Business analysis in the OLAP context. In: Cordeiro, J., Filipe, J. (eds) ICEIS 2009, Milan, Italy, pp. 325–330 (2009)
Caron, E.A.M., Daniels, H.A.M.: Explanation of exceptional values in multi-dimensional business databases. Eur. J. Oper. Res. 188, 884–897 (2008). doi:10.1016/j.ejor.2007.04.039
Feelders, A., Daniels, H.A.M.: A general model for automated business diagnosis. Eur. J. Oper. Res. 130, 623–637 (2001). doi:10.1016/S0377-2217(99)00428-2
Alles, M.G., Kogan, A., Vasarhelyi, M.A., Wu, J.: Analytical Procedures for Continuous Data Level Auditing: Continuity Equations (2010)
Feelders, A., Daniels, H.A.M.: Methodological and practical aspects of data mining. Inf. Manag. 37, 271–281 (2000). doi:10.1016/S0378-7206(99)00051-8
Van Oosterhout, M.P.A.: Organizations and flows in the network. In: van Baalen, P., Zuidwijk, R., van Nunen, J. (eds.) Port Inter-Organizational Information Systems: Capabilities to Service Global Supply Chains, pp. 176–185. Now Publishers, Hanover (2009)
Pham, D.A.: EDA & Data Mining for Supply Chain Security: Risk Analysis at the Dutch Customs. Erasmus University Rotterdam (2008)
Acknowledgements
This work was supported by the EC FP7 project CASSANDRA (Grant agreement no: 261795). We are thankful to Dr. Jan van Dalen and Dr. Marcel van Oosterhout for their constructive advice, and to Ron Triepels for his help in developing the case study.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Liu, L., Daniels, H., Hofman, W. (2014). Business Intelligence for Improving Supply Chain Risk Management. In: Hammoudi, S., Cordeiro, J., Maciaszek, L., Filipe, J. (eds) Enterprise Information Systems. ICEIS 2013. Lecture Notes in Business Information Processing, vol 190. Springer, Cham. https://doi.org/10.1007/978-3-319-09492-2_12
Download citation
DOI: https://doi.org/10.1007/978-3-319-09492-2_12
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09491-5
Online ISBN: 978-3-319-09492-2
eBook Packages: Computer ScienceComputer Science (R0)