The impact of supply chain management on business intelligence

Authors

  • Audrey Langlois La Rochelle University, France
  • Benjamin Chauvel La Rochelle University, France

DOI:

https://doi.org/10.37380/jisib.v7i2.239

Keywords:

Business intelligence, information systems, real-time business intelligence, supply chain management

Abstract

This conceptual paper investigates the impact of the supply chain on business
intelligence (BI) in private companies. The article focuses on these two subjects in order to
broadly understand the concept of business intelligence, supply chain and characteristics
implement such as OLAP, data warehouse or data mining. It looks at the joint advantages of
the business intelligence and supply chain concepts and revisits the traditional BI concept. We
found that the supply chain includes many data samples collected from the first supplier to the
last customer, which have to be analysed by the company in order to be more efficient. Based
on these observations the authors argue for why it makes sense to see the BI function as an
extension of supply chain management, but moreover they show how difficult it has become to
separate BI from other IT intensive processes in the organization.

References

Adelman, S., Moss, L., & Barbusinski, L. (2002).

I found several definitions of BI. DM Review,

-1.

Amara, Y., Søilen, K. S., & Vriens, D. (2012).

Using the SSAV model to evaluate Business

Intelligence Software. Journal of Intelligence

Studies in Business, 2(3).

Azvine, B., Cui, Z., & Nauck, D. D. (2005).

Towards real-time business intelligence. BT

Technology Journal, 23(3), 214-225.

Sahay, B. S., & Ranjan, J. (2008). Real time

business intelligence in supply chain

analytics. Information Management &

Computer Security, 16(1), 28-48.

Berson, A., & Smith, S. J. (2002). Building data

mining applications for CRM. McGraw-Hill,

Inc.

Berthiaume D., (2015). Getting smart about

supply chain efficiency. BT Technology

Journal, Vol. 23 No. 3, pp. 214-25.

Chen, H., Chiang, R.H.L. & Storey, V.C., (2012).

Business intelligence and analytics: From big

data to big impact, MIS Quarterly 36(4), 1165–

Christopher, M. (1998). Logistics and supply

chain management: strategies for reducing

cost and improving service. London. Financial

times.

Gartner (2012). Gartner says worldwide business

intelligence, analytics and performance

management software market surpassed the

$12 billion mark in 2011.

Imhoff, C. (2003). Intelligent Solutions Keep Your

Friends Close, and Your Enemies Closer. DM

REVIEW, 13, 36-41.

Ittmann, H. W. (2015). The impact of big data and

business analytics on supply chain

management: original research. Journal of

Transport and Supply Chain

Management, 9(1), 1-9.

Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S.,

Nix, N. W., Smith, C. D., & Zacharia, Z. G.

(2001). Defining supply chain

management. Journal of Business

logistics, 22(2), 1-25.

Krupnik, Y., (2013). 7 ways predictive analytics

helps retailers manage suppliers, Predictive

Analytics Times, 26 August 2013, viewed 07

November 2014, from

http://www.predictiveanalyticsworld.com/pati

mes/7-ways-predictive-analytics- helpsretailers-

manage-suppliers/

Lambert, D. M., Stock, J. R., & Ellram, L. M.

(1998). Fundamentals of logistics

management. McGraw-Hill/Irwin.

Malhotra, Y. (2001). From Information

Management to Knowledge Management.

Beyond the'Hi-Tech

Hidebound'Systems. Knowledge management

and business model innovation, 115-134.

Negash, S. (2004). Business intelligence. ,

Communications of the Association for

Information Systems (Volume13) 177-195.

Nguyen, T. M., Schiefer, J., & Tjoa, A. M. (2005,

November). Sense & response service

architecture (SARESA): an approach towards

a real-time business intelligence solution and

its use for a fraud detection application.

In Proceedings of the 8th ACM international

workshop on Data warehousing and

OLAP (pp. 77-86). ACM.

Reinschmidt, J., & Francoise, A. (2000). Business

intelligence certification guide. IBM

International Technical Support

Organisation.

Roach Partridge. A, (2013). Business

Intelligence in the Supply

Chain. Avaliable at

http://www.inboundlogistics.com/cms/article/b

usiness-intelligence-in-the-supply-chain/

Robinson, M. (2002). Business intelligence

infrastructure. DM Review, BI Report,

available at: www. dmreview.

com/article_sub. cfm

Rao, S., & Swarup, S. (2001). Business

intelligence and logistics. Florida: Wipro

Technologies.

Šerić, N., Rozga, A., & Luetić, A. (2014).

Relationship between Business Intelligence

and Supply Chain Management for Marketing

Decisions. Universal Journal of Industrial

and Business Management, 2(2), 31-35.

Stefanovic, N., Majstorovic, V., & Stefanovic, D.

(2006). Supply Chain Business Intelligence

Model. In Proceedings 13th International

Conference on Life Cycle Engineering (pp. 613-

.

Søilen, K. S. (2013). An overview of articles on

Competitive Intelligence in JCIM and

CIR. Journal of Intelligence Studies in

Business, 3(1).

Sabanovic, A., & Søilen, K. S. (2012). Customers’

Expectations and Needs in the Business

Intelligence Software Market. Journal of

Intelligence Studies in Business, 2(1).

Solberg Søilen, K. (2012). The fallacy of the

service economy: a materialist

perspective. European Business Review, 24(4),

-319.

Jenster, P., & Søilen, K. S. (2013). The

Relationship between Strategic Planning and

Company Performance–A Chinese

perspective. Journal of Intelligence Studies in

Business, 3(1).

Søilen, K. S. (2010). Boosting innovation and

knowledge through delocalization: market

intelligence at trade shows. Problems and

Perspectives in Management, 8(3), 200-207.

Søilen, K. S. (2012). Geoeconomics. Bookboon.

Søilen, K. S. (2013). An overview of articles on

Competitive Intelligence in JCIM and

CIR. Journal of Intelligence Studies in

Business, 3(1).

Stadtler, H. (2004). Supply chain management

and advanced planning––basics, overview and

challenges. European journal of operational

research, 163(3), 575-588.

Trebilcock, B. (2016). Top 20 supply chain

management software suppliers: the market

for conventional solutions continues to rise,

even as innovative variations help the

industry chart a new course. Logistics

management (Highlands Ranch, Colo.: 2002).

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Published

2017-07-10