Evaluating A Business Intelligence Solution. Feasibility Analysis Based On Monte Carlo Method
Mihaela Muntean and
Cornelia Muntean
MPRA Paper from University Library of Munich, Germany
Abstract:
Business Intelligence (BI) initiatives are challenging tasks, implying significant costs in their implementation. Therefore, organizations have adopted prudent policies requiring a financial justification. A business-driven methodology is recommended in any BI project initiative, project scoping and planning being vital for the project success. A business-driven approach of a BI project implementation starts with a feasibility study. The decision-making process for large projects is very complicated, and will not be subject of this paper. Having in mind a middle-sized BI project, a feasibility study based on the Monte Carlo simulation method will be conducted. A SaaS BI initiative versus a traditional one will be taken into consideration.
Keywords: Business Intelligence (BI); Software as a Service (SaaS); Monte Carlo method; BI project feasibility; Total Cost of Ownership (TCO); Return on Investment (ROI); Internal Rate of Return (IRR) (search for similar items in EconPapers)
JEL-codes: C02 C88 G17 L21 L86 M15 (search for similar items in EconPapers)
Date: 2012-11-18, Revised 2013-05-28
New Economics Papers: this item is included in nep-cmp, nep-ore and nep-ppm
References: View references in EconPapers View complete reference list from CitEc
Citations:
Published in ECECSR Journal 2/2013 (2013): pp. 85-102
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/48478/1/MPRA_paper_48478.pdf original version (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:48478
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().