Abstract
Strategic management is one of the most important aspects that lead to companies’ success. The process of building a complex strategy needs a lot of time and effort, especially with the increasing speed of changes in the markets and the speed of obtaining information. It was necessary to use new tools that help decision makers. Here the role of business intelligence has emerged, which provides all that is necessary for the decision makers to be in a state of readiness to build strategies or modify them based on real-time data.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
X. Belle, Peng, Review of business intelligence through data analysis. BIJ 21(2), 300–311 (2014). https://doi.org/10.1108/BIJ-08-2012-0050
R. Heath, Prediction machines: The simple economics of artificial intelligence. J. Inform. Technol. Case Appl. Res. 21(3–4), 163–166 (2019). https://doi.org/10.1080/15228053.2019.1673511
Larson, Chang, A review and future direction of agile, business intelligence, analytics and data science. Int. J. Inform. Manage. 36(5), 700–710 (2016). https://doi.org/10.1016/j.ijinfomgt.2016.04.013
Vercellis, Business intelligence: data mining and optimization for decision making (Wiley, London, 2009)
L. Arnott, Song, Patterns of business intelligence systems use in organizations. Decis. Support Syst. 97, 58–68 (2017)
D. Wiltbank, Read, D. Sarasvathy, What to do next? The case for non-predictive strategy. Strat. Manage. J. 27(10), 981–998 (2006). https://doi.org/10.1002/smj.555
Thevenet, Salinesi, Aligning IS to organization’s strategy: The InStAl method BT, in Advanced Information Systems Engineering, (Springer, Berlin, 2007), pp. 203–217
M.-R. Bragge, Nurmi, Tanner, A repeatable e-collaboration process based on thinklets for multi-organization strategy development. Group Decis. Negot. 16(4), 363–379 (2007). https://doi.org/10.1007/s10726-006-9055-5
F. Yean, K. Yahya, The influence of human resource management practices and career strategy on career satisfaction of insurance agents. Int. J. Business Soc. 14(2), 193 (2013)
Tomlin, Wang, Operational strategies for managing supply chain disruption risk, in The Handbook of Integrated Risk Management in Global Supply Chains, (Wiley, Oxford, 2011), pp. 79–101. https://doi.org/10.1002/9781118115800
J. Teece, A capability theory of the firm: An economics and (strategic) management perspective. N. Z. Econ. Pap. 53(1), 1–43 (2019). https://doi.org/10.1080/00779954.2017.1371208
P. Rony, Florinda, Knowledge management as a factor for the formulation and implementation of organization strategy. J. Knowl. Manage. 21(2), 308–329 (2017). https://doi.org/10.1108/JKM-02-2016-0068
Gurel, Tat, SWOT analysis: A theoretical review. J. Int. Soc. Res. 10(51), 51–66 (2017). https://doi.org/10.17719/jisr.2017.1832
M. Abdel-Basset, Smarandache, An extension of neutrosophic AHP–SWOT analysis for strategic planning and decision-making. Symmetry 10, 4 (2018). https://doi.org/10.3390/sym10040116
C. Merino, S. Rivas, Piattini, A data quality in use model for big data. Futur. Gener. Comput. Syst. 63, 123–130 (2016). https://doi.org/10.1016/j.future.2015.11.024
Kahlawi, An ontology driven ESCO LOD quality enhancement. Int. J. Adv. Comp. Sci. Appl. 11, 60 (2020). https://doi.org/10.14569/IJACSA.2020.0110308
M. Smith, A. Roster, L. Golden, S. Albaum, A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel to MTurk samples. J. Bus. Res. 69(8), 3139–3148 (2016). https://doi.org/10.1016/j.jbusres.2015.12.002
Choi, Luo, Data quality challenges for sustainable fashion supply chain operations in emerging markets: Roles of blockchain, government sponsors and environment taxes. Transp. Res. 131, 139–152 (2019). https://doi.org/10.1016/j.tre.2019.09.019
R. CĂ´rte-Real, Oliveira, Leveraging internet of things and big data analytics initiatives in European and American firms: Is data quality a way to extract business value? Inf. Manag. 57(1), 103141 (2020). https://doi.org/10.1016/j.im.2019.01.003
G. Juddoo, Duquenoy, Windridge, Data governance in the health industry: investigating data quality dimensions within a big data context. Appl. Syst. Innov. 1, 4 (2018). https://doi.org/10.3390/asi1040043
T. Taleb. A. El Kassabi. Serhani, Dssouli, and Bouhaddioui, Big data quality: A quality dimensions evaluation, in 2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld), 2016, pp. 759–765
Z. Fang, J. Elmore, A. Chien, UDP: A programmable accelerator for extract-transform-load workloads and more, in Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017, pp. 55–68
A. Yulianto, Extract transform load (ETL) process in distributed database academic data warehouse. J. Comp. Sci. Inform. Technol. 4(2), 61–68 (2019). https://doi.org/10.11591/aptikom.j.csit.36
E. Pearlson, S. Saunders, F. Galletta, Managing and Using Information Systems: A Strategic Approach (Wiley, New York, 2019)
S. Tohir, Kusrini, Sudarmawan, On-Line Analytic Processing (OLAP) modeling for graduation data presentation, in 2017 2nd International conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE), 2017, pp. 132–135
Quiceno et al., Scenario analysis for strategy design: A case study of the Colombian electricity industry. Energ. Strat. Rev. 23, 57–68 (2019). https://doi.org/10.1016/j.esr.2018.12.009
Cairns, Wright, in Evaluating the Effectiveness of Scenario Interventions Within Organizations BT-Scenario Thinking: Preparing Your Organization for the Future in an Unpredictable World, ed. by G. Cairns, G. Wright, (Springer, Cham, 2018), pp. 247–255. https://doi.org/10.1007/978-3-319-49067-0_11
F. Hartmann, R. Moawad, L. Traon, GreyCat: Efficient what-if analytics for data in motion at scale. Inf. Syst. 83, 101–117 (2019). https://doi.org/10.1016/j.is.2019.03.004
C. Carvalho, Cazarini, Gerolamo, Manufacturing in the fourth industrial revolution: A positive prospect in sustainable manufacturing. Proc. Manuf. 21, 671–678 (2018). https://doi.org/10.1016/j.promfg.2018.02.170
Malik, Creating competitive advantage through source basic capital strategic humanity in the industrial age 4.0. Int. Res. J. Adv. Eng. Sci. 4(1), 209–215 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kahlawi, A. (2022). Amalgamation of Business Intelligence with Corporate Strategic Management. In: Jeyanthi, P.M., Choudhury, T., Hack-Polay, D., Singh, T.P., Abujar, S. (eds) Decision Intelligence Analytics and the Implementation of Strategic Business Management. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-030-82763-2_10
Download citation
DOI: https://doi.org/10.1007/978-3-030-82763-2_10
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-82762-5
Online ISBN: 978-3-030-82763-2
eBook Packages: EngineeringEngineering (R0)