Business Intelligence and Analytics in Supply Chain Management
Main Article Content
Abstract
The objective of this study is to provide informative information to assist practitioners, researchers, and decision-makers in navigating the ever-changing environment of operations management. The constantly shifting terrain of the contemporary corporate world places a premium on strong operations management as an essential component of any organization. It is impossible to satisfy the needs of customers, bring down operating expenses, and achieve operational excellence without first developing a seamless orchestration of resources, processes, and people. Business Intelligence (BI) and Analytics are becoming more important to enterprises as crucial tools for making decisions based on data for them to succeed in the current fast-paced environment.
Downloads
Metrics
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.
References
C. Wilder and C. Ozgur, “Business analytics for business analysts in manufacturing,” Operations
and Service Management, pp. 272–280, 2018. doi:10.4018/978-1-5225-3909-4.ch013
R. Saxena and A. Srinivasan, “Business intelligence,” International Series in Operations Research
& Management Science, pp. 85–99, 2012. doi:10.1007/978-1-4614-6080-0_7
“Supply Chain Performance Management (SCPM) Als interorganizational steuerungskonzeption
für das Supply Chain Management,” Supply chain Performance Management, pp. 211–263.
doi:10.1007/978-3-8350-9026-2_4
S. Zeng, M. A. Cohen, B. J. Steele, and J. Sairamesh, “A supplier performance evaluation solution
for proactive supplier Quality Management,” 2008 IEEE International Conference on e-Business
Engineering, 2008. doi:10.1109/icebe.2008.90
“Inventory control,” Springer Reference. doi:10.1007/springerreference_6796
A. J. Noga, Adjustable bandwidth concept (ABC) performance evaluation, 2003.
doi:10.21236/ada416986
C. R. Silversides and U. Sundberg, “Operational efficiency,” Operational Efficiency in Forestry,
pp. 3–4, 1989. doi:10.1007/978-94-017-0506-6_2
“Key performance indicators,” Project Management Metrics, KPIs, and Dashboards, pp. 117–164,
doi: 10.1002/9781118826751.ch4
Y. Cook and T. Naidoo, “Business process automation: Automating and monitoring the
mortgage process,” Business Process Automation, pp. 73–82, 2004. doi:10.1007/978-3-540-24702-
_6.