ArticleOpen Access http://dx.doi.org/10.26855/ea.2026.09.006
Enterprise Data Analytics Frameworks and the Improvement of Operational Decision Response Efficiency
Chengfeng Jin
Carey Business School, Johns Hopkins University, Baltimore, MD 21218, USA.
*Corresponding author: Chengfeng Jin
Published: July 21, 2026
Abstract
Enterprise operational decisions are being influenced by fluctuations in orders, supply chain delays, inventory usage, customer response pressure, and cross-departmental collaboration costs. Traditional reporting-based analysis often relies on periodic summaries and manual verification. When anomalies propagate from the front-line nodes to the management level, they have already shown significant delays, making it difficult to support rapid response and resource reallocation. By building an enterprise data analysis framework around data governance, real-time collection, scenario modeling, hierarchical response, and feedback calibration, it is possible to integrate scattered data from ERP, CRM, WMS, MES, and external logistics platforms into a unified analysis chain. This enables continuous closed-loop processes for anomaly identification, cause location, solution generation, execution tracking, and result review. Anonymous samples of enterprise order fulfillment and inventory scheduling show that this framework demonstrates improvement trends in indicators such as anomaly detection time, cause location time, closed-loop completion time, warning accuracy, and manual verification frequency, providing a feasible technical path for enterprises to shorten operational decision response cycles, enhance resource scheduling accuracy, and stabilize cross-departmental collaboration.
Keyword
Enterprise data analysis framework; operational decision; response efficiency; real-time analysis
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Copyright
© 2026 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
https://creativecommons.org/licenses/by-nc-nd/4.0/
How to cite this paper
Enterprise Data Analytics Frameworks and the Improvement of Operational Decision Response Efficiency
How to cite this paper: Chengfeng Jin. (2026). Enterprise Data Analytics Frameworks and the Improvement of Operational Decision Response Efficiency. Engineering Advances, 6(3), 162-166.
DOI: http://dx.doi.org/10.26855/ea.2026.09.006