Accelerating Financial Close Cycles in Multinational Enterprises: A Digital Optimization Model Using Power BI and SQL Automation

• Author(s): Nnadozie Odinaka ; Chinelo Harriet Okolo ; Onyeka Kelvin Chima ; Oluwatobi Opeyemi Adeyelu
• Paper ID: 1709976
• Page: 504-523
• Published Date: 31-05-2021
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 4 Issue 11 May-2021

Abstract

Multinational enterprises (MNEs) face increasing pressure to reduce their financial close cycles without compromising data accuracy, compliance, or audit readiness. This paper proposes a digital optimization model that integrates Microsoft Power BI with SQL-based process automation to accelerate the financial close process. The model addresses major inefficiencies in traditional workflows by enabling real-time reporting, automated reconciliations, and seamless data integration across multiple subsidiaries and ERPs. Leveraging insights from both internal implementation and comparative industry benchmarking, the study demonstrates how automation improves timeliness, reduces manual interventions, and enhances governance. Using a multi-phase methodological approach, the model was tested across a sample of five MNEs operating in diverse regulatory environments. Results revealed a 35% average reduction in close cycle time and notable improvements in data transparency. The findings have significant implications for digital finance transformation in large-scale enterprises seeking agility, control, and compliance in an increasingly complex regulatory landscape.

Keywords

Power BI, SQL Automation, Financial Close, Digital Optimization, Multinational Enterprises, Compliance

Citations

IRE Journals:
Nnadozie Odinaka , Chinelo Harriet Okolo , Onyeka Kelvin Chima , Oluwatobi Opeyemi Adeyelu "Accelerating Financial Close Cycles in Multinational Enterprises: A Digital Optimization Model Using Power BI and SQL Automation" Iconic Research And Engineering Journals Volume 4 Issue 11 2021 Page 504-523

IEEE:
Nnadozie Odinaka , Chinelo Harriet Okolo , Onyeka Kelvin Chima , Oluwatobi Opeyemi Adeyelu "Accelerating Financial Close Cycles in Multinational Enterprises: A Digital Optimization Model Using Power BI and SQL Automation" Iconic Research And Engineering Journals, 4(11)