THE FUTURE OF FINANCIAL PLANNING: TRENDS AND INNOVATIONS IN ENTERPRISE PERFORMANCE MANAGEMENT
Keywords:
Enterprise Performance Management (EPM), Artificial Intelligence In Finance, Cloud-Based Financial Planning, Blockchain In AccountingAbstract
This article explores the transformative impact of emerging technologies on Enterprise Performance Management (EPM) and the future of financial planning. It examines how artificial intelligence (AI), cloud computing, and blockchain are revolutionizing traditional EPM practices, enabling organizations to shift from reactive to predictive financial planning. The article delves into AI-driven analytics for deeper financial insights, the benefits of cloud-based EPM solutions in fostering scalability and real-time collaboration, and blockchain's role in enhancing data security and transparency. Through a comprehensive analysis of these technological advancements, the article highlights their potential to improve forecasting accuracy, streamline complex financial tasks, and bolster trust in financial reporting and compliance. Additionally, it provides strategic guidance for organizations looking to implement these innovations, addressing key considerations such as data quality, security concerns, and the need for upskilling finance teams. By synthesizing current research and industry trends, this study offers valuable insights into how businesses can leverage these technologies to optimize their financial performance, make more informed decisions, and maintain a competitive edge in an increasingly dynamic global marketplace. The article concludes by emphasizing the critical role of these technological innovations in shaping the future landscape of financial planning and management.
References
M. Smith, "Predicts 2021: Data and Analytics Strategies to Govern, Scale and Transform Digital Business," Gartner, Dec. 2020. [Online]. Available: https://www.gartner.com/en/documents/3993855
Y. Wang and A. Kogan, "Designing privacy-preserving blockchain-based accounting information systems," International Journal of Accounting Information Systems, vol. 30, pp. 1-18, Mar. 2018. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S1467089518300794
S. Makridakis, E. Spiliotis, and V. Assimakopoulos, "Statistical and Machine Learning forecasting methods: Concerns and ways forward," PLOS ONE, vol. 13, no. 3, p. e0194889, Mar. 2018. [Online]. Available: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194889
R. Buyya et al., "A Manifesto for Future Generation Cloud Computing: Research Directions for the Next Decade," ACM Computing Surveys, vol. 51, no. 5, pp. 1-38, Nov. 2018. [Online]. Available: https://dl.acm.org/doi/10.1145/3241737
M. Stieninger, D. Nedbal, W. Wetzlinger, G. Wagner, and M. A. Erskine, "Impacts on the organizational adoption of cloud computing: A reconceptualization of influencing factors," Procedia Technology, vol. 16, pp. 85-93, 2014. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2212017314002989
F. Casino, T. K. Dasaklis, and C. Patsakis, "A systematic literature review of blockchain-based applications: Current status, classification and open issues," Telematics and Informatics, vol. 36, pp. 55-81, Mar. 2019. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0736585318306324
M. Nofer, P. Gomber, O. Hinz, and D. Schiereck, "Blockchain," Business & Information Systems Engineering, vol. 59, no. 3, pp. 183-187, Jun. 2017. [Online]. Available: https://link.springer.com/article/10.1007/s12599-017-0467-3
A. Troshani, D. Janssen, A. Lymer, and L. D. Parker, "Digital transformation of business-to-government reporting: An institutional work perspective," International Journal of Accounting Information Systems, vol. 31, pp. 17-36, 2018. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S146708951730180X
M. Niranjanamurthy, B. N. Nithya, and S. Jagannatha, "Analysis of Blockchain technology: pros, cons and SWOT," Cluster Computing, vol. 22, pp. 14743–14757, 2019. [Online]. Available: https://link.springer.com/article/10.1007/s10586-018-2387-5