THE RISE OF PREDICTIVE ANALYTICS IN MANAGEMENT ACCOUNTING: FROM DESCRIPTIVE TO PRESCRIPTIVE

Abstract

The rapid development of predictive analytics is deeply changing the face of management accounting, from its traditional descriptive reporting orientation to dynamic data-driven insight generation. Predictive analytics uses statistical modeling, machine learning, and big data to provide forward-looking views of future trends and proactive decisions on budgeting, planning, and performance management. Moving beyond historical data analyses, it empowers management accountants to anticipate risks, discover new opportunities, and simulate business scenarios for strategic decisions. This evolution allows the introduction of prescriptive analytics, which, besides predicting an outcome, would also suggest the optimal strategy towards achieving those outcomes and hence facilitates higher-value decision-making within organizations. However, the full potential of predictive and prescriptive analytics needs concerted efforts in data quality management, technological adoption, and upskilling of the workforce. The ICAI underlines the primacy of ethical standards, transparency in processes for algorithms, and stewardship over confidential financial information to sustain confidence in the outputs of accounting. As predictive analytics becomes more central to the practice of management accounting, there is a strong need for professionals to focus on strong data governance, continuous professional education, and ethical responsibility to use such tools competently and responsibly. In that sense, the advent of predictive analytics presents a sea change in the way management accounting works and enables the transition of organizations from retrospective reporting towards prospective, strategic leadership in the digital era.