Intelligent Management Analytics: A Blockchain and Machine Learning Framework for Finance, CRM, Human Resources, and Education management

Abstract

The advent of digital technologies, the ways in which businesses manage their organizations have changed drastically, creating huge amounts of data to be collected across a range of areas including finance, customer relationship management (CRM), human resources (HRM) and education. Many traditional management systems struggle with issues of data security, transparency, scalability, and predictive decision making. To overcome these challenges and enable intelligent organizational governance, this study proposes an Intelligent Management Analytics Framework (IMAF) which combines Blockchain and Machine Learning technologies. The architecture of the blockchain is decentralized and immutable, while the machine learning capabilities predict and analyze data, improving data integrity, efficiency of operations, and decision accuracy. The framework was designed using an approach called Design Science Research, which involved collecting data, preprocessing, validating the blockchain, creating smart contracts, implementing machine learning analytics, and establishing decision-making tools. The significant improvements gained through simulation-based evaluation included fraud detection, customer retention, employee performance management, and student outcome prediction. The results show improvements in transparency, security, auditability and predictive performance in all areas of management. The proposed framework is a comprehensive, scalable, and secure solution for data-driven decision-making and helps evolve intelligent and sustainable organizational management in the digital era.