User Behaviour Analytics for Personalised Reporting in Enterprise Business Intelligence

Abstract

Organisations are spending a lot of money on analytics platforms, but business intelligence tooling adoption is still painfully low. Empirical data indicate that despite the growth in the use of analytics in most organisations, in practice, only about one third of employees engage with analytics and business intelligence tools. Simultaneously, conventional dashboards tend to be cognitively loaded and require high data literacy, which restricts their influence on daily decision practice. This conceptual essay discusses how user behaviour analytics can be applied to create automated personalised reports that are more aligned to the tasks, roles, and decision contexts of organisational users, and which meet high privacy and governance standards. Based on a narrative review of scholarly and practitioner literature on dashboards, behavioural analytics, and compliance frameworks, the article suggests a reference architecture that links behavioural telemetry with personalisation levers including widget ordering, narrative text, and alert policies. It then places this architecture in the context of privacy and risk frameworks such as the General Data Protection Regulation, the California Consumer Privacy Act, the ISO and IEC privacy information management standards, and the National Institute of Standards and Technology Artificial Intelligence Risk Management Framework. The essay ends by stating that informed personalisation based on behaviour can enhance perceived relevance, time to insight, and trust in analytics, but only when it is integrated into explicit governance structures and open organisational communication.