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Information systems research has made impressive progress in understanding the potential of big data and its analytics, often resulting in valuable managerial advice on how these could benefit various organisational operations and entire industries. At the same time, intensive research on how new data-driven practices, organisational changes and managerial intentions interact when big data analytics enters a specific organisational setting is still sparse. The adoption of a new technological artefact comes often with side effects that may twist, qualify or even overshadow the intended gains of technology.

We draw from Transformational Model of Social Activity (TMSA) to adapt the theory of reactivity to explain how the introduction of big data analytics (BDA) leads to both intended and unintended organisational changes. The analysis brings together the level of work-practices and organisational change that have been hitherto analysed separately in learnings analytics and, more generally, in big data analytics literature.

We conduct a case study of an internationally recognised business school that has deployed a sophisticated learning analytics (LA) system in response to the need to closer monitor student and staff activity. We find that:

1. The introduction of new measurement and monitoring capabilities shapes various work practices
2. Big data analytics systems become nexuses of reactive mechanisms by introducing new ways of producing, displaying and circulating data
3. That these lead to both intended and unintended reproduction and transformation of organisational structures.