Bike-sharing platforms are becoming increasingly popular in urban transit systems worldwide. However, maintaining a balance between bike availability and user demand is crucial for a convenient user experience and operational efficiency. This study focuses on identifying bike imbalance within bike-sharing platforms, particularly the Digital Bikes service at Makerere University. The paper examines the presence of bike imbalance at a highly trafficked docking station within the platform and suggests using data visualisation and analytic methods to address it. The study proposes various metrics for detecting imbalance and uses data visualisations to clearly represent the surplus and deficits of bikes in a bike-sharing network.