Excess inventory negatively impacts financial performance due to increased holding and working capital costs, stock value depreciation and lost sales from other products. For durable finished goods inventory within e-commerce, this issue of excess stock could be amplified given the risk of long-term accumulation and specific nature of goods, as well as the industry's competitive emphasis on broad product assortments and short delivery times. Despite improvements in forecasting, procurement and inventory management, the problem of excess stock is likely to persist, highlighting the importance of effective reactive control. This study proposes a binary programming model for optimizing reactive control strategies for excess inventory through cost minimization, tailored to the use case of a large e-commerce company, which remains specified due to confidentiality. The total costs consist of holding costs, working capital costs, transport costs and opportunity costs from lost revenue opportunities. The model considers three control strategies: 'keep in stock', 'return', 'liquidate', and incorporates warehouse capacity constraints. The model has been deployed for optimizing the excess stock from 27 November 2024, consisting of over 44 thousand excess items. Under limited warehouse capacity, the model yielded a 19% retention rate, 67% return rate, 14% liquidation rate, resulting in total excess stock costs of - €166k. Under unlimited warehouse capacity, eliminating opportunity costs of keep-in-stock, the model yielded a 31% retention rate, 59% return rate, 11% liquidation rate, resulting in total excess stock costs of - €215k. Thus, in both capacity scenarios, profit could be generated through optimal excess stock management. Optimal control decisions showed significant sensitivity to capacity constraints, return eligibility, expected stock days and the financial benefit of clearing compared to regular sale. Excess stock costs are mainly impacted by the opportunity costs of keep-in-stock and clearing, which are mostly sensitive to the rate at which excess stock depreciates in value, and the expected days in stock. Working capital, inventory holding and transport costs only have little effect. Given the clear relationships, optimal control decisions can be closely approximated with simple decision rules based on stock metrics, presenting a time-efficient alternative to exact optimization. Concluding, the optimization of reactive control strategies can significantly improve the performance of excess stock of the company. In the broader context of durable finished goods e-commerce platforms, this study suggest that incorporating opportunity costs alongside direct costs, and differentiating excess stock management strategies based on seasonality, could enhance excess stock management.