When an order arrives at a warehouse it is usually assigned to a batch and a decision is made on how long to wait before assigning the batch to a picker and starting the picking tour. If the idle time of the pickers is minimised, the batch is immediately assigned, and the picking starts. Alternatively, if a time window is introduced, other orders may arrive, and more efficient batches may be formed. The method to decide how long to wait (the time-window strategy) is therefore important but, surprisingly, almost completely overlooked in the literature. In this paper, we demonstrate that this lack of attention is unwarranted, and that the time-window method significantly influences the overall warehouse performance. In the context of the online order batching problem (OOBP), we first demonstrate that the effects of different time-window strategies are independent of the methods used to solve the other subproblems of the OOBP (batching and routing). Second, we propose two new time-window strategies, compare them to existing methods, and prove that our methods outperform those in the literature under various scenarios. Finally, we show how time-window methods influence different objective functions of the OOBP when varying numbers of orders and pickers.