Tandem queues with zero buffers find many applications in systems where jobs are processed via a predefined number of sequential processing steps. From an analytic point of view, the analysis of such systems is highly complicated, caused by the phenomenon of after-service blocking (ASB). ASB occurs when a completed job occupies a server while waiting for the next phase. This challenge is addressed by introducing and comparing heuristics to quantify the impact of ASB on the performance of the tandem queue. Our proposed heuristics offer significant advantages over existing methods, delivering more insightful and accurate performance estimations. This allows for faster evaluations and their use in optimization, making it ideal for real-time decision making and capacity allocation. This research presents a valuable tool for queueing system designers and managers to make informed decisions regarding capacity allocation, resource management, and service level optimization, particularly in scenarios with limited budgets.