Dynamic microsimulation models have long promised to provide a new level of detail on the image of the future. The Australian model DYNAMOD is one such example. DYNAMOD models behaviour at the individual level, has used groundbreaking techniques to achieve this, and can produce an incredibly in-depth view of Australia’s population out to 2050. However, it has proved to be a long process getting DYNAMOD to the point where it is seen as a valuable tool by potential users – much longer than originally anticipated. The main reason for this has been the lack of attention to alignment in the original model design, and the work subsequently entailed in adding alignment to the model. Alignment is important both in order to enable the specification of future alternative scenarios and to match model output with actual outcomes – such as, labour force outcomes to date. Recognition of the importance of alignment as an essential element for a useful model has seen an emphasis on these aspects of development in recent versions of DYNAMOD. This paper describes some of the alignment processes that have been introduced into the most recent versions of DYNAMOD, with a focus on the techniques used to align processes which are modelled using survival functions. Examples, such as the alignment of fertility, are used to highlight the incremental improvements that have been made to the model. The examples illustrate the benefits of moving from the original unconstrained survival function model to a model using adjusted survival functions and finally to a model which uses survival functions as part of a transition process. Only now, with this capacity for alignment in place, can DYNAMOD start to claim the plausibility, flexibility, transparency and user utility to serve as a useful model.