Summary: This paper describes our experience with a simple modeling and programming approach for increasing the amount of constraint propagation in the constraint solving process. The idea, although similar to redundant constraints, is based on the concept of redundant modeling. We introduce the notions of CSP model and model redundancy, and show how mutually redundant models can be combined and connected using channeling constraints. The combined model contains the mutually redundant models as sub-models. Channeling constraints allow the sub-models to cooperate during constraint solving by propagating constraints freely amongst the sub-models. This extra level of pruning and propagation activities becomes the source of execution speedup, real-life nurse rostering system. We perform two case studies to evaluate the effectiveness and efficiency of our method. The first case study is based on the simple and well-known \(n\)-queens problem, while the second case study applies our method in the design and construction of a real-life nurse rostering system. Experimental results provide empirical evidence in line with our prediction.