Wind energy currently is one of the most attractive solutions to help in the goal of switching to a more sustainable way of energy production. To stay competitive with other forms of energy production, the reduction of the Levelized Cost of Energy (LCoE) is an important indicator. One way of achieving this goal is by increasing the size of the wind turbine. As a result, the increased blade length also comes with a significant increase in fatigue loads present on the wind turbine’s rotating and fixed structure. Individual Pitch Control (IPC) forms an interesting opportunity in attenuating these fatigue loads. IPC is generally applied with the help of the Multi-Blade Coordinate (MBC-) transformation. The IPC control strategy uses the Out-of-Plane (OoP) bending moments measured on each blade. The MBC-transformation transforms the measured OoP bending moments towards the non-rotating reference frame. As a result the OoP bending moments are transformed into non-rotating yaw- and tilt-moments. The minimisation of these signals is then used as a control objective. Subsequently, the provided non-rotating control signals are then transformed back to the rotating domain to obtain the implementable individual pitch signals. In the literature this controller synthesis is often employed by two separately operating Single-Input Single-Output (SISO) control loops. Whereby implicitly (or sometimes explicitly) assuming that the yaw- and tilt-moments are sufficiently decoupled to make this type of control viable. In the literature, a recent frequency domain analysis has shown that the coupling is non-negligible. Literature suggests that the introduction of an offset in the inverse MBC-transformation can help decouple these yaw- and tilt-moments, although this offset is usually found in a heuristic manner and its real effects are unknown. In this study a thorough analysis on the effects of the azimuth offset is given on simplified and high-fidelity models. It is shown that the choice of blade-dynamic model structures has a significant effect on the analysis for maximum decoupling. It is also shown that a first-order model approximation is able to locate the ideal offset of a complex high-fidelity non-linear wind turbine model, which is subsequently verified by simulations and a sensitivity function analysis.