Applying accurate normal load to a specimen in direct shear tests under constant normal stiffness (CNS) is of importance for the quality of the resulting data, which in turn influences the conclusions. However, deficiencies in the test system give rise to a normal stiffness, here designated as system normal stiffness, which results in deviations between the intended and actual applied normal loads. Aiming to reduce these deviations, this paper presents the effective normal stiffness approach applicable to closed-loop control systems. Validation through direct shear tests indicates a clear influence of the system normal stiffness on the applied normal load (13% for the test system used in this work). The ability of the approach to compensate for this influence is confirmed herein. Moreover, it is demonstrated that the differences between the measured and the nominal normal displacements are established by the normal load increment divided by the system normal stiffness. This further demonstrates the existence of the system normal stiffness. To employ the effective normal stiffness approach, the intended normal stiffness (user defined) and the system normal stiffness must be known. The latter is determined from a calibration curve based on normal loading tests using a stiff test dummy. Finally, a procedure is presented to estimate errors originating from the application of an approximate representation of the system normal stiffness. The approach is shown to effectively reduce the deviations between intended normal loads and the actual applied normal loads. Funding details: BeFo 391; Funding details: Svensk Kärnbränslehantering, SKB; Funding details: Nuclear Waste Management Organization, NWMO; Funding text 1: Open access funding provided by RISE Research Institutes of Sweden. The authors would like to acknowledge the research funding granted by BeFo Rock Engineering Research Foundation (grant proposal BeFo 391) and SKB, Swedish Nuclear Fuel and Waste Management Co, Solna, Sweden. The authors would also like to thank Adjunct Professor Diego Mas Ivars at SKB, Swedish Nuclear Fuel and Waste Management Co; Associate Professor Fredrik Johansson at KTH Royal Institute of Technology; and Adjunct Professor Erland Johnson at RISE Research Institutes of Sweden AB for their valuable contribution to this work.