Since the landmark papers of Conway and Abrahamson many studies have tried to quantify spatial variability. Many different methods have been used and the studies covered a variety of scales. Accordingly, some results appear contradictory, suggesting that the degree of spatial variation varies widely. This is not surprising, and is partly due to the methodology used and of course, due to varying natural conditions. Spatial variability is doubtless an inherent property of the snowpack. One important result seems to be that the layering is less variable than, for example, the stability of small column tests. Whereas it is often perceived that the results of the studies were not conclusive, it seems clear that they completely changed our view of spatial variability. We realized the importance of scale issues. For example, the variation will strongly depend on the measurement scale – the so-called support – of the method (SnowMicroPen vs. compression test vs. rutschblock test). Geostatistical analysis has been introduced and used to derive appropriate input data for numerical models. Model results suggest that spatial variation of strength properties have a substantial knockdown effect on slope stability and that the effect increases with increasing spatial correlation. The focus on scale has also revealed that spatial variations can promote instability or inhibit it. With the awareness of scale we can now address the causes of spatial variability. Many processes such as radiation and wind act at several scales. The most challenging process is probably wind that might hinder prediction of variability at the slope scale. However, at the regional scale, already today, many avalanche forecasting services try to address differences in respect to slope aspect. We will review the present state of knowledge, discuss consequences for avalanche forecasting and snow stability evaluation, and recommend future research directions.