In supply chain management, the term “distribution-free” methods typically refers to special forecasting and, above all, safety stock methods that enable reliable statements to be made even if the prerequisite of a normal distribution of demand for items does not exist.
All classic methods for determining forecasts or safety stocks assume that the frequency distribution of demand quantities for an item follows a Gaussian normal distribution. In practice, this is not the case for 80% to 90% of articles. The more sporadically an item is requested, the greater the probability that there is no normal distribution. In this case, distribution-free methods are a key lever for achieving reliable forecast values and safety stocks.
Our tip:
You can pragmatically recognize whether the demand for an item deviates from the normal distribution by comparing the mean value of a demand time series with its median. If the median and mean value diverge, demand is definitely not normally distributed.
For sporadic items and spare parts, you should always use non-distribution methods, at least for the safety stock calculation.
Picture: ©Manuel Pfeiffer/aboutpixel
