So, like many things, in the end, the best way to determine these things seems to be to use some math combined with good judgement.Įxcellent point, and I agree with you. These formulas generally leave out two things however, the cost of collecting the sample, and the population size - meaning they could suggest you collect a sample that is way beyond your budget or worse yet, larger than the actual population. Once that is established, there are sample size formulas that will estimate the size of the sample needed. I find the key to determining how large a sample size should be is to be very clear on what exactly it is you want to know, and how precisely you have to know it. This is also the case when calculating things like process capability metrics. As you point out, when you have seasonal effects, using a data sample that covers a few weeks, or months, will only give you the short-term average and the short-term variation. The question of what is an appropriate sample size is a bit tricky. Kanban sizing will be addressed in future Lean Math TM posts. We will be addressing this subject in greater detail in a future post about demand segmentation.įurthermore the coefficient of variation is necessary, depending upon the formula(s) used, for sizing kanban.