I definitely remember that standard deviation is used in safety stock calculations, but I’m not sure if it’s the most critical factor compared to the others listed.
Okay, I've got this. Reducing distribution centers means less handling and shorter transport distances, so the transport costs should go down overall. The key is figuring out which specific legs of the supply chain see the cost reductions.
This is a tricky one. I'm not entirely sure which solution is the most appropriate. I might need to do a bit of research on the different Salesforce features mentioned to determine the best approach.
I'm not sure about this one. The question asks about the events table, but the solution mentions logs. I'll need to double-check the Kubernetes commands to see the difference.
I feel confident about this one. The customer show ratings, number of returning customers, and percentage of aborted bookings are all clear KPIs that align with the CSFs provided.
B) Mean absolute deviation (MAD) is the way to go. It gives you a better idea of the average deviation from the forecast, which is crucial for safety stock planning.
C) Standard deviation seems like the obvious choice here. I mean, the higher the variability in demand, the more safety stock you'll need to keep things running smoothly.
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