The primary purpose of Consumption Rate report is to estimate how many days of stock you have left. This enables you to quickly make a decision regarding souring the product from your supplier allowing for the lead time.
Type of Stock Consumption Rate
There are various methods of working out the consumption rate of stock. The difficulty is always striking the balance between complexity and accuracy. It is also worth mentioning that there is no absolute model that gives an accurate forecasting of the rate of consumption. Here we present two models most commonly used for estimating when you run out of stock.
Average rate of consumption
The report can be accessed from Dashboards > Query Data > query type Consumption Rate - Avg Stock Rate
Report only lists sold products in the selected date range.
This is the most basic report, where daily consumption rate is an average of products sold over the selected date range (SoldQty/number of days selected). The AvailableStockDaysLeft is Available / DailyConsumptioRate, where Available is your current stock level minus what is in open orders (unshipped orders)
StandardDeviation - displays Standard Deviation of rate of consumption. See Standard Deviation. This figure tells you how variable the selling patter is for this product (the higher the value the more variability there is for this product). For example if you sold 1 in first day then another 2 in the second day and then suddenly sold 300 on the day 3, the standard deviation is high showing you that there are spikes in your sales. Where as if you sold 1 then another 1, then another 1 the standard deviation is 0, meaning there is no variability whatsoever.
Average rate of consumption - Normal Distribution (selling spikes smoothened out)
The report can be accessed from Dashboards > Query Data > query type Consumption Rate - Avg Stock Rate - Normal Distribution
The report delivery the same figures as a standard average consumption rate, however the system attempts to smoothen the spikes in sales and where possible to disregard the massive spikes in sales. To get rid of the spikes we use Normal Distribution smoothening (or Gaussian) to achieve preliminary consumption rate. Then we use this smooth average consumption rate to disregard spikes (where rate is 300% higher than the smooth average consumption we will drop this sales from the consumption rate calculation). The whole purpose of this exercise is to remove uniform spikes in sales from the calculation as much as possible.
In the nutshell: The report is more delivers more optimistic AvailableStockDaysLeft figure (usually more than standard report) because we optimize the daily consumption rate and get rid of the spikes all together.