This page illustrates and documents a sample sales forecast report produced by Salescast. This sample report should give you a good insight into actual output of Salescast.Download sample Excel report: salescast-northwind-sample.xlsx
Salescast starts a project run
by retrieving the data from BigFiles
, our file hosting service. Then, quantile and/or classic forecasts are produced. Finally Salescast creates a consolidated Excel report gathering key inventory optimization metrics.
This page documents a typical Excel report produced by Salescast. More details are provided below for each section. Depending on the information present in your IT systems, your mileage may vary. Salescast is flexible and can produce reports with extra columns and eventually less. We do not cover those aspects here.
The data columns, in gray in the schema here above, represents the context
, that is to say all the information retrieved from your IT system.a) Item ID
: identifier for each product or SKU.b) Product Name
: human-readable title for the product.c) Service Level
probability of not hitting a shortage. This value represents the performance goal in term of stock availability. Read more on setting the right service level
. This value is provided as input to Salescast.d) Lead Time
: delay expressed in calendar days
between reorder and renewed stock availability. This value typically depends on your supplier. Read more on calculating lead times
. This value is provided as input to Salescast.e) Stock On Hand, Stock On Orders
: number of units readily available, resp. number of units already reordered.f) History
: aggregated sales (per day, week or month) over the last 12 periods. Those values are provided to facilitate quick validation of the sales forecasts. History not displayed is still used while computing the forecasts (both classic and quantiles).
Forecasts and optimization metrics
The forecasts are produced by Lokad. Based on those forecasts, Salescast infers a few inventory optimization metrics. Those are represented over an orange background in the schema here above.1) Reorder Point
: The number of units that should trigger a replenishment order when the stock on hand gets strictly lower
than the reorder point value. This value is calculated by Lokad, if quantile forecasts
are active.2) Order Quantity
: The number of units that should be reordered. This value is defined by the relationship
ReorderQuantity = ReorderPoint - StockOnHand - StockOnOrder
(minimal value is zero). If
is also provided, Salescast will round up OrderQuantity to be a multiple of it.3) Lead Demand
(short-hand for lead time demand
): the number of units that will be sold during the lead time. This value is inferred from the classic forecasts combined with the lead time.4) Stock Cover
: the number of days
left before stock-out if no reorder is made. This value is inferred from the classic forecasts and the stock on hand.5) Accuracy (followed by Forecasts)
: The expected accuracy of the forecasts delivered by Lokad, which can be enabled in the project settings. This value is a percentage, and included between zero and one. The higher the value the more accurate forecasts are. We have the following relationship Accuracy = 1 - MAPE
, where MAPE is the Mean Absolute Percentage Error
. The expected accuracy is computed by Lokad - like the forecasts themselves - through advanced statistical analysis. Check Measuring forecast accuracy
for more details.
: The classic
demand forecasts produced by Lokad. These classic forecasts can be absent, if quantile-only technology is selected. Check our Forecasting Technology
page for more details.