Demand Forecast

This table is used within the Simulation experiment only. It allows you to estimate expected customer demand for certain products over the specified period of time. The table uses periodic or historic data for demand forecasting.  

You can as well specify the sales forecast in this table that is used in case of MRP Inventory policy.

In contrast to the Demand table, the record in this table can be applied to a customer (to work with the data on placed orders of a single customer) or a site (representing aggregation of all placed orders).

Column

Description

Facility

Defines the source of demand. Double-click the corresponding row cell to choose among the available (previously defined in the Customers, DCs and Factories, Suppliers table) facilities.

Product

The product required in the Facility column. Double-click the cell and choose the required product from the drop-down list of the available products (previously defined in the Products table).

Type

Type of demand definition:

  • Periodic demand - select this option if the demand is of repetitive nature: a certain volume of products is ordered in a certain period of time. You can define quantity and period values in the Parameters column. 
    Alternatively this option is used to create demand in case no historical data is available.
  • Historic demand - use this option if you have historic demand data (this could be order records from CRM). Define the data in the Parameters column.

Parameters

The column cell contains editable data of the chosen demand definition type:

If the Type is set to Periodic demand, the cell will display Period=5.0, Quantity=10.0

If the Type is set to Historic demand, the cell will display total q=0.0, standing for the sum of all ordered products for the specified period of time.

Learn how to define demand parameters.

Time Period

Defines the period of time (from the previously defined in the Periods table) for the demand forecast specified in the Parameters.



 

Related topics

Expanding table records 

Defining demand parameters

Editing fixed or stochastic numerical data