Demand Analysis outputs

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Demand Analysis outputs

Demand Analysis provides the following information:

Demand statistics – The demand profile tables contain the set of demand statistics generated by Demand Analysis. These statistics include Non-zero Demand Mean, Non-zero Demand Std Dev, Inter-Demand Interval Mean, squared coefficient variation of non-zero demand, Min Non-zero Demand, Demand Count, Outlier Count. These statistics are then used to determine the Demand Class.
Demand classes – Demand classification enables Safety Stock Optimization to distinguish different types of demand and assign an appropriate approach for safety stock calculation.

This information is presented in a set of output tables:

Aggregated Customer Demand table – The Aggregated Customer Demand table is used to identify outliers. It reports adjusted demand if the If Outliers are Detected setting is set to "Replace with Non-Zero Demand Mean". This table shows aggregated demand for customer-product pairs from the Customer Demand or Customer Orders table. If the customer-product pair has a demand profile override in User-Defined Customer Forecast Profile in a specific period, demand during that period will not be written to the Aggregated Customer Demand table.
Demand profile tables – The demand profile tables provide the demand class by site-product-period, along with a set of statistics mentioned previously. The Customer Demand Profile contains statistics and demand classes for demand reported by scenario-customer-product-period. The Site Demand Profile table contains statistics and the demand class at all sites including upstream sites. The profile of customer-facing sites includes both customer demand and the portion of demand from other sites. This information is reported by scenario-site-product-period.

Zero demand and Demand Analysis statistics

Demand Analysis provides demand mean and demand standard deviation for both zero and non-zero demand. For zero demand, aggregation buckets that are missing demand data will be considered to have demand=0 (zero).

For example, consider the following Customer Demand table entries, assuming that they belong to the same customer and product. In this case, we are using daily aggregation levels:

Date	Quantity
1/4/2011	12
1/6/2011	10
1/7/2011	13
1/9/2011	15
1/10/2011	20
1/13/2011	16
1/15/2011	11
1/16/2011	4

Demand Analysis calculates the non-zero statistics as:

Non-Zero Demand Mean	12.63
Non-Zero Demand Std Dev	4.72

The other statistics apply a value of 0 to all missing aggregation levels. The resulting customer daily demand is considered as shown in the following table.

Date	Quantity
1/3/2011	0
1/4/2011	12
1/5/2011	0
1/6/2011	10
1/7/2011	13
1/8/2011	0
1/9/2011	15
1/10/2011	20
1/11/2011	0
1/12/2011	0
1/13/2011	16
1/14/2011	0
1/15/2011	11
1/16/2011	4

The resulting statistics are:

Demand Qty Mean	7.21
Demand Qty Std Dev	7.35

Last modified: Wednesday May 15, 2024

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