How MFG/Pro update the Last average (in_avg_date)
- Thread starter Namasiva
- Start date
Kishor Chari
Member
From QAD support
There are two fields on the inventory master that are used to store total quantity sold and total quantity issued since the last time ABC analysis was run and averages were updated.
in_sls_chg stores sales quantity.
in_iss_chg stores issued quantity. (This includes all issues including sales quantity.)
The averages are updated based upon several conditions, depending upon timing since last update, value of the average interval, and whether an update has ever occurred before.
The five examples attached represent various conditions which exist and the re-averaging calculations which would occur based upon the conditions.
The examples presented are for sales average update. However, the logic is the same for issue average, but issue average uses the quantity issued field.
NOTE: Examples assume all months = 30 days.
EXAMPLE 1 (Previously updated, 30 days since last update)
Date of last average update 7-1-94
Value of average (existing) 2.0
Value sales qty. (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (Old average sales
x (1- (number of days since last update/avg. interval)))
+ ((new sales/number of days since last update)
x (number of days since last update/avg. interval))
= (2 x (1- ( 30 / 90 ))) + (( 100 / 30) x ( 30 / 90))
= 2.4444
EXAMPLE 2 (System previously updated, but no sales at that time or new item added in 7-1, first time update.)
Date of last average update 7-1-94
Value of average (existing) 0
Value of sales qty. (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = New sales/number of days since last update
= 100 / 30
= 3.33
EXAMPLE 3 (Previously updated, number of days since last update EXCEEDS the INTERVAL DAYS)
Date of last average update 4-1-94
Value of average (existing) 2
Value of sales (since last update) 300
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (new sales/number of days since last update)
= 300 / 120
= 2.5
EXAMPLE 4 (New part, user set original value of Average. System never updated before.)
Date of last average update Blank
Value of average (existing) 2
Value of sales qty (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (Old average sales
x (1- (number of days since last update/avg. interval)))
+ ((new sales/number of days since last update)
x (number of days since last update/avg. interval))
= ( 2 ( 1- ( 1 / 90 ))) + (( 100 / 1) x ( 1 / 90))
= 3.0889
Note : Number of days since last update is set to "1" in this case
EXAMPLE 5 (New item, no user input of current average)
Date of last average update Blank
Value of average (existing) 0
Value of sales (since last update) 200
Today's date 8-1-94
Averaging interval (days) 90
New sales average = New sales/number of days since last update
= 200 / 1
= 200
Note : Number of days since last update is set to "1" in this case
There are two fields on the inventory master that are used to store total quantity sold and total quantity issued since the last time ABC analysis was run and averages were updated.
in_sls_chg stores sales quantity.
in_iss_chg stores issued quantity. (This includes all issues including sales quantity.)
The averages are updated based upon several conditions, depending upon timing since last update, value of the average interval, and whether an update has ever occurred before.
The five examples attached represent various conditions which exist and the re-averaging calculations which would occur based upon the conditions.
The examples presented are for sales average update. However, the logic is the same for issue average, but issue average uses the quantity issued field.
NOTE: Examples assume all months = 30 days.
EXAMPLE 1 (Previously updated, 30 days since last update)
Date of last average update 7-1-94
Value of average (existing) 2.0
Value sales qty. (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (Old average sales
x (1- (number of days since last update/avg. interval)))
+ ((new sales/number of days since last update)
x (number of days since last update/avg. interval))
= (2 x (1- ( 30 / 90 ))) + (( 100 / 30) x ( 30 / 90))
= 2.4444
EXAMPLE 2 (System previously updated, but no sales at that time or new item added in 7-1, first time update.)
Date of last average update 7-1-94
Value of average (existing) 0
Value of sales qty. (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = New sales/number of days since last update
= 100 / 30
= 3.33
EXAMPLE 3 (Previously updated, number of days since last update EXCEEDS the INTERVAL DAYS)
Date of last average update 4-1-94
Value of average (existing) 2
Value of sales (since last update) 300
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (new sales/number of days since last update)
= 300 / 120
= 2.5
EXAMPLE 4 (New part, user set original value of Average. System never updated before.)
Date of last average update Blank
Value of average (existing) 2
Value of sales qty (since last update) 100
Today's date 8-1-94
Averaging interval (days) 90
New sales average = (Old average sales
x (1- (number of days since last update/avg. interval)))
+ ((new sales/number of days since last update)
x (number of days since last update/avg. interval))
= ( 2 ( 1- ( 1 / 90 ))) + (( 100 / 1) x ( 1 / 90))
= 3.0889
Note : Number of days since last update is set to "1" in this case
EXAMPLE 5 (New item, no user input of current average)
Date of last average update Blank
Value of average (existing) 0
Value of sales (since last update) 200
Today's date 8-1-94
Averaging interval (days) 90
New sales average = New sales/number of days since last update
= 200 / 1
= 200
Note : Number of days since last update is set to "1" in this case