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Japanese How-To: Interpreting Inventory Opt Cubes

In the following, you will find a detailed reference of the cubes and the Inventory Opt fields, in order to facilitate users' interpretation and use in the continuous improvement of production and operations processes, in terms of efficiency and automation.

Optimised Inventory Qinvopt: Description and Structure

Consolidates portfolio items related to finished products. The cubes include the identification and characterisation fields of the references, inventory stock, in transit, historical and forecast demand. Additionally, it estimates and updates with each change of information the indicators of an optimised inventory: availability, safety inventory, reorder point, days of inventory and inventory turnover.

Column Column Description Parameters
Item
Item
Identification code of the items or references that make up the portfolio.
Description
Description
Description of items or references facilitating their identification
CeDi
CeDi
Identification of distribution centre or item location
Inventory
Inventory
Number of stocks in the inventories of all warehouses
InTransit
Transit
Quantity of stocks in transit to CeDi
Committed
Committed
Number of items that are set aside for shipment
Location
Country
Identification of location, e.g. channel, point of sale, etc.
AvgLeadTime
Leadtime Price
Average time period from when an order is placed with a supplier to when it is delivered to the customer.
SalesHistory
Sales History
Last month's demand
SuggestedForecast
Suggested Forecast
Number of forecasted orders of the item in units
AvgDailyUsage
Average Daily Use
Average number of units ordered daily one year backwards from present date
(OrdersDay 1 + ... + OrdersDay 120)/120
MaxDailySales
Maximum daily sales value
Maximum number of units ordered daily four months backwards from the present date
MaxLeadTimes
Maximum Lead Time
Maximum value of the time period from when an order is generated from a supplier to when it is delivered to the customer.
Availability
Availability
Available quantity of the item in units considering stock on hand and orders in transit
Inventory+InTransit
SuggestedAvailability
Suggested Availability
Available quantity of the item in units considering the stock in inventory, orders in transit and forecast demand.
Inventory+InTransit-SuggestedForecast
LeadtimeDemand
LeadtimeDemand
Average lead time of the item one year backwards from present date
SecurityStock
Stock Seg
Suggested number of units for safety stock, considering sales and leadtimes one year backwards from the present date.
(MaxDailyUsage*MaxLeadtime)-(AvgDailyUsage*AvgLeadtime)
SecurityStockDays
Stock Seg Days
Suggested number of days for safety stock, considering sales and leadtimes one year backwards from the present date.
((MaxDailyUsage*MaxLeadtime)-(AvgDailyUsage*AvgLeadtime))/30
ReorderPoint
Reorder Point
Minimum number of units suggested by a buy-back order
(AvgDailyUsage*AvgLeadDemand) + SecurityStock
ReorderPointDays
Pto Reorden Days
Minimum number of days suggested by a buy-back order
(AvgDailyUsage*AvgLeadDemand)/30 + SecurityStockDays
SuggestedReorderQty
Suggested Reorder
Suggested purchase taking the next month's forecast, the safety stock of the item and the amount of items to be routed, if the value is negative it is the amount of inventory that would be left in stock, if the value is positive it is the amount that the model suggests needs to be ordered to cope with the next month's demand.
Inventory+InTransit-Committed-SuggestedForecast-SecurityStock
Reorder Status
Reorder State
Suggested Purchase or Hold action for the item in the quantity set in the SuggestedReorderQty column.
ReorderPointDate
Date Pto Reorder
Date when the reorder point is reached
Today()+(SuggestedPurchase-ReorderPoint)/AvgDailyUsage
StockoutDate
Break Date
Stock out date taking into account current availability, safety stock and average daily consumption of the product.
Today() + (Availability-SafetyStock)/AvgDailyUsage
SuggestedStockOutDate
Suggested Break Date
Forecasted date for stock-outs taking into account current availability, demand forecast, safety stock and average daily consumption of the product.
Today() + (SuggestedAvailability-SafetyStock)/AvgDailyUsage

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