The average inventory stock time for commodities varies greatly based on the industry and the type of products offered. The inventory shelf-life period can be affected by a number of reasons, including supply chain problems, consumer demand, and seasonal swings. Furthermore, all goods sold within the same industry or domain may not follow the same pattern of inventory stock periods, and their stock periods have a significant skew.
The Inventory shelf-life across industry keeping slow-moving and obsolete inventory can vary based on the industry, the nature of the inventory, the shelf life of the products, and the company’s financial status. Inventory in industries like as fashion and technology, for example, may soon become obsolete owing to changing trends and technological breakthroughs. In contrast, businesses such as healthcare and pharmaceuticals may keep inventory for an extended period of time.
Here are some typical inventory stock periods for various industries:
1. Retail industry: The average inventory stock time for retail items is 30-60 days, but this might vary based on the sort of goods offered. Perishable commodities, such as food, may have a substantially shorter inventory time.
2. Fashion industry: The inventory stock time in the fashion business can be as short as a few weeks for fast-fashion products or as long as several months for higher-end designer items.
3. Automobiles industry: The inventory stock time for autos varies based on the brand and model, but it normally runs from three to six months.
4. Electronics industry: Because new models and technology are continuously being introduced, the inventory stock time for electronics can be relatively brief. The inventory stock duration for electronics typically spans from 30 to 90 days.
5. Pharma industry: When compared to other industries, the inventory stock period for pharma is relatively short. This is due to the fact that pharmaceutical goods have expiration dates and can become less effective or even harmful if not utilized within a particular time frame. There are, however, exceptions. Some drugs have a few months’ shelf life, while others can last for several years.
Inventory Aging KPI
Inventory aging reports are used to keep track of the age of inventory stock items. The report shows how long each item has been in store, helping businesses to detect slow-moving or obsolete inventory that may be wasting important resources. This report also assists firms in making critical business decision including pricing, promotion, and inventory management strategy decisions.
Typically, the incoming and outgoing transactions (along with transaction date) are used to calculate the inventory aging KPI.
The necessity to move inventory aging KPI information is one of the primary objectives during the business transformation project (assuming Oracle SCM Cloud for this paper). Due to various constraints in migrating closed transactions, we frequently transfer only the open transaction details during the implementation of Oracle SCM/ERP Cloud.
Key Constraints in Closed transaction Migration
During Business transformation projects, there are numerous limits on migrating closed transactions.
(1) Potential Data Duplication: If closed transactions are moved without attention, there is a danger that duplicate transactions will be created in the new system, resulting in errors, confusion, and financial loss.
(2) Potential Data Corruption: If closed transactions are moved erroneously or incompletely, the data may become corrupted and unusable. This could lead to further mistakes and financial losses.
(3) Time-consuming: Migrating closed transactions might take time and resources. Extraction, transformation, and loading of data into the new system may involve significant effort, causing delays and disruptions in business operations.
(4) Implementation/System Constraints:
- Due to some Target System constraints, past historical transactions are not permitted.
- Migrating closed transactions necessitates the opening of historical closed periods. Period closure is also required when opening a 7-10-year term for historical data migration. This in and of itself will result in a sub-project.
- The majority of current ERP systems will establish sub-ledgers or ledger journals for every transaction, causing problems during reconciliation.
- Dependent master’s may undergo modifications over time that must be considered prior to data migration. This necessitates the exact duplication of transactions and master data changes that occurred in the previous system in the exact same order as it occurred in source system. This is a nearly an impossible data transformation requirement.
- Transactions may have an impact on certain dynamic masters. Inventory transactions, for example, will alter the cost of an item if customer leverages average costing method as their Costing strategy.
- The volume of transactions is excessive, which may cause project delays.
As a result, it is critical to carefully weigh the benefits and hazards of moving closed transactions during data conversion and to devise a thorough migration strategy that accounts for these limits.
Business Use Case
Consider a use case in which the client utilizes average costing and keeps slow-moving stock for a duration ranging from a few months to a few years. Following the migration to Oracle ERP Cloud, inventory aging information must be migrated in order to make crucial business decisions.
This necessitates the migration of closed transactions so that inventory aging can be calculated utilizing the inventory aging report capabilities. However, with the implementation and system constraints mentioned above, it is tricky and necessary to design an approach that migrates OPEN transactions and can provide details for deriving aging information.
Solution Approach in Migrating Inventory Aging
The following is one technique to moving inventory stock and on-hand with aging information without migrating closed transactions and opening numerous prior periods:
A typical stock migration will extract stock balances as the current system’s closing balance.
(e) Lot Number or Serial Number
(f) Transaction Date (the latest month’s end date preceding the cut-over activity)
(g) Stock Balance (as of the Transaction Date (f)) for the combination of Item, Organization, Subinventory, Locator and Lot/serial Numbers
+ Other information that may provide more insight into stocks
The aging details cannot be retrieved in the new system (Oracle SCM/ERP Cloud) with only the aforesaid information moved.
To extract aging information, the stock information must be derived with a transaction date representing the aging information. It should be noted that in the case of stock picks employing FIFO, LIFO, and other stock consumption procedures, the aging extraction logic may differ because the inventory consumed or used is not the same across various stock consumption techniques.
Stock balance with aging information needs to be derived with additional Aging date as below:
(e) Lot Number or Serial Number
(f) Aging Date**
(g) Transaction Date (the latest month’s end date preceding the cut-over activity)
(h) Stock balance for the combination of item, organization, Subinventory, Aging date, Locator, and lot/serial number
+ Other additional information that may provide additional insights for stocks
** Data extraction will be more complicated because this logic should follow the standard Aging report functionality, but with the added complexity of deriving aging at the individual incoming transaction date, stock consumption based on FIFO or LIFO, and so on. Only aging dates with net incoming and consumed quantities at the aging date level should be considered for open data migration.
It is critical to compare the results of the above extraction to the aging report output from the present system. Prior to data transformation and cleansing on this data, the Data extraction output should match output of Aging report at the aging bucket level.
Once the data extraction with aging date is obtained, the oldest aging date in the dataset must be identified.
♠ If the oldest aging date is within the last 60-90 days (average stock term for most businesses), including slow-moving and/or obsolete items, it is recommended to open inventory periods (maximum of two or three prior periods) and migrate transactions whose aging date falls inside the relevant period.
This method is ideal since it involves inventory stock migration with an aging date as the transaction time. The new system (Oracle SCM/ERP Cloud) will be able to generate an aging report utilizing regular Oracle capability using this technique.
♠ In circumstances when the oldest aging date is more than 3 months ago, the above method of moving inventory stock is not recommended because it necessitates a significant amount of effort in managing item cost adjustments, period open/closure, and reconciliation with the ledger.
In such instances, it is best to migrate all stock information into a single period (the final period prior to cut-over activity), with the aging date contained in the inventory transactions “Additional Information (DFF)”.
The aging balances cannot be obtained using standard Oracle Cloud Ageing Report capabilities due to the consolidation of all stocks into a single period. During migration, however, the information is retained in the DFF and the Aging report can be achieved by creating a custom BIP report (copied or customized on top of the standard report) which leverages it.
The specification will be included to consider the aging date (for migrated stock transactions only) if it is available for age bucket computation. The aging date will be blank for transactions that occur on the Oracle SCM/ERP cloud after go-live, hence the actual transaction date (as per standard oracle) must be considered for the aging bucket calculation for such transactions.
To avoid the maintenance effort of a custom BIP report, once the oldest aging date of any item crosses the go-live date, the custom BIP report can be abolished and a standard Oracle aging report can be used (in fact, both reports should provide the same output in such cases).
In conclusion, Inventory Aging is a significant KPI that must be moved from Legacy/traditional to Oracle SCM/ERP cloud since it provides vital information for key business decisions in inventory strategies. With historical data migration limits and regulatory requirements/longer shelf-life necessitating things to be kept for more than 3 months, identifying a balanced solution during business transformation becomes critical. This article seeks to propose a solution to this use case. We have suggested this approach to one of our current customers (who readily employed this strategy) with remarkable success.