Inventory Age Analysis

Objective

Assess inventory aging through age distribution, identify long-stagnant slow-moving goods, and take timely action to clear or dispose of them to avoid incurring high storage fees.

Entry: Left Navigation → Analytics → Inventory Age Analysis

Key Metrics Overview

Inventory age refers to the number of days from the date goods were received into the warehouse to the current date. The longer the age, the "older" the inventory, the higher the storage fees, and the lower the clearance value.

The system divides inventory age into 5 tiers, each with corresponding handling recommendations:

Age Tier	Meaning	Recommended Action
0-30 days	Recently received, inventory is healthy	Normal sales, no action needed
31-90 days	Short-term backlog, needs attention	Monitor sales, consider promotion
91-180 days	Medium-term backlog, promotion recommended	Start clearance sale to accelerate turnover
181-365 days	Long-term backlog, action recommended	Evaluate whether continued storage is worthwhile
Over 365 days	Severely slow-moving; storage fees may exceed product value	Dispose or discard

Common Business Scenarios

Scenario 1: Review Overall Inventory Aging

1. Open Inventory Age Analysis; the default view is "Dashboard Mode."
2. Check the "Average Product Inventory Age" card on the left:
   • Average Age (days): The average inventory age across all product inventory.
   • Year-over-Year / Month-over-Month: Compare with the same period last year and the previous period to determine aging trends.
   • A rising year-over-year (red) indicates worsening inventory aging; a declining year-over-year (green) indicates improved inventory turnover.
3. Check the "Average Age Trend Chart" to observe how inventory age changes over time:
   • Continuously rising: Inventory backlog is worsening; immediate investigation is needed.
   • Continuously declining: Inventory turnover is improving; stocking strategy is sound.
   • Stable fluctuation: Inventory is healthy; no special action needed.

Field Descriptions:

• Average Age: Weighted average number of days of inventory, calculated based on receipt dates.
• Year-over-Year: Percentage change compared to the same period last year, reflecting long-term trends.
• Month-over-Month: Percentage change compared to the previous period, reflecting short-term changes.

Scenario 2: Identify Long-Backlogged SKUs

1. Switch to "Detail Mode."
2. Click the "Average Age" column header to sort in descending order; SKUs with the longest age appear at the top.
3. Focus on SKUs with an average age > 90 days:
   • Age 91-180 days: Evaluate product value vs. storage fees to decide whether to clear.
   • Age > 365 days: Recommend immediate action to avoid storage fees exceeding product value.
4. Check the "Quantity by Age Tier" column to understand the distribution of this SKU's inventory:
   • If most is concentrated in the 91-180 day tier: There is still an opportunity for clearance.
   • If most is concentrated in the 365+ day tier: Recommend direct disposal.

Field Descriptions:

• Quantity by Age Tier: The number of units of this SKU in each tier: 0-30, 31-90, 91-180, 181-365, 365+ days.
• Total Inventory: The total inventory quantity of this SKU in the warehouse, useful for assessing the scale of action needed.

Scenario 3: Identify SKUs Incurring High Storage Fees

1. In "Dashboard Mode," view the "Age Distribution" bar chart.
2. Switch the display dimension in the upper-right corner to "Percentage" to see the inventory share of each age tier.
3. Pay close attention to the bar heights for the 91-180 day and 181-365 day tiers:
   • If these two tiers exceed 30% of the total, storage fee pressure is significant.
   • If the 365+ day tier exceeds 10%, immediate action is needed.
4. Switch to "Detail Mode" and filter for SKUs with age ≥ 181 days:
   • Higher-value items: Consider transfer to another warehouse or return to domestic.
   • Lower-value items: Directly initiate a scrap request for disposal.

Scenario 4: Inventory Check Before Clearance

1. Switch to "Detail Mode."
2. Filter by warehouse to select the target warehouse.
3. Sort by "Average Age" in descending order, then export the full SKU age details for that warehouse.
4. Mark clearance priorities in Excel:
   • Clear Immediately: Age > 365 days and low product value.
   • Priority Promotion: Age 181-365 days and still sellable.
   • Continue Monitoring: Age 91-180 days; allocate some promotional resources.
5. Create corresponding scrap requests or transfer requests based on the clearance plan.

Scenario 5: Compare Inventory Age Performance Across Warehouses

1. In the filter criteria, select Warehouse A and note its average age and age distribution.
2. Switch to Warehouse B and compare the same metrics.
3. If a warehouse's average age is significantly higher:
   • It may be overstocked; reduce replenishment to that warehouse.
   • Sales distribution may be uneven; consider transferring inventory to higher-sales warehouses.
   • Products may not suit the local market; adjust product selection strategy.
4. Focus on SKUs aged 90+ days in that warehouse and clear them promptly.

Scenario 6: Assess New Product Sales Performance

1. Switch to "Detail Mode."
2. Search for new product SKUs by receipt date or product name.
3. Check the "Quantity by Age Tier" column:
   • If inventory is mainly in the 0-30 day tier: New product just launched; sales are normal.
   • If inventory has shifted to the 31-90 day tier: New product is selling slowly; needs attention.
   • If inventory has entered the 91-180 day tier: New product is underperforming; consider promotion or delisting.
4. Further assess using the turnover rate from Inventory Analysis.

FAQ

How is inventory age calculated?

• Inventory age = current date - receipt date.
• For the same SKU received multiple times, inventory age is calculated separately for each batch; the average age is a weighted average.
• Example: 100 units received 30 days ago + 50 units received 90 days ago; average age = (100×30 + 50×90) ÷ 150 = 50 days.

What to do if average age suddenly rises?

• It may be due to a recent surge in receipts combined with declining sales, leaving new inventory unabsorbed.
• It may be caused by certain SKUs being backlogged long-term, pulling up the overall average.
• Switch to "Detail Mode," sort by age in descending order, and identify severely backlogged SKUs for action.

Can the age tiers be customized?

• Current age tiers are set uniformly by the system: 0-30, 31-90, 91-180, 181-365, 365+ days.
• The first tier starts at 0-30 days (start age = 0); subsequent tiers start at 31, 91, 181, 366, with end ages of 30, 90, 180, 365, 99999 respectively.
• If you need to adjust the tier thresholds, please contact your OSL account manager to submit feedback.

Why does the slow-moving warning in Inventory Age Analysis differ from Inventory Analysis?

• Inventory Age Analysis shows the complete age distribution details, offering finer granularity.
• The "Slow-Moving Warning" in Product Inventory is only a simplified indicator (average age > 90 days).
• Both share the same data source but differ in display granularity; use Inventory Age Analysis for decision-making.

How often is the data updated?

• The top of the page displays the "Data Updated" timestamp, generally updated at Japan time 00:00:59 (UTC+9:00).
• If you need to view the latest data, please refresh the page.