Inventory ReportAnalysis.

Act as an experienced inventory controller, warehouse analyst and supply-chain operations specialist.

TASK:
Analyze the inventory report or inventory data provided below and identify important stock risks, exceptions, trends and required actions.

INVENTORY REPORT / DATA:
[Paste the inventory report, table, CSV data, summarized figures or relevant stock information.]

BUSINESS / OPERATION:
[Example: warehouse, retailer, distributor, e-commerce business, 3PL, spare-parts operation.]

REPORT TYPE:
[Stock on hand / Inventory ageing / Variance / Expiry / Movement / ABC / Stock valuation / Reorder / Combined report.]

REPORT DATE:
[Date.]

ANALYSIS PERIOD:
[Example: current snapshot, last 30 days, last 12 months.]

LOCATION:
[Warehouse, branch, store, zone or multiple locations.]

NUMBER OF SKUs:
[If known.]

CURRENCY:
[If financial values are included.]

BUSINESS RULES:
[Reorder levels, safety stock, expiry rules, ageing definitions, service levels or other relevant rules.]

IMPORTANT KPIs:
[List any KPIs that should receive particular attention.]

ANALYSIS GOAL:
[Example: reduce excess stock, investigate discrepancies, identify expiry risk, prepare management report.]

SPECIAL REQUIREMENTS:
[Any other instructions.]

INVENTORY ANALYSIS REQUIREMENTS:

1. DATA QUALITY CHECK
Before analyzing the inventory, inspect the available data for:

- missing SKU codes
- duplicate SKUs
- missing descriptions
- missing quantities
- negative quantities
- zero quantities
- inconsistent units of measure
- missing dates
- invalid dates
- missing costs
- unusual cost values
- inconsistent locations
- duplicate inventory records
- missing batch / lot data
- missing expiry dates where required

Separate genuine inventory exceptions from possible data-quality problems.

Do not silently correct uncertain data.

2. REPORT OVERVIEW
Summarize available information such as:

- total SKUs
- total units
- total inventory value
- active SKUs
- zero-stock SKUs
- negative-stock SKUs
- number of locations
- number of batches

Only calculate metrics supported by the provided data.

3. STOCK AVAILABILITY
Identify:

- out-of-stock items
- critically low stock
- stock below reorder level
- stock below safety stock
- adequate stock
- unusually high stock

Do not classify stock as excessive or insufficient without appropriate demand, reorder or policy information.

4. SHORTAGE RISK
Where demand or consumption information is available, identify SKUs at risk of shortage.

Consider:

- current stock
- average demand
- open orders
- lead time
- safety stock
- reorder point
- stock cover

For each risk identify:

SKU:
Current stock:
Demand:
Stock cover:
Risk:
Recommended action:

5. EXCESS STOCK
Identify possible excess inventory using available evidence such as:

- stock significantly above normal demand
- stock above maximum level
- unusually high stock cover
- large quantities with little movement
- duplicated inventory across locations

Do not label inventory as excess solely because the quantity looks large.

6. SLOW-MOVING STOCK
Where movement or sales history is available, identify slow-moving SKUs.

Consider:

- last movement date
- movement frequency
- average monthly usage
- stock on hand
- stock cover
- ageing

Define the slow-moving rule being used.

7. NON-MOVING STOCK
Identify inventory with no movement during the relevant period.

For each item show where possible:

SKU:
Description:
Quantity:
Value:
Last movement:
Days without movement:
Recommended review:

Do not assume non-moving stock is obsolete.

8. OBSOLETE STOCK RISK
Identify potential obsolescence based on evidence such as:

- prolonged inactivity
- discontinued products
- superseded items
- expired demand
- damaged inventory
- end-of-life status

Classify as "potential obsolete stock" unless obsolescence is confirmed.

9. INVENTORY AGEING
Group inventory into appropriate ageing buckets.

Example:

0–30 days
31–60 days
61–90 days
91–180 days
181–365 days
365+ days

If business-specific ageing rules are provided, use them instead.

Analyze:

- quantity by age
- value by age
- percentage of inventory
- high-risk ageing categories

10. EXPIRY RISK
For batch-controlled or expiry-controlled inventory identify:

- expired stock
- near-expiry stock
- medium-term expiry risk
- healthy remaining shelf life
- missing expiry information

Use the business's defined expiry windows where provided.

Do not invent expiry thresholds if they materially affect the decision.

11. FEFO REVIEW
Where expiry-controlled inventory is involved, check whether stock movement appears consistent with FEFO.

Look for situations where:

- newer batches are moving before older batches
- older batches remain in stock
- short-dated stock is not prioritized
- expiry dates are missing

Flag potential FEFO issues for investigation.

12. NEGATIVE STOCK
Identify negative inventory balances.

Possible investigation areas include:

- delayed receipts
- incorrect issues
- transaction timing
- wrong location
- incorrect unit of measure
- backdated transactions
- system configuration
- interface problems

Do not assume the cause without investigation.

13. ZERO STOCK
Identify zero-stock SKUs and distinguish where possible between:

- active item with demand
- inactive item
- discontinued item
- awaiting replenishment
- data issue

Prioritize zero-stock items with active demand.

14. INVENTORY VARIANCE
If system and physical quantities are provided, calculate:

Variance Quantity = Physical Quantity - System Quantity

Variance Value = Variance Quantity × Unit Cost

Variance % = (Variance Quantity / System Quantity) × 100

Handle zero system quantity carefully rather than producing an invalid percentage.

Classify:

- shortage
- overage
- exact match

Highlight high-value and repeated discrepancies.

15. STOCK ACCURACY
Where physical-count data is available, calculate relevant accuracy measures.

Possible metrics:

SKU Accuracy % =
Accurate SKU Count / Total Counted SKUs × 100

Quantity Accuracy % =
1 - (Absolute Variance / Relevant Inventory Quantity)

Clearly state the formula used.

Do not mix different inventory-accuracy definitions without explanation.

16. ABC ANALYSIS
Where annual consumption and cost information are available, calculate:

Annual Consumption Value =
Annual Usage × Unit Cost

Rank SKUs by annual consumption value.

Classify into ABC groups using either:
- business-defined thresholds
or
- clearly stated standard thresholds

Do not assume ABC means only unit quantity.

17. MOVEMENT / VELOCITY
Where movement data is available, identify:

- fast-moving
- medium-moving
- slow-moving
- non-moving

State the rule used for classification.

Compare movement with current stock to identify unusual combinations such as:

- fast-moving + low stock
- fast-moving + excessive stock
- slow-moving + high stock
- non-moving + high value

18. STOCK COVER
Where consumption information is available, calculate stock cover using an appropriate formula.

Example:

Stock Cover (Days) =
Stock on Hand / Average Daily Usage

or

Stock Cover (Months) =
Stock on Hand / Average Monthly Usage

Handle zero consumption separately.

Do not describe infinite stock cover as a normal numeric result.

19. REORDER REVIEW
Where relevant data is available, evaluate whether stock is:

- below reorder point
- approaching reorder point
- above reorder point
- significantly above expected requirement

Consider:

- demand
- lead time
- safety stock
- open purchase orders
- current stock

20. INVENTORY VALUE
Where cost data is available, analyze:

- total stock value
- high-value SKUs
- high-value slow movers
- high-value non-movers
- ageing inventory value
- expiry-risk value
- variance value

Prioritize exceptions based on both quantity and financial impact.

21. LOCATION ANALYSIS
If multiple locations exist, look for:

- same SKU unnecessarily spread across many locations
- stock in unexpected locations
- duplicate storage
- empty pick faces while reserve stock exists
- stock concentration
- blocked stock
- location imbalance

Do not recommend consolidation without considering operational requirements.

22. BATCH / LOT ANALYSIS
Where batch information exists, check:

- batch quantities
- expiry
- age
- status
- movement
- duplicate records
- unusual batch balances

23. UNUSUAL INVENTORY PATTERNS
Look for anomalies such as:

- sudden stock increases
- unexplained decreases
- repeated adjustments
- high stock with no demand
- demand with zero stock
- frequent stockouts
- repeated negative stock
- repeated variance
- unusually high unit costs
- duplicate SKU-location records

Flag anomalies for investigation rather than automatically labeling them as errors.

24. ROOT-CAUSE SIGNALS
For major exceptions identify possible investigation areas.

Use categories such as:

PEOPLE
Training, transaction errors, counting practices.

PROCESS
Receiving, putaway, picking, returns, adjustments.

SYSTEM
WMS / ERP timing, interfaces, configuration, master data.

LOCATION
Incorrect bin, mixed stock, wrong putaway.

DOCUMENTATION
Missing or incorrect transaction documents.

PRODUCT
UOM, barcode, batch, expiry or packaging issues.

SUPPLIER / CUSTOMER
Short shipment, over-delivery, returns or documentation issues.

Clearly separate:
- evidence
- possible cause
- confirmed cause

25. RISK PRIORITIZATION
Classify important exceptions by:

Operational Impact:
High / Medium / Low

Financial Impact:
High / Medium / Low

Customer Risk:
High / Medium / Low

Expiry / Obsolescence Risk:
High / Medium / Low

Priority:
P1 / P2 / P3 / P4

26. ACTION PLAN
For each important issue provide:

Issue:
Evidence:
Possible cause:
Immediate action:
Investigation required:
Preventive action:
Owner / responsible role:
Priority:
KPI / follow-up measure:

Do not invent employee names.

27. MANAGEMENT SUMMARY
Create a concise management-level summary covering:

- most important inventory risk
- highest-value issue
- biggest availability risk
- major slow / non-moving concern
- expiry risk
- significant data-quality issue
- most important investigation
- highest-priority action

28. KPI RECOMMENDATIONS
Where relevant recommend measurable KPIs such as:

- Inventory Accuracy %
- Stockout Rate
- Inventory Turnover
- Days / Months of Stock
- Slow-Moving Inventory %
- Non-Moving Inventory %
- Expired Inventory Value
- Near-Expiry Inventory Value
- Adjustment Value
- Cycle Count Accuracy
- Negative Stock Count
- Excess Stock Value

Only recommend KPIs that can realistically be measured from available or obtainable data.

29. INFORMATION GAPS
Identify information that would improve the analysis.

Examples:

- sales / consumption history
- lead time
- safety stock
- reorder point
- open purchase orders
- physical count
- unit cost
- expiry
- batch
- last movement date
- inventory status

Explain how each missing field limits the conclusions.

OUTPUT FORMAT:

1. Executive Summary
2. Data Quality Findings
3. Inventory Overview
4. Critical Exceptions
5. Stock Availability
6. Shortage Risks
7. Excess Stock
8. Slow-Moving Stock
9. Non-Moving / Obsolescence Risk
10. Inventory Ageing
11. Expiry & FEFO Risks
12. Negative / Zero Stock
13. Inventory Variances
14. Stock Accuracy
15. ABC / Movement Analysis
16. Stock Cover & Reorder Review
17. Inventory Value Risks
18. Location / Batch Findings
19. Unusual Patterns
20. Root-Cause Signals
21. Risk Priority Matrix
22. Recommended Actions
23. KPI Recommendations
24. Information Gaps
25. Management Summary

IMPORTANT:
- Never invent inventory data.
- Never invent missing demand, lead time, cost, expiry or movement information.
- State when the available data is insufficient for a conclusion.
- Separate confirmed findings from possible causes.
- Do not label slow-moving inventory as obsolete without evidence.
- Do not label high stock as excess without appropriate demand or policy information.
- Show formulas when calculating important inventory KPIs.
- Protect against division-by-zero errors.
- Preserve units of measure and currencies.
- Prioritize operationally and financially significant exceptions.
- Focus on actions that can realistically improve inventory control.