Sales or transaction lines
Useful fields include transaction or order-line identifier, date, SKU, units and sales value. Identify returns, discounts and cancellations separately when possible. State whether amounts include tax or shipping.
Practical analytical guidance
What Data Do You Need for Inventory Analysis?
Prepare sales, SKU and inventory exports for an inventory review. Learn which fields support stock cover, sell-through, aging, cost exposure and replenishment analysis.
Start with the decision and the dates.
The right dataset depends on what the business needs to decide. Reviewing current stock exposure requires different evidence from evaluating historic sell-through or setting replenishment priorities. Before exporting, write down the business question, the relevant products or categories, the sales period and the inventory as-of date.
This checklist describes useful analytical inputs, not a requirement to upload every file. Elarva’s Project Request requires a relevant file so the question and available evidence can be reviewed. A General Contact question does not require a business-data upload. Additional requirements are agreed during scope review.
Prepare three core views.
Product / SKU master
Use a stable SKU key with product name, category and relevant variant attributes. Style, size, color, material, collection, launch date or lifecycle status may support meaningful comparisons.
Inventory snapshot
Provide the as-of date and units on hand by SKU. Where supplied, distinguish saleable, reserved, damaged and location-level stock. Note whether the snapshot includes goods in transit.
Business context
Describe the decision deadline, selling season, supply constraints and known data gaps. Explain exceptional promotions, launches or changes in product identifiers.
Add files only when they support the question.
- Purchase orders and lead times: open units, expected receipt dates, order status and supplier timing support replenishment review. Ordered stock is not the same as stock available today.
- Opening inventory and stock movements: receipts, transfers, returns-to-stock and adjustments help reconcile the period and define sell-through consistently.
- Costs and margins: compatible unit costs or cost-of-goods records support capital-exposure and gross-margin analysis. Note cost changes and the valuation method used by the business.
- Inventory history and aging: dated availability snapshots help interpret constrained sales; receipt or age records support aging analysis.
- Customer or marketing information: include only if relevant to the agreed question. Basic inventory analysis does not normally need names, personal contact details or full customer profiles.
Make the exports usable before combining them.
Keep original exports intact and explain each file’s source, date range, time convention and row meaning. Use consistent SKU identifiers, unambiguous dates and numeric quantity/value fields. Avoid hiding important definitions in color coding or merged cells.
Check whether order totals repeat across line items, whether returns use negative quantities, and whether a SKU appears under more than one category. Reconcile a few known totals to the source system. Record unresolved differences rather than manually adjusting figures until they appear to match.
Separate currencies or provide a documented conversion basis. Where multiple locations are involved, include a location field. A combined inventory balance may conceal units that cannot be moved quickly enough to meet a specific availability need.
Know what cannot be concluded from a limited export.
A stock snapshot with sales history can support observed velocity and a clearly defined cover calculation. It cannot establish actual inventory age without receipt history, historic stockouts without availability information, or demand that was never observed. Margin requires cost evidence; turnover requires a compatible average inventory measure.
Short histories, launches, promotions and seasonal changes may limit forward-looking interpretation. Those limitations should appear beside the recommendation. Missing data can narrow a project to a useful first review while identifying what would be needed for a deeper decision.
See how the SKU measures fit together and the illustrative decision report for the relationship between data, findings and recommendations.
Share only information needed for the review.
Use the website’s Project Request form for a relevant sample or export and explain material gaps in the business-question field. Do not include passwords, payment-card information, Social Security numbers or unrelated sensitive personal information. Confirm that you are authorized to share the files.
For handling information across the engagement, read the Privacy Policy. If you need to discuss the scope before uploading business information, use General Contact.
Start with your decision
Start with a question and the evidence available.
Elarva reviews the information, confirms the analytical scope and identifies any additional data needed before work begins.