Know what you have, what is moving, and what needs attention

Common inventory and supply chain problems

• Stock balances differ between systems
• Teams cannot see stock availability across locations
• Slow-moving and excess inventory is identified too late
• Replenishment depends on manual spreadsheets
• Supplier lead times and delays are difficult to measure consistently
• Sales demand and inventory are reported separately
• Warehouse, purchasing, and finance numbers do not reconcile cleanly
• Management reporting is assembled manually every week or month

What Datazeb can deliver

From source systems to one inventory view

1. ERP / POS
2. WMS / Purchasing
3. Map & Reconcile
4. Trusted Inventory Model
5. Power BI / Alerts

The important work often sits between source and dashboard: SKU mapping, location mapping, unit conversions, receipt logic, transfers, open orders, supplier codes, and inventory reconciliation.

Inventory visibility

• Stock on hand
• Available stock
• Committed / reserved stock where available
• Stock by warehouse / store / location
• Stockouts
• Negative or unexpected stock
• Inventory ageing
• Movement history

Outcome: one clearer operational picture of what the business has and where it is held.

Stock ageing and slow-moving inventory

Make working-capital problems visible earlier

• Age buckets
• Days since last movement
• Slow-moving items
• Dead stock indicators
• Excess stock
• Inventory value by age
• Location / product comparison

Ageing logic should follow the client’s business rules and the way inventory value is recorded in the source systems.

Replenishment and reorder analytics

Support replenishment with demand, stock and lead-time context

• Recent sales / demand velocity
• Current available stock
• Open purchase orders
• Supplier lead time
• Minimum / maximum levels
• Safety-stock rules
• Stock cover
• Reorder exceptions

Supplier and purchasing analytics

• Purchase value and volume
• Supplier concentration
• Lead-time trends
• Order vs receipt
• Late deliveries
• Price changes
• Supplier-linked stockouts
• Purchasing by category / product

Supplier scorecards should use definitions agreed with procurement and operations.

Warehouse and location performance

• Inventory by site
• Movement volume
• Transfers
• Stock ageing
• Availability
• Stockout frequency
• Slow-moving stock
• Location comparison

For multi-site businesses, a shared model can give central management one view while preserving local drill-down.

Product and SKU master data

Inventory analytics breaks quickly when product identifiers do not align

• SKU mapping
• Barcodes
• Supplier product codes
• Pack / unit conversions
• Category hierarchies
• Brand / range mappings
• Location-specific product codes

Datazeb can help create reference logic so products reconcile across POS, ERP, inventory, supplier, and warehouse sources.

Sales and inventory alignment

Stock decisions improve when demand and availability are reported together

• Sales velocity vs stock
• Stockouts on high-demand items
• Excess stock on low-demand items
• Product availability by channel
• Revenue / margin context where available
• Seasonal or promotional context

Explore Sales Analytics

Inventory and finance alignment

Where reliable cost data is available, Datazeb can support management views around:

• Inventory value
• Ageing by value
• Cost by product / category
• Working-capital indicators
• Write-down / adjustment categories where available
• Stock vs margin context

Accounting treatment and valuation rules should remain under the client’s finance governance.

Exception reporting and alerts

Do not make teams search every dashboard for what needs action

• Low-stock alerts
• Stockout alerts
• Excess-stock exceptions
• Slow-moving stock
• Late purchase orders
• Missing supplier receipts
• Inventory reconciliation differences
• Failed source feeds

Explore Business Process Automation

AI opportunities

• Natural-language questions over approved inventory data
• AI-assisted exception summaries
• Supplier / product knowledge assistants
• Document and purchase-order classification
• Operational summary drafting for review

AI should sit on top of a trusted inventory model, not compensate for poor master data or unreliable stock balances.

Data quality and reconciliation

• Missing SKUs
• Duplicate products
• Negative stock
• Unmapped warehouses
• Sales without matching products
• Open orders with inconsistent status
• Inventory movements that do not balance
• Late or missing source feeds

Automated validation can surface these issues before they distort replenishment or management reporting.

Why Datazeb for inventory & supply chain analytics

• Power BI and data engineering in one delivery model
• Strong SQL, Python, API, database, ERP, POS, and file-integration capability
• Focus on product and inventory reconciliation before visualisation
• Ability to connect sales, inventory, purchasing, suppliers, warehouses, and finance
• Alerts, automation, and managed support after launch
• Flexible project and retainer models
• Senior-led global delivery

Engagement options

• Inventory reporting assessment
• Stock visibility dashboard
• Replenishment analytics project
• Supplier / purchasing analytics
• Warehouse reporting
• Product master-data mapping
• Automated exception reporting
• Managed analytics support

How we work

1. Understand
   Clarify products, locations, inventory processes, suppliers, replenishment rules, users, and reporting pain points.
2. Map
   Document ERP, POS, WMS, purchasing, finance, product IDs, locations, units, and source relationships.
3. Reconcile
   Align SKU mappings, units, stock definitions, orders, receipts, transfers, and business rules.
4. Build
   Develop integrations, trusted inventory models, Power BI reporting, validation, alerts, and automation.
5. Validate & Improve
   Reconcile outputs with operations and finance, support adoption, and refine the model as processes change.

FAQ