Stock

Stock, lots and expiry dates under control in every store

See the red, amber and green before the write-off

Real-time stock status per SKU and store, stock-out management, lot and expiry-date tracking, and transfers to the store that will sell a lot in time.

Who uses it
  • Supply chain director
  • Store manager
  • Quality and compliance

What is inside

01

Real-time stock status

Red, amber and green per SKU and store, from the latest ERP import, with days of coverage.

02

Stock-out management

Current and predicted stock-outs, lost-sales estimate, root cause: late supplier, wrong forecast, missing transfer.

03

Batch and expiry tracking

Stock by lot with expiry date, alerts before a lot becomes unsellable, sell-through by lot.

04

Transfers

Proposed transfers from stores with excess to stores with demand, created as transfer orders in the ERP.

05

Transit stock

Goods in transit between the central warehouse and stores are tracked and deducted from the need.

06

Alerts and rules

Your own rules: coverage below X days, lot expiring in Y weeks, overstock above Z, sent by email or in IRIS.

The module, screen by screen

01

Stock status and projection

Real-time stock status per SKU and store, with a twelve-month projection of stock levels from the forecast and the planned orders.

  • Red, amber and green by coverage

  • Twelve-month stock projection

  • Filters by city, brand, store, category and ABC class

Stock status and projection
02

Inventory levels and health

Total SKUs, units, value, critical and warning counts, plus stock by lifecycle and by ABC class. The charts show where value is sitting and how healthy it is.

  • Stock by lifecycle: growth, mature, end of life

  • Stock by ABC class

  • Export to Excel

Inventory levels and health
03

Stock-out management

Current and critical stock-outs, lost revenue estimate and the monthly trend, with root causes: late supplier, missing forecast, missing transfer.

  • Lost revenue estimated per stock-out

  • Root cause per SKU

  • Trend by month and by store

Stock-out management
04

Batch and expiry tracking

Stock by lot with expiry dates, near-expiry counts and value at risk, with batch upload from Excel for networks whose ERP does not manage lots.

  • Lots with expiry date per store

  • Near-expiry and expired counters

  • Batch upload from Excel

Batch and expiry tracking

Key benefits

  • Stock-outs seen before they happen

    Projected stock-outs per SKU and store from the forecast and the open orders.

  • Expiry loss cut

    Lots are tracked with their dates; alerts fire weeks before a lot becomes unsellable.

  • Transfers instead of write-offs

    Excess in one store is moved to the store that will sell it in time.

  • Store-level visibility

    Every manager sees the status of their own store; the network sees the whole picture.

  • Stock value under control

    Coverage in days and value by lifecycle and ABC class, per store.

  • Traceability for pharma

    Lot and expiry per pharmacy, from receipt to sale.

What it changes

-30 to -50 %

overstock and expiry loss

31 days

of stock on the pilot, target 30

Per lot

traceability for skincare and pharma

How it works

  1. Stock by warehouse, transit and lot is imported several times a day.

  2. Status and coverage are recomputed per SKU and store.

  3. Alerts and transfer proposals reach the planner before the loss.

Connected to your ERP

Stock from your ERP, lots from the ERP or a file

Stock by warehouse and transit stock are imported every four hours. Lot numbers and expiry dates come from the ERP when it manages them, or from a CSV / SFTP file or the REST API when it does not.

Integrations

Stock from your ERP, lots from the ERP or a file

Implementation

Implementation

The same plan on every project. Your team spends a few hours a week; IRISYS does the rest.

  1. Week 1

    Connect and check

    ERP connector or CSV / SFTP export. Item master, stock by warehouse, sales history, open purchase orders. Data quality report.

  2. Week 2

    Calibrate

    Models trained on 12 to 24 months of history. Accuracy reviewed by category with the planner. Rules set: safety stock, service-level targets, case packs.

  3. Week 3

    Run in parallel

    IRIS proposals compared every morning with the current process. Differences explained; rules and events added.

  4. Week 4

    Go live

    Proposals validated in IRIS and created in the ERP. Thresholds opened category by category. On-site or remote training.

Questions about this module

Ready to see your own numbers in IRIS?

Send us an anonymised sales export. We show you your forecasts and order proposals within 10 days.