Inventory Forecasting for Malaysian Distributors — Signals, Not Guesswork
Trading SMEs bleed cash on overstock and stockouts. LLM-assisted demand signals from sales history, supplier lead times, and field notes — integrated to ERP.
Distribution margins are thin. One bad container or one stockout on a hero SKU can erase a quarter.
What owners tell us vs what data shows
Owners often forecast from gut and salesman optimism. Audits usually find:
- No single view of sell-through by SKU × region
- Supplier lead times living in WhatsApp, not ERP
- Promotional spikes not fed back into reorder logic
- Finance discovers overstock at month-end, not week three
AI that helps vs AI that hurts
Helps: anomaly flags, natural-language exception reports, draft PO suggestions from rules + history
Hurts: "AI predicted demand" black boxes with no audit trail for purchasing sign-off
We integrate to SAP B1, Odoo, SQL-backed ERPs — read first, draft PO second, post only with approver.
90-day path (typical distributor)
Days 1–14: Audit — stockout/overstock RM impact, data hygiene score
Days 15–45: Dashboard + weekly exception brief in plain language
Days 46–90: Draft reorder suggestions with confidence bands; purchaser approves
Field sales connection
Forecasting without field CRM integration is half a system.
What to do next
Book a discovery call — bring last quarter's top 10 SKUs by revenue.