Order quantities, next week
| Product | Store | On hand | Forecast, 7 days | Order | Why |
|---|---|---|---|---|---|
| Ayam Bakar Madu · 12 pcs | Kemang | 4 | 38 | 120 | 4 days of cover against a 3-day lead time |
| Rendang Daging · 500 gr | Kemang | 61 | 31 | 48 | Steady demand, 12 days of cover already |
| Nasi Kuning Family Pack | Sudirman | 18 | 24 | 60 | Weekend uplift, forecast is 2.1× weekday |
| Sambal Ijo · 200 ml | All 6 | 210 | 22 | 0 | Five weeks of cover; ordering more would tie up cash |
Quantities are safety stock and reorder points driven by a demand
forecast — z × σ × √(protection period) —
then scored in a period-by-period simulation with lead time, review period and backorders.
A fixed days-of-supply rule gives 81% fill rate on the same demand.
Promotions that did not pay back
- “Buy 2 get 1” on Rendang, week 36 — volume up 22%, margin down Rp 6.4jt Elasticity of −1.9 against a true −1.2. The extra units were going to sell anyway.
- Flash sale on Nasi Kuning, week 37 — 41% of units sold at a loss Discount applied to every unit, including the ones that were not incremental.
- Bundle discount on the sambal range, week 37 — cannibalised Sambal Ijo Shifted demand between two products on the same shelf rather than adding any.
Promoted units only count as incremental when they would not have sold otherwise. The baseline here is trained on your own non-promoted store-weeks, so the comparison is like-for-like rather than against last month’s total.
Next month’s calendar
Planned under a fixed trade budget with a per-store frequency cap, so the calendar is something you can hand to a sales lead rather than a chart to interpret.
What it runs on
A fictional chain with illustrative figures. The methods are the ones in the replenishment and promotion lift case studies.