Hardware Store IMS
A hardware store was losing sales it never saw. Fast-moving items ran out while dead stock tied up the shelf and the cash. Counts were done on paper, reorders on instinct. We built an inventory management system that tracks every item in real time and reorders before the shelf goes empty, and the stockouts that were quietly costing sales fell off a cliff.
Custom Software + Inventory Automation
−81%
stockouts per month after rollout
What changed, charted.
Twelve months of the metric this engagement was hired to move, six before launch, six after, plus every headline KPI, before and after.
Stockouts per month
2026| Month | stockouts |
|---|---|
| Jan | 58 |
| Feb | 62 |
| Mar | 55 |
| Apr | 60 |
| May | 57 |
| Jun | 59 |
| Jul (launch) | 41 |
| Aug | 28 |
| Sep | 19 |
| Oct | 14 |
| Nov | 12 |
| Dec | 11 |
Representative sample data: the same live measurement dashboard ships with every engagement.
Before → after
- Stockouts / month−81%
- Before: 58. After: 11. Change: −81%.
- Inventory accuracy+26 pts
- Before: 72%. After: 98%. Change: +26 pts.
- Full stock count time−91%
- Before: 8h. After: 45 min. Change: −91%.
- Capital in dead stock−68%
- Before: ₱1.2M. After: ₱380k. Change: −68%.
The challenge
Stock levels lived on paper cards and in the owner's head. Bestsellers ran out between manual counts, so customers walked; meanwhile capital sat frozen in items that hadn't moved in a year. A full count took a day and was wrong by the time it finished, and there was no signal to reorder until a shelf was already bare.
What we did
Every item, tracked in real time
Barcode intake and point-of-sale updates keep a live count of every SKU, so the number on the screen matches the number on the shelf instead of a week-old paper card.
Reorder before the shelf empties
Per-item thresholds trigger low-stock alerts and draft purchase orders, so fast movers get reordered on time and buying stops running on gut feel.
See what's stuck, free the cash
Aging and sales-velocity reports surface dead stock and slow movers, turning frozen capital back into shelf space that actually sells.
The outcome
Two months after rollout, stockouts had fallen 81%, from around 58 a month to 11, while inventory accuracy climbed from 72% to 98%. A full stock count went from a full day to under an hour, and roughly two-thirds of the capital that had been frozen in dead stock was freed back into product that moves.
I used to reorder by walking the aisles and hoping. Now the system tells me what's running low before it's gone and what's just sitting there eating cash. We stopped running out of the things people actually come in for.
What shipped
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