Case study
Produce wholesaler speeds up orders and cuts berry waste
A wholesaler of berries, leafy greens and herbs with about 45 staff, 30 growers and 300 customers cut order entry from 8 hours a day to 2 and reduced dumped stock from 6% to 3.5% of purchases.
Free setup & training · Human support by named fresh produce consultants
At a glance
Order entry8 → 2 h/day
Stock dumped6.0% → 3.5% of purchases
Customer credits1.8% → 0.9% of sales
Trace a failed QC lot to customers≈ 2 hours → under 1 minute
The challenge
- About 120 orders a day arrived by e-mail and were retyped by two staff; typos caused wrong or short deliveries
- Older berry lots picked after newer ones – about 6% of purchases dumped
- Credits of about 1.8% of sales from wrong products, short shipments and quality complaints
- Finding which customers received a bad lot took about two hours
The solution
- Pak-Bot reads the order inbox and creates orders in Producepak for approval
- Available-to-promise answers from stock on hand plus incoming deliveries
- FIFO alerts at picking
- Expiry warnings so sales can discount ageing lots
- Failed inspections linked straight to the customers and pallets affected, with photos
Want results like these in your business?
100% accurate shipping starts hereResults
| Benefit | Estimate | Annual value |
|---|---|---|
| Less stock dumped | 6.0% → 3.5% of ≈ AU$6M purchases | AU$150,000 |
| Fewer customer credits | 1.8% → 0.9% of ≈ AU$7.5M sales | AU$67,500 |
| Order entry time | 6 h/day × 260 days × AU$40/h | AU$62,400 |
| Total | AU$279,900 |
One order-entry role moved to customer service, following up late payers and new accounts.
Related
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Sources and further reading
Questions
Is this a real Producepak customer?
Yes. Results are as published by Producepak; some customers asked for their names to be withheld.
How were the savings estimated?
From the before-and-after figures in the table, using the rates shown. They are the customer's estimates, not guarantees.