Real operations. Measurable results.
Three businesses — from multi-branch pharmacy groups to wholesale distributors — that transformed their operations with ZifyWMS. No projections. No estimates. Actual outcomes.
A 14-branch UK pharmacy group eliminated £180k in annual waste and cut order processing time by 74%
£180,000
annual waste eliminated through AI reorder optimisation
74%
reduction in order processing time
£38,400/yr
saved on emergency third-party stock sourcing
Zero
stockout events in first 90 days post-deployment
6 hrs/wk
of invoice admin time recovered
The Situation
A regional pharmacy group operating 14 dispensing branches across the Midlands was managing warehouse replenishment through a combination of phone orders, emailed spreadsheets, and a legacy desktop system that hadn't been updated since 2014. Stock reconciliation happened weekly. Invoices were raised manually by a two-person admin team. Stockouts of high-demand lines were occurring 3–4 times per week, forcing branches to source emergency stock from third-party suppliers at significant margin cost.
Key Pain Points
- ✗ No visibility of branch-level stock until end-of-week reconciliation
- ✗ Manual order entry causing 12–15% error rate on fulfilment
- ✗ Emergency stock sourcing costing £3,200/month on average
- ✗ Invoice disputes consuming 6+ hours of admin time per week
- ✗ No data on which SKUs were consistently over- or under-ordered
A US wholesale distributor serving 280 retail accounts reduced fulfilment errors by 91% and grew throughput by 40% without adding headcount
91%
reduction in pick errors within 60 days of deployment
40%
increase in weekly throughput — same 11-person team
$124,000/yr
saved in returns, re-ship costs, and credit notes
2.3 days
average invoice delay eliminated — now real-time
280
retail accounts now self-serving via digital ordering portal
The Situation
A wholesale health and beauty distributor based in the Greater Chicago area was managing order fulfilment for 280 retail accounts — convenience stores, independent pharmacies, and small supermarkets — across a three-state territory. Orders arrived via phone, fax, and email. Pick lists were printed and processed by hand. The warehouse team of 11 was processing roughly 340 orders per week but struggling with accuracy: a 9% error rate on picks was generating returns, re-ships, and customer complaints that were eroding account relationships built over years.
Key Pain Points
- ✗ 9% pick error rate driven by manual pick list interpretation
- ✗ No real-time visibility of orders for retail account managers
- ✗ Invoicing delayed by 2–4 days after dispatch due to manual data entry
- ✗ No prioritisation logic — high-value accounts treated the same as low-margin ones
- ✗ Seasonal demand spikes causing warehouse to fall 3–4 days behind
A 22-store UK convenience chain reduced stock holding costs by 28% and achieved full gross margin visibility for the first time
28%
reduction in total stock holding costs
£63,000
in slow-moving inventory identified and cleared
3.4 hrs/wk
per store manager recovered from ordering and chasing
Full margin visibility
achieved at SKU level for the first time in 15 years
22 stores
fully self-ordering within 3 days of deployment
The Situation
A family-owned convenience retail group with 22 stores across Greater London and the South East was supplying stores from a single central warehouse. The business had grown organically over 15 years and its warehouse processes had grown with it — in all the wrong ways. Each store manager rang through orders twice weekly. Stock was tracked on a shared Excel workbook that was updated inconsistently. The business had never had a clear picture of gross margin by SKU, meaning promotions and pricing decisions were made on instinct rather than data.
Key Pain Points
- ✗ No SKU-level margin visibility — pricing decisions made without data
- ✗ Overstock on slow-moving lines tying up £60,000+ in working capital
- ✗ Store managers spending 3–4 hours per week placing and chasing orders
- ✗ No invoice automation — accounts payable reconciliation done monthly
- ✗ Central warehouse team unable to forecast labour requirements accurately