
How a Lifestyle Retailer Eliminated Stockouts with Intelligent Replenishment Forecasting
Purchasing time
2 days/week → 30 min/week
Stockouts on top sellers
15-20/month → 0
Overstock on slow movers
Chronic → Controlled
“No more emergency supplier calls. The system tells us what to order before we even think about it.”
This anonymized multi-brand lifestyle retailer manages over 12,000 SKUs across catégories with strong seasonal patterns: outdoor gear peaks in spring, gift sets surge in Q4, and core basics hold steady year-round. They sell on their own Shopify store, Amazon, and two niche marketplaces. With a small purchasing team of two people, every hour spent on manual procurement was an hour not spent growing the business.
The Challenge
The purchasing process was entirely manual. Every week, the buyer opened a massive Excel file, cross-referenced current stock levels with sales from the last 30 days, and tried to guess what would sell next month. The fixed minimum quantities in the spreadsheet never changed -- summer bestsellers used the same reorder point as winter. The result was predictable: 15-20 stockouts per month on top sellers during peak periods, while slow movers accumulated. The buyer described it simply: 'We do purchasing by hand. It's truly time-consuming.' Seasonal shifts were the worst -- by the time the team noticed a summer item was surging, the supplier lead time meant they were already out of stock for the peak selling weeks.
Top challenges:
- Manual purchasing took 2 full days per week in Excel spreadsheets
- Fixed reorder points couldn't adapt to seasonal demand shifts
- 15-20 stockouts per month on top sellers during peak periods
The Solution
myFulfillment replaced the manual spreadsheets with an intelligent replenishment engine that continuously analyzes sales velocity and generates purchasing recommendations.
What We Configured
The replenishment module was configured with supplier lead times, minimum order quantities, and safety stock buffers for each supplier. The system calculates dynamic reorder points by analyzing actual sales velocity over configurable windows (7, 14, 30 days) and comparing against the same period last year for seasonal adjustment. When a product's projected stock cover drops below the safety threshold, it automatically appears in the purchasing recommendations dashboard. Purchase orders are pre-built and grouped by supplier, ready to review and send with one click. The buyer no longer decides what to order -- they review what the system recommends and approve.
The forecasting algorithm weighs recent sales trends against the same period last year, automatically adjusting reorder points for seasonal shifts. No manual minimum updates needed.
Key benefits:
- Dynamic reorder points adjust automatically to sales velocity and seasonality
- Purchasing reduced from 2 days to 30 minutes per week
- Zero stockouts on top sellers after the first quarter
The Results
Purchasing time
2 days/week → 30 min/week
Stockouts on top sellers
15-20/month → 0
Overstock on slow movers
Chronic → Controlled
The 2-day weekly purchasing routine was reduced to a 30-minute review session. Stockouts on top sellers dropped from 15-20 per month to zero within the first quarter. Seasonal transitions became smooth -- the system detected rising trends weeks before the buyer would have noticed manually. Overstocking on slow movers was brought under control because the algorithm naturally reduced reorder quantities when sales velocity declined. The purchasing team shifted from reactive firefighting to strategic supplier negotiation, securing better terms with the time they reclaimed.
Understand this case in video
Not just for lifestyle retail
Intelligent replenishment works for any retailer where demand isn't flat and manually tracking reorder points breaks down at scale.
- Sports and outdoor retailers with weather-driven seasonal demand
- Toy sellers managing holiday surge without year-round overstock
- Beauty retailers tracking trend-driven product lifecycles
- Any seller with 1,000+ SKUs still managing purchasing in spreadsheets
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