By Move Supply Chain
In DTC, stockouts don’t just hurt your cash flow, they erode customer trust.
For fast-growing Shopify brands in the accessories space, demand isn’t always smooth or predictable. Launch spikes, influencer promos, and seasonal surges make it harder to rely on default demand-planning software.
This LA-based, female-founded jewelry brand known for minimal, intention-based pieces and a strong repeat customer base, was running into a silent but serious issue: the tools they were using weren’t catching the full picture.
And it was costing them real money.
Here’s how we helped the brand build a custom inventory planning sheet that flagged 4,714 additional units for order, prevented 82% of forecasted stockouts, and redirected capital into their best-performing SKUs.
The Challenge: Missed Signals and Misaligned Replenishment Plans
Like many Shopify brands, this team was using Inventory Planner out of the box—trusting the platform to surface the right SKUs to reorder each week.
But here’s what was happening behind the scenes:
- Inventory Planner was only recommending 1,093 units to reorder
- It flagged 126 SKUs for replenishment—but without context for ABC classes, sell-through velocity, or lead time realities
- Meanwhile, key items were selling out, cash was tied up in slow-movers, and safety stock gaps were invisible until it was too late
They had the data. They just didn’t have the right lens to act on it.
The Strategy: Build a Smart Inventory Sheet That Mirrors Reality
We ditched the default filters and built a custom Google Sheet inventory tool designed for how this brand actually operates.
Here’s what the tool does:
- Consolidates real-time data from Shopify, Shiphero, and Inventory Planner
- Applies logic tailored to their:
- Lead times
- ABC SKU classes
- Sales velocity windows
- Lead times
- Uses calculated buffer triggers to catch stockouts before they happen
- Runs weekly reviews to highlight:
- Critical stockouts
- Overstock waste
- Active POs across SKUs
- Critical stockouts
The result? A dashboard the ops team actually uses—because it speaks their language, not software defaults.
Why This Worked (When Software Alone Didn’t)
Let’s zoom out: why did this approach outperform an automated planning platform?
Because replenishment is contextual. And most inventory software:
- Doesn’t account for your real-world lead time variability
- Misses SKU nuances like marketing cadence, product tiering, and shelf velocity
- Over-includes nice-to-have SKUs in reorders while missing high-risk stockouts
A smart spreadsheet, built on your real data, gives you:
- Flexibility to update logic without a developer
- Transparency so everyone—from ops to marketing—understands the plan
- Focus on what actually moves the needle this week
The Results: Fewer Stockouts, Tighter Buys, and Healthier Cash Flow
After just one inventory cycle using the custom tool:
- 4,714 additional units were flagged for reorder, preventing 82% of imminent stockouts
- The replenishment list was trimmed from 126 SKUs to 84 SKUs (a 33 percent reduction), giving the team a focused buy list
- Working capital was freed from “nice-to-have” orders and reallocated to bestsellers, improving in-stock rates and revenue continuity
What This Means for You
Yes, inventory software is powerful, but it isn’t perfect.
If you’ve ever:
- Run out of top SKUs despite “safe” stock levels
- Had a bloated PO full of slow-moving items
- Or felt like your tool is missing the story behind the numbers…
It’s time to add a layer of context.
Sometimes, the smartest move isn’t a new platform—it’s rethinking how you read the signals you already have.
Need Help Building a Smarter Reorder System?
We help DTC brands uncover hidden inventory risks, tighten their buy plans, and build leaner operations that scale without guesswork.
Whether you’re using Inventory Planner, Cogsy, or a spreadsheet from 2021, we’ll meet you where you are and help you move forward.
Let’s talk about what’s hiding in your stock reports.