What to reorder: the weekly list that closes the four-tool decision
Skip the what-to-reorder app sprawl: one weekly reorder list beats four tools and a Sunday-night guess. Page spec, migration steps, where sheets break.
InventoryX is in development and not available today. ClearStock is the live Shopify app.
Sunday night, four browser tabs: the shipping app that knows nothing about stock, the accounting tool where the purchase orders live, a planning product whose suggestions you half-trust, and a spreadsheet you built to keep track of all of them. The reorder decision — the only decision that spans every tab — gets made in a fifth place: your head, tired, working from memory and gut feel. That's not a tooling failure — it's a workflow failure, and the fix costs nothing: one page, five columns, reviewed at a fixed weekly time, that closes the decision the same way every time.
The anatomy of a scattered reorder decision
Velocity lives in one tool. Lead times live in another — or in a note on your phone, or nowhere. Purchase orders live in a third. And the decision itself, the thing that turns all of it into "order 420 more by Thursday," happens in a fourth place that updates exactly once a week: you.
A seller in r/ecommerce (October 2026, a thread of 17 comments) described running a one-person shop across exactly this stack: ShipStation for labels, QuickBooks for purchase orders, a separate planning tool for what to order, and Google Sheets to keep it all straight — with the actual buying decision assembled by hand each week from pieces none of the tools shared. An earlier thread in the same community produced the one-line summary of where this ends up: "500 SKUs and 100 suppliers… too complex for native reports and my trusty spreadsheet."
The tools aren't the problem; each does its one job fine. The problem is that the reorder decision spans all of them, and no tool — and no page — owns it.
Why the sprawl happens
Nobody ever bought a tool called "make the reorder decision." You bought labels, then books, then a planner, and the decision accreted around them. Each purchase solved one job and left the spanning job — combine velocity, lead time, and stock into one buying decision — homeless. So it lands wherever the data happens to be that evening — which is how it ends up made from memory: what sold, what's coming, the last time something ran dry.
The sprawl isn't a sign you chose wrong. It's the normal result of solving problems one at a time. The fix isn't a bigger tool; it's giving the decision a single home with a fixed shape.
The weekly-list pattern: one page that closes the decision
The shape that works is a buying list, not a dashboard. One page, five columns, sorted so the urgent rows sit on top:
| Column | What it holds | Where the number comes from |
|---|---|---|
| SKU | The thing you're deciding about | Catalog, filtered to rows below your cover target |
| Days of cover | How long current stock lasts at current velocity | On-hand ÷ recent daily velocity |
| Lead time | Days from PO to sellable stock | Your per-supplier number, from PO history |
| Suggested qty | What to buy | (Cover target + lead time) × velocity − on hand |
| Order-by date | When the PO must leave your outbox | Days of cover − lead time − your review buffer |
A worked row, with real arithmetic. A dog harness, selling 10 units a day, 90 on hand:
- Days of cover: 90 ÷ 10 = 9 days
- Lead time (measured from your last three POs with this supplier): 21 days
- Suggested qty: (30-day cover target + 21-day lead) × 10 − 90 = 510 − 90 = 420 units
- Order-by date: 9 days of cover against a 21-day lead → this PO was due 12 days ago
That last number is the point. The list doesn't just say what to buy — it says which decisions are already late, and by how much. On a healthy Monday the top of the page is nearly empty; a growing overdue block is the earliest warning that something upstream has slipped, whether that's velocity, lead times, or the weekly habit itself.
Shape rules that keep it a list and not another sprawl:
- One page. If it scrolls, it's a dashboard, and dashboards get skimmed while lists get executed.
- Sorted by order-by date — not by SKU, category, or alphabet.
- 10–25 rows. Everything else stays off. The tail can wait a week; it always could.
- No history, no charts, no second tab. Tracking is a different layer — if you want one, the Google Sheets inventory dashboard is a solid build-it-yourself version — but the buying decision gets one page.
Migrating from tool sprawl without buying anything
Consolidation here is a habit, not a purchase. Before evaluating a single new app, run this for three Mondays:
- Export velocity for the last four weeks (Shopify's own reports or your planning tool — whichever has it) plus current on-hand stock.
- Refresh lead times per supplier from your last few POs: order date to the date units were sellable.
- Compute the five columns for your 25 fastest SKUs and sort by order-by date.
- Place the POs that are due. Then close the page until next Monday.
Three Mondays of that tells you something no demo will: whether scattered data was the problem, or whether the missing piece was simply a fixed weekly slot for the decision. If the numbers habit wants structure beyond reordering — sell-through, aged stock, carrying cost — the weekly KPI ritual pairs with this list rather than replacing it. And if the wider loop wants a map — forecast, budget, buy, receive — the full inventory planning process is the bigger picture this list plugs into. If a tool eventually does earn a slot, the Shopify inventory apps landscape is where to compare categories first.
The DIY reality: where the spreadsheet version breaks
The spreadsheet version of this list works, and works for longer than most tool marketing admits. One public App Store review of a paid planning app (September 2026) says it outright: "I actually built a more useful/customized tool just with spreadsheets and ChatGPT for effectively $0." If your velocity is steady and your suppliers are consistent, build the sheet, keep the Monday slot, and spend the money on stock.
The honest boundary: the sheet holds while corrections are weekly. It breaks when they're daily. Two corrections in particular outgrow a Monday cadence:
- Velocity correction after gaps. Days a SKU sat at zero record zero sales, which looks exactly like zero demand. A harness selling 12/day that goes dark for a week then "averages" 8.6/day will under-order the moment it's restocked. The Monday sheet compounds that error unless you hand-correct every affected SKU, every week.
- Lead-time drift. Suppliers slip by season. The lead-time column is right the day you type it and decays from there, and nothing in a spreadsheet tells you a 21-day number quietly became a 28-day number.
When corrections start happening midweek, the list goes stale by Wednesday and the decision drifts back into your head — the exact failure this page exists to prevent. That's the boundary where a tool earns its keep: not by being cleverer than the sheet, but by regenerating the same five columns daily from corrected velocity and current lead times. The math underneath doesn't change — it's still the reorder point formula; what changes is how often it gets run.
Which is a fair place to say, once, that the Monday Buying List is exactly this page, generated: InventoryX rebuilds it weekly from in-stock-only velocity and lead times you enter, and turns the top rows into draft POs you approve or ignore. It doesn't forecast, and it still needs your 20 minutes — the list is the habit either way.
Common questions
How do I decide what to reorder each week? From one page, not four tools: list each SKU's days of cover, lead time, suggested quantity, and order-by date, sorted by urgency. Anything already past its order-by date gets a PO today; the rest waits. Review it at a fixed weekly time and the decision stops depending on memory or mood.
What should be on a reorder list? Five columns: SKU, days of cover (on-hand ÷ recent daily velocity), lead time per supplier, suggested quantity ((cover target + lead time) × velocity − on hand), and order-by date. Sort by order-by date, cap it around 10–25 rows, and keep history and charts off the page — those are dashboards, and dashboards get skimmed.
How do I calculate days of cover? On-hand units ÷ average daily velocity, computed on in-stock days only. A SKU with 180 units selling 15 a day has 12 days of cover. Compare that against supplier lead time plus a safety buffer, and the buying decision writes itself.
When does a spreadsheet stop working for reordering? When corrections outpace the weekly cadence: velocity needing correction for out-of-stock days every week, or lead times drifting by supplier and season between Mondays. The sheet's columns are right the day you type them and decay after that.
Is there a what-to-reorder app that replaces all four tools? Some come close on the planning half — reorder lists exist in most inventory apps — but shipping, books, and POs usually stay in their own systems, so full replacement is rare. Consolidate the decision first; the tooling follows. The older question still applies: do you need a new tool, or just one page?
Next step
Next Monday, 30 minutes: export on-hand and the last four weeks of sales for your 25 fastest SKUs, refresh lead times from your last POs, build the five columns, and place everything already past its order-by date — that overdue block is usually where the losses have been hiding. If you want the arithmetic behind column four checked rather than trusted, work one SKU by hand against the reorder point formula before you automate it. And if the sprawl keeps growing despite the list, the honest ERP go/no-go is the escalation worth pricing before buying anything.