Open-to-Buy Planning for Chains Without a Planning Team

Open-to-buy is budget discipline, and most chains run it blind

Open-to-buy is the dollar limit on what you can still order this month without blowing your inventory plan. It keeps the cash you commit to receipts matched to the sales you actually expect. Get it right and inventory turns. Get it wrong and you either strand cash in stock that won't sell or run empty on the items that would.

Most mid-market chains do not run a planning function. There is a buyer, a finance person who watches the bank balance, and a spreadsheet that someone updates when they remember to. The buyer commits to vendors on gut feel and last year's numbers. Finance finds out how much got spent when the invoices land.

That is open-to-buy by accident, not by discipline. The buy gets made, the money goes out, and nobody knew whether the category was already over its plan until the markdown rack told them.

This post covers what OTB actually is, why the spreadsheet version fails, what running blind costs, and why the plan has to live at the store and category level, not just the chain. The money at stake is your single largest balance-sheet line.

The OTB equation in plain terms

Open-to-buy is one equation. Planned end-of-month inventory, plus planned sales, plus planned markdowns, minus beginning inventory, minus receipts already on order, equals what you still have room to buy. Everything in retail planning is a variation on that line.

Read it the other way and it is simpler. You start the month with inventory on hand. You plan to sell some and mark down some. You plan to end the month at a target stock level that supports next month's sales. The gap between where you are and where you need to be, after what is already coming, is your open-to-buy.

When OTB is positive, you have room to order. When it is negative, you are already over-committed and every additional buy makes it worse. The number is supposed to be a brake. A buyer who knows the category is running negative does not place the order, or places a smaller one.

The discipline is not the math. The math is arithmetic a buyer can do in their head. The discipline is having current numbers in front of you at the moment you commit the buy. That is exactly what the spreadsheet cannot give you.

Think of OTB as a checkbook for inventory. You would not write a check without knowing the balance, and you would not trust a balance that was last updated a month ago. A buyer placing a vendor order against a stale OTB number is doing precisely that, signing for cash against a balance nobody reconciled. The size of the check is the largest discretionary spend the buyer makes, and it is the one made with the least current information.

OTB is forward-looking, and that is what trips people up

The trap is that open-to-buy is a forecast, not a fact. It depends on planned sales and planned markdowns, both of which are guesses about the future. If the plan assumed a category would sell at last year's rate and it is running 15 percent soft, the OTB number is wrong and the buyer is working from fiction.

This is why OTB has to be re-cut against actuals constantly. The plan you set in January is stale by February. Sell-through tells you whether the sales assumption is holding. Receipt timing tells you whether the on-order figure is real. Without fresh actuals flowing back into the equation, OTB drifts from a brake into a number nobody trusts.

Why the spreadsheet breaks the moment you save it

The OTB spreadsheet is out of date the instant it is saved. It was built from a snapshot of inventory and sales pulled on a Monday, and the store kept selling, receiving, and marking down all week. By Friday the numbers describe a version of the business that no longer exists.

The reconciliation cadence makes it worse. Most spreadsheet shops true up OTB monthly, because pulling and pasting the actuals is manual work nobody wants to do more often. So for three or four weeks the buyer is committing real dollars against numbers that are weeks stale. The brake is disconnected from the wheel.

Then there is the store-level problem. The spreadsheet runs at the chain level, because maintaining one tab per store per category is more than one person can keep up. So the plan says the chain has open-to-buy in a category while three stores are drowning in it and two are empty. The average looks fine and every individual store is wrong.

And the spreadsheet has no idea what is actually on order. On-order is the hardest field to keep current, because POs get cut, changed, partially received, and cancelled across the month. If the on-order number is stale, the most important input to OTB is stale, and the buyer over-orders on top of receipts that are already coming.

The cost of running blind: overbuy, dead stock, markdown cascades

Run OTB blind and the failures come in two directions, and both cost real money.

The first is overbuying. When nobody is watching the open-to-buy number, the buyer keeps committing because the vendor has a deal, the case pack is convenient, or the category felt strong last quarter. The receipts pile up past what sales can absorb. That is cash converted into inventory that now has to be sold at a discount or carried at a cost.

Overbuying triggers the markdown cascade. Stock that overshoots the plan does not sell at full price, so it gets marked down. The markdown clears some of it, but the next receipt is already arriving against an order placed weeks ago, so the shelf re-fills and the markdown deepens. McKinsey and retail studies put markdowns in the range of a tenth to a quarter of sales in soft-goods categories, and a large share of that is not strategic, it is cleanup for buys that should never have happened.

The second direction is underbuying. A buyer burned by last season's overstock pulls back too hard, and the fast sellers go empty. Stockouts in retail cost the obvious lost sale plus the shopper who walks, and IHL Group has pegged out-of-stocks as a multi-hundred-billion-dollar annual drag on retail revenue. Underbuying feels safe on the balance sheet and quietly bleeds the top line.

The cruelty is that both happen at once across a chain. The same buyer is overstocked in one category and empty in another, because the chain-level number averaged the two into something that looked balanced. You pay markdown on the overbuy and lost sales on the underbuy in the same month.

OTB belongs at the category and store level

A single chain-level open-to-buy number is almost useless for a multi-store retailer. Demand is not uniform. The same category sells at different rates in a downtown store and a suburban one, and the right buy for each is different. Average them and you get a plan that fits no store.

The unit of planning has to be the category within the store, or at least the category within a store cluster. That is where sell-through actually diverges. A category running hot in your top quartile of stores can be soft in the bottom quartile, and the buy needs to flow to the stores that can move it, not spread evenly because the chain number said there was room.

This is also where allocation meets open-to-buy. It is not enough to know the chain can buy. You need to know which stores have the room and the velocity to justify the receipts. OTB at the store-category level tells you both how much to buy and where it should land.

No spreadsheet team can maintain that grid by hand. A 30-store chain with 40 categories is 1,200 cells, each needing fresh sales, receipts, and inventory every week. That is precisely the math that does not get done, so the plan collapses back to the chain average and the store-level signal is lost.

How Ward surfaces this before the buy is committed

Ward is a read-only observability platform for multi-store retailers. We do not run your buying, place your orders, or change your plan. We watch the POS, ERP, and inventory data you already generate and tell you when a category is drifting off its open-to-buy plan while there is still time to act.

The model is detect, decide, execute, audit. Ward detects when actual receipts and sell-through are pulling a category away from its OTB plan: a category that is over-receiving against soft sales and heading for markdown, or one selling through faster than planned and about to go empty. You decide whether to adjust the buy, because your team owns the vendor relationships and the calendar. Your team executes in your own systems. Then Ward audits whether the corrective buy actually pulled the number back.

Ward never cuts a PO and never cancels one. It tells you the category is $180K over its open-to-buy with another buy still pending, and then it stops. The buyer decides what happens next.

And it is not another planning dashboard to maintain. You get insight cards. A card might say that a category in your top-volume cluster is running 18 percent over its open-to-buy plan with a vendor order due to ship Friday, driven by sell-through that came in soft three weeks running. That is a thing a buyer can act on before the dollars leave, not a chart to reconcile at month-end.

The point is to put a live brake under a process most chains run on a stale spreadsheet. Open-to-buy is your largest controllable cash decision. Ward keeps the number current at the store-category level so the buy matches the plan while you can still change it.

Key takeaways

• Open-to-buy is the brake that keeps inventory dollars matched to planned sales. Planned end inventory plus planned sales plus planned markdowns, minus beginning inventory and on-order receipts, equals what you still have room to buy.
• The spreadsheet is stale the moment it is saved. Built from a Monday snapshot and reconciled monthly, it has the buyer committing real dollars against numbers that are weeks out of date.
• On-order is the field that breaks first. POs get cut, changed, and partially received all month, so the most important input to OTB is the one hardest to keep current, and stale on-order means over-ordering on top of receipts already coming.
• Running blind costs in two directions. Overbuying strands cash and triggers markdown cascades that run a tenth to a quarter of sales in soft categories, while underbuying creates stockouts that quietly bleed the top line.
• A chain-level OTB number fits no store. Demand diverges by store and category, so the average hides categories that are overstocked in some stores and empty in others at the same time.
• The store-category grid is too big to maintain by hand. A 30-store chain with 40 categories is 1,200 cells needing fresh data weekly, which is exactly the work that does not get done in a spreadsheet shop.
• The signal only matters before the buy is committed. Ward detects OTB drift from live receipts and sell-through, surfaces it as an insight card while the order is still pending, and audits whether the correction worked, read-only, lane assist not autopilot.