Spreadsheet vs. Inventory Planning Software

Posts comparing spreadsheets to inventory software are almost always written by people who sell inventory software. This one is too, so here is the part that usually gets left out: for a store with a small catalog and steady demand, the spreadsheet is the correct answer. Not the cheap answer or the starter answer. The correct one.

What follows is the decision, not the diagnosis. If you already know the file is failing and want to understand exactly how, when your inventory spreadsheet stops working covers the failure modes in order; this post is about whether to do anything about it.

What a spreadsheet genuinely does well

It costs nothing, which for a store with thin margins is not a small point. Every number in it is a number you can trace: you wrote the formula, so you know what feeds the reorder point and you know exactly how much to trust it. Very little software offers that, and dashboards in particular are good at presenting a number without showing its working.

The bigger advantage is shape. A spreadsheet has no opinion about how you plan, so it holds what your operation actually looks like: the supplier who closes for three weeks in August, the case pack that is 24 for one colourway and 12 for another, the SKU you deliberately keep understocked because storage is tight. Planning software has fields, and what does not fit a field does not go in. It is also faster to change: trying a different buffer on one product takes seconds in a sheet and a settings page in most tools.

What software adds

Everything a spreadsheet cannot do comes down to one property: it only acts while a person has it open. That single limitation produces the whole list.

Read the fourth row. It is where the spreadsheet wins outright, and the reason many stores keep the file after installing something.

The other rows come down to timing. Recalculation on a schedule matters because velocity and lead times drift continuously while a typed-in number does not, so the gap opens silently. Alerting matters because it inverts who has to remember. Live stock states matter because Shopify tracks available, committed and incoming separately, and a pasted export flattens all three into one number that was true on Tuesday.

StockCue is our own app, so treat this as disclosure rather than a recommendation: it reads 24 months of your Shopify order history and recalculates velocity, seasonality and reorder points on its own schedule, with forecasting on every plan including Free (up to 50 SKUs). Know where the plan lines fall before installing. Purchase orders, receiving and stock counts start at Starter rather than Free, and inventory transfers are Scale only, so if the buying workflow is what you want off the spreadsheet, Free will not cover it.

The real cost of each

The spreadsheet's price is not zero, it is just not billed. It costs review time, which scales with catalog size, and it carries four failure modes that surface as wrong numbers rather than as errors: velocity that went stale without announcing it, nothing firing when a product crosses its reorder point, no record of what changed or who changed it, and formulas only one person fully understands. Those are covered properly in the failure-modes post. The point here is that a spreadsheet does not break. It goes quietly wrong while looking exactly the same.

Ignore the confident percentage about spreadsheet errors that circulates online; it does not survive checking. Ray Panko's research (EuSpRIG, 2015) concludes that errors are rare per cell but very likely somewhere in a large spreadsheet, that they are hard to detect, and that the people who build them are overconfident about their accuracy. It studied corporate spreadsheets rather than merchant reorder sheets, so take the overconfidence finding and leave the rest.

Software's price is more visible and easier to reason about: a subscription, a setup afternoon, and a dependency on a vendor who may change either. The figure worth comparing it against is not another vendor's price. It is what your last two avoidable stockouts and your slowest over-order actually cost you, which only your own store can produce.

The upgrade triggers

Four gates, and they are genuinely gates rather than a score. One clear "no" is usually enough on its own.

Catalog size. Roughly 30 SKUs is where a spreadsheet-and-monthly-review approach commonly starts to strain, which is the line automatic versus manual reordering argues from the reordering side. It is a strain point rather than a cliff, and it moves: 60 SKUs with one supplier and flat demand is easier to hold than 25 SKUs with four suppliers and a seasonal peak. What planning looks like far past that line is its own operational problem.

Demand stability. A number typed in once stays correct only while the thing it describes stays still. Steady demand forgives a stale velocity figure; seasonality, promotions and a product whose sales rate is climbing do not, and they punish it exactly when it matters most.

How many people touch the file. A second editor is not twice the work, it is a new class of problem: two versions, an overwritten formula, and a change nobody can date because the file keeps no record of itself.

What the misses have cost. The only gate with a number attached, and it is your number. If last quarter included stockouts an earlier warning would have caught, or an over-order you would not have placed with a current forecast in front of you, compare that against a year of subscription before arguing about features. If nothing has slipped, the gate stays shut.

None of this is a formula, and treating it as one is the mistake. It is a judgment call, and the honest threshold is a range with your own conditions in it. For the symptoms that show up outside the file, ten signs a store has outgrown manual forecasting has the fuller list.

Switching cost and data migration

The switching cost gets quoted as "a few minutes to install", which is true of the install and not of the switch. What actually has to move:

The effort tracks supplier count, not SKU count. A 900-SKU catalog buying from three vendors is a shorter setup than a 120-SKU catalog buying from fifteen, which is why "how long does migration take" has no general answer.

Then run both for one full ordering cycle. Keep placing orders the way you always have and compare the tool's recommendation against yours each time. Where they disagree, one of you has a wrong input, and finding out which is the whole value of the parallel run. Only then is it safe to stop maintaining the file. Which tool to run it against is a separate question: the forecasting and planning app comparison is the place for it.

When to stay on the spreadsheet

Here is the store that should not install anything. Under roughly 30 SKUs. Demand that looks much the same in March as in September. One or two suppliers you have used long enough to predict. One person doing the buying, one location, and a review that genuinely takes under an hour a week. If that is your store, a spreadsheet is not a phase you are behind on. It is the right tool, it will stay the right tool for as long as those conditions hold, and paying a monthly fee to replace it buys you nothing except a dependency.

There is a second case for staying, and it is more common: your inputs are wrong, and software will not fix that. If lead times are guesses, if nobody has checked whether the supplier who says twelve days delivers in twelve days, or if on-hand counts disagree with the shelf, a tool built on those inputs produces confident, precise, wrong recommendations, and those are harder to catch than a wrong number in a sheet you wrote yourself. Fix the inputs first. That work pays off regardless of what you end up planning in.

Frequently Asked Questions

Is a spreadsheet good enough for inventory management?

For a small store with steady demand it is the right tool, not a compromise. Under roughly 30 SKUs, with one or two reliable suppliers, one person buying and one location, a spreadsheet costs nothing and can be bent to any supplier rule you need. It stops being good enough when the file has to notice things on its own rather than when you open it.

At what point should you move off a spreadsheet?

There is no clean number. The practical signals are that review time no longer fits in the week, that demand has stopped being steady enough for a number typed in once to stay right, that more than one person edits the file, or that you have had stockouts an earlier warning would have caught. Catalog size correlates with all four, which is why it gets used as shorthand for them.

What does inventory planning software do that a spreadsheet can't?

Three things, all about acting without being opened: it recalculates velocity and reorder points on a schedule, it raises an alert when a product crosses a threshold, and it keeps a record of what changed and when. It also reads live Shopify stock states, including committed and incoming units, rather than an export that started going stale the moment it was pasted in.

How long does it take to move off a spreadsheet?

The effort tracks how many suppliers you have, not how many SKUs, because the manual part is entering supplier records, lead times and order minimums. Sales history is usually not migrated at all: a planning tool reads it from your Shopify orders. The slowest part is running both in parallel for one full ordering cycle, and it is the part worth not skipping.