During Target Canada’s 2013 launch, warehouse staff kept finding shipments that didn’t match the numbers in the system. A crate might be listed as having 12 boxes of paper towels when it only had 10. The system wouldn’t accept the shipment because the count was wrong. Workers eventually found their own way around the problem: they’d open the crate, squeeze in two extra boxes, tape it back up, and send it on to a store.

It worked, in the narrowest sense. The shipment moved. But nobody would ever design a supply chain that way, and the fix did nothing about why the data and the crates didn’t match in the first place.

Most online stores have their own version of those taped-up crates. See how leading ecommerce stores approach operational workarounds in this article, and how to tell whether your store is quietly depending on them.

A Workaround Is A Decision Nobody Wrote Down

Workarounds rarely start as bad ideas. A product keeps getting strange shipping quotes, so someone sets a fixed shipping price on it. A box size isn’t in the system, so a staff member keeps a spreadsheet. One person learns which SKUs can ship together and becomes the unofficial expert.

Each fix makes sense on the day it’s made. The problem is that this gets the shipment moving without fixing what went wrong in the first place. Target Canada’s launch is a good example of what can happen when a retailer relies on inaccurate product data. Its automatic restocking system depended on correct product and shelf measurements, but much of the information in the system was wrong. As a result, the system struggled to get products where they needed to be. 

So when the first test stores opened, leadership switched the system off and had store employees walk the floor checking shelves by hand. That kept the stores running. It also meant head office software sometimes showed items in stock while store shelves sat empty.

Temporary Fixes Have A Habit Of Becoming Permanent

The phrase “we’ll automate it later” deserves more suspicion than it usually gets. When JPMorgan Chase investigated its 2012 “London Whale” trading losses, its internal task force found that a key risk model ran through a series of Excel spreadsheets that staff had to fill in manually by copying and pasting data between them. The model review group flagged the manual process as error-prone and approved the model with a plan to automate it. The automation never happened. The portfolio went on to lose more than $6 billion in 2012.

To be fair, the task force identified many failures, and spreadsheets weren’t the only one. The lesson for a store owner is narrower and more practical: a manual step that’s approved as temporary tends to stay in place until something forces the issue. Peak season is usually what forces it.

While these corporate missteps illustrate the systemic dangers of unrecorded workarounds, ecommerce stores encounter the immediate financial fallout of bad data most directly in their shipping and fulfillment operations.

Bad Product Data Turns Every System Into A Workaround

Target Canada’s deeper problem wasn’t the crates or the shelves. It was the catalog. New hires entered data for roughly 75,000 products under a tight deadline, with no system checks to catch mistakes. Dimensions were entered in the wrong units or in the wrong order. An internal investigation estimated the data was accurate about 30% of the time, compared with 98% to 99% in Target’s U.S. business. The company eventually shut down its merchandising division for what employees called “data week” so staff could verify every field by hand. Automatic validation to catch bad entries didn’t arrive until 2014.

Even if you run a smaller store, incorrect product information can still cause problems. Weight and dimensions affect how much shipping costs, what packaging you need, and how orders are sent out. When those details are missing or wrong, you may end up fixing shipping issues one order at a time instead of dealing with the real problem.

Shipping Is Where These Mistakes Can Get Costly

Shipping costs aren’t based on weight alone. Carriers also consider how much space a package takes up. This is called dimensional weight.

For most UPS shipments, the carrier divides the package’s volume (length × width × height) by 139 to calculate its dimensional weight. It then charges based on whichever is greater: the package’s actual weight or its dimensional weight.

USPS also adopted a divisor of 139 in July 2026 for several services, including Priority Mail Express, Priority Mail, Ground Advantage, and Parcel Select. That means getting your product measurements right matters, even if an item doesn’t weigh very much. A store shipping light, bulky products in oversized boxes is paying for air, and that air just got more expensive.

A common fix is to charge the same shipping rate for every order or set a fixed shipping cost for each product. But on BigCommerce, this can cause another issue. When a product has a fixed shipping price, BigCommerce ignores its weight and dimensions when requesting live carrier rates. The quote might end up being higher or lower than what it actually costs to ship the item.

Either way, you lose money: charge too little, and you cover the difference yourself. Charge too much, and customers may abandon their carts.

Baymard Institute found 40% of shoppers who abandoned their carts left because extra costs like shipping were too high, and 12% left because they couldn’t see or calculate the total cost upfront. Guess low and the store absorbs the difference on every order.

Instead of guessing shipping costs, you can calculate them based on the items in each order. InterDimensional for BigCommerce looks at product sizes, weights, and quantities to work out how they fit into boxes. It then checks live rates from carriers such as FedEx, UPS, and USPS, so the shipping price is based more closely on what’s actually being sent.

Some Workarounds Make The Numbers Look Better Than Reality

The most dangerous workarounds are the ones that improve a report.

In 2014, Target Canada discovered that some business analysts had been turning off the replenishment feature for certain products. Analysts were judged on in-stock percentages, and with the feature switched off, the system no longer reported those items as out of stock. Some of it may have been honest confusion with new software, but the effect was the same. The dashboard looked healthy while the shelves didn’t.

Stores can do this without meaning to. A shipping charge gets padded so margin reports look fine. A product gets marked in stock because the inventory sync is unreliable. Each one makes a number look better while making it less true.

What To Check Before Replacing A Workaround With An App

Look at manual tasks, settings that override a default, and every number someone adjusts by hand. That list is your real system, whether or not anyone designed it.

Then check the data each workaround is compensating for. If product dimensions are missing or inconsistent, fix those first. A shipping app fed bad dimensions will produce bad rates with more confidence.

To perform a proactive catalog audit, start by exporting your entire product catalog to flag SKUs with missing, zero, or improbable length, width, height, or weight values. Cross-reference high-volume products against physical warehouse measurements to verify accuracy, and establish automated validation rules within your store management software to prevent incomplete entries during future inventory uploads.

Before picking a shipping app, check how it handles the details that affect your rates. Will it tell you if a product is missing its weight or dimensions? Can you see why it picked a certain box for an order? And if you’ve already set fixed shipping prices for some products, will those settings cause any issues?

If there’s a free trial, put it to use. Run a few real orders through the app and compare its shipping quotes with what the carriers actually charged. That way, you’ll know whether the rates are accurate before relying on them for every order.

Most workarounds start for a good reason. Your team needs to get orders out, so you find a quick fix and move on. The trouble is that these fixes can stick around for years. A flat shipping rate might seem easier, for example, but it won’t solve the problem of missing or incorrect product dimensions. Until you fix the information causing the issue, you may keep losing money on shipping.

If you’re running into these problems on BigCommerce, take a look at InterDimensional to see if it can help you calculate shipping more accurately.