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Every product lineup grows. A new type of bread here, a customer request there, a seasonal item that simply stays in the lineup—after a few years, many bakeries carry 100 to 200 items, some of which contribute very little to their bottom line. Nevertheless, each of these items requires time, raw materials, and planning effort every day.
Streamlining the product lineup is therefore one of the most effective ways to increase margins—provided it is done based on data rather than intuition. After all, it’s easy to remove items. The real challenge is knowing which ones to remove.
Which articles qualify as candidates—and which do not
You can identify typical candidates for discontinuation by a combination of three indicators: low sales volume, high return rate, and low contribution margin. An item that is produced in small quantities every day, regularly remains unsold, and yields a low margin costs more than it brings in.
Be careful, however, with three types of items that look bad in raw sales statistics but are strategically important:
A crowd-pleaser. The specialty bread that three regular customers come for every Saturday—and end up taking half their weekly groceries with them. If you only look at the item itself, you’ll overlook the entire shopping cart.
Featured items. Products that give your business a unique character, even if they don't account for a large portion of your sales. A selection consisting solely of bestsellers looks just like any other large bakery.
Seasonal sleepers. Items that appear weak on an annual average but perform strongly during their season. Here, it’s important to take a seasonal perspective rather than relying on the annual average.
Here's how to approach the cleanup
1. Data, not opinions. Pull the sales and return figures for the past twelve months—by item and by store—from the point-of-sale system. Discussions about the product lineup become more objective when the numbers are on the table.
2. Sort by value, not by quantity. Rank items based on contribution margin and return value in francs. An item with a 40% return rate but low value is less urgent than one with a 20% return rate but high value.
3. Eliminate options in stages. First, narrow down the candidates to specific stores or days of the week before eliminating them entirely. This will show whether demand is shifting or disappearing.
4. Measure the impact. After four to eight weeks, it will become clear whether sales have shifted to other items and to what extent returns and production costs have decreased.
How GoNina Helps with Product Line Decisions
GoNina automatically provides the data you need: sales and returns trends by item and location, continuously updated without the hassle of Excel. This lets you see at a glance which items consistently generate excess inventory and which ones have hidden strengths.
There is also a second effect: More accurate forecasts save some items from being discontinued. An item with a 35% return rate is often not a bad item, but rather one that was poorly planned. With data-driven ordering quantities, the return rate decreases—and the item becomes profitable again. Businesses that use GoNina reduce their excess inventory by up to 52%.
Frequently Asked Questions
How many items should a bakery carry?
There is no set number. The key factor is whether each item deserves a place on the shelves—based on profitability, sales frequency, or product profile. Many bakeries can eliminate 10 to 20% of their product lineup without a noticeable loss in sales.
When is the best time to streamline operations?
Before the start of a new season—that way, the change feels natural, and the team has the capacity to adjust. More important than the timing is consistency: once a year as a standard process.
Conclusion
Streamlining your product assortment doesn’t mean cutting back just for the sake of it—it means directing resources toward the items that drive revenue, foot traffic, or brand image. With clean data, gut decisions become a clear-cut process. The article on POS data in bakeries shows you which metrics you need to make these decisions.
Our comprehensive guide to AI sales forecasting for bakeries provides a complete overview.
