Automating Baking Sheets: From Excel to an AI Production Plan

The production sheet is the most important document in any bakery. It determines what is produced, in what quantities, and for which location. And yet, in many bakeries, it is still created the same way: someone sits down, looks at the figures from the past few days, makes estimates, does the math, adjusts the numbers, and hopes that it will be roughly right.

In small businesses, this might take about 20 minutes. In chain bakeries with multiple locations and a wide range of products, creating production lists and order suggestions can easily take an hour or more each day. Every day, seven days a week.

Yet a large part of this process can be automated today—without the company relinquishing control over its planning.

How baking instructions are typically created today

In most bakeries, the process is similar. The production manager, store manager, or owner reviews the sales figures from the past few days, often using the point-of-sale system or an Excel spreadsheet. They also rely on their experience: What day of the week is tomorrow? Are there school holidays? What’s the weather forecast? Is there a local event?

Based on this assessment, quantities are determined, entered into a production list or baking sheet, and forwarded to the bakery. In the case of chain bakeries, delivery slips are also used to specify which branch receives how much of each product.

That works. But it has three weaknesses:

It takes a lot of time: Anyone who does this conscientiously every day invests a significant amount of work time in a process that repeats itself constantly. With multiple locations, the effort multiplies.

It is prone to errors: even experienced planners cannot take all influencing factors into account at the same time. A forgotten week of vacation, an overlooked change in the weather, or a misjudged store can lead to overproduction or underproduction.

It all comes down to individuals: There is often one person in the company who "knows how things work." If that person gets sick, goes on vacation, or leaves the company, the necessary planning expertise is suddenly lost.

What "automate" actually means

Automation doesn’t mean that a machine makes all the decisions. It means that data-related tasks—such as collecting, analyzing, and calculating—are handled by software. People remain in control and can adjust any suggestion.

GoNina how it GoNina with GoNina : The AI connects directly to the bakery’s point-of-sale system—such as HS Soft, ProtecData, or Lightspeed. It automatically analyzes historical sales data, takes into account weather forecasts, holidays, school breaks, and seasonal trends, and uses this information to generate a daily sales forecast for each product and location.

This forecast is fed back into the system as a specific order proposal or production plan. Instead of creating the baking sheet manually, the facility receives a data-driven proposal that it can either adopt directly or adjust manually.

This streamlines the daily process from "checking figures, estimating, calculating, and entering data" to "reviewing the proposal, adjusting it if necessary, and approving it."

How this changes everyday life

More time for other tasks: Instead of rushing to compile production lists, the proposal is already ready. The team can focus on craftsmanship and product development instead of Excel spreadsheets.

New employees can get up to speed faster: Planning no longer depends on the knowledge of a single person. Even someone who hasn’t been with the company for ten years can work with a data-driven proposal.

Store allocations are being planned more fairly. In many companies, the store whose manager makes the loudest demands receives the most merchandise—not necessarily the one that sells the most. With data-driven distribution, allocations become more objective and transparent.

Vacations and time off become predictable. Even if the production manager takes two weeks off, planning continues as usual. The AI generates suggestions based on data, not on the experience stored in a person’s mind.

Businesses that GoNina save up to 12 hours a month on planning. At the same time, excess inventory is reduced by up to 52% because the forecasts are more accurate than manual estimates.

Do I need to switch my POS system or software?

No, GoNina the existing infrastructure. The forecasts are integrated into existing workflows as order suggestions in the POS system, as production lists, or as exports for the inventory management system.

Direct integration with POS systems such as HS Soft, ProtecData, and Lightspeed means that no manual data transfer is required. Setup typically takes just a few days. Businesses do not need to change their processes or purchase new hardware.

Frequently Asked Questions

Does GoNina completely replace GoNina baking sheet? GoNina a data-driven production proposal that serves as the basis for the baking sheet. You can accept the proposal as is or customize it. The final decision rests with the business.

What happens if I add or remove an item at the last minute? You can make manual adjustments at any time. If you know that a special promotion is starting tomorrow or that a product is out of stock, you can update the suggestion accordingly.

Do I need IT skills to use it? No , GoNina designed so that it can be used without any prior technical knowledge. The GoNina handles the setup and integration. In everyday use, operating it is no more complicated than reading the old baking sheet.

Conclusion

In many bakeries, the baking schedule is still created the same way it was twenty years ago—manually, time-consuming, and dependent on the knowledge of individual staff members. It doesn’t have to stay that way. AI-based sales forecasts automate the most labor-intensive part of daily planning and provide recommendations that are more accurate than any manual estimate.

The recipe won't disappear. But it will be created faster, better, and more independently.

You can find a comprehensive overview of AI sales forecasts for bakeries in our complete guide.

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