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Many bakeries plan their production using Excel: one spreadsheet per location, with the previous year’s figures listed alongside, a slight increase here, a slight decrease there. This works—up to a point. The real question isn’t whether Excel is bad, but when its limitations become more costly than a proper solution.
This comparison presents both sides without oversimplifying them.
The Case for Excel
It doesn't cost anything extra, and everyone is familiar with it. No introduction, no training, no dependence on a single provider. The template can be customized exactly to fit the company's needs.
Full control. Every number is visible, every formula is transparent. For small businesses with a manageable product range and one person in charge of planning, this is often more than enough.
Where Excel Reaches Its Limits
Excel looks back, not forward. A spreadsheet can show figures from the previous year and the previous week—but it doesn’t know that the weather will change on Thursday, that vacation starts next week, or that the holiday falls on a different day of the week this year. A person has to factor all of that in manually every day.
The workload increases with every item and every store. Two stores with 80 items each mean 160 decisions a day. The spreadsheet doesn't calculate any of this on its own—it simply records the decisions made by people.
Prone to errors. An overwritten formula, a misaligned row, an outdated export—Excel errors often aren't noticed until the returns are already in the return bin.
Reliance on Individuals. Usually, only the person who created the template understands it. If that person is unavailable, the planning process comes to a standstill—an underestimated operational risk.
What Makes an AI Forecast Different
GoNina It handles exactly the tasks that would otherwise have to be done manually in Excel: Sales data is automatically imported from the point-of-sale system; the AI factors in weather, holidays, school breaks, and seasonal patterns, and provides a daily forecast for each item and location for the next seven days—in the form of specific order recommendations as part of the usual workflow.
The difference lies in three points: The forecast looks ahead rather than back; it scales effortlessly to any number of items and stores; and it continues to learn automatically, rather than requiring someone to maintain the template. Control still remains with the operations team—every suggestion can be adjusted.
Businesses that switch from manual scheduling to GoNina reduce their excess capacity by up to 52%, increase revenue by up to 6%, and save up to 12 hours of scheduling time per month.
The Honest Decision-Making Framework
Excel is probably sufficient if: there is one location, a manageable product selection, steady demand, and an experienced person with time to manage it on a daily basis.
An AI forecast is worthwhile if: you are planning to open multiple stores or carry a wide product range; the return rate exceeds 10–15% despite your experience; top-selling items regularly sell out too early; or planning depends on a single person.
Here’s a good test: Calculate the return rate for your ten top-selling items and the number of hours spent on planning each week. If the two figures add up to a significant amount, making the switch is a matter of math, not faith—especially since GoNina offers a 4-week trial period with a money-back guarantee.
Frequently Asked Questions
Can I combine Excel and AI forecasts?
During the transition phase, yes—many businesses run both in parallel and compare their accuracy. After a few weeks, it becomes clear which method is closer to reality.
Will I lose control over my planning if I use an AI solution?
No. The forecast is a suggestion, not an automatic process. Many aspects can be adjusted—the difference is that the starting point is data-driven rather than based on estimates.
Conclusion
Excel isn't wrong—it's a tool for documenting decisions, not for calculating them. As soon as product assortment, the number of stores, or fluctuations in demand become too much for manual planning to handle, an AI forecast quickly pays for itself through fewer returns and greater availability.
To learn how AI sales forecasts work in detail, check out our comprehensive guide for bakeries.
