.png)
Point-of-sale, inventory management, ordering, forecasting, accounting: The software landscape of a modern bakery consists of several components—and these terms are often confused in everyday use. This overview organizes the categories, explains what each component does, and highlights where the interfaces between them are critical.
The POS system: the data source
The point-of-sale system is the foundation: It processes sales and, in doing so, captures the business’s most valuable resource—sales data broken down by item, store, and day. In the Swiss baking industry, popular systems include CashAssist from HS-Soft and solutions from ProtecData and Aplus; in the restaurant and institutional foodservice sectors, systems such as Lightspeed K-Series and TCPOS dominate.
What matters from a planning perspective: clean product master data (each variant as a separate product) and open interfaces that allow other systems to access the data.
Inventory Management: Orders and Production
Merchandise management and order systems—such as WaWiAssist from HS-Soft, BackStar from ProtecData, or OPTIback from OptimoBercher—manage store orders, production lists, delivery slips, and, in some cases, recipes. They answer the question: How can the planned quantity be delivered in an organized manner to the bakery and the stores?
What they don't answer: How large the quantity should be. The inventory management system manages quantities—it does not calculate them based on future demand.
Sales Forecasting: Volume Intelligence
This is exactly where the forecasting module comes in: It answers the question every day of how much of each item is needed at each location. To do this, GoNina analyzes sales data from the point-of-sale system, factoring in weather, holidays, school breaks, and location-specific patterns, and provides order recommendations for the next seven days—by item and by store.
The key is the integration: The forecasting system draws data from the point-of-sale system and feeds the recommendations back into the standard ordering process. GoNina has an official partnership with ProtecData—the ordering recommendations flow directly back into the BackStar environment. Official integrations are in place with Aplus and OptimoBercher, along with integration with CashAssist/WaWiAssist from HS-Soft and connections to Lightspeed K-Series and TCPOS —the overview of all integrations provides the details. As a result, businesses achieve up to 52% less excess inventory, up to 8% more revenue, and save up to 12 hours of planning time per month.
The additions: Store, Personnel, Accounting
Online Store and Pre-orders: Increasingly Important for Cakes, Appetizers, and Bulk Orders — Pre-orders ensure sales and make forecasting easier.
Workforce Planning: Shift scheduling tools become more valuable when they are fed data on expected workload—and production forecasts provide the natural basis for this.
Accounting and Controlling: handle financial analysis—the more organized the operational systems are, the less manual work is required at the end of the month.
Three Questions for Your Software Landscape
1. Where is the data stored—and can it be extracted? Open interfaces are the most important criterion when selecting any system: Sales data that is locked away in the point-of-sale system cannot be used for forecasting.
2. Who calculates the quantities? In many businesses, the answer is: a person using Excel. The forecasting module closes precisely this gap between the point-of-sale system and the inventory management system.
3. Do the results feed back into the process? A forecast that ends up as a separate report isn't put into practice—it needs to reach the departments where orders are placed and production takes place.
Frequently Asked Questions
Do I need to switch my point-of-sale system to use AI forecasts?
No— GoNina integrates with common systems via interfaces. We’ll determine which integration option is available for your system during our initial consultation.
Do I need all the modules at the same time?
No—virtually every business has a point-of-sale system and some form of order management. The next biggest single lever is the forecasting module, because it improves daily volume decisions, which all other systems merely manage.
Conclusion
Point-of-sale data is recorded, inventory management is organized, and forecasts are calculated: Anyone who clearly separates these three levels will quickly recognize where their software landscape has gaps—usually in volume calculations. And that is precisely where the greatest untapped value lies in the data that the point-of-sale system has long been collecting.
To learn how the forecasting layer works in detail, check out our comprehensive guide to AI sales forecasting for bakeries.
