AI-assisted order advice

How AI-driven order advice optimizes your supplier orders in multi-site catering

By automating supplier order recommendations and adjusting quantities in real time, AI enables procurement managers to make more accurate decisions and optimize inventory management:

• Demand anticipation:AI analyzes historical sales data and upcoming events to adjust orders according to the actual needs of each outlet. These supplier orders are then consolidated at head office level for dispatch, taking into account the brand's price lists and negotiations.
• Reduction of overstocks: Thanks to a forecast perfectly adapted to the outlet's context, AI limits overstocks, thus reducing costs linked to unsold goods and food waste.
• Automated order management: AI recommendations enable supplier orders to be placed with just a few clicks, freeing up time for managers who can focus on other strategic tasks, often closer to the customer and their consumption needs.
• Alignment with supplier conditions: AI takes into account contractual conditions (best-before date, prices) to propose the best sourcing options, so that your objective is always to optimize your material costs.
• Continuous improvement: Each recommendation is automatically adjusted by AI according to feedback and sales achieved, guaranteeing a structural progressive optimization of inventory and margins.

Reduce food waste with AI-based predictive ordering

In commercial and collective catering, food waste represents a major issue in terms of both cost and environmental responsibility. AI, by integrating advanced predictive algorithms, makes it possible to significantly reduce these losses. Each order recommendation made to the supplier is adjusted according to past sales data, the CSD of products consumed and forecasts of footfall at the point of sale.

For example, a multi-site restaurant can adjust perishable product quantities based on sales history over a similar period, while taking into account local holidays or events that alter demand.

This fine-tuning of orders, based on cultural events, sporting events, weather or calendar periods, improves operating margins by ensuring that every product ordered will be used before its expiration date, while maintaining sufficient stock levels to meet fluctuations in demand. AI thus offers foodservice chains a major lever for controlling their material costs while limiting the environmental impact of their activities.

Predict your stocks according to sporting, cultural and weather events

External events, such as sports competitions, concerts or even weather variations, have a direct impact on catering demand. Thanks to AI, it's now possible to predict these fluctuations and adjust orders accordingly. Predictive algorithms analyze not only sales histories, but also event calendars and weather forecasts to anticipate product needs.

• Real-time adjustment: AI adapts order recommendations for each site according to the weather (sunny days, heat waves) or local events. This analysis ensures optimum availability of the most in-demand products, such as cold drinks or light dishes on hot days.
• Reducing stock-outs: Also, by anticipating demand peaks linked to sporting or cultural events, for example, AI avoids stock-outs, ensuring continuous service without loss of customer orders.
• Optimizing material costs: By precisely adjusting quantities needed, you avoid unnecessary overstocking while maximizing your sales during busy periods, which will improve your operating margin and reduce food waste.

Improve your profitability with orders aligned with menu cycles

The artificial intelligence embedded within the Adoria technical platform automatically synchronizes your supplier orders with your menu and recipe cycles. By analyzing production forecasts and comparing raw material requirements for each recipe, AI generates more precise order recommendations, and better adapted to menu planning and menu cycles in foodservice. This enables the exact quantities of products needed to be ordered, while avoiding the errors associated with manual order data entry.

This feature is particularly interesting for collective or commercial catering chains with repetitive or seasonal menu cycles. For example, if a weekly menu requires specific quantities of vegetables, AI will automatically adjust orders according to expected consumption and products already in stock, thus reducing waste and costs associated with unsold items.

This feature is particularly interesting for collective or commercial catering chains with repetitive or seasonal menu cycles.

• Precision of order quantities:Each supplier order recommendation is calculated based on actual requirements for planned recipes, ensuring that raw materials are always available without excess.
• Reducing procurement costs: By automatically aligning supplier orders with menu requirements, you optimize your purchasing and reduce losses linked to overstocks or out-of-date products.