AI & Automation

• Warehouse orders processed in real time with reduced data-entry errors.
• Automatic processing of large data volumes in seconds instead of hours.
• Faster and more accurate quality checks thanks to standardised and automated procedures.
• Flussi approvativi snelliti che riducono i tempi decisionali da giorni a poche ore.  

• Management of seasonal order peaks without the need for additional personnel.
• Warehouses able to process more packages thanks to automated picking systems.
• Integration of additional suppliers without redesigning existing processes.
• Aumento dei flussi di spedizione senza incremento proporzionale dei costi.

• New components introduced faster thanks to automated quality checks.
• Reduced production line setup times through predictive systems.
• Immediate supplier price list updates directly via integrated portals.
• Faster deliveries enabled by automated logistics planning.

• Planners freed from repetitive tasks can focus on strategic analysis.
• Integration of IoT systems to monitor production and transportation in real time.
• Rapid implementation of just-in-time or digitalised Kanban models.
• A more resilient Supply Chain than competitors thanks to end-to-end automation.

• Inventory automatically reallocated across warehouses to meet actual demand.
• Customer order prioritisation based on margins and contractual SLAs.
• Reordering decisions supported by predictive algorithms rather than estimates.
• Optimised distribution based on availability and delivery lead times.  

• Customer classification based on volumes, punctuality and profitability.
• Identification of strategic customers through value-analysis models.
• Personalised replenishment campaigns based on purchase history.
• Logistics cluster analysis to better manage delivery areas.  

• Demand forecasting integrating historical data, trends and external variables.
• Predictive algorithms anticipating seasonal peaks and promotional campaigns.
• Reduction of overstock and stock-out situations through machine-learning models.
• Scenario planning to better manage supply disruptions.

• Real-time measurement of transportation costs per customer.
• Margin analysis by product line compared with logistics costs.
• Dashboards highlighting the impact of supply chain initiatives on revenue.
• Continuous calculation of ROI for automation investments.

• Optimised production plans to reduce waste and energy consumption.
• Transport planning that minimises routes and environmental impact.
• More resilient and sustainable sourcing strategies enabled by predictive models.
• More stable and faster supply than competitors, ensuring business continuity.