DEMAND INTELLIGENCE

How many forecasts should you make each day?

ARE YOU USING YOUR RESOURCES EFFICIENTLY? 

The Demand Intelligence solution helps in managing the demand, aiming at an increase in efficiency and effectiveness of the supply chain. This is done by means of a selection of vertical modules, dedicated to the optimal management of the replenishment process, of the inventory at the stores/ distribution centers and of the promotional purchase. Such modules allow to increase sales by reducing stock-outs, reduce operational costs by reducing inventories, and improve customer satisfaction by offering the right goods, at the right time, in the right place. The technology behind the Demand Intelligence modules employs stochastic optimization to define the right quantity to order/ buy, satisfying all the supply chain operational constraints, with a given level of acceptable risk. 

The predictive power of the Demand Intelligence solution is ensured by several forecasting modules, organized in a predictive platform, able to manage classical time series analysis and more advanced methods like the ones offered by artificial intelligence and statistics, most suited to complex tasks like promotional sales forecasting and non-food product categories. The predictive platform is natively conceived to manage several data flows, from historical regular sales to price variations, from the introduction of new products to special events like sport events or promotional efforts, with the final aim of improving the quality of the forecast. Demand forecast is the starting point of Demand Intelligence, and the challenge of Ublique is to make the technology behind it explainable, when necessary, but transparent to the user when not. 

The Demand Intelligence solution allows to improve the supply chain management by leveraging a holistic view. Indeed, the replenishment module allows to manage the inventory and the orders to suppliers in an integrated manner, being able to manage multi-level supply chains by starting from the source, i.e. consumer demand, and propagating upwards the suggested decisions, i.e. inventory levels and orders, through intermediate warehouses/ distributions centers and, finally, to the suppliers. Furthermore, all the supply chain constraints (i.e. reorder calendars, packaging, min/ max order quantities, facing, …) are taken into account. The holistic view is completed by the promotional purchase module, allowing to centrally plan promotional purchase quantities, and by vertical modules dedicated to industries where the technological approach must be specific (e.g., fashion). In any of these applications, our technological modules need to solve a multi-objective optimization problem, since a trade-off between avoiding stock-outs and inventory levels must be found.