Retailers have to deal with a pool of customers who have their buying lists based on seasonal and personal requirements. This makes inventory management imperative because it will assist in predicting the required products based on the month, and date. The retailers will be able to improve the inventory management through a single view of demand that can assist with a solution by Oracle know as a Retail Demand Forecasting (RDF) cloud service. The RDF has a built-in facility of machine learning, design science and machine learning, it will enable the retailers to gain from the decision making for the processes, optimal planning strategy, decreasing the operational costs and enhanced customer satisfaction. The retail demand forecasting also adds in an intuitive dashboard improving the adoption of new information, agility, and workflow to improve the inventory process.
The current Oracle platform for the modern retail is cloud-native allowing the Oracle retail planning and optimization portfolio. As the current retail customers continue to evolve at a greater pace faster than before, making it imperative that the current retail solutions need to optimized and demand ready. Jeff Warren, Vice President, Oracle Retail added that if the retail provider gives the customer a limited number of options it might harm the prospective buying process. The forecast cycle of the Oracle is actually derived from the 15 years of data from various retailers worldwide.
Recently the RDF cloud service was evaluated against the major specialty retailer for the 2017 holiday season. The scenario actually was implanted to 2.2 million units that were sold, representing the revenue of close to $480 million. With added forecast feature the retailer could have achieved the same sales revenue without selling the 345K units of inventory. The retailer cloud has also added 70 percent of the promotional forecasts using data science technology.
