This case study is related to the manufacturing and distribution facilities of FMCG manufacturer and distributor with four manufacturing and distribution centres. Forecast needs to be generated monthly at least for a period of 4 months for up to 40 major SKUs for the main manufacturing and distribution centre considering the demand from the other facilities.
• High volume of historical data for sales for each SKU and distribution channel
• Several distribution locations with no consistency in customer ordering cycle
• No effective real-time analysis for effective decision making
• Long lead time for purchase products and raw materials
iERP developed secured on-premise business prediction platform integrated with customer’s ERP providing to customer Sales and Inventory demand forecasting solution with product group forecasting accuracy 98% and accuracy for the majority of products over 95%. iERP studio has various capabilities in order to achieve such an accuracy:
• Automatically performs monthly analysis of historical sales for SKUs and automatically pick one of 50 machine learning or quantitative algorithms based on the quality of the data and training/testing results.
• Generates every month updated sales forecast for the upcoming 4 months with automatic machine learning executed every single month to increase algorithm learning capabilities and to improve the accuracy of the sales forecast.
• Optimise stock levels for individual SKUs based on the generated forecast, current on-hand inventory, open manufacturing jobs, and purchase orders, and generating for users actionable reordering or job suggestions for immediate action.
• Providing insight on sales history along with the forecast in built-in business analytics.