Here is a list of key Software and Tools for Forecasting along with a brief summary of the functionality and applications. This is compiled without any specific endorsement of its usefulness or appropriateness for a specific situation. Please contact us if you want a more detailed report on each of the below software <br> <br>Oracle Demantra – Oracle’s own Demand Planning tool that integrates into the rest of the Oracle ERP applications. Demantra also include a Trade Promotions Management package to optimize promotions spend. <br>i2 – Rhythm Demand Planner, Supply Planner and Factory Planner along with several web-based trade matrix solutions. <br>Manugistics – The pioneering Demand Planning solution in the manufacturing space, particularly CPG and High Tech. <br>SAS – The Statistical Analysis System is a powerful data analytic and reporting tool. SAS is also trying to market industry specific applications and solutions for Demand Planning, Market Research <br>Forecast Pro – Software for Statistical Forecasting that is easy to implement as an off-the-shelf solution. This software is available as a single user as well as shared multi-user environment. <br>Logility – Traditional Demand and Supply Planning solution along with a solution for Collaborative Planning. <br>SAP Demand Planning – APO demand planning that integrates neatly into the SAP ERP applications. SAP also provides Business Warehouse which is a warehouse and reporting repository. <br>Steel wedge – Solution for Sales and Operations planning aimed at engaging the entire Value chain holistically in this process. This has an Excel GUI to view and manipulate the enterprise data. <br>Demand Forecasting and Inventory Planning – SCP’s Demand Forecasting and Inventory Planning, Demand and Supply Planning module is a time-phased Forecasting, Demand and Supply Planning, &amp; Demand Supply Planning Master Production Scheduling and Distribution Requirements Planning (DRP) tool <br>Autobox was first launched in 1975 and automatically builds customized Univariate and Multivariate models for time series data with automatic intervention detection for outliers, seasonal pulses, level shifts and local time trends.