Blog
Time Series Forecasting with RapidMiner and R
Learn more about time series forecasting in RapidMiner Studio and with R. R integrates well within RapidMiner in order to handle time series forecasting.
Demand Forecasting
Accurately forecast demand beyond seasonal trends so you can plan production, lower inventory costs, and maximize profits.
Improve planning and boost your bottom line
If you’re relying solely on historical data to forecast demand, you may not be seeing the whole picture. Identifying patterns from previous years can be helpful, but it doesn’t account for outside factors like changing consumer preferences or the market entry of new competitors.
Without accounting for those externalities, you run the risk of underproducing (harming customer relationships), overproducing (incurring excess costs), or simply being operationally inefficient. Here’s how RapidMiner helps you fill in the gaps.
Get the full picture
Build models that account for more than just historical trends to get a complete view of market demand.
Optimize production, inventory & supply chain
Use your more comprehensive forecast to plan how much product you’ll need to make and store.
Boost profits
Avoid over or underproduction and leave behind the brand damage and inventory costs that come with them.
Overcoming the computational demands of time series analysis
Ryan Frederick of Dominos explains how his data science team improved their supply chain by providing highly accurate and scalable demand forecasts through extensible time series forecasting and scaled R-based models using RapidMiner. Watch the full presentation.
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ROI
Users of data science currently see a 4.4x ROI and expect that figure to increase to 6.7x in next two to three years.
Understand how other execs are achieving success & planning for the future, so you can make the best decisions for your organization.
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