Accurate time-series forecasting service, based on the same technology used at Amazon.com, no machine learning experience required
Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts.
Companies today use everything from simple spreadsheets to complex financial planning software to attempt to accurately forecast future business outcomes such as product demand, resource needs, or financial performance. These tools build forecasts by looking at a historical series of data, which is called time series data. For example, such tools may try to predict the future sales of a raincoat by looking only at its previous sales data with the underlying assumption that the future is determined by the past. This approach can struggle to produce accurate forecasts for large sets of data that have irregular trends. Also, it fails to easily combine data series that change over time (such as price, discounts, web traffic, and number of employees) with relevant independent variables like product features and store locations.
Based on the same technology used at Amazon.com, Forecast uses machine learning to combine time series data with additional variables to build forecasts. Forecast requires no machine learning experience to get started. You only need to provide historical data, plus any additional data that you believe may impact your forecasts. For example, the demand for a particular color of a shirt may change with the seasons and store location. This complex relationship is hard to determine on its own, but machine learning is ideally suited to recognize it. Once you provide your data, Forecast will automatically examine it, identify what is meaningful, and produce a forecasting model capable of making predictions that are up to 50% more accurate than looking at time series data alone.
Forecast is a fully managed service, so there are no servers to provision, and no machine learning models to build, train, or deploy. You pay only for what you use, and there are no minimum fees and no upfront commitments.
Product Demand Planning
You can use Forecast to forecast the appropriate inventory levels for your various store locations. You provide Forecast information like historical sales, pricing, store promotions, store locations, and catalog data from your retail management systems in a CSV (comma-separated values) format into storage. You can then combine that with associated data like website traffic logs, weather, and shipping schedules. Forecast will use that information to produce a model that can accurately forecast customer demand for products at the individual store level. Export your forecasts in batch in CSV format and import them back into your retail management systems so that you can determine how much inventory to purchase and allocate per store.
Accurate financial forecasting like sales revenue predictions is fundamental to every business’ success. Forecast can forecast key financial metrics such as revenue, expenses, and cash flow across multiple time periods and monetary units. You first upload your historical financial time series data to storage and then import it to Forecast. After producing a model, Forecast will provide you with the expected accuracy of the forecast so that you can determine if more data is required before using the model in production. The service can also visualize forecasts with graphs in the Forecast Console to help you make informed decisions.
Planning for the right level of available resources, such as staffing levels, advertising inventory, and raw material for manufacturing is important to maximize revenue and control costs. For example, a broadcasting company may want to optimize ad inventory regionally. It can import historical viewership data across different program categories and geographic regions, content metadata, and regional demographics into Forecast. The service will learn from this data and provide accurate local forecasts.