Enhancements in Causal Forecasting: SPM 11.0.1/11.1 Overview
Key enhancements in SPM 11.0.1/11.1 focus on improving forecast accuracy through variable history slices, causal forecasting for multiple streams, multi-threading capabilities, easy access to product rollout and causal value pages, and more. The Next Gen Causal Forecasting introduces additional features like visibility to product rollout and causal value pages, ability to modify/delete causal values, and generate/view multiple causal forecasts for the same part/location. Links from Causal Forecast Detail allow for seamless reviewing of product rollout and causal values for a pair.
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SPM 11.0.1 / 11.1 : Key Enhancements Overview
SPM 11.0.1 Key Forecasting Enhancements Variable number of history slices by method Number of history slices can be set by forecast method for all statistical methods (except Crostons and Same as Last Year) to improve forecast accuracy. For example, Winters (seasonal) can use three years while exponential smoothing can use one year. Bestfit recommended forecast method uses variable # of history slices. Forecast parameter Number of history slices supercedes stream config history slices. Causal Forecast for multiple streams Multiple streams can be set with forecast method = Causal in stream config detail Example: Separate causal forecast for maintenance and unplanned removals with different failure rates and BOMs Ability to filter by forecast stream on causal forecast detail, prod rollout and causal value pages Product Rollout /Causal Values views (with OTF for a part) Ability to add/modify/delete causal values and product rollout amounts Easy access to causal values and product rollout pages from causal forecast detail page. To and from links between causal forecast detail and stocking policy page Multi-threading for Causal Forecasting Improves processing time for causal forecasting (also available in 10.7.0.5) 2
11.0.1 Next Gen Causal Forecasting Causal forecast for multiple streams Forecast stream added to Prod_rollout, Causal_value, Failure_rate, Part_causal_type , Failure_rate_global and cf_forecast_detail tables Ability to generate/view multiple causal forecasts for the same part/location 3
11.0.1 Next Gen Causal Forecasting Visibility to Product Rollout and Causal Value pages Ability to add/modify/delete causal values and product rollout amounts 4
Links from Causal Forecast Detail Easy to review the Product Roll out and Causal Values for a pair 5
SPM 11.1 Key Forecasting Enhancements Variable number of history slices by method Number of history slices can be set by forecast method for all statistical methods (except Crostons and Same as Last Year) to improve forecast accuracy. For example, Winters (seasonal) can use three years while exponential smoothing can use one year. Bestfit recommended forecast method uses variable # of history slices. Forecast parameter Number of history slices supercedes stream config history slices. Causal Forecast for multiple streams Multiple streams can be set with forecast method = Causal in stream config detail Example: Separate causal forecast for maintenance and unplanned removals with different failure rates and BOMs Ability to filter by forecast stream on causal forecast detail, prod rollout and causal value pages Product Rollout /Causal Values views (with OTF for a part) Ability to add/modify/delete causal values and product rollout amounts Easy access to causal values and product rollout pages from causal forecast detail page. To and from links between causal forecast detail and stocking policy page Multi-threading for Causal Forecasting Improves processing time for causal forecasting (also available in 10.7.0.5) 6