On Thursday, October 30, 11 am ET, Aris Syntetos delivers the next installment of the Foresight/SAS Webinar Series, "Forecasting by Temporal Aggregation." Based on his article in the Summer 2014 issue of Foresight, Aris provided this preview:
When we attempt to improve forecast performance we usually consider new or alternative forecasting methods. However, how about not changing the forecasting methods but rather changing our approach to forecasting altogether (by keeping the forecasting methods the same)?
Have you heard about, or ever considered, forecasting by aggregating demand in lower frequency time units (say weekly into monthly demand)? Aggregating demand will almost always reduce demand uncertainty. It also helps to see the linkages between the output of the forecasting process (forecasts needed to support specific decisions) and input (data available to produce the forecasts).
Best of all, it is highly likely that temporal aggregation will improve forecast performance. Ready to see how? Join us in this on-demand webinar to understand:
- How forecasting by temporal aggregation works;
- The different types of temporal aggregation (overlapping and non-overlapping);
- The data requirements for supporting forecasting by temporal aggregation;
- The linkage between decision making requirements and the time periods in which demand is recorded.
Aris is Professor of Operational Research and Operations Management at Cardiff University, UK. His research interests relate to supply chain forecasting and its interface with inventory management and he has advised many commercial organizations in this area. In addition, forecasting, demand classification and stock control algorithms co-developed by him have been implemented or are currently considered for implementation by commercial software packages.
Aris is the supply-chain forecasting editor for Foresight. He serves at the Executive Committee of the International Society for Inventory Research (ISIR) and at the Board of Directors of the International Institute of Forecasters (IIF).
Check out the video preview of the presentation, and register for free.
For more discussion of this topic, and to learn how to apply the approach in SAS Forecast Server software, see the BFD post "Forecasting across a time hierarchy with temporal reconciliation."