【正文】 20xx i2 Technologies, Inc. 14 14 Demand Collaboration Definition In situations where the customers of the enterprise have their own forecasting processes, demand collaboration will enable more accurate forecasting by ensuring rapid transmission of any downstream demand pattern changes to the enterprise. Furthermore, in the absence of such a workflow, every node in the supply chain invariably tends to put in ―sandbagging‖ inventory to pensate for the lack of fast information flow. Scenario Description The Inter enables the rapid collaborative demand forecasting process. A workflow can originate at either the enterprise or the customer, ., the enterprise could initiate a baseline forecast to submit to the customers for feedback, or a baseline forecast could be initiated by a customer and submitted to the enterprise for review and collaboration. The workflow used can differ depending on either the customer or product. The collaborative munication will be over the World Wide Web. Customers will only be able to see ―their‖ forecasts, not those of other customers. In addition to forecast, information regarding sell through rates, inventory levels etc. can also be municated between enterprise and customers. Inputs ? Enterprise initiated baseline forecast or customer initiated baseline forecast ? Revisions to the forecast by customer and enterprise Outputs ? A consensus forecast agreed upon between customer and enterprise for different product lines. Benefits Collaborative forecasting over the Inter reduces cycle time between forecast information propagation. Hence enterprise gets more real time updates of changes in downstream demand patterns. ? Collaborative forecasting processes will enable improving honest information exchange between enterprise and customers thereby reducing the ―sandbagging‖ inventory in the supply chain. I2 Products Used TRADEMATRIX Collaboration Planner 169。 Capture Forecast Netting Master Planning 169。 i2。 169。 i2 TECHNOLOGIES and design。20xx i2 Technologies, Inc. 7 7 Demand Forecasting TopDown Forecasting Definition Top down forecasting is the process of taking an aggregate enterprise revenue target and converting this revenue target into a revenue forecast by sales unit/product line. This allocation process of revenue targets can be done using historical performance measures or using rule based allocation techniques. The revenue targets can further be broken down into unit volume forecasts by using Average Selling Price information for product lines. Historical information is typically more accurate at aggregate levels of customer/product hierarchies. Therefore, statistical forecasting techniques are typically applied at these aggregate levels. At levels where historical information might not be very relevant or is not perceived to be accurate, this allocation can be done with a rulebased approach. Frequency: This process is typically performed at a monthly/quarterly frequency, with the forecast being generated for the next several months/quarters. Scenario Description Based upon historical bookings at an aggregate level across the entire pany (for all products and geography‘s), the system will automatically generate multiple forecasts using different statistical techniques. The statistical techniques will account for such things as seasonality, trends, and quarterly spikes. Each statistical forecast will be pared with actuals to calculate a standard error. This will automatically occur at every branch (intersection) in the product and geographic hierarchies. The aggregate statistical forecast generated for the entire pany will be automatically disaggregated at every intersection using the statistical technique with the smallest SCP Master Planning Technical Implementer Reference Manual 169。20xx i2 Technologies, Inc. 15 15 Flex Limit Planning Definition Contracts between the enterprise and their customers place restrictions on how much flexibility is provided to the customers in terms of varying forecast numbers from one time period to another. Based on the collaboration process with channel partners / customers, flex limits on the forecast values are established. These flex limits will then drive the amount of inventory that the enterprise needs to position to cover for the anticipated variation in demand. Scenario Description This process is currently not a part of the template. Future releases will incorporate this process as a standard workflow in the template. Inputs Outputs Benefits I2 Products Used TRADEMATRIX Collaboration Planner SCP Master Planning Technical Implementer Reference Manual 169。20xx i2 Technologies, Inc. 13 13 AttachRate Forecasting/Dependent Demand Forecasting in ConfiguretoOrder environments Definition In a Configure To Order (CTO) manufacturing environment, a particular product model can be sold with several options. The customer chooses the exact configuration at the time of placing an order. However, for the purpose of procuring these parts, the enterprise will need to forecast the mix of options that will potentially be sold. The forecast percentage mix of options is called ―attach rates‖. The consensus process essentially determines the forecast at the product model level. This process performs the option mix analysis to forecast attach rates. The ?attach rates‘ can be varying by time and/or geography. Product or Productseries level forecasts will be broken down into the ponents or options that prise them by using attach rates. Attach rates can be manually input or forecasted based upon history. Scenario Description