【正文】 ach 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 DescriptionInputs? Model to options mapping? Relationship to determine dependent forecastOutputs? Attach Rates? Dependent ForecastBenefits? Easy way to determine dependent forecasts in a CTO environment? Attach Rates can be forecast across time and geographyI2 Products UsedTRADEMATRIX Demand Planner, RHYTHM PRODemand CollaborationDefinitionIn 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 DescriptionThe 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 enterpriseOutputs? A consensus forecast agreed upon between customer and enterprise for different product lines.BenefitsCollaborative 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 UsedTRADEMATRIX Collaboration Planner15 / 36Flex Limit PlanningDefinitionContracts 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 DescriptionThis process is currently not a part of the template. Future releases will incorporate this process as a standard workflow in the template.InputsOutputsBenefitsI2 Products UsedTRADEMATRIX Collaboration Planner Forecast NettingForecast ting as a process can be done outside of Demand Planning or within demand planning. The decision as to where to perform this process would vary by industry. The template supports both types of workflow.DefinitionThe consensus forecast is used as input for supply planning for the enterprise. As customer orders / confirmed orders (order backlog) are realized in a short term (few weeks to few months), the orders are ted against the forecast for the supply planning purpose. The supply planning process, thus, plans for the ted forecast and the order backlog. It is important to distinguish between forecast and orders in supply planning because orders are firm demand that the enterprise has mitted to the customers. Therefore, it translates directly into revenue for the enterprise. By providing the orders and ted forecast as inputs to the supply planning process, we can allocate constrained material and supply first to the actual orders and then to the forecast, thereby ensuring that the orders are planned is important because during supply planning, orders must have a higher priority than forecasts as the orders MUST be planned for and fulfilled. Further, we would want that the capacity and the materials consumed by orders should not be available while planning for the remaining forecasts. So first we plan for orders (which consume some material and capacity) and next we plan for the ted forecasts (which is the remaining forecast for the period). Scenario Description1. Forecast Netting for BTS and BTO productsForecast ting for a BTS product is simpledone at a seller product level. Consider a particular sellerproduct bination. We know the forecast for the bucket. From the actual orders, we can determine the actual orders for the sellerproduct bination that fall in each bucket. These orders can then be ted against the forecast using prespecified business rules.2. Forecast Netting for CTO productsForecast for CTO products is done at a model level. However, unlike for BTS and BTO, actual orders for CTO e in at ponent level. The customer will specify a setbunch of ponents that he would want to be assembled into a model. Because of this discrepancy between the level at which forecasting is done (model level) and the level at which actual demand es in (ponent level), forecast ting for CTO is not so straightforward. So for CTO, we send—not a ted forecast but —an adjusted forecast to Master Planning. To arrive at an adjusted forecast, the gross forecast can be adjusted at two levels: a) The total forecast for the bucket at a sellerproduct bination node can be changed, and/or b) The for