【正文】 f an event related factor that may influence demand. The marketing forecast is adjusted up or down by a certain factor. The factor can be increased or decreased across periods to simulate a rampup or a rampdown in sales depending upon the nature of the event. Frequency: Event Based Scenario Description An event row will model the influence of the event that will change the marketing forecast. A promotional campaign or price change by the pany or the petition is an example of a factor that may influence demand. The user will populate the Event row with scalar values which when multiplied by the Marketing statistical forecast will adjust the Marketing forecast up or down by a factor ( for a 10% decline or for a 5% increase etc.). Event row can be increased or decreased across periods to simulate a rampup or a rampdown in sales depending upon the nature of the event. Inputs ? Event – constant factor typically ? Historical Bookings ? Marketing forecast Outputs ? Adjusted Marketing Forecast Benefits ? The ability to allow events to dynamically influence forecast I2 Products Used TRADEMATRIX Demand Planner SCP Master Planning Technical Implementer Reference Manual 169。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. 4 4 Contents SCM PROCESSES OVERVIEW SCM PROCESSES DEMAND PLANNING DEMAND FORECASTING TopDown Forecasting BottomUp Forecasting Life Cycle Planning – New Product Introductions and PhaseIn/PhaseOut Event Planning Consensus Forecast AttachRate Forecasting/Dependent Demand Forecasting in ConfiguretoOrder environments DEMAND COLLABORATION Flex Limit Planning FORECAST NETTING Forecast Extraction MASTER PLANNING SUPPLY PLANNING Enterprise Planning: Inventory Planning Enterprise planning: Long term capacity planning Enterprise planning: Long term material planning Facility Planning: Supply plan for enterprise managed ponents Collaboration Planning for Enterprise and Factory Managed Components – Procurement Collaboration Collaboration Planning with Transportation Providers Transportation Collaboration ALLOCATION PLANNING DEMAND FULFILLMENT ORDER PROMISING Promising new orders Configure to Order (CTO) Orders Build to Order (BTO) Orders ORDER PLANNING Factory Planning Transportation Planning SCM Processes Overview The following figure briefly describes the solution architecture for the core processes that 169。 i2 TECHNOLOGIES and design。 ORB NETWORK。 169。 i2 TECHNOLOGIES。 i2。 and RhythmLink. February, 20xx Document ID: HiTech SCM Template Workflow Document Version: V Document Title: HiTech SCM Template Workflow Document Revision: Draft 1 Revision Date: 3 February, 20xx Document Reference: . Primary Author(s): SCM Team – Krishnan Subramanian, Jatin Bindal, Abhay Singhal Comments: SCP Master Planning Technical Implementer Reference Manual 169。 Capture Forecast Netting Master Planning 169。20xx i2 Technologies, Inc. 10 10 Life Cycle Planning – New Product Introductions and PhaseIn/PhaseOut Definition Forecasting product transitions plays a critical role in the successful phasing out and launch of new products. New Product Introduction (NPI) and phase In/phase out forecasting allows the enterprise to forecast ramp downs and ramp ups more accurately. Ramping can be defined in terms of either a percentage or as units. Typically new products are difficult to forecast because no historical information for that product exists. NPI planning must allow for new product to inherit historical information from other product when it is expected that a new product will behave like the older product. In situations where a new product will not behave like any other older product, NPI planning allows a user to predict a