Austin Office S. Deployment: Platform:. Logility Demand Optimization A cloud-based suite of tools that help users with demand planning, forecasting, life cycle planning, proportional profile planning and more. Logility lets users keep an eye on important budget and demand information. This integration offers demand and supply modeling for precise planning, inventory visualization and real-time data synchronization from IoT sources. Machine Learning and AI: Machine learning and artificial intelligence lets users make informed decisions faster.
It analyzes product and market attributes to create demand profiles and automated accuracy assessments. Responsive to future demand signals and possible demand disruptions, it also automates forecast revisions for better accuracy. Key Features Demand Planning: Generate forecasts at business levels, while factoring in key aspects like sales and marketing to logistics and financials.
Users can also segment demand by customer profile, channel and product attributes. This helps users adjust the difference between high-level business planning and low-level product forecasting, optimize inventory carrying costs and align customer demands with inventory investments. Logility Pulse Wise: Logility Pulse Wise lets users respond favorably to dynamic market conditions and automate planning using an autonomous engine based on artificial intelligence.
This engine helps identify and analyze demand signals to update demand planning parameters in real time. Demand Sensing: Logility Demand Sensing utilizes big data to capture and analyze demand signals from all internal and external sources to identify demand patterns and trends while providing advanced warning of any possible gaps in supply and demand.
This helps users formulate fast responses in times of crisis and implement agile deployment to improve customer fill-rates. Life Cycle Planning: Analyzes the impact of multiple demand scenarios, past trends, patterns and additional demand signals with artificial intelligence.
Proportional Profile Planning: Create flexible, multi-tier, attribute-based and time-phased profiles for demand precision at each life cycle stage.
It also helps users predict high-level demand while driving precision at granular levels to synchronize sourcing and production, along with logistics and cost calculations. Limitations A free trial is not available.
RapidResponse A cloud-based tool that helps users create collaborative and comprehensive demand forecasts based on statistical factors and multiple functional perspectives. Top Benefits Improved Visibility: The platform, along with other supply chain applications associated with this suite, provide end-to-end supply chain visibility with the ability to integrate demand functions with other supply chain processes, improved forecast accuracy and execution of plans across departments.
Consensus Demand Plan: Create a consensus demand plan with collaboration between various departments like sales, marketing, finance and demand planning to minimize costs and maximize revenue opportunities. Key Features Consensus Forecasting: Offers a consensus forecast, combining statistical forecasts with multiple functional forecasts generated based on inputs provided by different departments. This feature allows users to combine demand planning with strategic capacity.
Performance Management: Users can measure forecast accuracy using numerous methods to perform a value comparison of each forecast stream against the demand plan and annual plan. With sales data conditioning, users can also identify data errors and outliers to be cleansed and minimize errors going forth.
Cross-functional Collaboration: Enables seamless collaboration between departments like marketing, sales, operations, and finance. Users can set up, benchmark and track financial targets and operational KPIs to maintain performance. Demand Inputs: The platform collects demand inputs across sales, marketing, finance and operations.
It lets the users submit their assumptions and perspectives, match them against historic patterns and actuals, review stats and revise forecasts accordingly. Reporting: Compare various plans for current demand, aggregate supply, annual demand and supply to track forecasts against actuals and improve strategic decisions.
Limitations Native mobile apps for Android and iOS devices are not available. It also integrates with third-party systems on demand to ensure seamless collaboration and sharing of data. Supply Chain Cockpit: Customizable and intuitive graphical instrument panel for managing, tracking and controlling the supply chain.
Supply Chain Collaboration: The Collaborative Planning CLP tool generates an optimized, collaborative plan based on data and assumptive inputs of business partners across the supply chain network. These product extensions provide valuable information regarding inventory overview, capacity load, supply plan evaluation and reliability of forecasts. They also identify possible bottlenecks and project supply shortages to help users plan ahead.
Data Persistency: Offers data persistence through transactional data storage within an object-oriented in-memory liveCache, which users can access as required. Primary Features Demand Planning: This module offers planning layouts, interactive planning books and a demand planning library of statistical forecasting and macro techniques. Utilizing these resources, users can adopt a consensus-based approach to create demand plans and forecasts with inputs from different departments.
It also allows users to add marketing intelligence, make required management adjustments and manage life cycles, promotions and collaborative demand planning. Supply Network Planning: Operates on heuristic, rule-based and optimization-based algorithms to manage purchasing, manufacturing, distribution and transportation.
It also uses constraints and penalties to plan products from across the supply chain network and factors in safety stock planning as well as load building for transportation. Production Planning and Data Scheduling: Manage multi-level production planning using a choice of existing or custom heuristics. Along with an order pegging feature, the platform supports lot quantity calculations and sourcing for make-to-stock, make-to-order, make-to-order with order BOM, engineer-to-order, project manufacturing and flow manufacturing.
This helps users allocate products, perform backorder processing and fulfill commitments to customers subject to global availability. Service Parts Planning: Caters to planning functions specific to service parts based on product attributes and product sales patterns to determine the frequency of required actions and maintain top-to-bottom transparency throughout the supply chain.
Oracle Demand Management Cloud Part of Oracle Supply Chain Planning Cloud, this cloud-based system combines forecasting algorithms with flexible analytics to help users adopt a customer-centric demand planning methodology. Demand plans let users lay out strategies and view helpful information.
Top Benefits Machine Learning: Automated machine learning algorithms that combine fifteen industry standard and proprietary forecasting models to manage demand patterns and product life cycles with accuracy.
Analytics: Has a patented Bayesian analytical forecast engine that generates accurate forecasts, and has built-in real-time updates to help users make quick and informed decisions. Statistical Forecasts: Generate statistical forecasts based on several factors and use them to understand demand variations and patterns per factor. Forecast Trees: Forecast trees organize and extrapolate analytical demand forecasts for a given profile. This helps users plan ahead for variations and disruptions, using historical actuals as well as predictive future analyses.
Creates a knowledge base by maintaining planners' comments and audit trails. Supports reason codes for forecast modifications. Includes capabilities for modeling and viewing information about events such as product introductions, product cannibalization, and product phase outs.
Provides feedback to planners through performance monitoring, exception reporting, comparative reports, and user-defined alert mechanisms. Oracle Demand Planning has component architecture. This means that in lieu of working directly from data generated by other Oracle Applications, Oracle Demand Planning copies the data to a localized data store in a process called collection.
This is done for two reasons:. It allows the computational-intensive planning and forecasting calculations to be off-loaded to a separate Demand Planning Server, where the localized data store resides, to avoid excessive load on the server hosting the transactions. It allows Oracle Demand Planning to be deployed against multiple versions of Oracle Applications versions There are separate collection programs for each version.
The business process of demand planning requires analyzing demand along different dimension levels. The ability to accept demand data input at one set of dimension levels, display it at another set of dimensional levels, and maintain a consistent set of underlying demand data that is independent of the levels at which it is displayed is covered by a technique known as Online Analytical Processing OLAP.
The Oracle 9 i database release 2 contains Online Analytical Process. A representation of Oracle Demand Planning in the Oracle Database is illustrated below shows that Relational and Online Analytic Process data are managed in a single, integrated instance. This integration allows for an internal movement of data when downloading data from the Demand Planning Server to the Demand Planning Engine and uploading data from the Demand Planning Engine to the Demand Planning Server.
The Oracle Database stores multidimensional data directly in the database. The database engine runs within the database kernel and internally executes all multidimensional data calculations. All data in the Oracle Database, both relational and multidimensional, is stored in Oracle data files. Multidimensional data is stored in an Analytic Workspace within a relational schema. An Analytic Workspace is a container for collections of multidimensional data types and may contain one or many 'cubes'.
These cubes are the plans created in Oracle Demand Planning. The Demand Planning Server holds the inputs such as sales history, as well as the forecast outputs for feeding to Oracle Advanced Supply Chain Planning and other Oracle applications. Data such as items, sales history, and inventory organizations are collected from the source into staging tables in the Demand Planning Server. The purpose of the staging tables is to provide a temporary repository that allows users to review the collected data, adjust the data as necessary, and clean out any irrelevant data, thus making the data more useful for forecasting.
Note that Oracle Demand Planning does not provide an explicit data viewing or cleansing tool. You can use any data manipulation tool such as SQL for this purpose. The data are then pulled into fact tables on the Demand Planning Server. If the data are clean, then it can be collected directly into the fact tables.
The administrator defines a demand plan in the Demand Planning Server. He or she specifies the dimensions and hierarchies within dimensions such as geography and sales group. The administrator also specifies one or more scenarios based on different histories or date ranges for forecast horizons. The administrator also specifies what type of historical data will be used and how much of the history to use. In addition to historical data, the administrator can select reference data such as manufacturing data for comparing forecasts generated by Oracle Demand Planning based on historical data.
If the system collects data from the Bills of Material BOM , the administrator can set up the Demand Planning Server so that planners and the Demand Plan Manager can view and edit data for dependent demand and planning percentages. The Demand Planning Server is a source of integrated data that can include the following:. The Demand Planning Server defines the parameters of the source data as well as events, scenarios, demand plans and system setup. However, all the items within a forecast set are shown, including overconsumption, when this window is accessed in the view mode through the Inquiry menu.
You can define and maintain forecasts for any item, at any level on your bills of material. Forecast explosion is a process that creates forecasts for components from the forecasts of their parents. It occurs in the following situations:. Product family forecasts to product family member item forecasts. The planning engine considers these exploded forecasts as independent demand and uses pegging to link then to their product family forecast. Model forecasts to other model, option class, option item, and included item forecasts.
In Oracle Bills of Material, you can define multilevel planning bills, with multiple levels of planning items, to represent groups of related products that you want to forecast by family. Typically, you can order components of a planning bill, but not the planning item itself.
The planning item is an artificial grouping of products that helps you to improve the accuracy of your forecasting since, generally, the higher the level of aggregation, the more accurate the forecast. Before you can perform forecast explosion, set up planning percentages in the product family and model bills of material.
Planning percentage is the percent of the parent forecast that is attributable to the component. After forecast explosion, the forecast quantity for product family member item A is , for product family member item B is , and for product family member item C is The following table illustrates a planning bill for Training Computer, a planning item that represents a planning bill for three types of computers: laptop, desktop, and server.
The planning percent assigned to each member of the planning bill represents anticipated future demand for each product. The following table illustrates forecast explosion, via the planning bill described in the previous table, for a forecast of Training Computers. The table also illustrates forecast consumption after you place sales order demand for 20 Laptop Computers.
Original forecast shows forecast quantities before forecast consumption. Current forecast shows forecast quantities after consumption by sales order demand. You control forecast explosion to each component by setting its organization item attribute Forecast control:.
Consume and derive: There can be planning engine forecast explosion for models depending on plan option Explode Forecast. The planning engine does not explode multi-organization models. None: There can be planning engine forecast explosion for product families depending on plan option Explode Forecast. For information about forecast explosion for model forecasts, see Configure to Order Forecast Explosion.
This topic lists forecast considerations for Oracle MRP. The forecast quantities exploded to the components are calculated by extending the planning item forecast by the component usages and planning percents defined on the planning bill.
You can also choose to explode forecasts when you load a planning item forecast into a master schedule. A model is an item with some configurable components. A configurable component is a component that different customers may order differently, for example, a color of paint.
Assemble-to-order: The manufacturer or distributor assembles the components and ships the configured item, for example, an automobile. Pick-to-order: The components are shipped separately and assembled by the recipient, for example, a childrens' outdoor play set. Oracle Advanced Supply Chain Planning uses the pick-to-order model item for forecast explosion; it does not plan it. Option classes: A bill of material structure whose components are the options that the customer can select, for example, paint color.
Standard items: The options from which the customer chooses, for example, red, green, and blue. They are components of the option classes. Included items also known as mandatory components : A standard item that the customer receives regardless of options selected, for example, an instruction brochure.
They are components of the model item. Another model: For example, a personal computer. The customer chooses the main components and the manufacturer assembles them into a case assemble-to-order.
The customer also chooses peripheral items that the manufacturer or distributor ships separately from the main unit and that the recipient attaches to the main unit. The personal computer is a pick-to-order model, the main unit is an assemble-to-order model component under the pick-to-order model, and the peripherals are option class components under the pick-to-order model.
The following table illustrates a model bill for Laptop Computer, a model that includes two mandatory components and three option classes. The planning percent assigned to optional option classes represents anticipated demand for the option class. The planning percent assigned to each option within each option class represents anticipated demand for the option. Notice that the Monitor option class is not optional.
This means that customers must always choose one of the Monitor options when ordering Laptop Computer. Predefined configurations are configurations that you have defined as standard items, with standard bills and standard routings. You might define a predefined configuration because you often use the configuration in sales promotions, or the configuration is one of your most commonly ordered configurations, and you want to build it to stock to reduce delivery lead times and improve customer service levels.
Your customers can order predefined configurations by item number, just as they order any other standard item. Forecast consumption, forecast explosion, master scheduling, planning, production relief, and shipment relief for predefined configurations behave as they do for any other standard item.
Use item attribute Forecast Control to specify the types of demand that you place for models, option classes, options, and mandatory components. The configure to order processes uses the Forecast Control value that you assign to each assemble-to-order and pick-to-order item to guide the behavior of those processes. The following section discusses the four types of demand that you can place for an item, and identifies the appropriate Forecast Control attribute value for each type of demand.
There are the types of demand that you can place for your models, option classes, options, and mandatory components:.
Independent forecast demand is demand that you place for an item by entering forecasts for the item directly, rather than exploding forecast to the item using forecast explosion. You typically define direct forecasts for items, such as a planning items or models, whose demand is independent of any other item. Define direct forecasts by entering them manually, or by loading them from other products or systems. Exploded forecast demand is demand that you generate for an item when you explode forecasts to the item using forecast explosion.
You typically generate exploded forecast demand for items, such as option classes and options, whose demand is directly related to or derived from the bill of material structure for other items.
If you forecast demand for an item by exploding demand from a higher level item in a bill of material, set Forecast Control to Consume and Derive. In some cases, you may have items that are subject to both types of forecast demand. For example, the keyboard that is forecast and sold as a mandatory component with a Laptop Computer may also be forecast and sold separately as a spare or service part. You use Forecast Control to control which models, option classes, options, and mandatory components in a model bill receive exploded forecasts, since forecast explosion only generates exploded forecast demand for items where you have set Forecast Control to Consume and Derive.
Important: Set Forecast Control to None to identify items that have dependent demand that should be calculated by the planning process, using standard planning logic, rather than through forecast explosion. An example of this type of item is a user manual that is either gross-to-net or minmax planned and replenished. If you forecast demand for an item directly, and explode forecast demand to the item, set Forecast Control to Consume and Derive.
Sales order demand is demand that you place when your customers order configurations. As your customers order configurations, Oracle Order Management automatically places sales order demand for each model, option class, and option selected by your customer when they place the order. If you place sales order demand for an item, but do not forecast the item, set Forecast Control to None.
Under normal circumstances, Oracle Order Management does not place sales order demand for mandatory components when your customers order configurations.
If you are forecasting key mandatory components, however, you will usually want to maintain your forecasts by generating sales order demand for the mandatory components and consuming the forecasts as your customers place sales orders. You can set the Forecast Control attribute to Consume or Consume and Derive to automatically place demand and consume forecasts for mandatory components when you place sales orders demand for configurations that include the mandatory components.
If you forecast demand for a mandatory component, either directly or through forecast explosion, set Forecast Control to Consume or Consume and Derive. The following table summarizes, for each type of item, the types of demand that configure to order assumes you place for different values of Forecast Control. Oracle MRP lets you master schedule any planned item on your master schedules, including models and option classes. With the two-level master scheduling approach, you typically master schedule your key subassemblies your options and mandatory components since they are the highest level buildable items in your model bills.
Although models and option classes are not buildable items, you may want to master schedule them so that you can calculate available-to-promise ATP information for promising order ship dates by model or option class.
You might also want to master schedule your models and option classes so that you can perform rough cut capacity checks by model and option class. This is particularly valid when different configurations of your models have very similar capacity requirements.
Note: Oracle MRPg does not support planning for picktoorder models and option classes. The following table summarizes the effect of Forecast Control on the following major processes that Oracle MRP uses to implement twolevel master scheduling:. Forecast Consumption a and Forecast Consumption b represent forecast consumption before and after the Auto-Create Configuration process creates the configuration item and single-level bill for a configuration.
Note: Notice that the only difference between the Consume option and the Consume and Derive option is that forecast explosion generates exploded forecast demand for items where Forecast Control is set to Consume and Derive.
You can use the Bills of Material window in Oracle Bills of Material to define model and option class bills with multiple levels of option classes, options, and mandatory components to represent your complex configure-to-order products. You can then use forecast explosion to explode model and option class forecasts the same way you explode forecasts for planning items.
The logic for exploding models and option classes is the same as the logic used to explode planning items. You can choose to explode model and option class forecasts, just as you can choose to explode planning item forecasts when loading forecasts into other forecasts or master schedules.
The following table illustrates when forecast explosion explodes forecast from a parent item to its components. The following table illustrates when forecast explosion explodes forecast to a component from its parent item.
The following table illustrates how forecast explosion explodes a forecast for Laptop Computers. The FC column shows forecast quantities. You explode forecasts by choosing the Explode option when loading a forecast into another forecast or a master schedule. You can change your planning and model forecasts at any time and reexplode new forecasts to your option classes, options, and mandatory components.
You can choose to reconsume your new forecasts using the sales order demand history maintained by Oracle MRP. This lets you quickly adjust your exploded forecasts in response to forecast or bill of material changes. Forecast consumption is the process that replaces forecast demand with sales order demand. Each time you place a sales order, you create actual demand.
If the actual demand is forecasted, you typically want to reduce the forecast demand by the sales order quantity to avoid overstating demand. For source instance forecasts, the consumption occurs against forecasts for product families, configurations, models, option classes, and options when you place sales order demand for configurations.
By default, forecast consumption consumes forecasts by item. If you want to consume your forecasts by distribution channel, customer type, or order type, use demand classes to control forecast consumption.
You can also choose to consume your forecasts by one of the following forecast consumption levels:. With inline forecast consumption, toe consumption occurs at the beginning of the planning run, using the forecasts and sales orders that you use to drive the plan. Forecast consumption takes place both before and after the AutoCreate Configuration process creates a configuration item, bill, and routing for a configuration.
The configure to order process ensures that forecast consumption is consistent before and after the creation of the configuration item. Note: The fact that forecast consumption takes place twice, both before and after the creation of the configuration item, is transparent to the user.
The purpose of this section is only to provide detailed information. When your customers order configurations, Oracle Order Management places sales order demand for all ordered models, option classes, and options.
Note: Under normal circumstances, no sales order demand is placed for mandatory components. You can also generate derived sales order demand for selected mandatory components, since forecast consumption generates derived sales order demand for all items where you have set Forecast Control to Consume or Consume and Derive. This lets you define and maintain forecasts for key mandatory components as well as models, option classes, and options.
Before you run the AutoCreate Configuration process, forecast consumption uses actual sales order demand for models, option classes, options, and derived sales order demand for selected mandatory components, to consume your forecasts. The following example illustrates how forecast consumption consumes an exploded forecast for Laptop Computers when a customer places a sales order for 10 Laptop Computers with processors, VGA1 monitors, and DOS operating system. The SO column shows sales order quantities.
Notice that forecast consumption generates and consumes derived sales order demand for each mandatory component where you have set Forecast Control to Consume or Consume and Derive. The AutoCreate Configuration process replaces sales order demand for ordered models, option classes, and options with sales order demand for the newly created configuration item. This prompts forecast consumption to unconsume forecasts for the models, option classes, options, and selected mandatory components, and consume forecasts for the new configuration item and its components.
When creating the configuration item, the AutoCreate Configuration process also creates a single level bill of material for the configuration item. The single level bill includes all ordered options, all mandatory components of all ordered models and options classes, and each ordered model and option class.
The models and option classes appear on the configuration bill as phantoms, and are only there to consume forecasts and relieve master schedules. They are not used by the planning process or Oracle Work in Process since all mandatory components from the model and option class bills are also included directly on the single level bill. The following table illustrates the single level configuration bill created by the AutoCreate Configuration process in response to the sales order for 10 Laptop Computers with processors, VGA1 monitors, and DOS operating system.
In the post configuration stage, forecast consumption uses the sales order demand for the new configuration item to consume forecasts.
Typically, you do not have any forecasts defined for unique configurations. Therefore, forecast consumption does not find any forecasts to consume. If forecast explosion cannot find any forecasts to consume, it explodes the configuration bill and consumes forecasts for each model and option class on the bill. It also consumes forecasts for each standard item on the configuration bill where Forecast Control is set to Consume or Consume and Derive. To ensure that forecast consumption is consistent before and after the AutoCreate Configuration process, forecast consumption only consumes forecasts for standard items on configuration bills where Forecast Control is set to Consume or Consume and Derive.
Note: If you set Forecast Control to None for an option, and then define forecasts for the option, you get inconsistent forecast consumption before and after the AutoCreate Configuration process. Before the AutoCreate Configuration process, forecast consumption uses actual sales order demand to consume any existing forecasts. After the AutoCreate Configuration process, forecast consumption does not consume those same forecasts since it only consumes forecasts for standard items on configuration bills where Forecast Control is set to Consume or Consume and Derive.
The following table shows how forecast consumption consumes the exploded forecast for Laptop Computers after the AutoCreate Configuration process replaces sales order demand for the model, option classes, and options with sales order demand for the newly created configuration item. Forecast consumption for predefined configurations is exactly the same as forecast consumption for configuration items created automatically from sales orders for ATO models.
Typically, if you have created a predefined configuration, you have also defined forecasts for it. If so, forecast consumption finds and consumes forecasts for the predefined configuration. If you have not defined forecasts for the predefined configuration item, then forecast consumption explodes the configuration bill and consumes forecasts for each model and option class on the bill.
The following table illustrates a predefined configuration for a commonly ordered version of Laptop Computer called Laptop Basic. The following table illustrates consumption of a forecast for Laptop Basics after a customer places a sales order for 10 units.
If you have not defined forecasts for the predefined configuration, forecast consumption explodes the configuration bill and consumes forecasts for each model and option class. Forecast consumption also consumes forecasts for each standard item on the configuration bill where Forecast Control is set to Consume or Consume and Derive. The following table illustrates consumption of the same sales order for 10 Laptop Basics when you have not defined a forecast for Laptop Basic.
Note that the original forecast quantities for Laptop Basic's components have not been exploded from Laptop Basic, since you cannot explode forecasts from a standard item. Any forecasts that do exist for Laptop Basic's components must have been entered manually or exploded from a planning item, model, or option class forecast. This example assumes that Forecast Control is set to Consume or Consume and Derive for all standard components on Laptop Basic's configuration bill.
Forecasts and Sets Forecast sets consist of one or more forecasts. Forecast Set Defaults Each forecast inherits the forecast level, consumption options, and other defaults defined for the set. Time Buckets You can forecast with daily buckets in the short term, weekly buckets in the midterm, and periodic buckets in the longer term. Entry Options You can define a forecast for a particular item by entering a single date and quantity.
Planning Bills and Models You can include planning bills and models in forecasts. Alternate Bills You can associate alternate bills of material to multiple forecasts for the same item, exploding different components, usages, and planning percentages.
Consumption You can manually or automatically consume forecasted demand with sales order actual demand. Consume by Demand Class You can define demand classes that represent groupings of similar customers or order types. Consume by Item, Customer, Bill to Address, or Ship to Address You can consume forecasts at four different forecast levels: item, customer, billto address, or shipto address forecast level.
Copy To help manage and consolidate your forecast information, you can create new forecasts from existing forecasts or forecast sets. Forecast Rules You can define item forecast rules in Oracle Inventory to establish the forecast method, bucket type, and sources of demand that are considered when compiling a statistical or focus forecast.
Generate Focus and Statistical Forecasts You can create forecasts by applying statistical and focus forecasting techniques that use historical transaction information. Load Forecasts into the Master Schedule You can use forecasts or forecast sets to generate master demand or master production schedules.
Review You can review all aspects of your forecasts using online inquiries and reports. Deleting Forecasts and Forecast Sets You can delete forecast and forecast sets. The two methods of generating forecasts are: Focus forecasting which produces only single period forecasts Statistical forecasting which you can use to forecast any number of periods into the future See Also Defining Forecast Rules Defining Forecast Rules Before you can generate a focus or statistical forecast, you first define a forecast rule in Oracle Inventory.
In the Parameters window, select a forecast name and forecast rule. Select an overwrite option: All Entries: Deletes everything on the forecast before loading new information. Enter a start date and cutoff date. Choose OK. In the Generate Forecast window, choose Submit. See Also Submitting a Request, Oracle Applications User's Guide Forecast Levels In addition to designating the minimum level of detail for which the forecast is defined, the forecast level also serves as a consumption level.
You can define the following consumption levels for a forecast set: item level customer level bill - to address level ship - to address level Important: If you have not installed Oracle Order Management or Oracle Receivables, you can only consume forecasts by item level.
Forecast sets: Group complimenting forecasts that sum together to a meaningful whole Group forecasts that represent different scenarios. See: Forecast Set Examples. You can associate a forecast to one forecast set only. To define a forecast set: Navigate to the Forecast Sets window.
Enter a unique name. Select a bucket type to group forecast entries by days, weeks, or accounting periods.
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