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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Administration and Configuration | 20% | - Configure product and asset management - Set up territory management - Customize page layouts and record types - Manage users and roles in Manufacturing Cloud - Implement security settings |
| Topic 2: Reports and Dashboards | 15% | - Build executive dashboards - Use analytics for decision making - Configure report sharing and subscriptions - Create and customize Manufacturing Cloud reports |
| Topic 3: Manufacturing Cloud Overview | 10% | - Describe Manufacturing Cloud value proposition - Understand use cases for manufacturing organizations - Identify key capabilities and features |
| Topic 4: Predictable Service Management | 20% | - Implement service case automation - Configure service entitlements and contracts - Manage service levels and milestones - Track service performance metrics |
| Topic 5: Account-Based Forecasting | 20% | - Manage demand forecasts at account level - Configure Forecast Trending - Understand forecast adjustment workflows - Set up forecast sharing and visibility |
| Topic 6: Einstein Activity Capture for Manufacturing | 15% | - Manage connected calendars - Configure Einstein Activity Capture - Synchronize emails and events - Understand data privacy considerations |
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問題 #100
UC is implementing Advanced Account Forecasting for its national business. UC has three primary product materials it wants to forecast for each of its key distribution partners. Each of UC's individual products has one of these material attributes on its record, but UC doesn't need to see the product detail in its forecast.
What should the administrator do to meet these business requirements?
答案：B
解題說明：
Advanced Account Forecasting is designed to support business-specific forecast dimensions without requiring the organization to expose unnecessary product-level detail. Salesforce defines a dimension as an attribute used to categorize forecast data. For a new Material dimension, the administrator extends the forecast fact structure with the appropriate field, defines that field as a dimension source, and includes the dimension in the applicable forecast set.
The preferred implementation pattern is to leverage Salesforce-provided Data Processing Engine templates rather than develop the complete processing model from the ground up. Salesforce specifically documents that the standard DPE templates can be cloned and customized to accommodate additional dimensions and measures. The cloned definitions can then aggregate source data into the Advanced Account Forecast Fact records according to the required dimensional structure.
A custom forecast context is unnecessary because the distribution partner remains the forecast context; Material is the additional grouping dimension.
This structure keeps the forecast concise for business users while preserving the material-level segmentation required for planning and reporting.
Study Guide references/topics: Configure and Build - Advanced Account Forecasting; Forecast Sets; Custom Dimensions; Data Processing Engine customization.
問題 #101
Badger Power wants to have a complete picture of both their run-rate and net-new business.
Which two Manufacturing Cloud functions should be configured?
答案：B,D
解題說明：
Account Based Forecasting and Sales Agreements are two Manufacturing Cloud functions that should be configured to have a complete picture of both run-rate and net-new business. Account Based Forecasting allows you to forecast your sales revenue based on the account level, rather than the opportunity level. This gives you more visibility into the demand from your existing customers, as well as the potential from new customers. Sales Agreements allow you to manage the sales lifecycle of your long-term contracts with customers, including pricing, volumes, and order realization. This helps you to track and fulfill your run-rate business, as well as to identify and capture new business opportunities within your agreements. References: Forecast Your Run-Rate and New Business with Account-Based Forecasting - Salesforce Help, [Create and Work with Sales Agreements - Salesforce Help]
問題 #102
Universal Containers would like to use Manufacturing Cloud to forecast its spare part demand based on the number of defective part cases logged by customers and part orders requested by distribution partners.
Which customization is required for Advanced Account Forecasting to meet these requirements?
答案：A
解題說明：
Spare-parts demand forecasting is a service forecasting use case, and Salesforce explicitly requires a different data-processing model from the standard sales-oriented Advanced Account Forecasting implementation.
Salesforce documents that service revenue and spare-parts demand forecasts require organizations to create custom forecast fact objects together with Data Processing Engine templates and jobs. Those DPE definitions can then be invoked through custom flows to generate the required forecasts.
This distinction is technically important because the underlying forecast inputs differ from conventional sales forecasting. UC needs to derive expected spare-parts demand from signals such as defective-part Cases and requests or Orders originating through distribution partners. The custom fact structure defines the service- specific forecast grain and measures, while the custom DPE logic retrieves, filters, transforms, aggregates, and writes those service signals into the forecast facts.
Salesforce explicitly notes that the default Advanced Account Forecast Fact objects and DPE templates supplied for sales use cases do not work for service use cases. Therefore, the Product Category forecasting prebuilt asset is not sufficient for this requirement.
A custom fact table alone would provide storage but not the processing logic necessary to generate the forecasts.
Study Guide references/topics: Configure and Build - Service Revenue and Spare Parts Demand Forecasting; Custom Forecast Fact Objects; Custom DPE Definitions; Advanced Account Forecasting.
問題 #103
The warranty claim adjudicators on the global warranty team at Universal Containers noticed that the Claims page in the Warranty Lifecycle Management app is not showing when the warranty for the asset ends.
What should the consultant recommend the warranty team do as part of claims processing?
答案：A
解題說明：
To address the issue of the Claims page not showing when the warranty for the asset ends, the consultant should recommend registering the asset by creating the Asset record and the Asset Warranty Terms record.
This ensures that all relevant warranty information, including the end date, is captured and displayed as part of the claims processing workflow, thus providing warranty claim adjudicators with the complete data needed for effective claims management.
問題 #104
Which insights does a user get from Order Forecasting for Manufacturing CRMA app?
答案：A
解題說明：
Order Forecasting for Manufacturing provides substantially more than a single predicted quantity or revenue value. The statistical forecasting capability is intended to help planners understand both the expected demand and the uncertainty surrounding that expectation.
Salesforce describes Statistical Order Forecasting as producing predicted order quantity and order revenue values and supporting analysis of forecast accuracy. Salesforce also documents that the statistical forecast output includes a 95% confidence level, enabling planners to understand the likely range around the forecast rather than treating the prediction as an absolute point estimate.
The associated dashboard allows users to review forecast values, analyze trends, evaluate forecast distribution according to dimensions, and measure the accuracy of the predictions. This is particularly valuable for manufacturing planning because uncertainty ranges help operations teams assess safety stock, capacity, and supply requirements.
The functionality is not inherently restricted to a single specified period or exactly three months. Forecast horizons are determined through the forecasting configuration, including period groups and forecast sets.
Therefore, the relevant insights consist of the forecasted value, forecast range or confidence interval, and forecast accuracy.
Study Guide references/topics: Configure and Build - Statistical Order Forecasting; CRM Analytics; Forecast Confidence; Forecast Accuracy; Demand Planning.
問題 #105
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