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1. You want to be able to filter your data by the planner code attribute on the item. Where can you go to do this?

A) Configure Planning Analytics > Levels and Attributes tab
B) Enable planner code on Planning Analytics page.
C) Configure Planning Analytics > Measure Catalog
D) The process "Add Levels and Attributes" must be run to associate new attributes.
E) The process "Associate Measure Catalog Attributes" must be run to associate new attributes.

2. Demand is high leading up to the Christmas holiday every year between Dec 20 and Dec 24 and not on Christmas day (Dec 25). Your customer has two demand plans. Describe the steps to model Christmas causal factor in both demand plans.

A) Open a demand plan and edit Christmas casual factor measure. Place value of one from Dec 20 to Dec
24 and zero for non-impacted days including Dec 25. Causal factor changes are plan specific, so repeat the steps in the 2nd demand plan.
B) Open a demand plan and add a new customer specific Christmas causal factor. Create a table displaying the causal factor measure and relevant time period and modify as required. Causal factor changes in this demand plan will reflect in the 2nd demand plan also.
C) Use FBDI to create a new customer specific Christmas causal factor. Place value of 1 from Dec 20 to Dec 34. Causal factor upload to one demand plan will reflect in the 2nd demand plan also.
D) Use FBDI to create a new customer specific Christmas causal factor. Place value of 1 from Dec 20 to Dec 24. Causal factor changes are plan specific, so repeat the steps in the 2nd demand plan.
E) Open a demand plan and add a new customer specific Christmas causal factor. Create a table displaying the causal factor measure and relevant time period and modify as required. Causal factor changes are plan specific, so repeat the steps in the 2nd demand plan.
F) Open a demand plan and edit Christmas casual factor measure. Place value of one from Dec 20 to Dec
24 and zero for non-impacted days including Dec 25. Causal factor changes in this demand plan will reflect in the 2nd demand plan also.

3. During Implementation of Planning Central, your client has discovered that no Material Planners have been defined in Manage Material Planners in Planning Central.
In this situation, which three statements are true? (Choose three.)

A) Planned Orders will not release successfully.
B) Collect Planning Data has not been run for Material Planners.
C) Your client has not been assigned the Material Planner role.
D) The Planner field will be null for all items.
E) You have not been assigned the Materials Planner role.

4. A supply plan has just been run that contains a configured item. You notice that the sourcing rules of the base model were used instead of sourcing rules for the configured item. Why did this happen?

A) The sourcing rules of the base model overrode the sourcing rules of the configured item.
B) No planning percentages were defined at the operation level within the work definition.
C) It is not possible to create sourcing rules for the configured item; all configured items always use the same sourcing rules as the base model.
D) No sourcing rules have been defined for the configured item.
E) The sourcing rules of the base model had a priority of 1, while the sourcing rules of the configured item had a priority of 2.

5. You analyzed your customer's shipment history data at item and organization level. You found that the customer has many new products with limited history.
Does Planning Central support forecasting products with limited history, and what is this process called?

A) Yes, Planning Central supports the Holt Exponential Smoothing forecasting method used for newly introduced products.
B) No, Planning Central does not support the Croston Method for Sparse Demand forecasting method.
C) Yes, Planning Central supports the Regression for Sparse Demand forecasting method, typically used for new products.
D) No, Planning Central does not support the Regression for Sparse Demand forecasting method.
E) No, Planning Central does not support the Holt Exponential Smoothing forecasting method.

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