KX3-003 Certified RapidResponse Author Level 3 Exam Questions and Answers

Structure II shows BuyerCode connected to Department and Department connected to Manager. This setup supports multiple departments per manager while allowing for each department to be on a specific floor. Since users may want to filter on combinations of BuyerCode, Manager, Department, and Floor, this design accommodates such queries efficiently by structuring the Department as a central entity that relates to the others. In Structure II, Department is linked to BuyerCode and Manager, enabling a query to traverse from BuyerCode to Manager through Department, making it optimal for the desired filters.

ReferencesBest practices for database design suggest structuring your data model to reflect the relationships between entities in a way that supports the expected queries and filters. In Kinaxis RapidResponse, this often means creating a logical structure that minimizes join complexity and optimizes the data model for typical user operations.

Given that the control table setting for OrderPriority.AllocationRule is FairShare and all demands are the same priority, the available supply quantity will be allocated evenly among the demands. The graphic shows there are demands due on Monday, Tuesday, and Wednesday with planned orders due on each day as well. If the total supply on Thursday is not specified in the question, we assume it is enough to meet or exceed the demand. Since all demands have the same priority and the allocation rule is FairShare, the entire supply quantity for Thursday will be evenly distributed. Without the exact supply quantity, the best assumption is that the full quantity needed for the demand due on Wednesday will be allocated.

ReferencesThis explanation is based on the FairShare allocation rule which distributes available supply evenly across all demands when they have the same priority, as per the Kinaxis RapidResponse documentation on supply allocation.

To highlight differences between scenarios, a hidden column that calculates the difference (QuantityDelta) can be created. The actual Quantity column would show the actual value, while the QuantityDelta column would calculate the difference between the baseline scenario and the comparison scenario. Conditional formatting can then be applied to the Quantity column to highlight when the QuantityDelta is not equal to zero, indicating a difference between the scenarios.

ReferencesThe method for comparing scenario data and highlighting differences using conditional formatting is a common practice in Kinaxis RapidResponse, as outlined in the application's user guide and best practices for building worksheets.

To report the date used to convert the calculated field EffectiveUnitPrice, the CONVERTONDATE function is the appropriate one to use. This function converts a measure's value from one date to the value it would have on another date. The $ConversionDate variable (or similar) would typically be used within the worksheet to reference the date to which the conversion is applied.

ReferencesThe Kinaxis RapidResponse documentation on calculated fields and conversion functions explains how the CONVERTONDATE function is used to adjust financial measures based on changes over time, which would apply to fields such as EffectiveUnitPrice.

Given the order policies of MultipleQty: 10, MinimumQty: 15, MultipleUsage: Use, and MinimumUsage: Use, the sizes of the planned orders are determined by rounding up to meet the minimum quantity and then to the nearest multiple of the MultipleQty. Order A needs to meet the demand of 25, so it must at least meet the MinimumQty of 15 and then round up to the nearest multiple of 10, which is 30. Order B, with a demand of 12, will also round up to the minimum quantity of 15 and then to the nearest multiple of 10, which is 20, since the MultipleUsage is "Use." The same logic applies to order C, with an initial demand of 20, it is already at a multiple of 10, so it remains 20.

ReferencesThis answer applies the principles of order quantity rounding based on multiples and minimums as commonly used in supply chain planning and as described in Kinaxis RapidResponse's order policy settings.

References:

• The Kinaxis RapidResponse documentation and training materials provide guidelines on how to apply order policies to determine the sizes of planned orders123.

To provide a worksheet based on the CRPOperation table that reports the destination location and to view all valid work centers that feed a given stock location:

• Statement B:Create a reference field on the CRPOperation table to the Location table. This approach establishes a direct relationship between operations and their respective locations, enabling efficient reporting and querying capabilities for the secondary requirement of viewing work centers related to a stock location.

Creating a reference field on the CRPOperation table to the Location table (B) is the most efficient way to report destination location while allowing visibility of all valid work centers that feed a given stock location.

References:

• Kinaxis RapidResponse Author Level 3 training emphasizes the importance of efficient data modeling and reference creation for performance optimization1.
• The Kinaxis RapidResponse documentation suggests that creating direct references between tables ensures better performance than creating additional lookup tables or worksheets23.

When defining a new table in the TRM namespace that requires a key reference to a table in another namespace (in this case, the Mfg namespace), you must add the namespace containing the referenced table as a dependency to the namespace where the new table will be created. By doing this, the new namespace acknowledges the existence of the other namespace and its tables, allowing for proper reference linking. This is why the correct action to take is to add the Mfg namespace as a dependency for the TRM namespace.

ReferencesThis information is in line with the principles of data modeling in Kinaxis RapidResponse, where namespaces serve as containers for data model components such as tables and fields, and dependencies between namespaces must be defined to create cross-references between tables located in different namespaces.

References:

• Kinaxis RapidResponse Author Level 3 training materials emphasize the importance of setting dependencies between namespaces to ensure proper reference and functionality within the data model12.
• The Kinaxis documentation on data modeling and table creation within RapidResponse provides guidelines on how to manage namespaces and their dependencies34.

To enable customers to view only their independent demands within RapidResponse, profile variables and worksheet filters are used. The profile variable 'CustomerView' will be set to match the customer name to the user's group name. In the worksheet filter, theOrder.Customer.IDis the correct field to match against the profile variable because user IDs and customer IDs are more likely to be used as unique identifiers in system configurations, rather than customer names which could potentially have duplicates or variations.

Thus, when customers log in, the worksheet filter will apply, and they will only see the independent demands that correspond to their own customer ID, ensuring data visibility is restricted appropriately.

References:

• Kinaxis RapidResponse documentation on user group configuration and data access control.
• Kinaxis training materials on creating profile variables and configuring worksheet filters for personalized data views.

ReferencesThe information is based on the best practices for creating filters and profile variables within RapidResponse as indicated in the training materials and documentation provided by Kinaxis123.

When forecasts are spread into smaller time intervals using a spreading profile, the quantities are distributed according to the specified proportions in the profile. The graphic indicates that the profile points are 20, 20, 25, and 35 for each of the four weeks, respectively. To spread the monthly forecast of 500 units into weekly intervals, you multiply each proportion by the monthly forecast and divide by the sum of the profile points. So, (20/100) * 500 for the first two weeks, (25/100) * 500 for the third week, and (35/100) * 500 for the fourth week, which results in the weekly forecasts of 100, 100, 125, and 175, respectively.

ReferencesThe calculation uses basic arithmetic based on the principles of proportionally spreading a total quantity across a defined profile, as described in the Kinaxis RapidResponse demand planning documentation.

In the WhereConsumed table, the PegPart represents the item driving the need for the component. In this case, the independent demand for AAA requires components BBB and DDD to be produced. The DriverPart is the direct parent in the Bill of Material (BOM) for DDD, which is BBB. The NeedQuantity is calculated by multiplying the demand for AAA by the quantity per of BBB (100 units * 4) and then by the quantity per of DDD (400 units * 4), resulting in a NeedQuantity of 1600 for DDD.

ReferencesThis answer follows the logic of BOM explosion and the principles of MRP (Material Requirements Planning) that can be found in the Kinaxis RapidResponse documentation, which outlines how to calculate the required quantities of each item in the BOM based on the independent demand.

The code block IV is correctly using the script execution pattern in RapidResponse. It first gets the script usingrapidResponse.scripts.get()method with the correct parameters for the name and scope, and then calls the script with.call()method, passing the necessary scenario argument. This is how you would invoke another script from within a script.

ReferencesThe use ofrapidResponse.scripts.get()andcall()methods is standard practice in Kinaxis RapidResponse for executing one script from within another, as detailed in the Kinaxis RapidResponse scripting documentation.

A. The DeliveryRoutes being a Set data type indicates that there can be multiple Delivery Routes referencing a carrier, allowing for one-to-many relationships between a carrier and delivery routes.

C. The Shipments being a Set data type as well indicates that multiple shipments can reference a single carrier, also suggesting a one-to-many relationship.

D. The DefaultTransportationMode being a Reference data type allows for the possibility that several carriers can share the same transportation mode, as references do not enforce uniqueness.

B is not correct because the TransitCalendar being a Reference data type indicates a one-to-one relationship; each carrier can reference only one Transit Calendar. E is also incorrect because the Sources field being a Set data type implies that a carrier can be associated with multiple sources.

References:

• Kinaxis RapidResponse documentation on data modeling and table relationships.
• Kinaxis learning resources on understanding data types and their implications on table relationships.

The migration of the Supplier.Id filter to the secondary filter expression box allows for enabling caching because it is a user-specific filter. Moving user-specific or session-specific expressions to the secondary filter ensures that the primary filter canbe cached independently of user sessions. This way, the overall data set can be cached, and the user-specific filtering is applied afterward, improving performance.

References:

• Kinaxis RapidResponse documentation on primary and secondary worksheet filters.
• Kinaxis support resources on caching strategies and performance improvements for worksheets.

In the context of creating a metric worksheet for calculating the number of late orders, you want to group by DueDate to consolidate orders that are due on the same day, and then sum the Count for each of these groups to get the total number of late orders per day. Therefore, DueDate should be the grouping column, and Count should use the Sum function to add up all instances of late orders for each DueDate.

References:

• Kinaxis RapidResponse documentation on creating metric worksheets.
• Kinaxis learning resources on the use of expressions and functions for grouping and aggregation in worksheets.

This setup allows for flexible data visibility based on user permissions. By creating a profile variable that contains the allowed countries for each user, you can then apply a filter expression to the worksheet that evaluates this variable. If a user is permitted to see all countries (indicated by an asterisk '*'), the expression returns TRUE, otherwise, it checks if the demand's country is in the user's permitted list.

References:

• Kinaxis RapidResponse documentation on configuring data visibility through profile variables and worksheet filters.
• Kinaxis training materials on setting up user permissions and responsibility definitions.