Apo Demand Planner Quiz

In Demand Planning, you can see the historical data and future forecast for a specific period of time. The correct answer states that you can see 3 years of historical data and 2 years of future forecast. This means that you can analyze and plan based on the past 3 years of data and make projections for the next 2 years. This gives you a comprehensive view of the demand patterns and helps in making informed decisions for inventory management and production planning.

In APO 5.0 Demand Planning, you cannot make a selection at Customer Level 4.

Total Demand is the key figure that is transferred to SNP. This key figure represents the overall demand for a product or service. It includes all the demand from different sources such as customers, sales channels, and distribution centers. By transferring the total demand to SNP, the system can use this information to plan and optimize the supply chain, ensuring that the right amount of products are available at the right time and place to meet customer demand.

Both statistical forecast 1 and statistical forecast 2 can be used when using the Linear Regression Method for generating a baseline. The Linear Regression Method involves using historical data to establish a relationship between the independent variable (statistical forecast) and the dependent variable (actual demand). By using both statistical forecast 1 and statistical forecast 2, the accuracy of the baseline generated through the Linear Regression Method can be improved.

The correct answer is PUD is calculated by adding up the events and agreed selected baseline. This means that PUD is determined by summing together the events and the agreed selected baseline.

The "Use Storage Buckets Profile" serves to show how the forecast is distributed to both parts of the shared week. It allows users to analyze and understand how the forecast is allocated and distributed across different time periods within a week.

The MMS KPI's defined for Demand Planning are Forecast Bias and Forecast Accuracy. These KPI's are used to measure the accuracy and reliability of the demand forecasts. Forecast Bias measures the tendency of the forecasts to consistently overestimate or underestimate the actual demand, while Forecast Accuracy measures the overall accuracy of the forecasts in predicting the actual demand. These KPI's are important in evaluating the performance of the demand planning process and identifying areas for improvement.

The key figure that is not included in the Agreed Unconstrained Demand is Sample Stock. The Agreed Unconstrained Demand refers to the agreed upon forecasted demand for a product without any constraints. It includes factors such as competitor %, Agreed Baseline Forecast, and CPFR (Collaborative Planning, Forecasting, and Replenishment). However, Sample Stock is not a factor that is typically considered when determining the Agreed Unconstrained Demand.

The correct answer is that all of options a, b, and c serve for shared week forecast management. This means that the shared week forecast can be managed manually by CPRF, by uploading CPFR through manipulating the file extracted from APO Event Planning book, or by changing the proportional factors in APO manually. All three options are valid methods for managing the shared week forecast in the system.

The forecast data will be transferred to SNP on Fridays.

The Baseline Generation book includes primary sales for split banded components, primary sales for banded packs-not split, and secondary sales for split banded components. However, it does not include secondary sales for banded packs-not split.

The question is asking how many times data will be transferred to finance in a month. The correct answer is 2, indicating that there will be two instances of data transfer to finance in a month.

The question is asking how many times in a month proportional factors are generated by background jobs. The correct answer is 1, indicating that proportional factors are generated only once in a month by background jobs.

If there is no value in the CPFR key figure, the Agreed Unconstrained Demand would equal the Proposed Unconstrained Demand. This is because the CPFR key figure represents a collaborative forecast between the supplier and the customer. If there is no value in this key figure, it means that there was no agreement or collaboration on the forecasted demand. Therefore, the Agreed Unconstrained Demand would default to the Proposed Unconstrained Demand, which is the forecasted demand suggested by the supplier.

In APO 5.0 Demand Planning, you can make a selection at the packsize level. This means that you can specify the size or quantity of products that are being forecasted. This allows for more accurate forecasting and planning, as different pack sizes may have different demand patterns. By selecting at the packsize level, you can better align your forecasting with the actual demand for each specific packsize, rather than making a general forecast for all pack sizes.

The proportional factor is generated automatically based on data from the past. In this case, the correct answer is 6 months, which means that the system takes into account data from the past 6 months to generate the proportional factor. This time period is likely considered to be an appropriate balance between using enough historical data to make accurate calculations, while also accounting for more recent trends and changes in the data.

The forecast will be transferred as input for financial calculations to the BI-IP system.

The planning book/books used for forecast generation are Baseline Generation and Event Planning Book. These books provide the necessary data and tools for generating accurate forecasts. Baseline Generation helps in creating a baseline forecast based on historical data and other factors. Event Planning Book allows for incorporating specific events or promotions that may impact the forecast. Both books are essential in generating reliable forecasts for effective planning and decision-making.

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The correct answer is that Statistical forecast 1 can be calculated by background jobs. This means that it is possible to use background jobs to calculate Statistical forecast 1. However, it does not imply that Statistical forecast 2 can also be calculated by background jobs or that both forecasts can be calculated this way.

The data view is available for both weekly and monthly time buckets in planning books. This means that users can view and analyze data at both the weekly and monthly levels in their planning books. Quarterly time buckets are not included in the available data view, so users cannot view or analyze data at the quarterly level.

The location book is the planning book where the products are assigned to APO Locations. It is also where the location disaggregation factors are kept or modified. Additionally, the location book assists the forecast release process to SNP.

The event forecast can be uploaded to APO through three different methods. The first method is manually giving the forecast as input by the demand planner. The second method is by uploading the MI template. The third method is by uploading the excel file extracted from the APO Event Planning book after adding the events forecast.

The proposed unconstrained demand includes competitor %, agreed baseline forecast, and CPFR. However, sample stock is not included in the proposed unconstrained demand. Sample stock refers to the inventory that is kept for demonstration or display purposes, and it is not directly related to the demand forecast or planning process. Therefore, it is not considered as a key figure in the proposed unconstrained demand.

The key figure that is transferred to BI-IP is the Agreed Unconstrained Demand. This key figure represents the demand for a product without any constraints or limitations. It is an important figure for forecasting and planning purposes as it provides insights into the potential demand for a product. The Agreed Baseline Forecast, Total Demand, and CPFR are not specifically mentioned as key figures transferred to BI-IP, so they are not the correct answer.