Which two key performance indicators are available on the Forecast Analysis dashboard in Tableau CRM for Manufacturing?

The correct choice involves key performance indicators that are integral to analyzing and validating forecasts in the manufacturing context. The mean absolute percentage error (MAPE) is a crucial metric used to measure the accuracy of a forecasting method. It provides insight into how close the forecasted values are to the actual values, allowing businesses to assess the reliability of their predictions and make necessary adjustments.

In the context of the Forecast Analysis dashboard within Tableau CRM for Manufacturing, MAPE helps highlight areas where the forecast may not align with actual outcomes, aiding in refining forecasting processes and strategies. This metric allows a manufacturing organization to make data-driven decisions, thereby enhancing operational efficiency and refining sales strategies based on past performance.

The other options may represent important metrics in different contexts or dashboards but are not specifically recognized as key performance indicators within the Forecast Analysis dashboard for manufacturing insights. Therefore, focusing on mean absolute percentage error aligns directly with the primary purpose of the dashboard, which is to evaluate forecast accuracy and performance.