What can affect the accuracy of forecasts in OneStream?

The accuracy of forecasts in OneStream can be influenced by a variety of factors, all of which play significant roles in shaping the reliability of the forecasting process.

Manual data entry errors can introduce inconsistencies and inaccuracies into the dataset, which ultimately distort the forecast model. Even small mistakes can lead to substantially incorrect forecasts, making accurate data entry essential for reliable outputs.

The dimensionality settings used in the model also have a critical impact on forecast accuracy. These settings determine how data is structured and analyzed, and if they are not configured properly, they can lead to erroneous interpretations and results. A model that does not accurately reflect the dimensional needs of a business could yield forecasts that are misaligned with the actual business environment.

Lastly, the historical actuals used as benchmarks are vital for creating future predictions. If the historical data is not representative of typical performance due to anomalies, it could mislead the forecasting process, resulting in inaccurate projections.

Considering these aspects, it is clear that each of these factors independently contributes to the accuracy of forecasts in OneStream, and therefore, recognizing that all these elements collectively influence forecasting is crucial for implementing effective forecasting strategies.