Forecasting

Hi SamJohnson ,

Thank you for reaching out to the Microsoft Community Forum.

The model is a cyclical pattern caused by a one-time event the large store purchase and is incorrectly projecting similar spikes every 4 years due to the seasonality settings.

You can address this without compromising the integrity of your data.

1. Since the seasonality is set to 4 points likely auto-detected, try manually settings it to a value that reflects your actual business cycle like yearly or quarterly rather than letting the model infer it from the spike.

2. Flag the expansion year as an outlier and exclude it from the forecast input or adjust the sales data for that year to reflect normalized growth like average growth rate from surrounding years.

Note: This can be done by creating a separate column with adjusted values and using that for forecasting.

3. Split your data into Organic growth (excluding expansion years) and Expansion impact (separate analysis)

Note: Forecast only the organic growth and then layer in expected expansion effects manually if needed.

4. Switch to DAX for Custom Forecasting. By using DAX you can build a more flexible model that detects and adjusts for structural breaks. Applies custom smoothing or regression techniques.

I hope this information helps. Please do let us know if you have any further queries.

Regards,

Dinesh