You’ve probably experienced that simply aggregating your product-group forecasts will not give you the same numbers as the total forecast - leading to total forecasted sales that do not match your product-level numbers.
With hierarchical forecasting in place, you can reconcile all forecasts in your forecast hierarchy and improve accuracy for all levels.
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Forecast accuracy can frequently suffer when forecasting at many levels, such as product groups and regions, as volatility tends to increase with granularity.
Simply summing up these bottom-up forecasts would also aggregate the error.
By applying optimal forecast reconciliation, your forecasts are adjusted using a method that weights them based on their historical accuracy,
This improves accuracy at every forecast level.
Many demand planners use only univariate models when forecasting. However, you risk missing the opportunity to discover and incorporate leading indicators into your aggregated forecast.
By taking macroeconomic factors into consideration, you get a stronger sense of which external variables are impacting demand,
How can you identify your key demand drivers? Indicio calculates and ranks each explanatory variable according to its causality to your main variable of interest, using partial correlation and lasso regularization.
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Many demand planning teams rely on sales input to gain insight from the market environment.
However, these teams have experienced that the information provided from sales is often prone to bias.
By using multivariate models in your forecasting, you can apply a data-driven approach to capture and incorporate the market dynamics into your forecasts.
Experience the ease and accuracy of Indicio’s automated forecasting platform firsthand. Click to start a virtual demo today and discover how our cutting-edge tools can streamline your decision-making process.
We are an automated forecasting software that bridges the latest statistical models from academia with the specific leading indicators in an organization's market environment. Helping your organization achieve the highest forecast accuracy.
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