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Text Content

SAS Institute







On-Demand Webinar


EXPLAINABLE AI FOR CONSUMER GOODS AND RETAIL DEMAND FORECASTING

How transparent analytics establish trust and increase forecast adoption for
reliable, efficient demand planning


ABOUT THE WEBINAR

Often the biggest challenge with forecasting is adoption – incorporating
forecasts into decision making.

This is frequently due to a lack of trust and the inability to answer the
question: Why has the forecast changed?

Transparency into the underlying drivers of demand, such as competitive
pressures, promotional tactics and economic effects, boosts trust in the
business and reduces the need for forecast overrides.

In this webinar, SAS forecasting experts explore the importance of
explainability for translating forecasts into useful components.



WHAT YOU'LL LEARN:

 * Practical explainability techniques across time series and machine learning
   models.
 * Key considerations for consuming explainability results and for using data
   efficiently.
 * A forecast explainability framework for consumer goods and retail.

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