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Overview
This article provides an overview of the Forecast Accuracy Dashboard developed for HotelIQ. It details the metrics used to assess forecast accuracy, the visual representations of data, and how users can interpret the information presented in the dashboard.
Introduction to the Dashboard 0:00
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The Forecast Accuracy Dashboard was created based on user feedback to help hotels understand their forecast accuracy.
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It focuses on identifying areas of success and opportunities for improvement in forecasting.
Mean Absolute Percentage Error (MAPE) 0:23
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The dashboard uses Mean Absolute Percentage Error (MAPE) to represent forecast accuracy.
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A lower MAPE indicates higher accuracy.
Visual Representation of Forecast Accuracy 0:58
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The dashboard displays average absolute percentage error for forecasts 3, 2, and 1 month out.
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Example values:
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3 months out: 33.56%
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2 months out: 23.41%
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1 month out: 18.08%
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Users can drill down into market segments to see trends in accuracy across different segments.
Tabular Data Representation 2:37
The dashboard includes tabular views for detailed data analysis:
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Actual Values Table: Displays actual room values for the selected date range.
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Forecast Comparison Table: Shows how forecasts changed over time for specific months.
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Absolute Error Table: Highlights the difference between actualized values and forecasts.
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Percentage Error Table: Converts absolute errors into percentages for easier interpretation.
Forecast Management Tools 4:49
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Users of the monthly forecast builder will start cataloging historical forecasts from the release date of this dashboard.
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Historical data will accumulate over time.
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Users of the forecast management tool will have immediate access to historical values upon release.
Conclusion 5:13
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The Forecast Accuracy Dashboard is designed to enhance understanding of forecasting accuracy.
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Feedback is encouraged to improve the tool further.