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Refining Forecast Accuracy with APE
Refining Forecast Accuracy with APE

This article introduces the Absolute Percentage Error (APE) in FLYR for Hospitality, explaining its role in forecast accuracy evaluation.

Ashley Dehertogh avatar
Written by Ashley Dehertogh
Updated over a week ago

In the hospitality industry, where strategic planning and operational efficiency hinge on the accuracy of forecasts, FLYR for Hospitality is dedicated to offering the most advanced tools for our users. We're proud to incorporate Absolute Percentage Error (APE) into our forecasting toolkit πŸ› οΈ, enhancing your ability to assess and refine forecast accuracy at the property-level.

Introducing Absolute Percentage Error (APE)

Absolute Percentage Error is a crucial metric for evaluating the precision of forecasts by comparing the actual outcomes with predicted values. By offering a percentage-based measure of accuracy, APE simplifies the assessment of forecast performance for entire stay months, aligning perfectly with the monthly forecasting workflow prevalent in the industry.

Dual Forecasts at FLYR for Hospitality: System and User Forecasts

FLYR for Hospitality provides two types of forecasts: System Forecasts, which leverage our data science intelligence 🧠 for automated predictions, and User Forecasts, derived from user inputs within the Planning product. With the introduction of APE, we're excited to offer the capability to critique the accuracy of these forecasts both individually and in comparison with each other, empowering users with unparalleled insight into their forecasting strategies.

Getting Started with APE

FLYR for Hospitality has developed two specialized dashboards to facilitate in-depth analysis at the property level for an individual month, focusing on key performance indicators: Occupancy, ADR (Average Daily Rate), and Revenue. These dashboards enable users to leverage APE for comprehensive forecast analysis:

  • Property-Level System & User Forecast Accuracy Dashboard: View user-generated and system forecasts alongside each other, observing their evolution to provide a comprehensive view of forecast performance. This dashboard is your go-to for evaluating how user inputs compare to our data science-driven predictions, allowing for a direct comparison of forecasting accuracy.

  • Property-Level User Forecasting Assessment: This dashboard is specifically designed to assess the user forecast, offering insights into the overall forecast evolution and the performance of each segment within the month. It's an invaluable tool for users looking to dive deep into their own forecasting process, from the broader monthly overview down to the segment-level analysis.

Both dashboards are crafted to support detailed analyses at the property level for an individual month across each KPI πŸ“Š, enabling users to make informed decisions and strategic adjustments based on accurate, data-driven insights.

Support and Resources

To help you maximize the benefits of APE in your forecasting efforts, FLYR for Hospitality provides a comprehensive suite of support resources. From an overview on how we forecast to in-depth tutorial that guides you through each dashboard to FAQs designed to answer your pressing questions, we're committed to ensuring you have the knowledge and tools needed to effectively utilize APE.

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