HEDNA-酒店分销数据管理与分析（英文）-2018.1-34页-1mb

HOTEL DISTRIBUTION DATA MANAGEMENT AND ANALYSIS Summary

Executive Summary

This report presents findings from a 2017 survey of 1,053 hoteliers, representing over 40,000 hotels globally. The survey aimed to understand current practices in data collection, storage, and usage within hotel distribution operations. It revealed that while data collection is widespread, the ability to use this data effectively for operational and commercial decision-making is lacking.

Key challenges include data quality, integration from internal and external systems, and limited access to real-time data. The working group identified the need for guidance and change in data analytics practices across the hospitality industry.

Core Content

Purpose of the Study

• To understand global and regional practices in hotel distribution data management.
• To develop best practice recommendations and identify opportunities for data-driven decision-making in distribution, revenue management, and marketing.
• To explore the potential for leveraging data analytics to improve operational efficiency and commercial outcomes.

Key Segments Analyzed

The study focused on three main segments:

• Hotel Chains
• Management Companies
• Independent Hotels

Each segment showed different levels of data usage, availability, and challenges.

Main Findings

Data Collection and Usage

• Chains and Management Companies focus heavily on distribution costs, GDS and OTA fees, and modifications/cancellations.
• Independents also collect key data like guest data, OTA fees, and cancellations, but with limited resources and education.
• OTAs are the most widely used distribution channels, with over a third of all respondents relying on them for the majority of their inventory distribution.
• GDSs are used more by corporate and consortia bookings, and are still significant for Chains and Management Companies.

Data Storage

• Spreadsheets and internal databases are the most commonly used tools for storing distribution data.
• Management Companies and Chains show higher usage of spreadsheets and internal databases.
• Independents have lower usage of third-party data warehouses and BI tools.

Data Challenges

• Data quality / cleanliness is the most cited challenge (41.74% of all respondents).
• Integrating data from external and internal systems is a major concern.
• Independents face challenges in retaining/training skilled data staff and sharing data across departments.
• Management Companies have higher investment in human resources and data analysis tools, leading to better performance in KPIs like Cost of Distribution.

Key Performance Indicators (KPIs)

• Performance-based KPIs (e.g., revenue, bookings, nights) are most commonly used.
• Efficiency-based KPIs (e.g., cost of distribution, look-to-book) are less prioritized.
• Operational performance KPIs (e.g., response times, error rates) are the least used, with only ~30% of Chains and Management Companies tracking response times and ~15% error rates.

Research Methodology

• A 20-part survey was conducted in Q4 2017, distributed via HEDNA Member and Vendor Networks, and social media.
• The survey segmented responses by hotel category: Chains, Management Companies, and Independents.
• Data was analyzed across three key areas: collection, storage, and usage.

Regional Insights

• North America had the highest number of properties surveyed.
• Independents made up 59% of survey responses, reflecting their global and open participation.
• OTAs dominate distribution across all segments, with significant use by Chains (32%), Management Companies (29%), and Independents (37%).

Conclusions and Next Steps

• The survey results indicate a need for better data management and analytics practices.
• Two main approaches are being explored:
  • Enhancing access to and usability of existing data in real-time operational contexts.
  • Promoting collaboration between vendors and hoteliers to establish standardized data formats across distribution channels.
• The working group aims to produce global and regional best practice guidelines to improve data utilization and analytics in the hotel industry.

Working Group Overview

• Founded in 2017, the Hotel Analytics Working Group is part of HEDNA.
• Co-Chairs: David Turnbull (Snapshot) and Matthew Goulden (Triometric).
• Mission:
  1. Increase awareness and adoption of data analytics practices and tools.
  2. Demonstrate how data analytics can be applied to hotel distribution.
  3. Create global and regional recommendations for hotel best practices.

Key Participants

Group	Participants
Chains	Matthew Goulden, Clive Wood, Dave Chestler, Julie Garrett, Michael Klein
Management Companies	Sonja Woodman, Criss Chrestman, Nicole Young, Jodie Gibson
Independents	David Turnbull, Caroline Faries, Casey Davy, Arunn Ramaduss, Rajesh Vohra

Key Recommendations

• Improve data quality and integration across internal and external systems.
• Invest in data infrastructure and tools for better analytics.
• Enhance training and education for data management, especially for Independents.
• Promote standardized data formats and collaboration between hoteliers and vendors to reduce fragmentation.

Final Notes

• The findings were presented at the Winter HEDNA Conference in Austin, Texas, on January 30th, 2018.
• Only 50% of respondents felt their organization was measuring the right KPIs for effective distribution.
• The study highlights the importance of data-driven decision-making in the competitive hospitality landscape.