This article focuses on a few salient points from the Hotel Analytics whitepaper from our Hotel Analytics Working Group. Read the full white paper for more on hotelier attitudes towards data and analytics.
In one of the most far-reaching surveys on the state of data and analytics in hotels, our Hotel Analytics Working Group surveyed 1,053 hoteliers representing over 40,000 hotels and management companies. The sheer number of responses shows that the topic remains very much top-of-mind across the industry.
The objective of the survey was to quantify current practice in data collection, storage, and usage across independents, chains, and management companies, as well as test respondents’ overall data satisfaction. The survey reveals an industry still finding its footing with data. Here are three of the most noteworthy findings around the ongoing opportunities and challenges of data in the hospitality industry.
Quality data and systems integration remain elusive
When looking to unlock commercial value and data, the top two challenges identified by hoteliers were the quality of data and systems integration. These two issues are inextricably linked; one of the greatest challenges of integrating both internal and external systems is the quality of data shared between them.
Hoteliers identify the most significant challenges to data availability in their organizations.
When one system doesn't directly connect with another, data must be routed through an integration; this complicates adoption as it requires time and capital. And when data is routed back and forth from internal systems to external systems, there is data drop off that affects data quality.
Take a single booking as an example. Since a reservation goes through multiple systems, it’s often the case that essential data, such as time of reservation, channel or guest preferences, never makes it through the process intact. The PMS loses essential details, and the data is now problematic to integrate into other sources for further insight. This affects the guest experience and, in the short-term, eliminates opportunities for additional revenue. In the long term, it skews data and makes it less useful for aggregate trend tracking.
Data captured but not always used
Data inundates most hoteliers -- from internal systems, social media platforms, vendors, and third-party channels, there is data overwhelm. In fact, only 3.89% of respondents across categories identified having sufficient data infrastructure as a challenge to data availability.
Yet, it remains much easier to capture data than it is to use it; availability isn't analysis. This is partially exacerbated by the staying power of spreadsheets, as seen in the graphic below.
Survey data showing which tools hoteliers use to store and analyze data.
Without the right tools to analyze multiple data sources quickly and easily, the allure of using data to drive decisions is diminished. While powerful for analyzing ad hoc data, spreadsheets with stale, out-of-date data can make insights less relevant and representative of the current state of business.
This temporal disconnect between a spreadsheet and real-time data is a “perfect storm” for bad decisions made from faulty data, says Ash van der Spuy from Altis:
“The perfect storm is the scenario where a spreadsheet contains both good data from a data warehouse and bad quality data and incorrect formulae input by analysts, which is then used by Management to make decisions. Since some of the data is from the data warehouse, the results are taken with high regard and decisions are made with confidence.”
The first step toward better data usage is understanding the limitations of specific data storage techniques:
A spreadsheet is easy-to-implement but has less robust analytical capabilities and risks inaccuracies through irregular updates of data.
A database is familiar and accessible but doesn’t usually provide a multi-faceted view into business performance.
A standalone data warehouse stores large amounts of data from many sources/databases and offers a deeper relational framework to analyze data. Data warehouses are optimized to perform complex queries across massive data sets that would otherwise max out a database’s resources.
Business intelligence tools layer analytics and visualization capabilities on a given collection of data sources.
Data warehousing and business intelligence tools are the most robust, but also require a relatively sophisticated data practice.
As revealed in the survey, independent hotels and management companies still have room to grow their own analytics capabilities. The distributed nature of analytics at chains underscore some potential blind spots when analytics sits at the property, regional, and departmental level. Also, with some chains handling all analytics from HQ, there may be some capability disparity between the home office and individual properties.
Survey data showing the analytics capabilities across hotel categories.
More collaboration -- and transparency -- needed
Collaboration is necessary to transition from capture-only to a capture-and-analyze approach. Moving to a data-driven decision process has plenty of upside: hoteliers can adapt quickly, in real-time, to changing market dynamics.
A chasm exists between third-party channels provide and hoteliers when it comes to sharing data. The survey found that many channels provide low-to-no data reporting. Hoteliers thus grapple with blind spots in their data and often must extrapolate demand trends based on incomplete historical data.
Data shows low data penetration of other distribution channels with over a third reporting No Access of Metasearch, late Booking or Wholesale platforms.
To resolve this issue, more collaborative relationships can bring the transparency that delivers data-driven results. This is an ongoing challenge, as certain vendor categories either prefer to withhold data or have under-invested in data capabilities of their own.
Hoteliers are also seeking solutions to deliver on the promise of interconnected data sources, requiring focus to shift more on how to collaborate across data sources -- and put available data to work. This complexity requires collaboration, says Luis Segredo of HAPI:
"Data and system complexity in the global hospitality market has undergone exponential growth in recent years. Traditional sources of operational data from property systems like the PMS can be augmented by the vast volume of data from an array of outside sources, such as IoT systems, social activity, and publicly available data points."
Without data transparency and collaboration across technologies and vendors, there’s less power in data captured by hotels.
When vetting vendors, available integrations and data strategy should be a core part of the conversation.
Hoteliers should leverage whatever pressure points available to encourage more data sharing among channel partners -- and to reward those partners that provide at least weekly reports. Anything longer than a week and the data gradually loses some of its power to help hoteliers price more profitably.
At HEDNA, we strive to be an active forum for dialogue and collaboration between the suppliers and users of hotel technology. Such a constructive environment leads to more formal standards in data management from a distribution perspective. To keep this conversation going, we need further engagement between subject matter experts from the vendor and hotel groups. Only once we have a common language and approach can we make begin to unlock the latent commercial value of a hotel’s data.
To see the complete results of the hotel analytics working group’s survey, download the white paper.
Contribute to the discussion with vendors and hoteliers at our next conference in Los Angeles. More info here.