This hospitality organization operates over 5000 hotels globally with over 800,000 guest rooms. The vast majority of the hotel brands are franchised, with only a few physical hotel properties owned directly. The organization focuses on providing the best resources, information, and support for their global network of hotel owners and the best experiences for the customers who visit each of the franchised properties.
Four key objectives are central to this company’s mission:
However, with a franchise business, there is no direct management of individual hotels and no guarantee of data quality in terms of consistency and accuracy. In fact, the considerable logistical challenges of effective data collection across the organization had resulted in low data quality in individual customer records.
Given that nearly all hotels are franchised, the organization has little control over the local staff. Ensuring continuity and proper training of front desk staffing contributes to the struggle of maintaining data quality when gathering customer data in numerous languages for 5000+ hotels globally. The data quality challenge ripples downstream through the organization’s organization, to work through the issues and analyze the data was also a challenge and often required generating huge quantities of reports simply to get a bigger picture. As a result, the organization suffered from inefficient, poorly targeted customer interactions that limited business opportunities and put business unit revenue goals at risk. Further, it was challenging for the organization’s sales teams to acquire new customers without accurate, complete contact information.
The organization’s substantial businessto-business (B2B) team focuses on driving revenue from business travelers from large organizations. The B2B division faced similar issues due to poor data quality, such as incomplete or inconsistent data for airline crew stays. Manually quantifying B2B relationships and calculating key metrics such as sales volume was costly and inefficient. With no processes in place to tune their Master Data Management (MDM) system, no measurement of key metrics, and no data remediation happening for data quality issues, the organization could not even quantify airline activity accurately, a significant part of their B2B business.
Effectively, the organization was unable to leverage the data they collected, leading to both unsatisfactory customer experiences and a lack of business insight.
Addressing customer data challenges is part of the organization’s broader data governance initiative. The organization’s Global Data Quality Leader and his team focused attention on several core goals including:
As their Global DQ Leader commented, “How can you improve data if you don’t know what it is?
As a global business with sensitive customer data, addressing compliance for GDPR, the China Data Law, and the California Consumer Privacy Act (CCPA) is also a key component of the organization’s broader data governance strategy. Connecting customers with the right countries is a critical part of the business process.
The organization turned to Syncsort Trillium’s data quality products to help resolve their customer data challenges. Although the point of data entry was the ideal place to fix the issues, the organization knew it was unreasonable to expect 100% compliance from franchised front desks, or even their call centers. Instead, the organization chose to implement Trillium DQ at the central points of the data collection and aggregation processes, both in batch and real-time. Within those processes, the data quality team has taught Trillium DQ to recognize variances and common quality issues so they can output a consistent customer address. Trillium DQ cleanses, matches, and validates the customer data and sends the verification information to the MDM system for further consideration as a “legitimized” customer record, meaning they can clearly assign it a unique customer ID. From there the customer record goes to the enterprise for use across the business. Everyone now uses the same data, rather than relying on multiple isolated analytics teams and inconsistent data “clean-up” routines.
The organization has also incorporated Trillium DQ into the processing of customer satisfaction surveys. As regulations do not allow sending surveys in certain countries, Trillium DQ identifies customer records by country to establish who the organization can legally contact with survey requests.
For the past 7 years, the organization processes an average of 2 million records per day in real-time and another 2 million per day in batch with Trillium DQ. The Global DQ Leader noted that Trillium DQ “is super reliable. We run both batch and real-time, and it is a workhorse.” For a global enterprise, having reliable, consistent, high-value data quality processing in place for nearly 1.5 billion annual touchpoints establishes trust in the data downstream where the organization sees the benefits.
Hotel companies don’t sell tangible products, they sell experiences. For the organization, good customer experiences establish loyalty and increase the likelihood that customers will continue to grow their use of the organization’s services and recommend the organization to others.
While simple, the ability to quantify activity and report on it accurately has been of great value to the organization. With higher quality data, they are able to quantify $100Ms in sales results, which they could not do before. Analysts spend far less time preparing data and working through so many reports, and they can really see what is happening in the business. The ability to prioritize initiatives, and to obtain better contracts with high-profile customers, has allowed the organization to better target their marketing, achieve better contracts with high profile customers, and build stronger partnerships.
B2B partners such as airlines have been the easiest to quantify because the repeated record volume is so high. The Global DQ Leader indicated, “With any highvolume customer, it’s easier to improve relationships. Similar to buying in bulk, we can leverage cost savings to those clients in exchange for more business. That also opens the door for things like credit card flight miles, vacation packaging, and other partner opportunities.” The data quality team sees this being applied to new efforts that rely on good data quality, such as AI and machine learning initiatives.
Despite the complexities of being a global, franchise business with thousands of hotels globally, multiple languages, and high front desk turnover, the organization has been able to place data quality at strategic points in their operational processes, accompanied by strong data governance controls. As a result, they have driven tangible, visible results to the bottom line and to customer value, and they have achieved cost efficiencies in the process. the organization is ultimately able to deliver on their mission.”