Hospitality Leaders: Are your analytical capabilities ready to support you through the recovery?

by Kelly McGuire and Arun Shastri

The hospitality industry has been hit hard by Covid. But just as surely Spring follows Winter, we will emerge from where we find ourselves today. After this period of extreme volatility, the recovery is likely to be uneven across geographies and customer segments, reinforcing the need for fact and data-based recovery strategies. Many organizations have been forced into layoffs or furloughs, so the analytics functions may not be as strong today as they were last year. However, this begs the question, how was industry doing with the use of analytics for decision making prior to Covid?

The following statements illustrate best-in-class use of analytics in hospitality prior to the pandemic.

· Omni-channel, hyper-personalized communications drive known customers to brand.com, where the visit is personalized based on what is known about the guest and their current interaction. Relevant cross- and up-sell products and services are offered through the booking process, pre-stay and at the property. Post-stay communications are tuned to prior stay behavior and encourage increased spend, loyalty and incremental visits.

· Advanced analytics is used to set pricing across all segments (transient, group, contract) and all products, or product attributes. There is minimal user intervention in pricing, and the pricing is implemented as part of an overall revenue strategy, considering channel, competitive set and market potential.

· Leads are scored using analytical models, so the sales teams can priorities the best opportunities. Corporate contract negotiations are supported by analytical methods that balance longer term relationships against current market conditions. Sales resources are deployed across segments and accounts to maximize productivity and territory coverage. Routine RFPs and small group reservations requests are responded to automatically (using natural language processing), freeing sales resources for more complex negotiations.

· Finally, there is a pervasive test and learn culture. A/B testing and experimentation, across marketing, ecommerce, pricing and product development are part of the arsenal. No changes are made to any programs without validation from test and learn algorithms.

· To support these data-dependent capabilities, companies allow for access and exploration of data with relative ease. Senior executives are committed to asking for data-driven validation before decisions are made. The organization invests in people and technology to support analytics, and there is a focus on developing skills and staying current with innovations in the space.

There is ideal and then there is reality. You can gauge for yourself how mature your organization is. Our industry assessment however is that there is much room for growth. Even leading hospitality companies have not advanced much past foundational capabilities on four critical dimensions, data, analytical capability, organizational buy-in and people.

· Data has always been a challenge for hospitality companies. Most companies have invested in a data warehouse, likely for structured data, and have a plan for guest data acquisition and governance. Critical data governance strategies and plans to implement enterprise data lakes are in very beginning stages even at the most advanced companies.

· In terms of internal analytical capabilities, many organizations have started to use visualization platforms to display business intelligence more dynamically, moving away from static spreadsheets and reporting. Companies are just starting to think about more proactive analytical techniques like forecasting, predictive modeling or optimization. Most advanced analytics like these are accessed through vendor-provided, SaaS solutions such as the revenue management system (RMS). The leading companies have data science capabilities focused on supporting functional areas like marketing, operations, development and revenue management, and are experimenting with incorporating artificial intelligence or machine learning into their modeling efforts.

· When it comes to organizational buy-in, most hospitality companies today at least recognize the value of analytics, have heard how other companies or industries benefit from these programs, and are talking about wanting to become more data-driven. Leading companies have invested in a senior leader with analytics responsibility, but few have a true vision for the role of analytics across the enterprise.

· Analytics solutions are produced in silos and execution and decision making rarely spans departments. Performance management and business intelligence skills sets are common, but only a few leading companies have any advanced modelers or data scientist on staff. In those that do, the data scientists can be relatively isolated, and there is not a lot of focus on growth and development for these roles.

What is holding companies back from achieving State-of-the-Art?

Setting aside the current challenges introduced by the pandemic, there are two main barriers to hospitality achieving transformational analytics capabilities: legacy technology and organizational conflicts.

At the core of the hospitality technology ecosystem is the technology that facilitates booking hotel rooms, such as property management systems (PMS) and central reservation systems (CRS). These systems began to be implemented as early as the 1980s and 1990s. While some companies chose to build them internally, many companies acquired these solutions from external vendors. Since this is mission critical technology, much of the original legacy is still in place, and the rest of the ecosystem evolved around it. This created a “spaghetti jungle mess” (as one executive once described it to us) of bolted on systems, tenuous integrations and jerry-rigged data transfers. These systems place constraints on a company’s ability to collect and use data, and to operationalize analytical results. However, since they are mission critical, it is expensive and risky to replace them. Many have undergone decades of custom configuration and custom development, so newer, more nimble platforms can’t easily replace current functionality. Leading companies have plans to upgrade or replace this legacy technology, but this is an expensive and risky proposition. This problem is complicated by the fact that companies who have grown through acquisition have to rationalize disparate technology systems and data sets before being able to move forward with analytics initiatives.

There are several organizational conflicts that also limit the ability of hospitality organizations to move forward with analytics initiatives. IT departments are consumed with managing “essential systems”, like selling systems, in-room technology and wi-fi. In most cases they are not equipped with either the time or the skills sets to be a strategic partner to analytics efforts, such as data provisioning or analytical systems selections. Lines of business are reluctant to “give up control” of their reporting or analytics resources to any sort of centralized or federated organization, which in turn creates inefficiencies in resource deployment and reinforces barriers between departments. Finally, analytics and technology can be intimidating and confusing for those that aren’t familiar with the techniques. Lack of education internally means that executives struggle to see the value and find it difficult to justify investment.

Data-driven decision making will be increasingly critical through the recovery and into the new normal. Now is the time to start planning on how to overcome the current challenges, and prepare your organization with the data, capabilities, organizational buy-in and people to do more with analytics. In the next article, we will discuss how to overcome these barriers. As this series continues, we will provide advice and best practices for building your analytics prowess.