Real time data streams for hospitality

May 17, 2019


Data needs and system complexity in hospitality are undergoing exponential growth. Traditional sources of data (PMS, CRS, POS and S&C) are being supplemented by data from web site interactions, online booking activity, IoT and social media posts.

This data is collected and stored in various systems of record. To connect with each other, vendors have developed interfaces that exchange data between systems, with each interaction typically triggered by some kind of an update such as a new reservation gets created, room is assigned, guest checks in/out or a room charge is posted.

In many cases the same data ends up exchanged, stored and managed in different systems of record. For example, profile records of a guest that has stayed in multiple hotels will exist simultaneously in each property’s PMS database, in the central reservation system, in the OTA database, in an enterprise data warehouse and in a variety of guest service applications.

So what we have is dozens of systems talking to each other in a point to point fashion exchanging the same kinds of information that each system tries to control. As an organization’s data needs grow and system complexity is increased and when it needs to scale out and think about distributed infrastructures, it ends up with a web of unreliable and unmanageable data connections.

A tangled web of point to point connections

What is data? Is it a series of records, such as profiles, reservations, inventory, etc.? Yes, but more importantly it is a stream of events. Events that are not only able to tell us about the current state of affairs, but also the sequence, pace and customer interactions that have been leading up to the current state. Events are important facts that create the knowledge about one’s customers and one’s business.

The HAPI approach is to put hospitality’s data on a streaming platform that would facilitate real time sharing of events between systems, services, and applications. Guest looks for a room, makes a reservation, changes it, checks in, changes rooms, checks outs. Does only the PMS system care about it? What about applications for guest service, digital marketing, revenue management, loyalty, CRM.

Normalized data streams

The HAPI platform acts as a central hub for hospitality data streams. Applications that integrate don’t need to be concerned with the details of the original data source or specific message formats of contributing systems (OXI, HTNG, etc.). As data enters the platform, it gets normalized to a canonical format representing specific business entities and events. The platform acts as a buffer between systems — the publisher of data doesn’t need to be concerned with the various systems that will eventually consume and load the data. This means consumers of data are fully decoupled from the source.

Real-time streaming to CRM

Several specific use cases come to mind where HAPI is particularly well suited.

One of them is Real Time Event Notifications or data streaming. This is best suited for real time applications and use cases where services are decoupled from user actions. For example, the need to send a confirmation email when a reservation is created, or an alert to housekeeping to clean the room, or a welcome message to the guest via an online app. These services have traditionally relied on notification-based interfaces via messaging systems that are difficult to manage and scale, and implementing them via calls to a REST API layer is impractical. The HAPI platform enables real-time applications built to react to, process, or transform streams. This is the natural evolution of the world of Enterprise Messaging which focused on single message delivery.

Another use case is Data Integration, or the need to move data between systems. For example, feeding and consolidating data from PMS and POS into an enterprise data warehouse. Traditionally this has been handled by ETL tools, but this approach lacks real time, does not scale and becomes messy with growing sets of data sources are integration complexity. The HAPI platform captures events or data changes in real time from source systems and processes them mid-stream as it feeds data to consuming systems such as relational databases, key-value stores, Hadoop, or a data warehouse. As this is happening in near real time, systems are always up to date. Due to the persistent nature of event data storage in HAPI as the streams flow through the platform, when new systems are added to the flows they can be quickly re-populated with past events, facilitating historical analytics as opposed to just capturing the current state.

There are more use cases that are opening up with the new and open technologies that lie at the heart of HAPI. As the ecosystem grows, so does the potential for innovation that goes beyond the solving of traditional integration challenges that have faced the hospitality industry. It’s time to join the charge and get HAPI!

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