How to Understand & Utilize Different Types of Data in Hotel Systems

Does this situation sound familiar? You walk into a meeting with the entire operational team and every department – from Finance to Sales to Revenue Management to Operations – has different figures that they’ve extracted from the system(s) they use for monitoring their progress; in some cases, the same source systems give each department different versions of the truth, in different reports. As I’m sure you’ve experienced many times before, this situation leaves you wondering which department has the most accurate data, resulting in confusion and uncertainty – and makes it almost impossible to make accurate strategic decisions to benefit the profitability of your property.

If this is something that you experience at your property, don’t worry… you’re not alone and I’m here to help.

In my 22 years of providing hotels with in-depth property analytics and decision support solutions, I’ve lost count of the number of times I meet frustrated hoteliers who have spent hours trying to figure out why their inter-departmental statistics don’t match and which data to trust when they are making crucial operational decisions.

Over time, these questions haven’t gotten any easier to answer; on the contrary, they have become even more complicated with the advent of AI-powered analytics solutions now offered in the hospitality industry.

You’re probably thinking: “But seriously, how can it be so hard to get consistent data across all your internal departments? After all, the number of room nights that were booked and stayed is a fixed figure, so how can our numbers be so inconsistent?!”

Unfortunately, the answer to this age-old question (and one that many don’t like to hear) is that it’s not always a bad thing to have inconsistent or differing reports; in fact, it can actually help your business, if applied properly.

Inconsistent data isn’t always a problem…

Even if you have the most accurate data in your systems, the way that the data is being aggregated (compiled) and the selected attributes (variables) of the data that your system is analyzing can often result in opposing insights and inconsistent versions of the truth; as such, there is no such thing as the “best” or “most accurate” data.

In reality, having different numbers across different departments can give you a more holistic view of your property, which can lead to better decision-making, IF you understand what the differing data means and where to apply each data set for best results.

Let’s get techy for a moment to explain why your data is often not consistent across all departments…
 

Data Collection

There are many ways data can be tallied and reported but the three most common ways of collecting data are:

1. Streaming Operational Data

Reservation updates moving from an OTA to CRS to PMS is an example of streaming operational data, as multiple transactional systems (the OTA, CRS and PMS) are communicating with each other. Ideally, this transactional data would be updated in near real-time enabling you to take immediate action (in this case, book, modify or cancel a reservation if necessary).

This type of data is constantly changing and it communicates what’s happening now and what’s going to happen next (rather than what happened in the past); as such, streaming operational data is crucial data for a Revenue Manager to use in pricing and booking channel distribution decision-making.

2. Aggregated Operational Data

Not all data is streamed in near to real-time; aggregated operational data is not as current (pun intended!), as it is often aggregated on a daily or weekly basis and is designed to enable tactical decision-making by hotel teams.

A good example of the use of this type of data is the dashboards and reports that General Managers review with their teams on a daily or weekly basis to keep track of business performance. While this data is partially curated (reviewed) as it is aggregated after the night audit, it hasn’t undergone all the necessary audits, corrections and adjustments that financial reporting does. This brings us to…

3. Curated Financial Data

Financial data is the most regulated and controlled type of data, as there are procedures, standards and laws that dictate how financial statements are prepared. Financial data tends to focus on what happened in the past and is often adjusted to meet reporting requirements.

As such, financial data can often differ significantly from operational data; in fact, something as seemingly inconsequential as an out-of-order (OOO) room can change the stats drastically. Let’s look at an example…If a 100-room hotel has 5 rooms OOO for a day and the rest of the hotel is sold out, stats produced from operational data alone will show 100% occupancy while financial reporting standards dictate that the occupancy for that day must be reported as 95% occupancy.

Similarly, when it comes to revenues, you can have multiple variations based on net room revenue, package elements, taxes, agency mark-up, collected date vs. stay date – the list goes on and on. Neither of the stats are wrong; they’re just different data that is serving different purposes for different people within different departments.

At the same time, it’s important to note that just because data is tallied in one way or the other, it doesn’t mean that all your reporting that comes from it must be different. You can adjust your reports to create a more consistent view of the data for the type of decision-making you want to do.

Continuing with the OOO rooms example (above), you may choose to ignore OOO rooms in operational reporting (particularly if you’re trying to make broader strategic decisions rather than focusing on a single day for tactical decisions) and only manually change the available rooms when you know you’ll have OOO rooms for 6 months or more. The key is to be cognizant of such adjustments and why you’re making them.

Data Dimensions

Another key factor that can lead to multiple versions of the truth is the lens with which you’re looking at the data. Any data will have multiple attributes or dimensions that help you understand the story around the data. In a hotel booking, you receive your guests’ details, stay dates, room rate, booking channel, room type, preferences, and many other details associated with the reservation. When you collect similar data and start analyzing it using these dimensions, patterns and trends become easily evident. You can even create multi-dimensional report views to optimize your business performance.

What can sometimes lead to confusion is when you’re trying to answer the same question using different dimensions. For example, let’s imagine that your team wants to understand the performance of an OTA. Revenue pulls the production for the OTA’s negotiated rate codes, Sales pulls production from the agency profiles and Distribution looks at the booking channel code; they all come back with three slightly different sets of figures.

Here are some possible reasons why...

1. The OTA is probably selling BAR rates for high occupancy nights when its negotiated rates are closed out.
2. It has multiple profiles for its different office locations and the sales analyst missed one.
3. The CRS doesn’t process all reservations for that OTA through the direct-connect. Some of those bookings are flowing in through the generic ‘IDS’ code.

The point to note here is that each approach has its merits. Accordingly, each discipline is looking at the data from the perspective of how they can best impact the situation; however, teams often can’t see that and get caught up in trying to discredit each other’s figures rather than collaborating and approaching the problem in a collaborative, united way, looking at the data from all directions.

Of course, it’s not reasonable to expect a team to manually stay on top of so many variables or even be able to identify them in a timely manner. To be effective at interdepartmental collaboration and managing disparate data reports, your business needs an automated solution that offers data aggregation, data quality management and multi-dimensional views of the data so that everyone on your team, across all of the departments, can easily understand the different perspectives and take collaborative action.

Collaboration between departments also brings other very important benefits for your property or company. By uniting previously siloed departments, you can facilitate more accurate inter-departmental, data-driven decision making and identification of new revenue opportunities, while also identifying any potential issues that can be addressed to boost profitability.

Get collaborating today to effectively leverage all the different types of data and analytics that your business has access to – and boost bookings and revenue at the same time.