Interview with Gustavo Cueva, Data & Analytics Manager of Palladium Hotel Group

Palladium Hotels Group bets on data quality and a vision of personalized experiences

We took advantage of the Fitur fair to gain insights from different perspectives on the challenges, achievements, and trends that are shaping the tourism sector in the complex post-COVID recovery scenario.

Gustavo Cueva, in his role as Data & Analytics Manager at Palladium Hotel Group, has been noted for implementing advanced data analysis and machine learning techniques to optimize decision-making and operational efficiency of the hotel group. With solid previous experience at companies like Oney and EY, and as an educator at Esade and The Valley Digital Business School, Gustavo has significantly contributed to the development and implementation of data strategies, improving trend prediction and customer behavior in the tourism sector.

In this interview, we see from the specific perspective of Data, a concept that is highly relevant within business strategies in the sector. Therefore, Gustavo has explained the challenges faced by Palladium Hotel Group, a pro-digital and innovative chain that bets on machine learning and personalized experiences.

Xavier López, CEO of EISI SOFT, and Gustavo Cueva, Data & Analytics Manager at Palladium Hotel Group

Within the framework of 2023, what goals have you set and achieved?

For 2023, we have focused on two lines. The first has been to stabilize everything we had already implemented in previous years, in terms of standardization, quality, and data homogenization. In the end, what we seek is for everyone within the departments of Palladium Hotel Group to speak the same language. What we don't want is to have information silos where everyone goes separately. What we have been building during 2023 is stabilizing this part, ensuring that everyone, for example, in a committee, sees the same data and knows what we are talking about and which KPI we are going to make decisions on.

I am very proud that this year this project could really start to materialize, and we are already seeing the green shoots after many years of work, which has been very satisfying.

The other line we have worked on has been to start using success cases where we have used machine learning. For example, we have already carried out a real pilot, where we started casting a revenue that should have been done a long time ago, but we are starting to do it now by incorporating intelligence, based on data, with what we know and the historical data from previous years. Today we are starting to use it, and we will continue in this line in 2024.

I have always considered Palladium as one of those pro-digital and innovative hotel companies, which has always been very daring, not only in product but also in digital strategy and technology application.

You mentioned that one of your objectives was to homogenize and ensure data quality. What has been the strategy within the organization to guarantee something as valuable as quality data?

Well, for data quality, in the end, it's an ongoing issue; there are always new things, and you always have to stay focused on it.

What have we done at Palladium? We have started a standardization process to make the data homogeneous, meaning that the data we see on different platforms can be worked on, processed, and errors detected to correct them at the source.

So, we have implemented audits to detect bad practices at the source, such as a receptionist entering a reservation. Additionally, we have introduced alerts to notify us and detect issues in time, preventing long-term errors, as this penalizes you and results in incorrect data. Essentially, to obtain quality data, we have conducted audits to see which data is correct or not, automated all processes and controls to receive direct alerts, and ultimately see this reflected in a dashboard, obtaining a final visualization. When you have bad data, it is reflected on a dashboard. We are reaching a point where business users now give us alerts to correct issues. It's as simple as a user calling and saying, "Hey, this data is wrong." When you start looking, you find other types of errors that can occur.

In the end, it's continuous evolution and never letting it go because it never ends. It's the evolution and standardization of continuous processes. And above all, creating a technological map of where we are extracting information, what type of information we want to display, and where the destination is. I believe this is fundamental to ensuring you are showing quality data.

At this edition of Fitur, there is a lot of talk about immersive management models and new technologies for managing and marketing tourist establishments. What practical cases are you implementing in your organization?

We must start by ensuring data quality, as I mentioned before. Without this, the predictions we make will be poor. An example is the forecast mentioned earlier, which seems simple but involves a lot of work behind the scenes in data cleaning and quality. Today we are starting to do it routinely, and now we have a timeline where, in the coming years, we want to use GPTI, which we have at our disposal today. We want to start using it as a tool to manage Palladium better.

We are already mixing the world of data quality with the world of artificial intelligence. Today, we apply what is called a golden record, the unification of a client, which is complicated to do, identifying a repeat client when you have 20 records of the same client that you don't know if they correspond to the same person. We already have some simple and more advanced processes where we use technologies like machine learning to unify and identify clients who are likely the same.

You started 2024 with achieved goals. What objectives should the sector set for the next two years?

From my point of view, the first thing is to stabilize data quality. For me, it's very important, as you can see, to continue increasing the application of machine learning in all business areas. Above all, we need to use these tools we have today to focus them on the customer. Our next level is to impact the customer, to be able to perform descriptive processes analyzing the past of what we already have. The next step is to use this to know our client and offer an unforgettable experience within the hotel, to create clusters to categorize a client and provide a unique experience. We need to follow that line to personalize the client and the experience in a hotel.