How to Democratize Data and Remove Functional Silos

Written by Vineeth Purushothaman, Regional Director, Commercial Planning & Distribution EMEA at Wyndham Hotels & Resorts & Ana Cachon, Sales Manager – Distribution at NH Hotel Group
Edited by Laurie Pumper, Communication Director, HEDNA

Data is everywhere. It is powerful. It is overwhelming.

Different people interpret it. We focus on data within our areas of interest or functions. Some people love data and others don’t. Some use it well while others don’t.

Are we cursed with this paradox of perceived power in data versus ineffective use? Is there a way to address it and make data more democratic? Is it realistic to strive for everyone to use the data? And what does this mean for a hotel/hotel company?

In this article, we look at how you can create an effective approach to data management.
We can democratize data by making it more accessible. This will allow you to work to achieve the high-level vision you are aiming for.

The question of why data is being requested should be driven by the organization’s vision at a high level:

It may be about improving the customer experience at the hotel.
It may be about targeting the right type of bookings to the right channels.
Perhaps it’s about encouraging loyalty program members to rebook, delivering a value proposition.

This clarity is essential when you set out on this journey.

The five-point approach that follows can help us think through a data management strategy. The action plan to achieve the objectives must be established in the organization.

Some of these steps can be taken in parallel. It is essential to establish clear objectives that are linked to the vision of the organization.

Establishing a Business Intelligence (BI) department
Specialized people are needed to professionalize data use

It will be much easier and more efficient to “translate” the data according to the needs of each department. In this way, we can provide the tools to everyone in the company. The use of data is important — but must be accompanied by interpretation of the data. Otherwise a wrong interpretation could lead to wrong decisions. In the hotel industry, different departments are involved in the decision making process.

Each department works on its own action plan: Marketing, Sales, Distribution, Revenue, Operations, F&B, etc. Each department will need specific data to help them make decisions.

The BI team will play an important role in data segmentation: data accuracy and interpretation.

1. Establish clear objectives for data management — set a data management strategy.

Establish clear objectives that relate to the organization’s vision for data management. These objectives will help provide all stakeholders with a common baseline to start with — and get their buy-in.

Ensure that you have clear answers for these questions:

Why is it important to our hotel/s?
What can improve guest service?
What are the strengths and weaknesses of our hotel?
What are the different ways in which it will increase hotel revenue?
Which channels are the most profitable?
How can it help reduce costs? Can we afford not to do this?

2. Identify all sources of data in your hotel

Start by identifying as many data sources as possible.
All stakeholders in the process must be involved. This will make the data management strategy more efficient. And we will be able to better understand the impact. It is very common, especially in operations, to ignore the use of available data. A clear example is food and beverage, where service elements are more relevant than data.

Where is your guest data and where is it being captured? Is it in a Property Management System (PMS) like Opera? Or also in a Customer Relationship Management (CRM) system like Salesforce? Or is it in an ERP system that connects to the PMS? Or do you need to look elsewhere?

Regardless of where the data is stored, the CRM will provide great knowledge of the customers. This will allow us to provide a personalized service. The whole team must take part in the data process, as each one will provide information from their area. Every detail we have of the “customer experience” process should be recorded. And it should be accessible to everyone. Over time, this will be a great database.

This information should be cross-referenced with the data generally provided by PMSs: Information about point of sale, when and which channel, lead time, rate confirmed, etc.

Again, all teams should be involved and all this information should be visible to the whole team. If we follow this model, it will be easier to work on an action plan together.

Traditionally, guest data typically included name, contact details and high-level demographic information. We now have so much more information available from a far wider range of sources. Let’s take a closer look as to what some of them could be.

In the data world, all data is classified into:

First-party data (gathered from hotel guests) — from CRMs, PMSs, Website sign-ups, etc.
Second-party data (gathered from partnerships) — from airlines, credit card companies
Third-party data (purchased data)

Where you look for data should depend on your objectives. The challenge and opportunity for hotels is the rich sources of primary data.

Consider the examples below; they can come from many functions and teams, both commercial and operational.

But because a typical hotel or a hotel chain operates as different functions (and needs to for practical and logistical reasons), it is quite challenging to bring these overlapping strands together.

Brand Website — subscriber lists, cookies, booking patterns.
Distribution channels — information like source markets, booking patterns, channel costs.
Social media channels — followers, competition participants, evangelists, bookers.
Restaurant point-of-sale systems analyze customer spending patterns.
Restaurant diners — collecting business cards or similar information through competitions.
Spa — information on guest usage from both residents and non-residents.
Events at hotel — events where individual participation is needed.
Reservation teams — from all enquiries, individuals and groups. This may include call centre logs.
Wi-Fi — from free Wi-Fi access to visitors using the dining areas in exchange for an email address.
Reception — check-in and check-out data.
Concierge — typical local reservations made before arrival and after arrival.
Trade Shows — visitors at a stand at a travel trade fair like ITB or Confex.
Sales teams — from account management activities.

This list can go on… but you get the idea. We have data everywhere, from all functions, and there are lots of overlaps.

How and where can you get started? A good place to start is reviewing the current data management process.

3. Understand the current data management process

Take a good look at where you are with data management.

We need to start by answering the following questions in as much detail as possible.
Also identify the processes and tools in play as they are an important part of this review.

Where is all this data stored?
How many systems are in play?
Is there a central data warehouse?
How much data are going into a data warehouse?
Which data are not?
And how much of the data that are getting to the data warehouse are being used?
What are the different outputs and formats?
Who consumes it?
What do they do with it once consumed?
What level of engagement and inputs were sought in developing these data outputs?

You may want to add more questions to the mix based on your needs. The collection and grouping of the answers will allow us to move on to the next steps on the action plan. Then we will need to compare the results with the typical problems of any organization.

4. The current data management process impact on day-to-day performance

If we analyze the main reasons why we do not optimize data usage, we find the following reasons:

Access: Slow process and complicated systems; too many restrictions on who can see what data.
Portability: Use it where needed, whether it is in meetings or elsewhere.
Presentation: Visual appeal and ease of use for non-data driven users.
Deep dive: Interrogate the data to find where the opportunities and issues lie so that they can be addressed.
Engagement: Have all team members contributed to developing the reports that are used by the team? Is data at the heart of business decisions? How does each member of the team propose actions and solutions to business question?
Cross functional impact: Do these reports highlight cross-functional opportunities?
Regularity: How often are data referred to and used in day-to-day business? Of the key decisions made by different functions, how many rely on data-driven reports? Is there a way to quantify this?

How is your organization structured to address these typical roadblocks? The answers will be the negative impact with the current data management process. We will be able to identify some gaps.

5. Democratize data

Democratization refers to “the action of making something accessible to everyone.”

The next step is to have a clear picture of the gaps and opportunities that exist. This will give us a new approach to data management that is cohesive, well-thought-out and accessible.

There are different options to optimize the use of data and make it accessible. These can be:

Assemble a group to work on the key areas listed above to articulate clear answers and focus.
Assign ownership as appropriate to drive this focus.
Work across commercial and operations functions to systematically address the above key areas.

We can move towards the democratization of data, putting all the above into practice:
A scenario where every team member uses data to support agile work and better decisions.

It will also help break down functional silos more effectively than any fundamental reorganization of functions and disciplines.

Conclusion

Democratization of data is key to achieving your organization’s vision. Effective use of data across the organization must be supported by top management. This is essential to identify the relationship between the vision and the approach to data management.

The various data management approaches must ensure that interpretation is actionable, understandable, and accessible.

Nowadays, data segmentation provides us with even the smallest details. With the help of technology, we can get all kinds of details that will be key to building our strategy. But to achieve a goal, all departments must be involved. The information must flow to every corner of the organization. It is important that each department uses its own approach. To guarantee success, everything must start from a common denominator: The source of data should be the same within the company.

Going through these 5 steps will help.

HEDNA Hotel Analytics Working Group
The Hotel Analytics Working Group raises awareness of the opportunities data analysis brings to optimize cost and conversion and thereby empower hoteliers to collect, store, analyze and action their data to make intelligent decisions about their distribution strategies. The group is currently Co-chaired by Matthew Goulden at OTA Insight, Connie Marianacci at Accor and Anisha Yadav at Revinate. Click here to find out more and how to join as a HEDNA member.

How to Democratize Data and Remove Functional Silos