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How quality data significantly increases hotel profitability

09 December 2021
Top management in hotels needs to focus on increasing data quality to eliminate the costs of solving problems and the cost of failure to deliver a great guest experience. Data is only the new gold for hotels if the data quality is absolute. Otherwise, hotels will discover that the gold is fake.
Hotel people are masters in problem-solving. That is excellent, and problem-solving skills are essential in any business. So how come people working in the hotel industry are better at solving problems than people in other sectors? One explanation is that there are more problems to solve in hotels and therefore everyone gets trained to solve problems. Without problem-solving skills, it is hard to survive when working in hotels. Another explanation is that hotels lack structure and organization, and well-defined processes to minimize problems in the first place. Hotels are not like Toyota, where the focus is to design methods to prevent problems instead of solving problems. Of course, some hotels have solid processes for parts of their operations, but many other hotels have too few well-functioning procedures and trust their employees' problem-solving abilities.

Failure is extremely expensive

Top management in hotels might take another approach to problem-solving if they better understand the cost differences in preventing and solving problems. Many problems occur because of insufficient data, such as a duplicate reservation, a misspelled name, and an inaccurate report. Incomplete data triggers the wrong actions and could even make the problem worse. The 1-10-100 rule developed by George Labovitz and Yu Sang Chang in 1992 is ideal for any business to follow to assess the impact of bad data quality. The 1-10-100 rule refers to the hidden costs of waste associated with poor quality and concludes that prevention is better than remediation. The cost to prevent is $1, the cost to correct is $10, and the cost to fail is $100. The cost of checking for a similar reservation when entering the reservation in the booking system is negligible. However, the cost is ten times as high when someone has to find a duplicate reservation when verifying reservations at some point before arrival. The failure happens when guests call to make a reservation, and the hotel responds "fully booked." The result is that the hotel will end up with one unsold room. This cost is at least 100 times the cost of doing everything right from the beginning.

Eliminate the hidden costs

Correcting errors is a hidden cost, but it is ten times as high as making something right from the beginning. Failures also happen frequently in hotels at a cost that is at least a hundred times the cost of making it right. In the hotel industry, we even have our name for failures. In hotels, we call a failure a service recovery if it successfully makes the guest happy again. However, many failures are not discovered by the hotel until the review shows up on Tripadvisor, Booking, or Google.

Quality data is the new gold

The 1-10-100 rule is why quality data is one of the most valuable assets in a hotel. So, why is it that so many hotels fail to keep their data clean? With inadequate data leading to failed service deliveries, poor customer communication, missed opportunities, and lack of compliance, it is vital that hotels start to assess the quality of their data.
Hotels invest a lot of time into implementing and managing the PMS and other systems. However, all these efforts can become useless if hotels enter inadequate data into these systems, which leads to lower productivity, unnecessary spending, and bad decision-making.

5 top tips to improve data quality in hotels

Hotels can easily prevent terrible data quality. Here are some effortless ways for improvement.

Data entry standards

Having an agreed set of guidelines for adding data into a PM, CRM, or other systems, is an important starting place for any hotel to improve data quality.

Determine key data

Time is critical for personnel in a customer-facing role, such as reservations or front desk.  Therefore, determining what data is needed as a minimum to proceed with a relevant transaction can reduce users' need to add extraneous data. The appropriate fields should be mandatory to ensure that this essential data is gathered (and entered).

Handling duplicates

If you are aware of duplicates in your system, then take action. Of course, in an ideal world, you want to prevent duplicates from getting into the system. Some systems will assist here, but copies will still take a lot of time to maintain.

All data in one system

Hotels are running multiple systems with data stored in many places. Data is entered manually in many different systems (What a waste of time!), increasing the risk of mistakes. Integrate all systems and keep data stored in one central system to monitor data quality.

Training and reminding

The employee turnover rate is high in hotels, so to keep a high data quality, hotels need to train and educate all employees on the importance of data quality and enhance the benefits of increased data quality from a personal and company perspective. In addition, hotels must ensure that deployed rules and guidelines are valid and used.