One of the cores of most businesses is guest or consumer satisfaction leading to loyalty and to be able to fully understand behavior of the guests, there are numerous ways of collecting data, data that should be used by management to adjust the marketing and sales strategies.
Now whether the information is used in the right way, is an entire different story. I would like to focus on the collection of the data.
Image 1. How did you experience our service today?
Rather than starting with the hotel industry I would like to take an example of another industry. Recently I walked into one of the largest if not the largest Scandinavian consumer electronics shops. On my way out there was something that caught my eye, my mind and put an instant question mark on reliable data research.
On the way out there was a machine, offering an option to rate the customer service that you received today. Interesting right, and a pretty nice way of showing that there is an interest into what we think after we shopped there.
4 Buttons, the one on the left was dark green, with one of those super smiles on it. The one next to it, light green, that green that reminds you of something natural and hygienic, still smiling, just not as much as his green brother, then there is the orange warning sign, not smiling, a little sad in fact. The red button on the far right is clearly the unhappy guy. So the machine invites to hit one of the buttons on the machine. Boom, I am a generous guy, I hit the dark green button, or should I have?
In data collection there a 3 phases that should be recognized and followed through.
The pre-data collection
The pre-data collection is the base for a good end result. This phase should start with defining goals and objectives of the data collection. Also the means and the method of the data collection should be agreed. There are many different methods and tools that can be used; each of them can be applied to different ways. Note as well that within the hotel industry there is incredible data available from all the internal systems, like front office or accounting systems.
Within the first phase also ensure that data is accurate, stable and can be reproduced. In my example how many kids do you think walk by and play with these colorful buttons, making the data collection totally inaccurate?
1. Define goals and objectives.
Collecting data starts with a description of the project. What is the project, is there a problem, is there something we can do different to improve a customer experience, is there sudden revenue decrease, are there unexpected expenses, or is the payroll going up following revenue increases?
What specific data needs to be collected? Is there data that is already available, and needs cleaning up to be understood or do we need to collect new data. What data can be used to best reach solutions to ensure we reach our goals.
What is the reason or purpose of collecting that exact data? There is an incredible variety of data available, which one serves us best in reaching our goals?
Changes to be made to reach our goals are always a process, and the data collected needs to make sure it reflects and provides insight to how that process can be improved. An example is luggage handling upon guest check in. The issue often is that when the guest has checked in and has entered the room, they would like the luggage to arrive immediately, as they are ready to go out, or take a shower. There is all kinds of data you can collect in this process, finding the source of the issue, to ensure that it can be improved. It turns out that communication, or to be more exact the telephone call, between the bellboy and reception is often the issue, relating to the ticket that has been given to the guest.
Besides collecting useful data, before it actually is collected, you need establish what you will actually use the data for, to avoid mistakes, confusion or unnecessary collection.
Finally and perhaps a combination of the above, some typical stratification groups should be established:
- Who: which people, groups, departments or organizations are involved?
- What: relevant machines, equipment, technology, products, services or supplies
- Where: the typical location of the defect or problem
- When: what time of the day, day of the week, or step of the process is involved?
In the example of the buttons at the Electronics shop why are the buttons there? Are we measuring staff friendliness, speed at check out, availability of products, the interior? What do we get out of people pressing those buttons; in fact do we want to catch all of them, or just the ones who received personal service? What insight can this data provide us about the customer who just walked out? And finally can this data be used at all and what is the objective, what are they trying to fix, what part in the process is broken?
2. Define the methodology and create clear operational definitions that are equally understood by all involved in the data collection as well as the interpretation of it.
Operational definitions literally mean to define something specific, like variables, or objects in terms of a process. That sounds pretty funny, but when we go back to the example of the Electronics shop, I keep talking about the machine with buttons. These buttons can be visualized in many different ways, they can be small, hardly visible, could look a like a computer. I think you know what I mean with buttons, I just need to make absolutely sure that we are talking about the same machine, in a data collection process.
The operational definitions tell us how we should measure something, what tool to use and how to document it. This is an important step for the improvement team. Remember all of this data collection is aimed to deliver a final improvement to your organization or hotel, solving a failure in a process, or creating a new or additional service.
This is immediately related to the guest or customer. So it might be a good way to ask what they have available. Why not ask a decent sample size of customers how they would like to give feedback on a specific service, perhaps it is an online survey, or an app, perhaps they want to share comments or an evaluation with other customers.
Creating clear operational definitions are also important in reducing waste. This means that the data needed for a change or pilot is true data, supplied by the right source. Data collection should always be cleaned from any waste of information that cannot be used.
In the example, we would have to remove all the touches of the buttons by kids, as that is not our target market, they are not the right source, and they do not are most likely not informed about the purpose of the data collection in the first place.
The reliability of the data is also important for future data collection or additional data collection that is needed for a change. Often teams go back to old data and adjust the way to collect data, as a part of reaching the ultimate desired input.
3. Understanding the measurement variation
More weird terms, measurement variation, it is actually quite simple. To be able to measure and collect data you need data that is accurate. Accurate information is needed to establish correct end values. Accuracy can slightly differ for example when another person collects the data, or a different tool is used. That is totally fine, but the difference between the two occasions of data collection should be as small as possible.
On many occasions the team looking for a solution needs to go back or wants to go back to collect more data, in exactly the same way it was collected the first time. Sometimes however the data needs to be collected in another way, to make sure that defects are removed.
An example is the color of the buttons on the machine at the Electronics shop. I am not sure if you have noticed, but they start the dark Green (positive) button on the left. That is rather unusual, as I can imagine most people would expect that on the right in stead. That seems more logical, and in this case can cause confusion. They could switch the buttons to make the actions repeatable but most do it in such a way that variation is small, and is explained well.
There are clearly benefits in continuing data collection, or going back to data, tools or means of collection. Again the deviation should be as small as possible. Further data collection can show variations because of some kind of action that has happened, and can be both positive and negative. The beauty of measuring data is that you can react fast and make the appropriate changes, repeating the great and the positive and removing the root cause of problems.
During data collection
Data collection is a vital step in the path to making the right decision, and creating or adjusting a company strategy. Data collection is a valuable process, and to ensure that the results are 100% accurate, the data collection should be followed through totally, in an allocated time span.
The actual data collection is very often a challenge. After you have established who should be asked and how the data should be collected, the actual collection commences.
4. Taking the path of collecting data
What is vital in this step is to inform all members of staff, what is going to be done, why it is important to support the data collection and what will be done with the information after. The support of your staff will help the process tremendously, but also they can assist in handing out forms, explaining machines and tools. They are the ones facing the people they collect from, or are implementing the collection. They will be able to explain reasons for the data collection and answer questions about the survey, form or machine.
Within the hotel industry, data collection is a very normal and accessible activity. Every day people are checking in with a lot of the personal data, passport, email address, phone numbers, credit card details, and much of such data. When you Google data collection for hotels, over 32 million search results appear. Interesting in that is that most large hotel chains have updated privacy policies to protect their guests and clients, and also clearly indicating what the data can be used for internally.
I have been part of numerous data collections since 2001, some more challenging than others, mainly because of cultural differences. Measuring productivity for example can be an interesting exercise when a union member follows you around, or on one instant even a security guard. What is also amazing is that data collection is such a beautiful and useful exercise, and yet it is done wrongly so many times.
Quite a while ago, I came across a restaurant questionnaire. The guest had to fill out ten questions, some open answers, and mostly multiple choice. Personnel handed them out at the end of a dinner. If you have followed me so far, you will start asking questions already, about the reliability of this tool. Indeed when I looked further into this type of collection the data was totally useless, and even more so with whatever statistical tool I tried, I could not find any correlation between any of the questions on the form.
For example the question was you dinner value for money, was totally unrelated to the scoring of the service. Again I am not saying that every form is like that or has to be like that, but it is a warning sign for the use. Other questions you can ask are, is the guest happy to fill this out; can every answer be read the same; is the questionnaire only handed to happy guests; are they also hotel guests; where are they from and you can continue forever.
The result of this data collection or survey was astonishingly useless. No correlation, no education, no target subject, no clear operational definitions, no solid objectives, no calculated data collection, no description of the guest or customer and much more. And I remember the boss of the hotel said in front of the executive team; this information is of extreme importance ‘it gives us a good indication of how we are doing’. Until today I am trying to understand what that meant.
Post data collection
Now here is the most interesting part of the data collection. In the many years of hotel consulting, data has been collected; solid data, from systems like Micros Fidelio, accounting systems, loyalty systems and revenue systems, mostly existing data. Follow through of results of data collection is a requirement of success.
Recently I was at a hotel, where all rooms were identical, absolutely no difference in design, look or amenities. The data on revenues, and room pricing was readily available in the system. The hotel had an average occupancy of 89% on Mondays, Tuesday and Wednesday nights. The rest of the week, and weekends occupancy was quite a lot less. The data showed the same prices on all days, except the weekend.
Now you can start asking questions; can they have higher rates on the high occupancy days, should they do something to get more long stays and what are we doing with the pricing on the weekends and how can the be booked, and made visible. When I looked at the data I also found that many guests had requested specific rooms.
So when I did a site inspection I immediately found out why. Half of the rooms was facing the park, a lovely green scene in the middle of the city, on other side, a car park, great if you are a fool for cars, but I am thinking most of us want that green view. The data here showed that the hotel should pilot a different pricing level on rooms with views. A great opportunity based on data already collected on a daily basis.
5. Use it and use it well
The data has been collected, with the tools established in the previous chapters. It is now time to enter this data into a collection tool and start analyzing it. There are numerous ways of doing this. In Six Sigma the information we now have is called raw data. This now needs to be implemented into yet more tools that can ensure that the right and accurate data has been collected and that the process can be repeated without any variation.
In the many years of data collection in the hospitality industry, I have not come across a form of data collection that seems to be entirely watertight. Trustworthy data in our industry is mostly data that is already being collected with the back of house systems that are in place. Some examples are housekeeping, front desk, engineering and inventory systems to name but a few.
I strongly recommend starting there, in house. Depending on what needs to be measured, the improvement team needs to validate the data that can be captured from this data.
There are however numerous companies available to assist with new data collection. You need a professional to ensure that your data collection process is a valuable one. Most of these professional companies use online data collection. Some suggestions to look into are Cendyn or LRAworldwide.
Some of the criteria to consider for outsourcing data collection are:
I prefer working with E-collection. Online data can be collected at the customer convenience through the web, or an app.
Make sure that data collected also has a tool that indicates a need for immediate action. Sometimes opportunities can be spotted immediately (low hanging fruit) or in case of dissatisfaction by a customer, immediate action can be implemented to make sure the customer is retained
Ensure that data collected is complete and that all x’s, y’s and z’s have been crossed off.
Make sure collection is repeatable at no considerable extra cost. As stated before there often is a need to repeat data collection, which can be a costly exercise
Ensure the company can support your staff with training or education where needed to both read the data, but also communicate with the customer
Make sure that data collected can be used not only to read your current guest or customer experience but also assist in marketing efforts to gain new customers
Ensure there is feedback possibility, this again helps retain customers and keeps them engaged in the process
Keeping it personal creates a bond, personal welcome or thank you note from the General Manager for example
Check and establish the reporting methods used, in some cases reports are not giving the answers you are looking for
Some final words
The example with the Consumer Electronics shop is one from another industry, to show you that opportunity is everywhere. You can see these kinds of methods throughout the hospitality industrty. Now you know not to just Google restaurant satisfaction questionnaire or hotel satisfaction questionnaire and start blindly using any of the 143,000 or so results or images.
Create a plan, a data management plan, and use the stages described before as basis of establishing means and tools that can help getting to your objectives.
Collecting data is fun, it creates direct contact with your customer, it increases loyalty; your customer wants to be heard in their preferred way. Appreciate and use the information collected wisely as it can make huge difference to your customer loyalty, personnel engagement and your bottom line improvements.
Which button will you press next time?
www.isixsigma.com - Six Sigma Memory Jogger II, Dana Ginn, Diane Ritter, Michael Brassard, Lynda Finn
Mocinno International Consulting " www.mocinno.com
Cornell University " School of Hotel Administration - www.studymode.com/
About the Author
Jeroen Gulickx is a well-traveled hospitality professional with two business degrees and a Black Belt in Six Sigma certification, and has extensive experience within the Hotel & Spa segment.
The main capabilities vary from streamlining cost and operational models, strategy yielding, business development, and marketing to digital marketing.
In 2006 he started Mocinno International, a hospitality consulting company that now has offices and representation in 7 countries in Europe, USA, Middle East, Asia and Russia.
The Mocinno International team is focused on delivering incremental revenues for Hotels, Spa’s and also develops and strategizes hotel suppliers, using mainly the Six Sigma methodology.
Mocinno International works with a network of highly experienced, energetic and innovative people, based in key locations. The team also leads Client or Mocinno originated projects or concepts.
Jeroen shares his over 20 years of industry knowledge through this blog, or other social media, and speaks at travel, marketing, innovation or strategy related forums.