IMPLEMENTATION OF YIELD MANAGEMENT Practices in hotel industry: Empirical Findings in three, four and five stars hotels in the city of Madrid (Spain). Master Thesis submitted at the IMC University of Applied Sciences Krems Master-Programme “Tourism and Leisure Management” & Universidad Rey Juan Carlos “Master in International Tourism Management” by Raúl MATEO LAPUENTE for the award of the academic double degree Master of Arts in Business (MA) Thesis Coach: Alberto Romero Ania, Prof Submitted on: 14.08.2010
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Empirical Findings in three,four and five stars hotels in the city of Madrid.
With this work we expect to know the concept in depth and contribute to theassessment of the degree of implementation of Yield Management strategies asan effective technique for decision making and profitability in three, four and fivestarhotels of the city of Madrid (Spain), with the new competitive environment andgrowth of new technologies, there is a need to innovate in price management anddemand capacity to maximize profits.
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Transcript
IMPLEMENTATION OF YIELD MANAGEMENT
Practices in hotel industry: Empirical Findings in three,
four and five stars hotels in the city of Madrid (Spain).
Master Thesis submitted at the
IMC University of Applied Sciences Krems
Master-Programme “Tourism and Leisure Management”
& Universidad Rey Juan Carlos
“Master in International Tourism Management”
by
Raúl MATEO LAPUENTE
for the award of the academic double degree
Master of Arts in Business (MA)
Thesis Coach: Alberto Romero Ania, Prof
Submitted on: 14.08.2010
Raúl Mateo Lapuente II
STATUTORY DECLARATION
“I declare in lieu of an oath that I have written this Master Thesis myself and that I
have not used any sources or resources other than stated for its preparation. I
further declare that I have clearly indicated all direct and indirect quotations. This
Master Thesis has not been submitted elsewhere for examination purposes.”
• The chain, the hotel or both perform YM management.
• The person responsible for YM in the hotel: director, housing director, sales
director, booking manager, receptionist or other to be specified.
Only note that question P4 skips to P6 if the hotel is independent, since question
P5 refers to the different alternatives of participation in the management when the
hotel is owned by a hotel chain (Management controlled entirely or partially by the
chain, either partially or totally by the hotel). P8 to P13 refers to culture issues and
resources they have or are employed in YM processes, which will be discussed in
the next section.
Yield Management Application.
Following this introductory block, the questionnaire was divided into nine sections;
these are the variables defined above by the implementation model that was
chosen for application and the results of the Delphi questionnaire mentioned
formerly, which make up a battery of questions from one to 77. With this battery of
questions we seek to know in detail the uses and specific applications of YM in the
respondent hotel.
YM Culture and Resources is the first section, which is divided into three sub-
blocks; two before the battery of questions and a third where we have three
Chapter 3: Research Methodology
Raúl Mateo Lapuente 42
questions which are the beginning of the battery of questions: in first sub-block the
purpose of the three questions is to ascertain how employees and customers see
YM Culture. These questions are answered with a Likert scale, one to five as
considered, quite agree or strongly disagree.
The second sub-block refers to resources used in the YM process; two questions
seek to know if there is a unique figure in charge of YM implementation and if
there is specific software. Is it answered dichotomously (closed questions) and
regarding software is requested name and year of purchase, as qualitative data.
The third block are three dichotomous questions (closed questions) by these three
specific questions about YM culture, it pretends to know whether the respondent
has had support of his superiors, if the RM team has received previous training,
and if the person or team are updated with regards to YM issues.
Forecast, is the second set of questions, including from question four until the 11
inclusive. They have tried to find out what kind of data is considered when making
a good YM forecast. Therefore issues asked are: historical data, cancellations,
denied room, future trends, future reservations forecasts or medium revenue per
room, among others.
Competitive analysis is the third section that extends from the 12 to 17, with the
aim to study what kind of strategies are used to analyze competition, either
directly, as in search engines, distribution channels, shoppers, bench. The later
questions in this section, more technical data is requested as related to ARI, MPI
or IRG.
Segmentation of demand is the fourth variable question ranging from 18 to 19.
This block seeks to know if hotels apply YM processes in demand segmentation
tasks and if so, find out how and to what degree it is done. They are asked how
many segments are accounted for, type, origin of segments, purchasing behaviour
of each segment, etc.
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Raúl Mateo Lapuente 43
Budgeting is the fifth variable, consists of only two questions, the 20 and 21,
where it is taken into account whether the budgeting is done by market segments
and if RM projected demand budget’s is considered.
Pricing is the sixth variable comprising questions 22 to 34, where it is expected to
know the YM team’s price techniques application and the circumstances taken into
account when deciding price setting, like events to be held in the city, if they
differentiate rooms by adding attributes that do not cause an increase in capital
costs, etc.
Distribution channels are the seventh variable, which is composed by only three
questions ranging from issue 35 to 37. The search is to find if distribution channels
are analyzed, if they recognize which are the most profitable channels, which are
better placed and if you cannot find cheaper rates in other distribution channels
better than those offered on the hotel’s website.
Reservation Update and sales limits, is the eighth variable, this block ranges
from question 38 to 45, analyzing what factors are taken into account in
establishing reservation and sales boundaries when applying the YM process,
such as acceptance or rejection of reservations based on the length of stay,
season, volume of reservations and reservations accepted when the benefits
produced are greater than the benefit of an extra room available, and other
technical data such as, if they are engaged in overbooking activities, Upselling and
Crosselling.
Evaluation is the ninth variable of this last block and ranges from the question 46
to 50. This seeks to learn the techniques of evaluation in the implementation of
YM, through daily review of results, comparing the actual with the budgeted as
well as whether hotels have an incentive program for employees who apply up
selling or Crosselling and will in turn show whether YM culture is integrated into
the company.
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Economic Data
This section asks for data concerning hotel performance from the year prior to YM
implementation and two years after implantation, it must provide the percentage
change in the data. The information is requested on the basis of a percentage of
real or approximate occupation, price, revenue per available room and gross
operating margin. These data will clarify the positive effects of YM on the
economic returns of hotels using this activity.
Benefit Analysis, challenges and obstacles in Yield Management implementation.
To finish analyzing the questionnaire the respondents are asked to assess
benefits, challenges and obstacles that have occurred in the hotel by the
application of YM. A Likert scale has been used, where one strongly disagrees
and five strongly agree in the benefits section. In the difficulties and obstacles
section one is little important and five very important.
To conclude the analysis of the questionnaire a glossary has been included to help
clarify some of the concepts objects of this study that may sometimes be unknown
to the users of the study. (See questionnaire in appendix).
3.4. Sampling and sample size
Sample is a subset or subgroup of the population, while the sample size is the
actual number of subjects chosen as a sample to represent the population
characteristics. Sampling is the process of selecting items from the population so
that the sample characteristics can be generalized to the population (Jennings,
2001). To guarantee the representativeness of the sample, the researcher must
make sure that it is random. In random sampling all members of the population
have an equal chance of being included in the sample (Veal, 1997).
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Raúl Mateo Lapuente 45
3.4.1. Design of the sample frame
The sampling frame of departure is a total of 180 hotels according to Tourspain
census of 2009. The field of research are the hotels the city of Madrid (Spain).
Companies have been differentiated by categories: hotels of three, four and five
stars.
The subject of the study in addition to hotels, are Revenue Managers and Hotel
Managers, in their absence an order of descending hierarchy was applied. Since
the objective is to study the implementation of Yield Management and Revenue
Managers, and if they are built in the hotel or are at a corporate level in hotel
chains and if so, who is the representative figure for YM in the hotel, if it exists.
3.4.2. Sample size and error level
The initial sampling frame, comprises 180 hotels, a theoretical sample has been
selected, comprising a representative population size of 160 of hotels in the city of
Madrid. The type of sample that was used for this selection was systematic
random per extract by type of hotel category (three, four and five stars). The
theoretical sample size has an error level of less than or equal to 5% for a
confidence level of 95.5%. Following, table ten shows the distribution of total
population according to category of hotel along with the count and percentage of
distribution of each category.
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Raúl Mateo Lapuente 46
Table 10. Population Distribution by category
Source: own elaboration.
As shown in table ten, four star hotels are, the most representative, reaching a
population size of 93 units that represents 58% of the total sample, three star
hotels with 51 units represent 32% of the total sample, and finally 16 five star units
represent 10% of the total sample.
3.4.3. Effective final sample
At the time of closure of the fieldwork June 1, 2009, we had received a total of 84
questionnaires; this represents a response rate of 52.50%. The downstream
purification of records found three questionnaires did not meet the minimum
requirements, so the final effective sample was reduced to 81 questionnaires, a
response rate of 50.63% on the total sample. 79 hotels abstained or refused to
collaborate in the study, representing a non-response rate of 49.37%.
As shown in the following table 11, four star hotels had a high response rate in the
effective sample with regards to the theoretical distribution, is represented by
60.22% followed by five star hotels with a response rate of 56.25% and finally
three-star hotels that reported a response rate of 31.37%.
Category Theorical Sample Sampling
Percentage
Five 16 10%
Four 93 58% HOTEL Three 51 32%
160 100%
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Raúl Mateo Lapuente 47
Table 11. Response rate
Category
Theorical sample
Sample Effectiveness
Percentual Response rate
Five 16 9 56,25%
Four 93 56 60,22%
HOTEL
Three 51 16 31,37%
160 81 50,63%
Source: owned elaboration.
3.4.4 Bias and error level
At this point it is worth asking about the possibility of finding bias in the sample
data. If we take the theoretical composition of the sample as the absolute truth, it
is concluded that there is a significant bias favouring three star hotels, since they
are overrepresented in detriment of four star hotels by its final weight in the
effective sample. As shown in the following table:
Table 12. Bias and error level
Category
% Theorical
Sample
% Effective
Sample Differentiation
Five 10% 11% -1%
Four 58% 69% -11%
HOTEL Three 32% 20% 12%
Source: owned elaboration.
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Having to correct the size differences is a common need in methodological
research, being weighting the most common measure. After the differences shown
in the table above, it is considered necessary to weigh the results because there
are fundamentals to assume that the quality of the sample collection may have
been affected by any bias resulting from the decisions taken during the fieldwork.
(See table 13).
Table 13. Weighting Factor
Category
Sample Effectiveness
Percentual Response rate
Five 8 10%
Four 47 58,1%
HOTEL
Three 26 31,9%
81 100%
Source: owned elaboration.
After obtaining the weight factor we see how new values are distributed, being first
the four star hotels with a 58.1% response rate, followed by the three star 31.9%
and finally five star hotels with a 10%. As a result of the small sample size and
high level of error, we consider taking with extreme caution the results crossed by
different variables.
3.5. Fieldwork: Protocols and results
This section describes the methodology followed during the fieldwork (protocols
applied, type of questionnaire, etc.) and the final results of its application.
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Raúl Mateo Lapuente 49
3.5.1. Pre-test questionnaire
Before starting the fieldwork, there has been a pre-test of the initial draft of the
questionnaire for possible errors in its approach to the subject, which would lead to
an ambiguous interpretation respondent of the surveyed questions. Four industry
experts were surveyed in order to close the questionnaire. Professionals
conducted the questionnaire designed it in this first phase, after which they
outlined their assessments, concluding that it was appropriate and feasible for
achieving the targets. This pre-test phase has helped refine the questionnaire and
correct errors difficult to appreciate at first. It was noted, that many of them had
very different profiles in terms of professionalism and training or address gaps in
hotel jargon technical terms, a glossary has been included (above) with common
definitions that has served as a tool for understanding the questionnaire. The
duration of each interview with hotel industry experts was around 20 minutes.
Upon completion of the pre-test the fieldwork began.
3.5.2. Fieldwork protocols
The date of completion of fieldwork has ranged from April 1, 2009 until its
completion on June 1, 2009 (for teaching requirements.) As of September 2009
the coding stage and the use for statistical data have been collected in the
fieldwork. The type of interview that has been applied in most of the sample is self-
administered questionnaire; the procedure for sending and receiving
questionnaires to the sample holder was as follows:
• Phone calls to verify contact details of Revenue Managers.
• Submitting cover letters via e-mail.
• Sending questionnaires via e-mail to the Revenue managers.
• Telephone contacts to encourage participation, repeated until a
sharp negative.
• Receipt of the questionnaire via e-mail.
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It has used two ways to complete the questionnaires, via e-mail and telephone.
The questionnaire has been sent to the person responsible for YM management of
each of the different hotels. On the other hand, centralized reservations have been
considered, all those belonging to hotel chains where YM management was
centralized. Finally, the survey has had no commercial purpose, information
collected is protected under the governing law of statistic government
confidentiality, not being able to discuss or release unless in a numeric and added
way to guarantee the anonymity of respondents.
First stage, April 2009: during the first days in collaboration with the Association
of Hoteliers Madrid, we emailed a questionnaire and cover letter with a sample
holder for hotels to comply with the requirements of the study (hotel name,
category, e-mails, telephone, named revenue manager, etc.). The cover letter
provided a contact number for advice should they want to verify the authenticity of
the study. A week later, the telephone contacts were initiated with each hotel
serving as a reminder and to find out the state the survey, had it been received
and was it being completed or if they did not want to collaborate in the study.
Second stage, May 2009: during this second stage, given the evidence that the
study had a low response rate, we proceeded to contact the hotels implied in the
survey via telephone, in order to close out the approaching fieldwork as far as
possible making the actual sample as similar as possible to size of the sample
theory. At this time of fieldwork there were some elements to address the reasons for the low response rate to the questionnaire. In most cases, when the
respondent was questioned over the telephone pointed to the lack of time to
gather information to answer the survey and asked for a longer period of time.
Finally there was a cleansing of the questionnaires received, for the acceptance or
rejection of those who did not meet the minimum requirements.
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3.5.3. Issues occurred during the fieldwork
Here are highlights on several incidents and problems experienced during the
fieldwork, so that they qualitatively illustrate the difficulties we faced during this
investigation.
The first issue arose when trying telephone contact with managers and Hotel’s
RM. Access to them has been very difficult in most cases because they are people
of high positions and they alleged a lack of time to complete the survey. The large
size of the questionnaire has been in itself a problem in carrying out fieldwork,
since in several cases; managers did not have the time needed to answer the
survey.
We found two types of non-respondents qualitatively different:
• On the one hand, owners of three star hotels are unfamiliar with hotel
management jargon (in this case concerning YM) and considered that the
greater part of the questionnaire "had nothing to do with them”.
• In addition, hotel and revenue managers, whom were very difficult to reach
often apologized for their tight agendas, the strategic nature of some of the
requested data and, in some cases, alluded to excessive saturation surveys
from multiple institutions.
Another scenario occurred during the study, several investigations were launched
simultaneously from the University Rey Juan Carlos. These facts caused problems
when asking for hotel cooperation, since several of these investigations, were also
addressed to hotel managers, who after collaborating in completing relevant
questionnaires flatly refused to cooperate again.
On the other hand, certain difficulties arose with those hotels belonging to chains.
In this sense, most hotels have not provided any information about applications or
YM actions carried out within their hotels. It has therefore been necessary to
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Raúl Mateo Lapuente 52
contact the head offices for the requested information, the latter being highly
heterogeneous and unrealistic.
On the other hand, it highlights the problems experienced in relation to some of
the questions posed in the questionnaire. An example has been the case in
question number 45, which was formulated in a negative way, "You can not find
cheaper rates on other sites other than the hotel’s", attributing a dichotomous
response (yes / no) so that the same approach led to the confusion both the
interviewer and the interviewee. Equally there has been misunderstanding issues
concerning the difficulties and obstacles, as in the approach, it lacked a
comprehensive and structured question. Given the ambiguity, to which these
issues have been subject, we believe that the results may not be true or "real".
Finally, we make special mention of the difficulties experienced in the collection of
data relating to profitability. The lack of confidence of the hotel managers to play in
facilitating economic data, which has led to obtaining a very low or almost non-
existent response rate in relation to these variables. In addition, the limited data of
the heads of the hotels have been, in the vast majority of cases, approximate
and/or rounded figures. Given this situation, it was decided to exclude these
variables of the research study.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 53
CHAPTER 4
FINDINGS AND ANALYSIS
In this chapter, we gather the analysis of results, after the completion of the
fieldwork, which ended June 2009 to hotels in the city of Madrid. As proposed in
the methodology we used a secondary data analysis (literature, articles, etc.) For
the theoretical framework for primary data analysis we used a quantitative, self-
administered survey method. SPSS has been used for the processing of the
results of primary data.
The following will present the results obtained, first a descriptive analysis, second
a multivariable analysis.
4.1. Descriptive data of effective sample Within the effective sample we found a number of socio-demographic variables
that allowed us to obtain more precise information regarding the hotels under
study. Among them are the following: hotel category, hotel size, YM applied as
hotel management /or not, year of YM implementation, management model used,
independent hotel or chained owned hotel, having a YM figure within the hotel.
The following will develop each socio-demographic variable block.
4.1.1. Socio-demographic analysis
Regarding the different categories of accommodation, we observed a large
presence of four star hotels, with a 58.1% representation of the effective sample.
Followed, by the three hotels, although their representation is lower, 31.9% of the
total. Finally, five star hotels make up only 10% of the sample under study. Figure
one shows each hotel categories’ response rate analyzed in the investigation.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 54
Figure 1. Hotel category
Source: Own elaboration
As for the size of the hotels, they have been grouped into three blocks, depending
on the number of rooms they have. We speak, therefore about small hotels,
medium and large hotels. The reason for this grouping was due to the multiple
responses from hotels giving us many different values. Thus, what we will find is a
much clearer and sorted result that will allow us to draw some conclusions.
To make this division, 34 rooms has been considered as minimum data and 790
as maximum data, being this last value, an extreme value for only one hotel
exceeds 400 units of accommodation. Three intervals were created: small hotels
of up to 100 rooms, medium hotels, from 101-250 rooms and large hotels, those
having from 251-790 which is the last numerical data record.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 55
The following table shows the distribution of the number of rooms according to
category and size of hotel.
Table 14. Hotel size Hotel size Small Medium Large Total
Three star 15 9 2 26
Four star 11 31 5 47
Hotel Category
Five star 0 3 5 8 Total 26 43 12 81
Source: Own elaboration
Data shows that average size, which is the interval from 101 to 250 rooms, is the
most representative for four star hotels followed by three star hotels which are
characterized by small size, also having medium-sized hotels although less
representative, five star hotels are located in the interval represented by a large
dimension of 251-790 rooms. We can say that three star hotels in Madrid are small
to medium size; four star hotels have average size and five star have a large size.
As regards to the application of YM, only two of the hotels surveyed did not apply
a YM philosophy compared to 79 hotels that do so, this represents a 98.1% of
effective sample if they apply this tool in their business management.
These are two small three star hotels, which, despite performing certain YM tasks
or functions (according to the survey), do not have YM culture incorporated as a
business management tool. This confirms some of the statements found in
previous literature, which states "most of the hotels perform some of the activities
of YM (such as having differential pricing, a specific rate structure, team meetings
forecasting, market segmentation, etc.), but the implementation of any of these
activities alone, does not involve the actual implementation of this philosophy in
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 56
the company, for a certain amount of premises should be given, the fundamental,
in our view, is the existence of a YM culture in the company" (Talón 2009).
Table 15 shows the variable frequency analysis of the YM application in three, four
and five star hotels.
Source: Own elaboration
Without any doubt, one of the most interesting demographic variables has been
the date of application of YM in each of the hotels, and that 40.7% of the sample
began to implement YM in the period 2003-2006.
Data confirms a part of what has been exposed in previous literature research,
2006 in Madrid, which stated, "On average YM activities begin in 2003. The
emergence Revenue Manager post and the weekly meetings date from 2004.
However, most of the hotels introduced YM philosophy and software in 2005... "
(Figueroa et al., 2008). Polls show that four and five stars hotels implemented YM
practices from 1999 to 2002 almost in identical proportion as from 2003-2006.
Table 16 describes the distribution with respect to the date of application of YM in
three, four and five star hotels.
Table 15. Applies Yield Management Applies Yield Management Yes No Total
Three star 24 2 26
Four star 47 0 47
Hotel Category
Five star 8 0 8 Total 79 2 81
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 57
Table 16. Implementation date of Yield Management Hotel Category Three star Four star Five star Total
Count 2 7 4 13 1999-2002
% of Total 6,3% 21,9% 12,5% 40,6%
Count 2 8 1 11 2003-2006
% of Total 6,3% 25,0% 3,1% 34,4%
Count 2 6 0 8
2007-2009
% of Total 6,3% 18,8% ,0% 25,0% Count 6 21 5 32 Total % of Total 18,8% 65,6% 15,6% 100,0%
Source: Own elaboration
We must keep in mind that of the 81 surveys collected, only 36.5% are valid cases
and 63.5% are lost cases (random sample size of the total sample) answered no
to this question, we must take it into account as it overcomes the invalid cases
more than N=60% valid cases, therefore we cannot be certain of the
correspondence of the 2003-2006 period of YM implementation.
In relation to the management model, ownership represents a 46.1% of the
effective sample, followed by renting, with 40.8%, and finally, the management
model depicted by 13.2% of the effective sample, being the ownership and renting
the most common formulas in the model of hotel management in Madrid. It could
confirm that hotels surveyed, are not involved in franchising model management,
however the response rate for this item collection, is valid N=93.8% versus a loss
of values of N=6.2%. This data contrasts other data gathered recently in which it
said: "The Hospitality sector seeks new growth strategies based on management
contracts and / or rental and not so much on property" (Vogeler, 2009). However,
it is considered that the results of the study do not have to contradict the fact that
they are looking for new growth strategies.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 58
Table 17 contains the frequency distribution according to the hotel management
model and type of hotel category.
Table 17. Hotel Management Model Hotel Category Three star Four star Five star Total
Count 9 21 5 35 Ownership
% of Total 11,8% 27,6% 6,6% 46,1%
Count 11 20 0 31 Rented
% of Total 14,5% 26,3% ,0% 40,8%
Count 5 3 2 10
Management
% of Total 6,6% 3,9% 2,6% 13,2% Count 25 44 7 76 Total
% of Total 32,9% 57,9% 9,2% 100,0% Source: Own elaboration
One thing to keep in mind is the fact that the vast majority of hotels in Madrid are
part of hotel chains, like NH Hotels, Sol Meliá, Starwood, Ritz Carlton, etc. Polls
show the independence item or membership to a hotel brand, 78.9% hotels in
Madrid are part of a hotel chain and another 21.1% are independent hotels. In the
next section we shall see, the variable person responsible for YM management,
this variable will be strongly affected by whether or not the hotel belong to a hotel
chain. Figure two shows the distribution according to the independence or
membership to a hotel chain.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 59
Figure 2. Hotel independence
Source: Own elaboration
To finish the socio-demographic descriptive analysis, the item addressed is who is
the figure is responsible for YM in the hotel is. Regarding this aspect, the
effective sample reveals that in 56.5% of the hotels the person in charge of YM is
the Revenue Manager, followed by Front Desk Manager or Head of Reservations,
17.2%. As a third responsible for the YM management, was found the figure of the
Hotel manager, with a 9% and Marketing manager with 4.2%. However, one
should consider that 78.9% of the hotels that make up the effective sample belong
to hotel chains, while only 21.1% are independent hotels, in this way, and
considering that almost all hotels belonging to chains have centralized YM
management, it is easy to understand the high percentage of Revenue Managers
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Raúl Mateo Lapuente 60
detailed above, it means that the same Revenue Manager works with several
hotels at once, therefore each hotel does not have a Revenue Manager on site.
Figure 3. Person responsible for Yield Management
Source: Own elaboration
4.1.2. Descriptive analysis of Yield Management variables
When addressing the analysis of the variables involved in the YM process, we find
that the blocks of questions of each variable have high response rates, the items
are characterized by dichotomous questions (Yes or No), the survey showed a
high response rate for Yes they perform YM activities and a low response rate of
No for the performance of some of the YM activities. To summarize each variable,
we proceed to cluster the Yes YM activities responses by summing to find the
possible frequency of population that performs this process, the recoding of each
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 61
variable shows that the population responds very favourably to Yes and that there
are very few No’s recorded. Noting this, we recoded the variables and turned them
into percentages to better observe if hotels perform YM and in what proportion. It
must be said that when information is synthesized in statistics, it is a fact that
information is lost, a fact to consider. The following will present the results of each
variable after the analysis of each.
In our first block on YM culture and resources, seen broadly, results show a very
high positive rate with respect to the variables analyzed. It shows that more than
87.9% of the staff in different hotel departments surveyed know and share YM
goals. On the other hand, while in the item referred to whether the guest perceives
as fair price changes, the survey found that 71.6% do "not perceived as fair price
changes" versus 28.4% of "prices changes perceived as fair". The following figure
shows whether they have specific YM software.
Figure 4. Yield Management software
Source: Own elaboration
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 62
On this block of resources, we have crossed the item, belongs to hotel chain and if
they have software, there has been a valid response N=95.2% and one of missing
data N=4.8%. In item response, whether hotels have specific YM software, data
suggests that hotels do have specific software in a 37.2%, of which 1.3% are
independent hotels and 35.9% are hotels belonging to chains that claim to have a
YM computer application. On the other we have recorded that in 62.8% of cases,
hotels do not have a specific YM computer application, of which 19.2% are
independent hotels and 43.6% are hotels belonging to chains. We can say that
independent hotels do not invest in specific YM software, as for example Rate
Tiger, possibly due to its high cost. However hotel chains do have special
computer application compared to independent hotels, but the non-acquisition of
software is still predominant. Possibly there will be a need for studying if hotel
chains have developed an integrated management tool, which implies some YM
variables.
More than 57.3% of the hotels in Madrid have a full-time YM responsible. Where
54.7% are hotel chains and 2.7% are independent hotels. These results could be
because of their belonging to hotel chains counting with more resources due to
increased funding and the allocation of costs between the various hotels. 42.7% of
the hotels do not have the YM figure implemented.
After the re-coding of the nine variables above, we will post the results. First, the
variable YM culture and resources, shows that 84.7% of hotels surveyed replied
they have YM incorporated in their business management philosophy. While
15.3% of hotels do some things regarding YM but not all.
As for the block associated with forecast, broadly, the results show positive
values, we find that the hotels meet at least 50% of the questions, while 70% of
the populations are above 75% response rates, when replying that they apply
forecast. We also find some variables with missing values, 12.5%, to be
considered. Data shows that most hotels consider their historical data when
forecasting, do pick up, analyze environmental factors and future events.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 63
In the analysis of competition is of N=84.8% of valid values against an N=15.2%
of missing values. 74.4% of valid values respond more than 75% of the questions
in this block, so hotels in Madrid perform tasks of identification of competition,
determining the positioning of the hotel in time (short and long term) analyzing
pricing strategies of competition, measuring the MPI, ARI, IRG and analyzing the
competition periodically. Either being independent hotels or belonging to hotel
chains, no significant differences have been found with previous results, in saying
that hotel chains are the ones who have more YM practices implemented as
business management.
The segmentation of demand shows that 76.9% respond positively to more than
75% of the questions, it reflects that hotels also do market segmentation and
distinguish types, the source, customer’s purchase behaviours, they also know the
contribution of market segmentation to the hotel’s benefit.
The budgeting variable, data shows that 45.7% take into account RM
departments’ demand forecast and the budget is done through market
segmentation. And 40.7% take into account at least one of these two activities,
which shows a high degree of YM budgetary activities. 60.5% of the hotels
belonging to hotel chains based their budgeting RM department demands, while
independent hotels, show that an 11.8% base their budgeting upon RM
department demands. This result seems logical because hotel chains have a
greater force in providing for this department, since it is themselves that mostly
have the Revenue Manager figure involved in YM tasks. (See figure five).
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 64
Figure 5. Demand forecasting Revenue Management department
Source: Own elaboration
In the results obtained in the variable pricing, we see that all the percentages
obtained are very positive in chains as in the independents. The response was
over 75% of the questions, registering a 87.1% engaged in price fixing, as the use
of differential pricing, price offer "packaged" with other services i.e., prices are
fixed taking into account costs, demand, competition and distribution channels,
etc.
In the item "TT.OO. rate variation and corporate accounts” shows that a 66.2% of
the hotels vary the rates, but 33.8% of cases cannot do so, this reflects that rate
negotiation is not as rigid as in the past and that TT.OO. do not have the
bargaining power they had in the past, hotels manage their room sales quota.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 65
In distribution channels, hotels perform analysis of the positioning of the various
channels then pick the most profitable ones and finally have a hotel website with
the possibility of marketing the product and selling it online. Data shows that
85.7% reported all these activities.
Table 18. Hotel web on-line bookings Hotel web
on-line bookings
Yes Total
Count 16 16 Independent
% of Total 20,5% 20,5%
Count 62 62
Hotel independence
Hotel Chain
% of Total 79,5% 79,5% Count 78 78 Total
% of Total 100,0% 100,0%
Table 18, reveals that both independent and chain owned hotels market and sell
their products through their own website, which reflects that they have developed
internet as a promoting and selling tool to the customer, on the other hand it is
related to the "variation of rates with tour operators” stated earlier, hotels choose
to negotiate with their direct customers through the hotel’s website. Results show
that 20.5%of the independent and 79.5% of the chain owned hotels have this tool
incorporated into the YM management.
In the case of the variable to update the reservations and sales boundaries, shows that only N=73.6% are valid, recording a loss of N=26.4%. This means they
you have not answered the entire effective sample, and that this effective sample
is biased by the response rate. 61.8% of hotels respond with a Yes to this variable
and, if reservations are accepted or denied depending on the season, length of
stay, if they perform overbooking activities, etc.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 66
It shows different results between "accepting or rejecting reservations depending
on the season" we appreciate heterogeneous rates among independent hotels
and chain owned hotels, we see that independent hotels accept or deny seasonal
reservations by 11.5%, yet it shows that chain owned hotels do not in a 44.9%,
data recorded are similar in both cases because independent and chain owned
hotels is performed or not in similar percentages. Five star hotels are the only
ones that do accept or deny reservations depending on the season by almost 9%.
In the item "accept or refuse reservations according to length of stay" is noted that
the hotel chains perform this activity in a 61.8% compared to independent hotels
who do it by 10.5%, also noted in the item "accept or refuse reservations
according to sales volume," is done in hotel chains in a 66.2% and by independent
hotels in a 16.9%.
Data shows that hotels in Madrid accept or deny reservations depending on the
length of stay and the booking volumes and do not operate much according to the
season, except in five star hotels, which reflects that for hoteliers in Madrid there is
not such a marked seasonality in their hotel management.
Finally, the YM evaluation of the process variable has recorded that 85.6% have
responded to more than 80% of the items, thus hotels in Madrid are engaged in
daily review of results comparing the actual with the budgeted, analyzing
deviations and encouraging counter and reservations staff to implement
Crosselling and Upselling techniques. It is stressed that the chain owned hotels
support Crosselling and Upselling by applying incentives to their front-desk and
reservations staff.
The following Figure six shows that only five independent hotels and 45 hotels
owned by chains encourage these practices.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 67
Figure 6. Motivate staff by Upselling and Crosselling
Source: Own ellaboration
4.2. Yield Managment implementation multivariable analysis In the dependence analaysis, obstacles, difficulties and benefits block, analysis of
variance was carried out, which measures the statistical significance of differences
between the dependent variable measures presented in the different groups. The
process for this dependence analysis was to create a new variable, which is the
sum of all amounts; it is reflected in the new recoding of the number of YM actions
the hotel performs.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 68
The new variable (percentage adder) is used as numerical; an analysis of variance
is performed with the benefits to compare averages. One thing to note is that all
blocks of questions have been given the same weight of importance, ignoring the
amount of questions in the different blocks.
In Figure seven it is seen that for a 30.2% of hotels YM is very influential and for a
65.6% it is completely influential, only three hotels disagree not meaning any
difference for the high positive response in increasing hotel benefits by YM
practices. Analysis shows that for hotels that replied that YM is completely
influential in hotel benefits made an average of 66 actions over 77 YM actions.
Following come the development of the mayor actions hotels carry out.
Figure 7. Increase profits
Source: Own elaboration
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 69
The following are the results obtained by comparing the response of item
"increases hotel benefits" with the added percentage of the actions of the variable
"YM culture and resources”. Data suggests that 100% of the hotels have YM
culture incorporated in business management and value as completely influential
management’s, ownership or chain support when implementing YM philosophy,
and a 90.91% finds it crucial to have a well trained RM team, 88.31% to be
updated in YM in forums, blogs, newsletters.
In the variable of "segmentation of demand" the recorded 88.31% claimed to
have more than four segments, a 77.92% finds it very and totally influential to have
market segmentation by types of activities, seeing the origin of the segments,
analyzing the contribution of each market segment to the benefit and to analyze
the segments that come through distribution channels. Hotels in Madrid find that
the performing correct segmentation of demand favours the hotels profitability.
Over 80% of the hotels performed actions on "analysis of competition", a fact to
note is that there has been many cases where they do not give much importance
to long-term position (more than 12 months) but to short term positioning (less
than 12 months). They do not commonly use tools for analysis of price competition
such as shoppers (rate shopping) or bench. Nor do they measure the MPI, RMI
and ARI, 50% have been recorded as they do perform, the other 50% do not
perform.
As for the "forecast" hotels perform in more than 80% occupancy forecasts, the
correct analysis of historical data, taking into account local events, future events,
knowing in advance the reservations made by each market segment, a good
analysis of the environment and keeping track of the pick up has a direct impact
on increasing the benefit of the hotel.
In the “budgeting” variable 78.3% of businesses believe that the impact of YM is
absolutely influential in increasing the profit of the hotel when engaging the RM
department in forecasting the demand, while those who think it is very influential
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 70
only do budgeting on forecasting demand on a 52.8%. In the item "the budgeting
is done by market segment”, the differences increases as in the aforementioned
variables, being a 72.4% those taking actions who consider it totally influential and
only a 28.6% of those who consider it very influential. In summary, those that think
that YM is absolutely influential in the profits of the company are precisely those
who mostly take into account this aspect when budgeting.
In the variable "pricing“, hotels think that taking these actions influences hotel
benefits, results are very similar to previous data on Revenue Manager believing a
90% that these actions are totally influential to increase the hotels benefit, and the
68% of them that think that these actions are quite influential record lower rates
but still quite high.
As for the "distribution channels" the recorded percentages are high 100% of
the hotels think it is totally influential that the hotels received on-line reservations
from their own websites a 93.1% think that is totally influential to analyze the
positioning of the various distribution channels and finally 91.95% consider to
choose the most profitable channels to influence hotel profit.
When it comes to "Limiting and updating reservations and sales" the most
valued by hotels and which are considered utterly influential in increasing the
hotels benefit are in 100% is to have updated information of number of rooms
available, 81.8% to apply Crosselling and Upselling techniques, 90% to carry out
overbooking activities, 80.5% to accept or reject reservations based on length of
stay and booking volume, 94% open or close sales depending on demand
forecast.
In the last variable "assessment" the actions that are taken into account as fully
influential in increasing the hotels benefit are: 100% to assess the benefits
resulting from the application of YM taking into account the average occupancy
rate, price average RevPar, etc., a 88.5% to check daily results, 90.2% to compare
the actual against budget, a 96.6% to analyze the deviations that occur during the
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 71
process and 73% to apply incentive schemes for front desk and reservation staff to
encourage the implementation of Crosselling and Upselling techniques.
The difficulties and obstacles block did not provide very relevant data about the
difficulties and obstacles of the implementation of YM in hotels of three, four and
five star reviewed. The results are:
In the average data recorded items of “difficulties and obstacles” range from 2.71
to 3.87 range. After an analysis of variance of a factor by hotel category, data
shows significant differences in the item of "lack of ICT", in three star hotels finding
it a mayor problem for their hotel management rather than for five star hotels that
do have them. We performed Pearson’s chi-square test to see if these two
variables are dependent or independent and the result was that the variables
“hotel category” and “shortage of computer applications” are dependent.
Another relevant fact in this analysis of variance, is related to the item of "the lack
of resources," comparing the categories of five and three star hotels, there is
considered to be a confidence interval of 95%, manifests an average difference in
post hoc test more, less 1.822, being the average 4.27 and 2.44 respectively.
There are also significant differences among four and five star hotels that show
more, less 1.111 in post hoc test with an average of 3.56 and 2.44. Pearson’s chi-
square test was conducted and it observed that the two variables are dependent
on each other. It follows from this that five star hotels use many resources in the
management of YM, compared to four star hotels that show less need for
resources but still demand it, three stars are the ones who present a lack of
resources compared to five star hotels, data is logical for there are great
differences in YM investment between the two categories. If the same analysis
was performed according to dependency or independency of the hotels studied,
no remarkable evidence would be found for they are independent variables that do
not influence the analysis results.
Chapter 4: Findings and Analysis
Raúl Mateo Lapuente 72
Another difficulty is linked to the lack of trained staff where the variable is
dependent of the hotel category, after the Pearson’s chi-square test of three
hotels, four and five star hotels it is seen that they find it difficult to recruit staff
trained on YM or even staff that has any knowledge of it.
Once exposed the most relevant results on the research, chapter five will discuss
the findings, limitations and possible lines of future research.
Chapter 5: Conclusions and Recommendations
Raúl Mateo Lapuente 73
CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS
5.1. Conclusions
This chapter presents the conclusions of the research based on the results that
the main findings draw from primary data. This paper attempts to see the overall
objective of determining the level of YM implementation and if three, four and five
star hotels have a Revenue Manager figure. The specific objectives that were
proposed were whether hotels made a correct YM application and thus obtained
an increase in economic and management benefits, and to know if the YM
philosophy or culture was incorporated into the company and identify the obstacles
faced by hotels in applying the YM process of as the research areas of the study.
Referring to the overall goal that was set previously, we conclude that the degree
of implementation of YM policies in three, four and five star hotels of the city of
Madrid is high, noting that a large number of the hotels that responded to the
survey, took at least 66 actions out of 77 proposals representing a 85.71%. This
fact is mainly influenced by the independence of the hotel or by belonging to a
hotel chain management, the latter representing 78.9% of the effective sample
against 21.1% of independent hotels, hotel chains have greater degree of
implementation than independent hotels engaged in YM but not at the level of the
hotel chains. Moreover, hotels are fully supported in the development of the YM
strategies by management or hotel property in 100% of the cases, and recognized
that a 90.91% of the RM team had received specific training and are informed
daily about the evolution of YM through forums, blogs, conferences, etc. Thus
demonstrating that the culture or philosophy is incorporated in business
management.
Chapter 5: Conclusions and Recommendations
Raúl Mateo Lapuente 74
However only 56.5% of the hotels surveyed have a Revenue Manager figure, on
the other hand, we must mention that many hotels belonging to chains do not
Revenue Manager figure in the hotel but work in central offices and operate
several hotels, data collected after the telephone interviews. Therefore the degree
of implementation of the Revenue Manager, recognized as the sole responsible for
managing YM, is in the process of integration into the hotels in the city of Madrid.
As for the specific objectives, it aims to show, if the correct application of YM
increases the economic and management benefits of the company, as well as the
obstacles encountered in their implementation. Referring to whether it increases
profits through proper information management, 93.4% of respondents agree that
the YM model maximizes information management. Information Management is
collected through the analysis of the YM department, which accounted for more
than four market segments in a 88.31% that influence the pricing in a way that
they offer different prices to different niche markets, where the hotel obtains profit
maximization. 72.4% hotels in Madrid apply market segmentation. When it comes
to analysis of the competition they often forecast short-term not at long-term, nor
they have tools for analysis of competition as bench and shoppers. 100% of the
hotels find Internet very profitable as it is becoming more common to self-manage
their own website which also serves as a marketing tool having their own built-in
CRS for on-line payments. Consequently they perform selection analysis and
positioning in the most profitable Internet channels they consider are distributing
their product in 91.95% of cases.
In recent years, hotels have incorporated Crosselling and Upselling in their
management techniques and a 81.80% recognizer it as a source of extra income
where they generate an increase in profit.
In terms of increasing economic benefits, a responsible conclusion cannot be
made, since the figures provided were insufficient to make a credible claim, due to
the reduced response rate that was very low or almost non-existent.
Chapter 5: Conclusions and Recommendations
Raúl Mateo Lapuente 75
As the main obstacles faced by managers in YM implementation, data suggest
that 71.6% of the hotels "do not perceive as fair price variations" compared to
28.4% who "do perceive price changes as fair". After a review of the literature,
there is research to partially support the results of this research. According to
Jones (2000, in Talón, 2009) the implementation of YM improves business
performance from three perspectives:
• Increased knowledge about the client: the mode of action and perception of
value product or service.
• Optimizes information management, enabling increased efficiency in
handling data and creating estimates of demand, allowing prices to adjust.
• Provides the effects of changes in reserves.
After analyzing the responses, I find myself in a position to strengthen with data
Jones first two statements, the incorporation YM actions allow hotels to "Select
better customers" and therefore implement a process that "optimizes information
management”. In the results analyzed it is seen that hotels have high number of
actions obtaining a broad vision of the market and enabling them to profit from
improving the profitability of economic and management benefits.
The lack of specific software applications and the lack of trained personnel in this
discipline is found as a major obstacle to achieve profitability in their management,
also state that they have not yet implemented integral YM and actions are
commonly performed towards rooms.
5.2. Limitations First limitation is considered to be the theoretical sample size of 160 hotels, where
there was a response rate of 81 hotels that represents a 50.63%. Despite not
being very representative and that the total of the effective sample is half of the
theoretical sample of departure which are160 hotels.
Chapter 5: Conclusions and Recommendations
Raúl Mateo Lapuente 76
The four star hotels group is over represented with respect to others, where five
star hotels represent a small sample compared with the number of hotels in three
or four star. This limitation was resolved at the time of the effective sample weight,
but even so the study results it cannot be extrapolated to other cities, a fact to take
into account.
The data collection period of our study occurred in June 2009, in an advanced
stage of the global economic crisis, therefore the quarterly balance sheet data,
and occupation data are not the same as in times of normal economic situation.
Economic benefits are reduced in many cases, and they do not invest in
equipment or training, so this circumstantial event has altered this point.
5.3. Recommendations for further research
This section discusses some ideas that have emerged during the review of the
literature and issues that appeared during the investigation. I give some
recommendations for future research, which aims to:
• The creation of a best practices manual regarding YM management: based
on the literature, consultations with experts and data collected in research,
it would be interesting to conduct a good practices manual that serves to
optimize YM management in hotels.
• Conduct a study on the job skills of a Revenue Manager, since Spain has
no information of the functions it effectively performs and the abilities
needed. This will help HH.RR. Departments when looking to recruit
Revenue Managers.
• Longitudinal studies: It would be good for better knowledge and control of
YM management in the city of Madrid, make continuous studies to measure
sporadic over time the implementation degree varies, and which aspects of
YM management have been modified or reinforced.
• Study the impact generated by the Upselling and Crosselling trainings in
reservations and front desk staff.
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Raúl Mateo Lapuente 77
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C1: Do you apply Yield or Revenue Managment in your hotel or hotel chain? Yes No
C2: ¿Since when? (indicate year):
P1. Hotel category: Three stars
Four stars
Five stars
P2: Size of Hotel: Number of rooms
Hotel capacity
P3. Management Model
Ownership
Rented Franchising
Management
Others:
P4. ¿Is it an independent hotel or does it belong to a hotel
chain?
Independent (pasar a P6) Belongs to a hotel chain (pasar a P5)
P5: IS YM tasks totally carried out in central headquarters,
totally in the hotel or both?
Totally at headquarters
Totally in the hotel Both
P6. ¿Who is the person responsible for YM in your hotel?
Manager Room Manager
Sales Manager
Reservations Manager Front desk staff
Hotel’s Revenue Manager
Others:
Appendix B: Questionnaire
99
YM CULTURE AND RESOURCES
Point from 1 to 5 the impact of YM in the following aspects (where 1= highly disagree and 5=
highly agree) 1 2 3 4 5
P8.- ¿Do you believe housing department,sales and Management staff have knowledge on and
share YM goals?
P9.- ¿Do you relieve front desk and reservations staff properly justicies price variations to guests?
P10.- ¿Do you relieve guests percieve price variations are fair?
Following you will find several questions concerning YM in your hotel, please answer YES or NO:
YES NO
YIELD MANAGEMENT CULTURE AND RESOURCES
19. Have you been or are you being supported by hotel manager and /or hotel property or chain when developing YM strategies?
20. Is the RM team updated on YM issues through forums, blogs, newsletters, etc.?
21. Has the RM team received any training onYM?
FORECAST
22. Historical data are taken into account:
4.1. Types of Customer
4.2. Rooms sold
4.3. Average occupancy
4.4. Hotel’s room denials
4.5. No show reservations
4.6. Walk in rooms
4.7. Average room price or ADR
4.8. RevPar
4.9. GovPar
4.10.Lenght of stay
4.11.Segmented key accounts
4.12.Conversion ratio of groups
YIELD MANAGEMENT RESOURCES RESOURCES YES NO Denomination (software) Year of Purchase
P11.- Does the hotel have any special
computer application software for YM?
P12.- Do you use Excel spreadsheets to
perform YM tasks?
P13.- In case of having a responsable for
YM tasks. Is the dedication full or part
time?
Appendix B: Questionnaire
100
4.13.Group denials, Group cancellations
23. Forecast compares the development of existing reservations with the evolution in the past
24. Estimation takes into account the rooms booked at present (OTB)
25. It is known with what advance the different segments book
26. Pick up is analyzed:
8.1. Daily
8.2. Weekly
8.3. Per total rooms
27. Enviromental factors are analyzed
28. Future events are analyzed
29. It takes into account future enviromental trends
COMPETITIVE ANALYSIS
30. It identifies competition
31. It determines the positioning of the hotel:
13.1. long-term (more than 12 months)
13.2. short-term (less than 12 months)
13.3. With regard to competition in search engines
13.4. With respect to its competition in distribution channels
14. It Analyzes :
14.1. Competitive advantages (location, price, marketing strategies) in competition with regard to your hotel
14.2. Pricing strategies of competition
14.3. The distribution channels strategies of competition
15. Tools are used to analyze the pricing strategies of competitors: Shoppers (Ej.Rate Shopping, etc..), The Bench, comparators (eg Traveljungle), etc.
16. It measures:
16.1. MPI
16.2. ARI
16.3. IRG
17. The Analysis on competition is periodic
DEMAND SEGMENTATION
18. Regarding segments, there are at least 4 market segments.
19. It Analyzes:
19.1. the types of segments
19.2. the origen of segments
19.3. Buying behaviour of each segment
Appendix B: Questionnaire
101
19.4. The contribution of each segment to profit
19.5. Segments that come through distribution channels
BUDGETING
YES NO
20. Is performed taking into account RM Departments demand forecast
21. The Budget is done by market segments
PRICING
22. The Sales and Revenue Management Departments are responsible for setting prices
23. Differentiated prices are used
24. Several different rates are used depending on different market segments
25. The lowest rates have restrictive criteria or barriers to their implementation
26. “Packaged” prices are provided (room with other services)
27. Room differentiation is done by adding attributes that do not pose a significant cost increase
28. Prices are fixed taking into account the costs, demand, competition and distribution channels
29. In Tour operador contracts and corporate business accounts rates can vary
30. BAR model is used "Best Avaible Rate"
31. There is equality of prices offered by the vendor in all distribution channels
32. Information of higher / lower rate applied is available
33. To apply promotions predetermined requirements are necessary
34. When reviewing rates the influence of local events are taken into account
DISTRIBUTION CHANNELS
35. The positioning of the various distribution channels are analyzed
36. The most profitable channels are selected
37. Online reservations can be done from the hotel’s website
UPDATING LIMITS OF RESERVATIONS AND SALES
38. Available Updated information on the number of rooms available
39. Upselling and Crosselling techniques are applied in sales
40. Over capacity reservations are made (overbooking)
41. Reservations are accepted or denied in terms of:
41.1. Lenght of stay
41.2. Season
41.3. Volume of reservations
42. Reservations are always accepted when producing more benefit than the profit of having an extra room avail-able
43. Rates are opened or closed depending on the demand forecasts
44. You can change rates at all "channels" (channel management)
45. Lower rates cannot be found on other sites other than the hotel’s site
Appendix B: Questionnaire
102
EVALUATION
46. Benefits resulting from the application of YM are assessed taking into account several variables: employment, price, RevPAR, etc.
47. Results are reviewed daily
48. It compares the actual with the budgeted
49. Deviations are analyzed
50. Reservations and front desk staff are encouraged with incentive schemes when applying Upselling and Crosselling techniques.
ECONOMIC DATA
Profitability Data Real Datal: % Approximate% of variation between
the year prior to the implementation of YM and the
Value from 1 to 5 the impact of YM in the following aspects (where 1= non influential and 5= fully influential)
1 2 3 4 5
1. Increases Hotel’s benefit
2. Increases knowledge on the market and my product
3. I obtain better results that my competition
4. It optimizes information management
5. Better manage my relationships with intermediaries
6. It allows me to select the best customers
7. Allows greater flexibility of the workforce
8. Improves the hotel’s image
9. Increases staff motivation
10. Increases decision making speed
Appendix B: Questionnaire
103
DIFFICULTIES AND OBSTACLES Value from 1 to 5 (where 1= non influential and 5= fully influential) should these situations take place in your hotel
1 2 3 4 5
1. Lack of staff understanding regarding YM goals
2. Lack of resources
3. Lack of trained staff
4. Lack of interconnectivity of systems
5. Lack of integral YM throughout the hotel
6. Shortage of computer applications
7. Lack of Historic Data
8. Customer lack of understanding
9. Distributors and trade’s lack of
10. Others:
GLOSSAR
RMS: Revenue Management Software. PMS: Property Management System. CRS: Central Reservation System. RevPar: Income per Room Available. GopPar: Profit per Room Available. ADR: Daily Average Ratio. ARI: Average Rate Index. IGR: Revenue Generation Index. MPI: Market Penetration Index. Pick up: Pick up: are the reservations we expect to receive, based on our experience and analysis.
Adding them to the reservations we have today (OTB), we can start making our forecast.
Appendix C: Presentation Letter
104
A/A: Hotel Name Hotel Manager Address - Location
Dear Mr/Ms., The University Rey Juan Carlos of Madrid together with the University of Applied Sciences FH Krems in Austria, through a collaboration agreement are conducting a survey on the degree of implementation of Yield Management in three,four and five star hotels of the city of Madird (Spain). This is an inquiry led by Professor Pilar Ballesteros Talón Department of Applied Economics at the School of Tourism at the Universidad Rey Juan Carlos. From the conviction of the protagonist character of tourism in the present and future, we intend to create a framework on the degree of implementation of the Management of Yield Management in the city hotels. This project aims to determine the strategies adopted by Hotels in Madrid to meet current industry challenges and the need to increase the economic benefits and management of hotels. For the success of this research it is essential the collaboration of managers and / or Yield Management Managers of the 160 hotels selected, by completing the questionnaire. The treatment of the information collected will be totally confidential and data will be analyzed in aggregate, so that no company can be identified by their results. The questionnaire will be send to you via e-mail where we direct you to the same email address [email protected], The questionnaire is quick to respond and if you have any question you would like to ask, do not hesitate to contact us, we will be glad to help you. In appreciation for your collaboration, once finished the research if you wish to, you will receive the report, which we believe will be of great interest, insisting that all answers are protected by existing legislation on data protection and statistical confidentiality (Governing Law 12/89 statistical confidentiality), and in no case will reveal the source or publish results that can be identified. I remain at your disposal for any additional information you may want on this issue and take this opportunity to send my best regards. Raúl Mateo Lapuente Inquiry Coordinator