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Energy and
Environment (E2)
Benchmarking —Performance Evaluation Tool for Indian Hotel Sector
S. Karthik,
Environmental Engineer,
Email: karthik@sdalt.ernet.in
In
today’s world, competition demands
leading hotels to find improvements by applying new strategies and
structures. Many hotels are seeking ways to understand, demonstrate
and improve their energy and environmental performance. The
necessary adaptation happens inevitably through innovation, that is
to say through an efficient and dynamic management of the change.
This can be achieved by effectively employing a benchmarking process
that helps the entire sector in managing those elements of their
activities, products and services that can significantly impact the
environment.
Relevance
of E2 benchmarking model for Indian hotel sector
The
Indian Travel and Tourism revenue represents 5.2% of the country’s
GDP, generating 17 Million jobs, covering 5.6% of the total
employment. This industrial sector is also known to be the world’s
largest resource (energy, water, materials & food) consuming
industry, generating disproportionate amounts of waste. Out of the
tourism industry’s total resource consumption, around 60% of it
are consumed by the accommodation facilitating units alone such as
hotels, resorts, guesthouses etc.
Hotel
industry consumes a vast range of goods in construction and
operation. They generally use huge amounts of energy, consume large
amounts of water, and generate disproportionate amounts of waste.
Collectively, they employ thousands of people and welcome millions
of guests through their doors. All this consumption and generation
of waste is done only for providing better services to their
clients. To get a competitive edge over their fellow units, the
management of hotel decides to extend more services which at times
cause greater environmental impacts.
In
the above context, Government of India has accorded hotels the
status of "high priority industry" to enable sustainable
development of the sector. Here the term hotel include hotels,
motels, way side amenities, restaurants, resorts, heritage
properties and other kinds of tourist complexes which provide
accommodation for or cater to the food requirements of tourists.
According to the Federation of Hotel and Restaurant Association of
India (FHRAI), there are approximately around 1327 approved hotels
(Five star Deluxe - 65, Five Star - 72, Four Star - 99, Three Star -
402, Heritage - 73, Two Star - 263, One Star – 50, approved 110
and 837 unapproved), 665 restaurants and 303 associates registered.
Need
of a benchmarking model for Indian hotel sector
Benchmarking
model will help a hotel to establish a continuous evaluation process
of its products, services and methods, which will help each hotel
member to compare it with its competitors and adopt the good
practices. Once developed, this benchmarking model will bridge the
gap by facilitating sharing of information among hotels and by
providing information on technologies, production methods, or
management systems that are required to implement and improve their
environmental and energy efficiency. This model provides the
information that is required to support and evolve the
cost-effective improvement decisions that hotel management and other
stakeholders would require. The performance indicators developed in
this model was department wise (see Table 1 for broad categories –
department-wise performance indicator), mainly focusing on energy,
environment and financial improvements (see Table 2 on page 6 for
broad categories of benchmark metric's).
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Table
1. Broad categories (department wise) of performance
indicators: |
|
Department |
E2
performance indicators |
|
Engineering |
Energy
Water
/ wastewater
GHG
Emission
Finance |
|
Laundry |
Energy
Water
/ wastewater
Chemicals
Packaging
material
Finance |
|
Housekeeping |
Soiled
linen
Solid
waste |
|
Food
and Beverage (production & service including kitchen
stewarding) |
Energy
Water
/ wastewater
Detergents
Food
waste
Finance |
|
Purchase |
Solid
waste
Finance |
|
Table
2. Broad
categories of the benchmarking metrics
|
| Financial |
Environmental
/ Energy |
|
Direct
-
Cooking fuel cost
-
Total purchase cost
-
Chemical cost |
Material
Consumption
-
Packaging material generated
-
Hazardous chemicals consumed |
|
Potentially
Hidden
-
Revenue to expenditure
-
Recycling revenue |
Energy
Consumption
-
Various energy consumption
-
Electricity use during operation |
|
Contingent
-
Repair & maintenance expenditure cost |
Local
Impacts
-
Waste recyclable
-
Impact upon local streams |
|
Externalities
-
Resource depletion |
Global
Impacts
-
CO2 Emissions
-
Ozone Depletion |
|
Stages
of benchmarking study
In
any bench-marking study, inter-pretation of data is
the last stage to draw final conclusions. Prior to
interpretation, the four stages of study are collection,
organi-sation, presentation and analysis, which is explained
below.
First
stage
(collecting the data): This stage refers to gathering of
facts by different methods (here the detailed questionnaire
was prepared and 30 days data was collected from six
different 5 star hotels).
Second
stage (organising
the data): This stage focusses on organising the data so
that collected information is easily intelligible. This is
the arrangement of data in a systematic order after editing. |
Benchmarking
In
essence, benchmarking is a process, which allows an
organisation to measure its performance against that of
other organisations as to assess whether its standards are
higher or lower. Benchmarking promotes ongoing assessments
of unit operations to determine whether changes are needed
to improve process efficiency. This includes identifying
specific changes and improvements that should be made to
meet or exceed. Over the past few years, benchmarking has
become a commonly used management practice for performance
measurement and improvement. It is being deployed by leading
companies across all sectors, and is considered to be a key
tool in strategic business development activities. |
Third
stage (presentating
the data): After collection and organisation, the data was
reproduced by various methods of presentation so that different
characteristic of data can easily be understood on the basis of
their quality and uniformity.
Fourth
stage (analysing
the data): There are various methodologies available for
analysing the data such as averages, medians, dispersion,
correlation etc. But here, the methodology adopted for data analysis
is very simple and straightforward. The best value achieved among
the six hotels for each performance indicator of 30 days data was
selected as a benchmark figure. For each of the indicator, though
there are many variables, only those variable factors that have a
direct affect on the resource consumption (see Table 3) have been
considered in deriving the final benchmarks.
Table
3. Various activities and resulting factors that
directly influence resource consumption |
| Activities
that have a direct influence on the resource consumption |
Resulting
factors that influence resource consumption |
| Total
occupied rooms (room nights) in the hotel |
Highest
occupancy
Lowest
occupancy |
| Total
number of guests stayed in the hotel |
Highest
guests stayed
Lowest
guests stayed |
| Total
number of guests served in restaurant(s), rooms, outdoor
catering, banquets & bars |
Highest
guests served in the restaurant
Lowest
guests served in the restaurant. |
| Total
number of guests served in the banquets alone |
Highest
Occupancy in the banquet
Lowest
occupancy in the banquet |
Fifth
stage (Interpretating
the data): This data interpretation was based on the performance
indicators developed. Performance indicators were developed
considering the operational and managerial aspects with respect to
environment and financial performance of the hotel. Table 4 (on page
7) explains some of the performance indicator developed in this
model along with its benchmark value in range.
As
mentioned in the Table 3, the detailed analysis is done for six
hotels, from the 30 days data. Out of these data from six hotels the
best value as benchmark is fixed after considering the above
mentioned affecting factors.
Capabilities
of the benchmarking model
The
benchmarking model is unique in its ability to provide distinguished
benchmarking services for Indian hotels with regard to energy and
environment. The specific features / capabilities of the model are
enumerated below:
| l |
The
model has the provision to maintain active databases
of the hotels that participated in this study as well as
every individual hotel that logs in to the model in future.
As already mentioned, the benchmarks developed as of today
are based on the data collected from the six participating
units in the past 18 months. Therefore, the model is based
on a sound database, though limited to six hotels (best in
class). |
| l |
The
model employed unambiguous data collection formats, which
helped participating hotels to collect only the required
data on their energy and environmental performance. The
model has provision to validate any newly entered data
against the existing database to find discrepancies if any
in data entries. Any abnormal entries will be
instantaneously resolved by cautioning the user on-line.
Resolution can be corrective or explanatory in nature. |
| l |
The
uniqueness of the performance indicators developed is
that, most of them is measurable, useful and helps each
department in setting realistic targets for improvements.
The validity and usefulness of these indicators have been
field tested rigorously with the help of the participating
units. |
| l |
Dynamic,
auto correction/updation is incorporated in the model,
which keeps a check on the benchmark ranges that were
already set for each performance indicator. For example, if
the value of a new entry is better than the existing
benchmark value and is with in the range prescribed for that
indicator, auto correction takes place (new /better value
gets entered as an updated benchmark value). However, if it
is not within the prescribed range for that indicator, then
the message is sent to the Data Base Administrator for
further validation. |
| l |
Exhaustive
list of performance indicators in each department has been
identified. These indicators include energy, solid waste and
other resources, which could lead to resource depletion. |
| l |
Good
practices against each indicator have been identified to
the larger extent. |
| l |
Confidentiality
aspect is taken very seriously. Unless CTI benchmarking
project/hotel association has prior consent to list the
hotel as part of the benchmark group, the participant
remains anonymous. Under no circumstances individual hotel
data will be disclosed. |
Benchmarking
under CTI Programme
Energy
and Environmental Benchmarking for hotel sector is a part of Clean
Technology Initiative - United States Agency for International
Development (CTI-USAID) project implemented in partnership with
ICICI Limited. This E2 project was implemented with the help of a
three-member technical assistance team. Development Alternatives
played the Industry Interface role, which includes the
various stages of the benchmarking model development (collecting,
organising, presenting, analysing and data interpretation). Tetra
Tech India limited played the role of Client Interface and
Battelle memorial institute as Technical lead.
The
developed benchmarking model is now with Federation of Hotel and
Restaurant Association of India (FHRAI) for large-scale
dissemination, so member hotels can login and be benefited.
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Table
4. Performance Indicator* and the Benchmark (BM) Range |
| Performance
Indicators |
BM
Range |
|
Engineering
Department |
| Power
factor |
0.98
TO 0.99 |
| Total
electricity consumed by hotel per unit area per year kWh
/ m2 / year |
175
TO 225 |
| Total
energy consumed by the hotel per unit area per year GJ
/ m2 / year |
1
TO 1.5 |
| Total
water (domestic + municipal water) consumed per 100 guest
stayed in the hotel M3 / 100 guest / day |
35
TO 45 |
| Repair
and Maintenance expenditure for engineering Vs Financial
turn over |
1
: 60 TO 75 |
| Laundry
Department |
| Electricity
consumed for processing linen (includes washing, rinsing,
finishing and lighting in the laundry department) per day kWh
/ Ton of linen processed / day |
130
TO 150 |
| Total
water (cold and hot) consumed for processing linen per day M3
/ Ton of linen processed / day |
36
TO 43 |
| Total
chemical (light, dark and white) load consumed for
processing linen per day Kg / Ton of linen processed /
day |
12
TO 15 |
| Repair
and Maintenance (R & M) expenditure on Laundry machinery
Vs guest laundry earning |
1
: 6 TO 10 |
| Repair
and Maintenance (R & M) expenditure on Laundry machinery
Vs Financial turn over |
1
: 500 TO 600 |
| Food
and Beverage (Production, service & Kitchen stewarding)
Department |
| Total
energy consumed excluding steam (LPG + NG + Coal) / total
food cooked (restaurant(s) + employee cafeteria) per day GJ
/ Ton of cooked food / day |
8
TO 12 |
| Total
water (cold + hot) consumed per 100 food cover (guest +
employee) served (includes water consumed for food
processing, dish washing) per day M3 / 100
food cover served / day |
1.5
to 2.0 |
| Chemicals
consumed per 100 food cover (guest + employee) per day Kg
/ 100 food cover served / day |
3.5
to 4.5 |
| Total
expenditure on cooking fuel Vs Total restaurant earning |
1
: 60 to 75 |
| Kitchen
Repair and Maintenance (R & M) expenditure Vs Total
restaurant earning |
1
: 320 to 350 |
| Housekeeping
Department |
| Soiled
linen generated per day per room night Kg / Occupied
room |
1.4
TO 2.3 |
| Solid
waste generated per day per room night Gm / Occupied
room |
200
TO 250 |
| Purchase
Department |
| Plastic
or PET bottles generated per 100 guest served per day Kg
/ 100 guest / day |
0.4
to 0.6 |
| Total
expenditure on purchase Vs Financial turn over per year |
1
: 8 to 10 |
| Total
revenue generated from selling waste Vs Total expenditure on
purchase per year |
1
: 250 to 350 |
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*
Note only few performance indicators are listed in Box -1 , to
see exhaustive list login to www.fhrai.com
then click My Environment benchmark under the
Members section. |
Environment
matters
Though
environmental impact of hotel activities / products / services are
considered low as compared to the manufacturing industries but still
the concern towards adoption of sound environmental and energy
efficiency technologies for conservation of resources by Indian
hotels has just began. Efficient management of resources not only
benefits the community, but it is also a good business practice. Log
on to www.fhrai.com
then click My Environment benchmark under the member section to
check your hotel benchmark status. q
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Box-1
Developing
performance indicators
This
is the crux of the benchmarking process. Performance
indicators can be broadly grouped under the following
categories:
| l |
Direct
measures or calculations: basic data or
information, such as kg of linen washed per day,
etc. |
| l |
Relative
measures or calculations: data or information
compared to or in relation to another parameter
(e.g. production level, time, location) such as kg
of chemicals used per kg of linen washed per day. |
| l |
Indexed:
describing data or information converted to units or
to a form which relates the information to a chosen
standard or baseline, Such as application of various
conversion factors to different type of energy to
convert in to the same energy unit. For ex:
electricity, HSD, LPG, NG are converted in to one
common unit Joules. |
| l |
Aggregated:
describing data or information of the same type, but
from different sources, collected and expressed as a
combined value, such as tons of CO2 emitted from
total energy consumption in a given year, determined
by summing emissions from multiple facilities
producing that product. |
| l |
Weighted:
describing data or information modified by applying
a factor related to its significance, such as solid
waste generated from the entire hotel is to a
greater extent from guest related activities and
also lesser extent from hotels own operation, here
the factor of conversion has been identified. |
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