Reducing Guest Room Moves

Project no. 81742

Sheraton Grand Hotel & Spa

Team Leader – Lizette Malan, Front Office Assistant Manager

Sponsor – Kirsty Cowan – Executive Housekeeper

Black Belt – Peter Cullen

Master Black Belt – Paul James

Project Justification

Our daily Duty Manager’s Log was showing an alarming number of room moves, adjustments and alterations

In the month of August we rebated a total of $2050 simply in the wrong rates being put onto guests’ accounts

Additionally, we also recognised that the value of products and services rebated to guests (eg bottles of wine / amenities etc in compensation for these inaccuracies) was far in excess of this immediate figure

The process involved with the administration of each of these room moves and rebates added further to the value of this project

A Quick Hit team was formed to examine the problem

High Level Process Map with NVA Analysis

From an early stage we realised that we were dealing with a totally non-value-adding process

Anything involved with Room Moves was, by definition, re-work

Guest Arrives

Guest Checks-In

Is room pre-allocated?

Is requiredroom typeavailable

Are otherbooking details

correct?

Guest completescheck in

Guest goes toroom

Is guest happywith room?

Guest stays inroom

Room move

Yes

No

Yes

Is alternativeavailable

No

Select alternativeroom

Yes

Explain thatrequired room

type is notavailable

No

Yes

Room move

Amend details

Yes

No

No

ReservationsProcess

Accounts Process

Value Added

Value Enabling

Non Value Added

See Reservations Process Map

See Check-In Process Map

See Accounts Process Map

See Front Office Room Move Process Map

High Level Room-Moves Process Map

Measuring the Main Issues

• The ‘accuracy’ of the reservations was defined as ‘the number of times a guest stays in exactly the room type they requested, at the rate they requested’

– What was causing so many people to arrive at the hotel with bookings and expectations that we couldn’t deliver?

– Why were so many people moving rooms?

• The ‘most likely’ reasons for room moves were brainstormed within the team.

• The top 6 reasons were used to develop a check sheet

• Check sheet was given to switchboard (who handle most of the room move requests) and the duty housekeepers (to cross reference and ensure that every room move was captured)

Measuring the Main Issues

• In addition to the room move check sheets, we also wanted to gather some raw Voice of the Customer data on what our guests were actually requesting

• A further set of check-sheets were designed and distributed to the in-house Reservations team.

• Their task was to record enquiry-by-enquiry information on exactly what people were asking for, regardless of whether we could actually accommodate them or not

• Sampling plan calculations showed that we needed to collect a minimum of 148 data points to get a result that would be a true reflection of the population

Reservations Check List

Objective – to gather data on what our customers are actually asking for – NOT just what we are able to offer them

To complete the form, please…1) Note the details of EVERY request / reservation or enquiry that comes in2) Fill in date and time that each one came in (so, for faxes & e-mails, please note the time it arrived here – not the time you dealt with it)3) Each category has two boxes marked:-‘R’ for what the guest requested ‘B’ for what was eventually booked4) Enquiries and requests that do not go ahead and book, please just fill in the ‘R’ boxes5) If we are able to give the guest exactly what they want the ‘R’ and ‘B’ boxes should all match6) If the boxes end up being different we will be able to tell what areas need attention

EXAMPLE

• To negate fluctuations in occupancy, we agreed that the baseline for ‘accuracy’ would need to be a proportion defective of total occupied rooms

• Correlation of no. of room moves per week against all different room segments did not show any relationship between no. of occupied rooms and no. of room moves greater than r=0.56

Base-lining

• Lack of any relationship to occupied rooms meant that we were able to continue simply using the number of room moves we had recorded / the weeks we had been recording for. The three months that we recorded room moves were August, September and October; a traditionally very busy month, a particularly quiet month with October somewhere in between. We felt that this gave us an even and true reflection overall. The average was 28 room moves per week

no. of r TOTAL RE TOTAL TR TOTAL RE TOTAL LE TOTAL TR TOTAL GR TOTAL GR

TOTAL RE 0.565

TOTAL TR -0.242 -0.075

TOTAL RE -0.113 0.151 0.975

TOTAL LE 0.218 -0.166 -0.555 -0.587

TOTAL TR 0.120 -0.021 0.440 0.431 0.477

TOTAL GR 0.001 -0.043 -0.113 -0.122 -0.395 -0.572

TOTAL GR -0.256 -0.124 -0.002 -0.030 -0.443 -0.526 0.950 0.032

COMBINED 0.130 -0.035 0.241 0.231 -0.080 0.161 0.706 0.193

TOTAL GU 0.555 -0.048 -0.271 -0.276 0.574 0.346 0.330 0.468

• In order to put a financial ‘value’ to the project, we decided to trace a sample of room moves back through our Duty Manager’s log and calculate the value of what we were giving guests in compensation for room moves.

• The variation in compensation was quite alarming, ranging from nothing to a complimentary weekend stay!

In addition to this, we included 2 other ‘Cost of Poor Quality’ values…

1) Front Office, Housekeeping and Accounts helped us put timings to each of the NVA steps we identified in the process maps. This, multiplied this by the hourly wage rate of the relevant member of staff, enabled us to put a financial value on the ‘wasted time’ of each room move

2) The ‘reduced capacity to generate revenue’ that each room moved caused. For example, if a person paying £150 for a basic room gets room-moved and up-graded to a luxury room that should be £200 a night, that is a luxury room that can no-longer be sold to anyone else. The business only has £150 to show for a £200 room – hence an opportunity cost of £50. Alternatively, if one guest got moved out of the £150 room then presumably no other guest will want it either and it becomes deemed un-sellable. In this instance, we could argue that there is no chance of recouping the other £150. Therefore the cost could be the full £200. For the purposes of base-lining we have chosen to assume that every moved room is resold and to go with the first rationale.

Hard Cash and CoPQ costs combined give each room move a value of £98.05 or $147.00

Base-lining

Reasons why people were moving rooms

Switchboard & Housekeeping feedback:-

Average number of rooms moves during the data collection period = 28 per week

Pareto analysis clearly shows the main reasons why people are asking to move rooms

1) Smoking / Non Smoking

2) Room category does not match the description that they booked

3) Room not ready on arrival

4) HVAC problems

5) Noise

6) Windows that will not open

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10

20

30

40

50

60

70

80

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20

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Defect

Cou

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Room Moves – Smoking Issues

The ratio of Non-Smoking requests to Smoking requests was used to generate an ‘ideal’ mix of smoking and non-smoking rooms that the hotel should have

Our theoretical ‘ideal’ is clearly very different from the rooms inventory that we actually have

The ratio of Non-Smoking requests to Smoking requests coming in to the hotel was more than 9 to 1

The ratio of Non-Smoking rooms to Smoking rooms in the hotel was less than 2 to 1

Essentially, we have far too few Non-Smoking rooms available to accommodate our guests’ preferences and, accordingly, this often results in non-smoking guests being allocated smoking rooms

Solution:

We decided to convert all smoking rooms on the 5th and 7th floors to non-smoking so as to more closely reflect the demand that was wanting to stay with us. Getting the mix right should eliminate smoking / non-smoking as a room move issue

Project Schedule for conversion of 5th and 7th floor bedrooms to Non-Smoking status

ID Task Name Start Finish Duration27 Oct 2002 3 Nov 2002 10 Nov 2002

31 1 2 3 4 5 6 7 8 9 10 11 12 13

1 1d06/11/200206/11/2002Gain approval from PM and agreedates

2 2d27/11/200225/11/2002Make any changes needed towebsites / sales collateral

3 1d28/11/200227/11/2002Re-programme Fidelio

4 2d26/11/200224/11/2002Inform MARRS / CRO of changes &check it’s correct

5 28d28/11/200201/11/2002Order door signage

6 7d24/11/200217/11/2002Pre-warn laundry company ofimpending influx

7 1d24/11/200224/11/2002Strip rooms

8 2d26/11/200225/11/2002Wash duvets in house

9 2d27/11/200226/11/2002Wash pillows in house

10 3d27/11/200225/11/2002Despatch items to laundry

11 3d27/11/200225/11/2002Steam clean curtains

12 1d27/11/200227/11/2002Deep hoover & spray carpet

13 1d26/11/200226/11/2002Spray mattress & furniture

14 1d28/11/200228/11/2002Re-assemble room

15 1d29/11/200229/11/2002Room goes on sale

17 Nov 2002

14 15 16 17 18 19 20 21 22 23 24 25 26

24 Nov 2002

27 28 29 30 1 2

1 Dec 2002

3 4 5 6

Gantt Chart for conversion of 5th & 7th Floor rooms to non-smoking

Other Room Move ReasonsAir Conditioning:

‘Versatemp’ thermostats in 14 rooms were found to be faulty. Reasons for this were:

• Units were very old, obsolete and needed replacing – currently undergoing a replacement programme after having sourced parts from Italy

• Routine maintenance on cleaning the filters had not been carried out causing the units to overheat and cut out (subsequently uncovered a problem of falsifying records in Engineering which we are now tackling as part of a separate project) – new ‘worksheet’’, inspection and routine maintenance procedure implemented in Engineering

• Currently devising a new changeover process for replacing faulty Versatemp units using SMED & Set-Up Reduction techniques

Housekeepingupdates on faulty

rooms

Engineeringupdates of faulty

rooms

Set any faultyrooms as ‘last let’

to avoidunnecessary use

Enter Opera

Set-up

SystemConfiguration

Reservations

Codes

AssignmentReasons

New

Enter new ‘reason’

Save & Close

Enter Opera

RoomsManagement

Housekeeping

HouseAssignment

Select & highlightrequired room

Click on ‘General’

Drop down‘reason’ menu

Select ‘reason’

Save & Close

To set-up a new‘reason’ code forlast-let (eg noaircon etc)

To assign a last-let ‘reason’ to aparticular room

Automatic last-let room allocation in Opera PMS

Assigning ‘last-let’ status to any faulty rooms will automatically avoid putting paying guests into faulty rooms unless absolutely fully booked

As a final ‘safety net’ to avoid guests being allocated sub-standard or faulty rooms, we discovered a way to actively manage room allocations through our PMS system. This ensures that any rooms flagged as being ‘last let’ (eg the rooms next to the passenger lifts which are very noisy), are allocated only when every other room is occupied.

Other InaccuraciesGuest comments not being picked-up

• Specific guest requests were inputted into notes section of Opera screen

• Notes section very small and easily missed

• ‘Alert’ capability within Opera was switched off - it has now been activated

• Slight change to Reservations data input process so that all notes, requests etc are inputted into ‘Alert’ field rather than ‘Notes’. This brings any requests / notes up as a screen-flash when the guest checks-in. The Receptionist cannot continue with check-in without physically pressing the screen to acknowledge the Alert

‘Alert’ is launched as soon as check-in screen is opened

Operator cannot continue until ‘OK’ button on alert has been pressed

Other InaccuraciesGuests querying rates & details

• Often no back-up documentation if a guest queried rate etc

• Guests were only receiving written confirmations if they requested them

• Automatic confirmation letter capability within Opera system was found to be switched off