Reducing Guest Room Moves

1. 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

2. 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

3. 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

4. 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

5. 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 Measuring the Main Issues

6. Base-lining • 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 • 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

7. Base-lining • 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… • 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 • 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

8. 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

9. 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

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

11. Other Room Move Reasons • Air 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

12. 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.

13. Other Inaccuracies • Guest 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

14. Other Inaccuracies • Guests 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