1 / 80

Revenue Management Training

Revenue Management Training. Agenda – Day 1. 09:00 Revenue Management the EzRMS Way 10:00 EzRMS™ Core Module system training History Bookings Booking Pick-Up Special Events 12:30 Lunch 13:30 EzRMS™ Core Module system training Forecast Revenue Opportunities Analysis Configuration

callahanr
Download Presentation

Revenue Management Training

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Revenue Management Training

  2. Agenda – Day 1 • 09:00 Revenue Management the EzRMS Way • 10:00 EzRMS™ Core Module system training • History • Bookings • Booking Pick-Up • Special Events • 12:30 Lunch • 13:30 EzRMS™ Core Module system training • Forecast • Revenue Opportunities • Analysis • Configuration • 15:00 Updating the PMS & CRS • 17:00 EzRMS™ New Features • 18:00 Questions

  3. Agenda – Day 2 • 08:30 EzRMS™ Overview • Ez-Compete • Ez-Bench • Ez-Quote • Ez-Region • Ez-Budget • 12:30 How to use EzRMS™ • 13:30 EzRMS™ Core Module system training • Daily tasks • Weekly tasks • Monthly tasks • 14:30 Case Study • 17:00 Questions

  4. Introduction toRevenue Management

  5. Introduction to EzRMSTM

  6. History • A young and dynamic company founded in 1999 • New technology incorporating lessons learnt from experience • ASP platform enabling easy access from any computer and easy upgrades and updates • Supplying to leading hotel chains

  7. Accor Hotels BDL Brochner Hotels Crown Plaza Cendant Centennial Hotels Chester Grosvenor Hotel & Spa Dorchester Hotel Elite Hotels of Sweden Express by Holiday Inn First Hotels Hasting Hotels Holiday Inn Hotel Amsterdam Hotel Fouquet’s Barrière Hotel Le Bristol Paris Hotel Le Meurice Hotel Plaza Athenée Leading Hotels of the World Lucien Barrière Millennium Hotels NH Hotels Paramount Group of Hotels Preferred Hotels & Resorts Worldwide Radisson SAS Radisson Edwardian Ramada Small Luxury Hotels of the World Somerston Hotels St George Lycabettus Hotel Summit Hotels The Merrion Dublin The Madison Concourse Hotel Trump Hotels Some of our clients (In alphabetical order)

  8. The EzRMS™ Setup

  9. Property Management System Central Reservations System Revenue Manager Internet Reservations Systems

  10. Property Management System Central Reservations System Revenue Manager Internet Reservations Systems Area Revenue Manager

  11. System Information Flow Emailed (data is encoded) Property Management System Snapshot Program (daily) Data Extract EzRMS Secure Server in Paris • Forecast • Revenue Opportunities • Restrictions

  12. EzRMS™ Modules Core Module Additional Module Database loading Ez-QUOTETM Modelling & Forecasting Ez-BUDGETTM Ez-REGIONTM Optimisation & Control Ez-COMPETETM Ez-BENCHTM

  13. Pricing • Pricing is an essential element of Revenue Management • Do you have the right price structure? • Why should you have the right price structure?

  14. Decision Cycle What occupancy will I achieve? At what price do I sell at? What demand does this generate ?

  15. Rate versus Occupancy? On which day does this hotel makes the highest revenue? 100 Bed room hotel

  16. Rate versus Occupancy? On which day does this hotel makes the highest revenue? 100 Bed room hotel

  17. You Have One Room to Sell, which Booking Do You Take? Reservation #1: 1 Night @ 275 Reservation #2: 1 Night @ 250

  18. Profitability Calculation Reservation #1 Reservation #2 Pax1 Pax2 Rate Profit Rate Profit Profit • Room • Breakfast 275 10 220 8 200 16 12 18 9 • Room • Breakfast • Dinner • Wine • Laundry 250 10 20 15 10 200 8 6 9 9 Profit 228 255 Profit 232 + 4 + 27 Room 80% - Brf 80% - Food 30% - Bev 60% - Laundry 90%

  19. Realising Total Potential! F&B Revenue Room Revenue Total Potential Revenue Other Revenue

  20. Five Core Components • Knowledge Database • Understanding of products and market motivation • Forecasting • By behaviour pattern • Optimisation • Choosing the optimal revenue • Control • Ensuring optimal revenues are achieved by translating the optimal results into control values understood by the user, PMS or CRS. • Communication • Communicate controls internally & externally

  21. Five Core Components • Knowledge Database • Understanding of products and market motivation • Forecasting • By behaviour pattern • Optimisation • Choosing the optimal revenue • Control • Ensuring optimal revenues are achieved by translating the optimal results into control values understood by the user, PMS or CRS. • Communication • Communicate controls internally & externally

  22. Knowledge Database

  23. Occupancy Revenues Booking Pick-up Cancellations Group Wash No Shows Early Departures Walk in.'s Extended Stays Book Outs Denials Waitlists Guest Type Business Type Room Type Day of Week Day in Advance / Lead-Time / Milestone Season Special Events Market Segment Rate Category Knowledge Database

  24. Occupancy / Volume Revenues Booking Pick-up Cancellations Group Wash No Shows Early Departures Walk in.'s Extended Stays Book Outs (relocates) Denials Waitlists Guest Type Business Type Room Type Day of Week Day in Advance / Lead-Time / Milestone Season Special Events Market Segment Rate Category Knowledge Database

  25. Special Events Event Categories Repetitive Events • Public Holidays • Religious Holidays • Trade Shows • Exhibitions • Conferences • Sporting Events One Off Events • Day of Independence • Summer Olympics • Birth / Death of Monarch • New Year 1999 Unpredictable Events • Delayed Flights • Strikes • Severe Weather

  26. Special Events Forecasted Demand Number of Bookings Days Booked in Advance of Arrival Example of Impacts Capacity Event Curve 1 Normal Curve Event Curve 2 Normal Special Event 1 Special Event 2

  27. Occupancy / Volume Revenues Booking Pick-up Cancellations Group Wash No Shows Early Departures Walk in.'s Extended Stays Book Outs (relocates) Denials Waitlists Guest Type Business Type Room Type Day of Week Day in Advance / Lead-Time / Milestone Season Special Events Market Segment Rate Category Buckets Knowledge Database

  28. Rate Bucket Definition: • A ‘Rate Bucket’ in EzRMSTM are based on the grouping of the Rate Categories or Market Segments. EzRMS produces Forecast and Recommendation by ‘Rate Bucket’ and by ‘Room Category’.

  29. Rate Bucket by rate categories • Rules when defining a bucket: • Do not mix transient rate codes with group rate codes • Do not mix no refusal rates (LRA) with refusal rates • A given ‘Bucket’ should be composed of Rate Codes having comparable rate values (single occupancy) • A ‘Bucket’ should represent between 5 to 15% of the total business

  30. Bucket Set-up by rate categories Hotel Transient Group BUCKETS 1 2 3 4 GRH GRL RATE CATEGORIES A & E S & T I J GRH GRL Q & R G & H O L TOU F

  31. Occupancy Revenues Booking Pick-up Cancellations Group Wash No Shows Early Departures Walk in.'s Extended Stays Book Outs Denials Waitlists Guest Type Business Type Room Type Day of Week Day in Advance / Lead-Time / Milestone Season Special Events Market Segment Rate Category Knowledge Database

  32. Booking Build Up Curves Number of Bookings 12 11 10 9 8 7 6 5 4 3 2 1 0 Days to Arrival

  33. Five Core Components • Knowledge Database • Understanding of products and market motivation • Forecasting • By behaviour pattern • Optimisation • Choosing the optimal revenue • Control • Ensuring optimal revenues are achieved by translating the optimal results into control values understood by the user, PMS or CRS. • Communication • Communicate controls internally & externally

  34. Forecasting Past/History Reservations Business on the Books Future Reservations Analysis Forecast * * A revised forecast is prepared every day

  35. Forecasting What does EzRMSTM use to make an accurate forecast? Multiplicative (pick-up) Exponential Smoothing Moving Average Linear Regression Additive (pick-up)

  36. Booking Curves are created Bucket H @ 275 Bucket C @ 250 Number of Bookings Bucket D @200 12 11 10 9 8 7 6 5 4 3 2 1 0 Days to Arrival

  37. Booking Curves are created A forecast is generated determining the booking behaviour of different: • Rate Bucket • Room Categories • Seasons • Length of Stay • Day of Week • Events

  38. Forecast Example • Suppose it is 5 days before arrival • Currently you have 4 rooms on the books • Normally at 5 days before arrival, you have 50% of total expected rooms on the books. • What is our forecast? 8 rooms • What happens if we only have 7 rooms?

  39. Five Core Components • Knowledge Database • Understanding of products and market motivation • Forecasting • By behaviour pattern • Optimisation • Choosing the optimal revenue • Control • Ensuring optimal revenues are achieved by translating the optimal results into control values understood by the user, PMS or CRS. • Communication • Communicate controls internally & externally

  40. Optimisation Unconstrained Demand Willing to pay “H” @ 275 Willing to pay “M” @ 250 Number of Bookings Willing to pay “L” @ 200 12 11 10 9 8 7 6 5 4 3 2 1 0 Days to Arrival

  41. Optimisation Willing to pay “H” @ 275 Willing to pay “M” @ 250 Number of Bookings Willing to pay “L” @ 200 12 11 10 9 8 7 6 5 4 3 2 1 0 Days to Arrival

  42. Capacity Optimisation Principle • When Demand is Greater than Supply. • Ensure that Sufficient Rooms are Reserved for Essential Clients. • Cherry-Pick the Best Revenues to Fill the Remaining Space

  43. Revenue Displacement Calculation of Revenue Loss / Gain due to the realisation of unexpected business or business not forecasted, Ad-hoc Groups, Tour Series etc...

  44. Revenue Displacement A simple example Capacity 100 rooms 10 Empty Rooms R: 10 Rooms @ 300 H: 20 Rooms @ 275 M: 20 Rooms @ 250 L: 30 Rooms @ 200 D: 10 Rooms @ 150

  45. Revenue DisplacementA simple example Capacity 100 rooms 10 Empty Rooms 10 Empty Rooms R: 10 Rooms @ 300 H: 20 Rooms @ 275 What business would the group displace? What business would the group displace? M: 20 Rooms @ 250 10 Empty Rooms = 100* 10 Rooms @ 150 = 1500 10 Rooms @ 200 = 2000 L: 20 Rooms @ 200 L: 30 Rooms @ 200 GROUP: 30 Rms Displacement= 3600 L: 10 Rooms @ 200 D: 10 Rooms @ 150 D: 10 Rooms @ 150 * Cost of Sales = 10

  46. Revenue DisplacementA simple example Capacity 100 rooms 10 Empty Rooms R: 10 Rooms @ 300 H: 20 Rooms @ 275 What is the group worth? M: 20 Rooms @ 250 30 Rooms @ 195 = 5850 L: 20 Rooms @ 200 GROUP: 30 Rms @ 195 Group Value = 5850 L: 10 Rooms @ 200 D: 10 Rooms @ 150

  47. Revenue DisplacementA simple example Capacity 100 rooms R: 10 Rooms @ 300 H: 20 Rooms @ 275 M: 20 Rooms @ 250 What is the additional revenue? L: 20 Rooms @ 200 Group Value = 5850 Displacement = -3600 GROUP: 30 Rooms @ 195 Additional = 2250

  48. Five Core Components • Knowledge Database • Understanding of products and market motivation • Forecasting • By behaviour pattern • Optimisation • Choosing the optimal revenue • Control • Ensuring optimal revenues are achieved by translating the optimal results into control values understood by the user, PMS or CRS. • Communication • Communicate controls internally & externally

  49. Controls There are many types of controls, examples are: • Rate Restrictions • Length of Stay Restrictions • Overbooking • Bid Price Controls are used to apply the Result of the Optimisation process and should be the same as the controls used in PMS / CRS / Manual Control processes.

  50. How do you select the Best Business? • Rate Restrictions • Length of Stay Restrictions • Overbooking • Bid Price

More Related