Revenue Management Webinar Series Good Data In/Good Data ...eoplugin.commpartners.com › HSMAI ›...

4/9/2013

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Revenue Management Webinar Series

Good Data In/Good Data OutApril 9, 2013

This webinar series is brought to you by HSMAI University, HotelNewsNow, and STR

Overview of Format and Topic

Webinar ModeratorFran BrasseuxExecutive Vice President, HSMAI

4/9/2013

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POLL QUESTION #1How many people are participating

in this webinar at your location today?

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Panel Moderator:

Patrick Mayock, Editor in ChiefHotelNewsNow.com

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Today’s Presenters: Panel Moderator: Patrick Mayock, Editor in Chief, HotelNewsNow.com

Panelists:

Steve Hennis

Director

STR Analytics

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Kevin Coleman

Partner & COOIntelligent Hospitality

Mark Molinari

Corporate VP

Revenue Management &

Distribution

Las Vegas Sands

Nathan Bacher

Regional Director

Revenue Management

Fairmont Raffles Hotels Int’l

Hotel InduSTRy OverviewHSMAI Webinar Series

Stephen Hennis, CHA, ISHC

Director, STR Analytics

4/9/2013

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U.S. In Review

2012 Year End: Strong Results Despite Headwinds

% Change

• Room Supply* 1.8 bn 0.5%

• Room Demand* 1.1 bn 3.0%

• Occupancy 61.4% 2.5%

• ADR $106 4.2%

• RevPAR $65 6.8%

• Room Revenue* $115 bn 7.3%

Total U.S. Results: Full Year 2012

* All Time High

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Jan + Feb 2013:

Highest Rooms Revenue - EVER

($16.6 billion)

-8

-4

0

4

8

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Supply Demand

Favorable Supply / Demand Fundamentals for 2013

-6.9%

-0.9%

- 4.7%

Total U.S.: Supply & Demand Percent Change

12 Month Moving Average Jan. 1990 – Feb. 2013

8.0%

2.9%

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-15

-10

-5

0

5

10

1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

Occupancy % Chg ADR % Chg

June ’91

-3.4

Jan ’92

0.1

Mar ’02

-6.7

Aug ’02

-4.5

Sept ’09

-9.7

Jan ’10

-8.9

Apr ’11

6.2

Total U.S.: Occupancy/ADR Percent Change

Twelve Month Moving Average – 1989 to Feb. 2013

Feb‘13

4.3

ADR Growth Stalls. Smooth Sailing From Here?

-20

-10

0

10

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012

Positive RevPAR Growth: Three More Years (?)

-16.8%

-2.6%

-10.1%

9%8.6%

Total U.S.: ADR & Demand Percent Change

12 Month Moving Average –1990 – Feb.2013

65 Months 30 Mo.112 Months

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U.S. Pipeline: Construction Accelerates

Phase YE 2012 YE 2011 % Change YE 2007

In Construction 68 54 25.5% 211

“Planned Pipeline” 236 254 -7.1% 204

Active Pipeline 304 308 -1.2% 415

Total U.S. Pipeline, by Phase, ‘000s Rooms; 2012, 2011, & 2007

“Planned Pipeline" includes projects in Final Planning and Planning phases

Total United States

Key Performance Indicator Outlook (% Change vs. Prior Year)

2013-2014

Year End Outlook

2013

Forecast

2014

Forecast

Supply 1.0% 1.5%

Demand 1.8% 2.8%

Occupancy 0.8% 1.3%

ADR 4.9% 4.6%

RevPAR 5.7% 6.0%

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Total United States

Occupancy Percent

2005 – 2014P

63.0 63.2 62.8

59.8

54.6

57.5

59.9

61.461.9

62.7

2005 2006 2007 2008 2009 2010 2011 2012 2013P 2014P

Slowly Catching Up to Prior Peaks

$85$104 $107

$85

$102

Nominal ADR

2000/2008 ADR Grown by CPI

2000 ADR Grown by CPI

2008 ADR Grown by CPI

$107

Total U.S. Room Rates

Actual vs. Inflation Adjusted 2000 – 2014F Note: 2012 & 2013 CPI forecast from Blue Chip Economic Indicators

$119

$116

Inflation Adjusted ADRs Well Out Of Reach

$111

$116

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Chain Scale In Review

Strong Demand Growth, Supply Not An Issue

0.0

0.0

1.9 1.8

0.8

-0.2

3.1

2.1

3.9

4.7

3.1

1.6

Luxury Upper Upscale Upscale Upper

Midscale**

Midscale** Economy

Supply Demand

U.S. Chain Scale: Supply / Demand % Change, Full Year 2012

**Upper Mid / Midscale: Same Store Basis to Account for Best Western Reclassification

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Under Construction Rooms Mostly In Middle Segments

4.5

7.3

22.4

20.4

3.3

1.1

8.8

Luxury Upper

Upscale

Upscale Upper

Midscale

Midscale Economy Unaffiliated

U.S. Pipeline, Rooms Under Construction , ‘000s Rooms, by Scale, YE 2012

ADR Growth > OCC Growth

3.2

2.11.9

2.9

2.4

1.8

4.64.3

4.6

3.8

3.3

4.0


Midscale**

Midscale** Economy

Occupancy ADR

73.2%

U.S. Chain Scale OCC / ADR Percent Change and Actual OCC & ADR, Full Year 2012**Upper Mid / Midscale: Same Store Basis to Account for Best Western Reclassification

$274.51

70.9%

$154.36

70.9%

$116.88

63%

$97.41

54.8%

$74.45

54.3%

$52.50

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RevPAR Slowly Catches Up To Prior Record Highs

$213

$113

$84

$62

$44$31

$202

$112

$84

$62

$41$29


Midscale**

Midscale** Economy

2007 2012

U.S. Chain Scales, RevPAR $, Full Year 2007 & 2012**Upper Mid / Midscale: Same Store Basis to Account for Best Western Reclassification

Upper Segments To Pass Prior Record Highs (hopefully)!

$213

$113

$84

$62

$44$31

$219

$114

$89

$65

$42$30


Midscale**

Midscale** Economy

2007 2013 Forecast

U.S. Chain Scales, RevPAR $, Full Year 2007 & 2013 Forecast**Upper Mid / Midscale: Same Store Basis to Account for Best Western Reclassification

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Total United States

Chain Scale Key Performance Indicator Outlook

2013F by Chain Scale

2013 Year End Outlook

Chain ScaleOccupancy

(% chg)

ADR

(% chg)

RevPAR

(%chg)

Luxury 2.3% 6.6% 9.0%

Upper Upscale -0.1% 4.5% 4.3%

Upscale 1.4% 5.5% 7.0%

Upper Midscale 0.5% 4.8% 5.3%

Midscale 0.7% 2.4% 3.2%

Economy 1.1% 3.3% 4.4%

Independent 0.5% 4.8% 5.2%

Total United States 0.8% 4.9% 5.7%

And If All Goes Well…Overall strong KPIs for 2013

Markets In Review

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RevPAR Recovery

through December 2012

RevPAR Recovery

tracts fully recovered

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RevPAR Recovery

tracts still recovering

37 mos

41

42

44

47

48

56

56

57

59

59

60

62

62

62

65

65

68

69

78

78

82

83

83

90+

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

San Francisco

Miami

Oahu

Boston

Nashville

Los Angeles

Detroit

Houston

Denver

Anaheim

Seattle

St. Louis

Chicago

Dallas

Philadelphia

Minneapolis

San Diego

New Orleans

Tampa

Norfolk

Orlando

Atlanta

New York

Washington

Phoenix

a

Actual

Estimated

RevPAR Peak-Trough-Recovery Timeframe

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$16.55 $16.04$15.27

$5.47

$2.35 $2.13 $2.10

-$0.93-$2.51-$2.77-$3.59-$3.95

-$4.99-$5.13-$5.47-$6.12-$7.46-$7.74-$7.79-$8.06

-$9.57-$10.56

-$10.60

-$18.61

-$30.82

Top 25 Markets, ADR $ Change From Prior Peak, as of Feb 2013

Peak ADRs Still Off Peak By Over $5 for Majority Of Top Markets

Group Demand Never Recovered After The Downturn

19.0%

-2.7%

Transient Group

Segmentation Demand % Change, 2012 (vs. 2007)

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Some Markets Are “Hot”

U.S. Pipeline, Top 26 Markets, Rooms Under Construction, Feb. 2013

Market Rooms UC % Of Existing

San Fran-San Mateo, CA 0.0%

Norfolk-VA Beach, VA 0.0%

Oahu Island, HI 0.0%

Las Vegas, NV 102 0.1%

Dallas, TX 256 0.3%

New Orleans, LA 207 0.6%

Seattle, WA 279 0.7%

Atlanta, GA 767 0.8%

Boston, MA 423 0.8%

Phoenix, AZ 564 0.9%

Houston, TX 736 1.0%

Tampa-St Pete, FL 461 1.0%

Anaheim-Santa Ana, CA 730 1.4%

Minn-St Paul, MN-WI 594 1.6%

St Louis, MO-IL 716 1.8%

LA-Long Beach, CA 1,855 1.9%

Detroit, MI 832 2.0%

San Diego, CA 1,185 2.0%

Chicago, IL 2,442 2.3%

Philadelphia, PA-NJ 1,029 2.3%

Orlando, FL 2,838 2.4%

Miami-Hialeah, FL 1,261 2.6%

Washington, DC-MD-VA 3,127 3.0%

Denver, CO 1,424 3.5%

Nashville, TN 1,764 4.9%

New York, NY 10,692 10.3%

As of 3rd Quarter 2012 Forecast

0% to 5% 5% to 10%

Denver Anaheim-Santa Ana

Minneapolis-St Paul Atlanta

New Orleans Boston

New York Chicago

Norfolk-Virginia Beach Dallas

Orlando Detroit

Philadelphia Houston

Phoenix Los Angeles-Long Beach

St Louis Miami-Hialeah

Tampa-St Petersburg Nashville

Oahu Island

San Diego

San Francisco/San Mateo

Seattle

Washington, DC

2013 Year End RevPAR Forecast

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To Wrap It Up….Takeaways

• Supply Growth: Uptick Beginning Slowly

• Demand Growth: Healthy Despite the Noise)

• ADR Growth: Drives RevPAR Growth

• Outlook: Steady for the Near Future

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Kevin Coleman


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A Closer Look at DataThe Art & Science of Data Transformation

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In the next 15 minutes we will:

• Look at what data is (are)

• Consider how data gets transformed into

information and knowledge

• Look at the role of Business Intelligence

• Consider what factors influence our data

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The DIKW Pyramid

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The Transformation of Data

Wisdom

Knowledge

Information

• Discrete, objective facts

• Unorganized and unprocessed

• Have no meaning because of lack of context and interpretation

Data

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• Deciding what to do within constraintsWisdom

• Understanding what the information meansKnowledge

• Information is data in contextInformation




Data

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• Understanding principles


• Understanding patterns


• Understanding relations





Data

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• Pathfinding

• Understanding principles


• Sense-making

• Understanding patterns


• Analyzing

• Understanding relations





Data

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Example

• It may be too late to impact transient business for the next 30 days

• We could still impact the summer with the right promotionWisdom

• We are not performing as well as the competition

• This tends to happen every spring and summer

• I think transient business is the causeKnowledge

• 200 sold of 300 = 66.7% occupancy

• $35,000 in rooms revenue = ADR of $175.00

• RevPAR of $116.67

• Comp set RevPAR of $155.56

Information

• $35,000

• 200

• 300Data

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As context increases, so does

understanding

Many of us spend much of our time

producing information (collecting

data, organizing, making

spreadsheets)

Ideally, we would spend more time

consuming information, applying

our expertise to practice our art

Art

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Technology helps here

Business Intelligence (BI):

• Helps turn data into information

by giving it more context

• Helps information to become

knowledge by making it more

accessible, more relevant and

better presenting it

• Automates transformation of

data and information to allow

shift from producing to

consuming information

• Enables increased knowledge and

wisdom

Science

Typical Scenario (no BI)

Wisdom

Knowledge

• 200 sold of 300 = 66.7% occupancy

• $35,000 in rooms revenue = ADR of $175.00

• RevPAR of $116.67

• Comp set RevPAR of $155.56

Information

• $35,000

• 200

• 300Data

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Information source is static

(ex: PMS reports)

Organizing & presenting is

manual (Excel)

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Scenario with BI

Wisdom

Knowledge

Information

• $35,000 Wednesday

• 200 GDS

• 300 Standard KingData

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Data is now stored in a data

warehouse at the most

granular level, so that all

facets can be accessed

Ex: (a reservation record)

revenue

# of rooms

room type

market segment

source market

date booked

date arrived

channel

etc.

Scenario with BI

Wisdom

Knowledge

• Mid-week RevPAR lowest at $109.92

• BAR production dips on Tues & Wed

• BAR production in Standard rooms is down 23%

• Discount business is up on these days

Information


• 200 GDS


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Information is compiled

and presented with a BI

tool

Can view data from

more angles

Can isolate the effect of

one attribute (DOW,

channel, etc.)

Can more easily

identify trends

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Scenario with BI

Wisdom

• Mid-week RevPAR index is the issue

• Need to look at BAR pricing specifically

• Might be displacing some BAR business with Discount or generating buy-down

Knowledge





Information


• 200 GDS


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Better information leads

to greater knowledge

(recognizing patterns)

Better theories can be

devised and tested

Scenario with BI

• We can impact short-term transient with the right BAR pricing

• Need to leave some availability for BAR by yielding discount

• Try to sell more BAR farther out through bonus points on our siteWisdom

• Mid-week RevPAR index is the issue

• Need to look at BAR pricing specifically

• Might be displacing some BAR business with Discount or generating buy-down

Knowledge





Information


• 200 GDS


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Greater knowledge leads

to enhanced wisdom (on

which actions are taken)

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Actions generate data

Once we apply our knowledge/wisdom and

take actions, more data are generated and

the cycle repeats

The data that are generated are affected by:

• Our business processes (or lack thereof)

• Our systems and their configuration

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Consider a single data element for your hotel(s)

Country of residence of guest

What is procedure in reservations and at

front desk to capture?

What is default value for PMS?

Can you accurately tell the volumes of domestic

business versus folios left at default?

How can you impact this process?

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Summary

• BI helps transform:

– Data into information

– Information into knowledge

– Producers of information into

consumers

• However, data:

– Remains the foundation

– Reflects your business processes

(or lack thereof)

– Requires consideration

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Mark MolinariCorporate VP of Revenue Management and DistributionLas Vegas Sands [email protected]

4/9/2013

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Great Gaming Myth

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Great Gaming Myth

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Sources of Data

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Big Data Overwhelm

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Good Data In/Good Data Out• Aggregate Data• Validate Data• Organize & House Data

• Data Warehouse• SAS• CRM• Microsoft Access• Microsoft Excel

• Power Pivot• Analyze Data• Disseminate Data

• Reports• Dashboards

• Microsoft SharePoint

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Know Your Audience

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Reporting for Executives

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Reporting for Colleagues

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Power Pivot Reports in SharePoint

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Power Pivot Dashboards in SharePoint

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Power Pivot Dashboards in SharePoint

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Nathan Bacher

Regional Director

Revenue Management

Fairmont Raffles Hotels International

DIDO: A Case Study

FRHI Restaurant Revenue Management Project

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DIDO Case Study:

FRHI Restaurant Revenue Management Project

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1. What data do we already have?

2. What data do we need?

3. How do we get more data?

4. How do we bridge the data gap?

5. How do we action the data?

DIDO Case Study: FRHI Restaurant Revenue Management Project

Rooms

• Occupancy %

• Average Daily Rate

• Total Revenue

• RevPAR

Restaurants

• Cover count

• Average Check

• Total Revenue

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What data do we already have?

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What data do we need?

Is our restaurant busy or not?


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How do we get more data?

FRHI partnered with Avero to maximize our access to F&B data.

• Category Sales• Item Sales• Server Sales• Party Size

• Promotional Sales• Voids• Payment Type Sales• Turn Time

4/9/2013

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How do we bridge the data gap?

Table Occupancy

Tables Occupied

Tables Available

Seat Occupancy

Seats Occupied

Seats Available

RevPASHF&B Revenue

Seat Hrs AvailableAvg Check Seat Occ%


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0%10%20%30%40%50%60%70%80%90%

100%

Tab

le O

ccu

pa

ncy

How do we action the data?

Sunday Monday Tuesday Wednesday Thursday Friday Saturday All

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Questions? Panel Moderator: Patrick Mayock, Editor in Chief, HotelNewsNow.com

Panelists:

Steve Hennis

Director

STR Analytics

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Kevin Coleman


Mark Molinari

Corporate VP

Revenue Management &

Distribution

Las Vegas Sands

Nathan Bacher

Regional Director

Revenue Management

Fairmont Raffles Hotels Int’l

Upcoming Webinars:

#2 – Revenue Management Webinar Series:

Social Media and Reviews are Changing the Landscape of Revenue Management

April 30, 2013 ♦ 2:00-3:30 pm Eastern

#2 – Digital Marketing Webinar Series:

Leveraging the Digital Tool Box to Increase Your Share of Unmanaged Business

Travel

May 14, 2013 ♦ 2:00 - 3:00 pm Eastern

4/9/2013

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The 2013 HSMAI Revenue Optimization Conference, prior to HITEC, is a unique one-day

interactive program featuring thought leaders and subject-matter experts in various aspects

of revenue management. You’ll learn about the latest trends and best practices in this

important discipline – and what they can mean to you and your company – from industry

experts and practitioners.

Revenue Optimization Conference

June 24, 2013

Hyatt Regency Minneapolis

Minneapolis, Minnesota

The conference is organized by HSMAI’s Revenue Management Advisory Board.

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Get Informed - Get Ahead – Get Certified!

Certified Revenue Management Executive (CRME)

Certified Hospitality Digital Marketer (CHDM)

Certified Hospitality Sales Executive (CHSE)

Certified in Hospitality Business Acumen (CHBA)

Go to www.hsmaicertifications.org

For more information and downloadable applications!

4/9/2013

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As the meeting and event-planning industry’s premier show, HSMAI's

MEET Mid-America brings a new vision to the business of connecting

planners with the right resources and suppliers to move their

meetings and events forward.

The 2013 MEET Mid-America will attract 800 planning professionals

from organizations of every size, plus 100 exhibitors, representing

hotels, resorts, inns, convention and visitors bureaus, technology

suppliers, food and equipment providers, and more.

Go to www.hsmaimeet.com for more information and to sign up!

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Today’s webinar is copyright 2013 by the Hospitality Sales & Marketing Association International with All Rights Reserved.

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Revenue Management Webinar Series Good Data In/Good Data ...eoplugin.commpartners.com › HSMAI ›...

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