travel procurement workshop

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NBTA Convention & Exposition | August 8-11, 2010Houston, Texas

Travel Procurement WorkshopScott GillespieAuthorGillespie’s Guide to Travel+Procurement

NBTA Convention & Exposition | August 8-11, 2010

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MODERNAIRLINE SOURCING

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Key Analytical Concepts

Fair Market Share (FMS)

Airline Supplier Map

Fare mix, discounts, and Net Effective Rate (NER); a.k.a. Weighted Average Discount

Scenario modeling

Program savings and CEO Map

Program optimization

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Fair Market Share (FMS)

• A.k.a. QSI, or neutral share, or share of lift

• Best estimate of carrier’s market share before pricing and loyalty factors

• Very important basis for all modern airline sourcing projects

• Drives minimum, maximum and goal share, and the corresponding spend projections

• Key variables are connection logic and interline logic

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Fare Mix, Discounts and NER(Net Effective Rate)Fare mix is key to calculating savings

Historic fare mix determines the spend-weighted Net Effective Discount

Share of Spend

Booked Fare Class

Discount Net Eff. Rate

10% J 30% 3.0%

20% Y 20% 4.0%

40% M 15% 6.0%

30% T 0% 0.0%

13.0%Net Effective Rate =

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Fare Mix Issues

Buyers use historic fare mix data

Airlines may use non-historic fare mixes when bidding

• Buyer’s calculation of Net Effective Rate, and savings, will differ from airline’s

No practical way to guarantee inventory availability – or the future fare mix

• Standard practice is to use last year’s fare mix

• But check with each airline!

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Airline Supplier MapS

pen

d a

t Fair

Mark

et

Sh

are

$3.0 MM

$0.0

Ability to Move ShareVery Low Very

High

DL

AA UA

Primary, or Tier 1

Secondary, or Tier 2

Tertiary, or Tier 3US AC

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Scenario Modeling is Critical

• Basis for modern airline sourcing

• Scenarios are “What if” options

• Typically involve Tier 1, 2 and 3 airlines• A.k.a. Primary, Secondary and Tertiary

• Can have Co-primaries, co-secondaries, etc.

• Easy to model alliances

• Calculates detailed carrier shares and buyer’s savings for each scenario

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scenario modeling

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Scenario Examples

• DL as Primary, Star as Secondary

• DL/AF/KL as Primary, Star as Secondary

• DL + AA as Co-Primaries, then Star

• Star as Tier 1, then DL + AA as Tier 2

• Avoid DL: Make FL/AA/UA/US as Tier 1

• Modeling tools test 50-250 scenarios

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Buyers Focus on Scenario Savings

Last year’s net program spend

- Scenario’s projected net spend

= Scenario Savings

Weaknesses:• Uses last year’s published fares and

last year’s fare mix• ** Understates savings when fares fall

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Sample Scenario Results (Illustrated)

Scenario ScenarioTotal Net Spend

Scenario Savings ($000s)

DL’s Net Spend ($000s)

1. DL, then Star 2,950 50 700

2. DL/AF/KL, then Star 2,940 60 600

3. DL+AA, then UA+AC 2,930 70 400

4. Star, then DL+AA 2,960 40 300

5. Avoid DL 2,970 30 200

Last year’s Program Net Spend was $3,000K

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Scenario Implications

Scenario Scenario Total Net Spend

Scenario Savings ($000s)

DL’s Net Spend ($000s)

1. DL, then Star 2,950 50 700

2. DL/AF/KL, then Star 2,940 60 600

3. DL+AA, then UA+AC 2,930 70 400

4. Star, then DL+AA 2,960 40 300

5. Avoid DL 2,970 30 200

Buyer prefers No. 3DL prefers No. 1

SkyTeam prefers No. 2

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Hotel Clusters 101

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How should you group hotels for negotiations?

Distance between hotels matters a lot

You want to group hotels into actionable markets

- Small enough to be create valid competition

- Regardless of artificial boundaries

Artificial boundaries:

•State borders

•City borders

•Zip Codes

•“Midtown”, “Downtown”

•“Near Airport”


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Clusters are actionable markets

• Clusters are small areas, maybe 1-3 miles in diameter

• Clusters are built around your program’s high-stay areas

• Artificial boundaries (State, City, Zip Code, etc.) are ignored

• Clusters include non-preferred and unused hotels

• Clusters create actionable markets, much like city pairs

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Ignore Orphan Hotels!

Orphans are low-stay hotels outside cluster boundaries

They show up in TMC booking and credit card reports

• Ignoring orphans can eliminate 50-70% of booked hotels, 10-20% of Room Nights

• In no way weakens negotiations

• Significantly streamlines the Hotel RFP process

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Slide 1 detail (Arial 44)From a Hotel Usage Map…

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Slide 1 detail (Arial 44)To Hotel Clusters

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Slide 1 detail (Arial 44)Including Unused Hotels

21NBTA Convention & Exposition | August 8-11, 2010

Modern

Hotel Sourcing

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Hotel Sourcing’s Typical Annual Cycle


Data Collection

RFPImplement

& Manage

Summer Fall / Winter Winter >>>

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The Missing Step: Sourcing Strategy


Data Collection

RFPImplement

& Manage

Summer Fall / Winter Winter >>>

Sourcing Strategy

Summer

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Strategy Study’s Key Deliverables

Estimates the Major Savings Opportunities• Higher compliance to “as is” program

• Broader coverage (more preferred hotels)

• Less upgrading and/or more rate availability

• Better rate negotiations

• Realistic tier-down scenarios

Which then drives the Bid List• Depends on management’s appetite for savings

and change

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Socialize with Senior Management

=

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Clusters Create Meaningful Insights

Which clusters need more preferred hotels?

Which clusters have competitive alternatives?

Where is there non-compliant spend? Is it a rate problem?

Which clusters have lower-tier hotels? By how much do rates differ?

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Strategy Study Shapes Your Bid List

• Compliance savings > existing preferreds

• Coverage savings > add more preferreds

• Tier-down savings > bid lower-quality hotels


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What’s the Total Cost of Stay? Models need:

• Prices for room rates - Last Room Avail., Non-LRA

- Best Available Rate (or AAA rate)

• Ancillary Costs (Internet, breakfast, parking)

• Utilization estimates for ancillaries

• Volume estimates per property

• Quality ratings (3 star, 4 star, etc.)


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Some Key Metrics

Spend Under Contract $2.0 million (80%)

$0.4 millionNegotiated Savings

Average Discount x 20%

Average Hotel Quality 3.7 stars -10% YoY

Average Booked Rate $143 -22% YoY

Total Hotel Spend $2.5 M -30% YoY

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Drivers of Average Booked Rate

Quality tier of hotel (5 star vs. 4 star)

Preferred vs. non-preferred status

Room type

Negotiating process

Room night volume

Room availability

Local market conditions

Travel Managers are expected to

influence most of these factors

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Chain Fitting

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If you had $1 million in spend in these secondary markets…

Tacoma

Tampa

Toledo

Topeka

Tucson

Tulsa


…Which hotel chain gives you the best coverage?


Scenario Option

Risk ScoreExpected Savings

Quality

Policy Mgmt.

Relationship

Strategic Value

Discount or New Price

Projected Spend

X

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“Well, let’s look at our historic spend by chain”

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Evaluate chain-wide deals on Neutral Share – not just Actual Share

Strong Candidates!

Share of beds in the selected clusters


Know which chains

best fit your

program

travel procurement workshop

Documents

sdls net

years program net

fare mix issuesbuyers

savingshistoric fare

net effective rate ner

historic fare mix dataairlines

scenarios projected

goal share