Transcript Document
Decision Support in Travel Procurement Applying Cluster Analysis to Hotel Data Goal: Select the best hotel chains for a corporate travel program. Two factors: • Coverage • Measuring the potential fit o Map the demand – known travelers' destinations o Map the supply – location of hotel properties • Cost • Bargaining aggressively yet credibly o Understand competitive alternatives o Make credible threats and promises Problems: Proximity and Comparability • Traditional proximity problems o Artificial boundaries - state, county, city, zip code o Impractical distances o Poor sorting/ranking/grouping options • Comparability is easily solved only after proximity is solved Start with Raw Hotel Data Mix Together Add More Ingredients, Then Mix Into a Very Useful Batter Slide 1 detail (Arial 44) Necessary, but not Sufficient Key Ingredients Include Tools and the Human Factor High Quality Data Ingredients 1-1/2 cups all-purpose flour 2 teaspoons baking powder 1/4 teaspoon salt 1/2 cup (1 stick) unsalted butter, softened 3/4 cup sugar 2 large eggs 1/2 cup reduced-fat sour cream 2 tablespoons milk 1/2 teaspoon vanilla extract 5 chocolate and creme sandwich cookies (such as Oreos), broken up Frosting: 2 cups confectioners' sugar 1/4 cup (1/2 stick) unsalted butter, softened 1/4 cup reduced-fat sour cream 1/4 teaspoon vanilla extract + Right Tools + Clever Analytics Directions 1. Heat oven to 350°. Line 36 indents of mini muffin pans (using 3 pans total) with paper or foil liners. If you have only one or two pans, bake batter in batches. 2. In small bowl, whisk flour, baking powder and salt. In large bowl, beat butter until smooth. Beat in sugar until fluffy. Beat in eggs, one at a time. 3. On low speed, alternately beat flour mixture and sour cream into butter mixture, beginning and ending with flour. Add milk and vanilla; fold in cookie pieces. Divide batter among prepared cups; for ease, place batter in a resealable plastic bag, snip off a corner and pipe into cups. 4. Bake at 350° for 15 minutes, until tops spring back when lightly pressed. Remove cupcakes to a rack; let cool. Slide 1 detail (Arial 44) From Hotel Mapping… Slide 1 detail (Arial 44) To Company-specific Hotel Clusters Slide 1 detail (Arial 44) Including No-Stay Hotels Analytical Approach • Construct clusters • Identify and map High-stay hotels • Build clusters in Matlab, SAS, etc. • Within each cluster o Map each cluster's centroid o Apply a maximum radius limit for each cluster Those hotels beyond the radii are "Orphans" o Bring in the Low-stay and No-stay hotels • For each hotel within a cluster: o Allocate "Fair Market Share“ to quantify coverage o Assign a Buyer Power score (similar to Herfindahl Index) Calculate Each Chain’s Coverage Hotel Chain Coverage Core Markets 34% 24% 17% 16% Hotel Chain Coverage 5% All Markets 29% Marriott Hyatt Hilton Starwood IHG 24% 21% 15% 9% Hotel Chain Coverage Core Markets Secondary Markets 40% Marriott 34% 32% 24% 17% 8% Marriott 16% 5% Hyatt 13% 5% Hilton Starwood IHG Hyatt Hilton Starwood IHG Plot Suppliers on 2 Key Dimensions Chain Coverage in All Markets Chain Sourcing Map 30% Hilton Starwood Marriott 25% 20% Hyatt 15% IHG 10% 5% 0% - 2.0 4.0 6.0 Buyer Power (10 = Very High) 8.0 10.0 Derive Expected Program Value Scores Chain Sourcing Map Core Markets 34% 24% 17% 16% 5% Marriott Hyatt Hilton Starwood IHG Expected Program Value 3.5 2.1 Marriott Hyatt 1.5 Hilton Starwood Starwood Hilton 30% Marriott 25% 20% 15% 10% IHG Hyatt 5% 0% - 2.0 4.0 6.0 8.0 Buyer Power (10 = Very High) Likely Best Chains: •Marriott, Starwood •Marriott, Starwood, Hilton 4.5 1.5 Chain Coverage in All Markets Hotel Chain Coverage IHG 10.0 High Quality Ingredients Clever Chefs and Recipes Proper Tools Thank you! Contact Dan Pirnat, VP & GM TRX Travel Analytics (O) +1 440 236 3561 (e) [email protected]