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REAL ESTATE BD Uses Dale Ross - RPR Sept. 10, 2014

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2 Defense Base Realignment and Closure Commission (BRAC) U.S Congress-November 2005 Ten Year Plan Transfer and Disposal of Military Institutions (Reduce pork-barrel politics)

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3 State of Maryland-Map 1

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4 State of Maryland Bethesda (Suburb of Washington D.C.) National Institutes of Health National Naval Medical Center-Now Walter Reed National Medical Center (November 2011) 20,000 Jobs (est.) Frederick (50 miles north of Washington D.C.) Ft. Detrick Army Medical Research-Institute of Infectious Diseases 5,000 Jobs (est.) Aberdeen (26 miles north of Baltimore) U.S. Army Communication Electronic Command 22,000 Jobs (est.) 2

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5 State of Maryland Lexington Park (65 miles southeast of Washington D.C.) Naval Air station Patuxent River (Pax River) Naval Air Warfare Center-Aircraft Division Air Test Wing Atlantic 17,000 Jobs (est.) Ft. Mead (Between Washington D.C. and Baltimore) National Security Agency (NSA) Largest Consumer of Electricity in Maryland Largest Employer in the State of Maryland Largest Concentration of Mathematicians in the World 54,000 Jobs (est.) 3

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6 The 3 keys to Big Data Preparation Analysis Context Growth of Structured vs. Unstructured Data Source: Oracle Unstructured Structured 4

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270 Terabytes of Property Data and Images 1 Terabyte = 1,099,511,627,776 bytes Processed on ultra-fast drives providing 1 million input/output operations per second Support for more than 1000 fields of MLS data Property characteristics covering 99% of the US population RPR Platform Assets 7 5

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8 Big Data Starts with a Big Shovel Its an absolute myth that you can send an algorithm over raw data and have insights pop up. - Jeffrey Heer, University of Washington Source: New York Times, Aug. 17, 2014 RPR Data Preparation High-level Workflow 6

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9 Property Data Changes Constantly With many thousands of sources updating 24-7, millions of U.S. properties change status every day On any given day, more than 5% of all MLS feeds are broken or changing at the source Countless data entry errors, typos, and duplicates must be detected and removed from MLS and public data 7

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10 Gaining Real Competitive Advantage Whats the current return on a bathroom remodel in Cheeseville, Wisconsin? 8

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11 Preventing Fall-thru Show only short sales within servicer-approved price guidance 9

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12 Commercial Consumer Trends Neighborhoods with high household growth potential in areas with concentration of financial professionals 10

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13 Commercial Consumer Trends Market Leakage graphs show where consumers are spending, both inside and outside of their communities 11

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14 Big Data-Real Estate Open New Offices Franchise Affiliation Profile for Future Agents Profile Future Sellers (Homeowners) Profile for Future Purchasers (Apartment Dwellers) Job Growth Trends (Future Customers) 12

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Pent-Up Demand 15 Lawrence Yun, Ph.D. Chief Economist NATIONAL ASSOCIATION OF REALTORS Presentation at NAR Leadership Summit Chicago, IL August 18, 2014 20002013 Existing Home Sales5.2 m5.1 m New Home Sales880 K430 K Mortgage Rates8.0%4.0% Payroll Jobs132.0 m136.4 m Population282 m316 m 13

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National Housing Forecast 16 20132014 forecast 2015 forecast Housing Starts925,0001.1 million1.4 million New Home Sales430,000Near 500,000Near 700,000 Existing Home Sales5.1 million4.9 million5.3 million Median Price Growth+ 11.5%+ 5% to 6%+ 3% to 5% 30-year Rate4.0%4.4%5.4% Lawrence Yun, Ph.D. Chief Economist NATIONAL ASSOCIATION OF REALTORS Presentation at NAR Leadership Summit Chicago, IL August 18, 2014 14

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17 Benchmarking and Forecasting Predicting Inventory and Pricing at Market and Company Level 15

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19 Mistaking Analysis for Insight With Big Data, it is easy to find correlations that are neither meaningful nor actionable. The U.S. murder rate corresponds highly to changes in the usage of Microsofts browser Source: Gizmodo 17

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20 You Get Out What You Put In IBM's Watson fails third-grade geography test World's smartest computer thinks Toronto is a U.S. city - NetworkWorld 18